Luminescent Nanofibers for Human Skin Textures Photocopying

Luminescent Nanofibers for Human Skin Textures Photocopying | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Luminescent Nanofibers for Human Skin Textures Photocopying Huan Pang, Tian Tian, Huixuan Han, Xinyi Lin, Hui Kang, Meifang Yang, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5658648/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract The domain of forensic science, dermatology, and regenerative medicine critically relies on the precise replication of human skin details. Nevertheless, conducting on-site analysis poses challenges due to the stringent requirements for stability, accuracy, and the use of safe imaging materials. Current skin imaging methodologies are hindered by the inherent limitations of their hardware components, particularly when it comes to capturing the intricate, micrometer-scale textures of human skin. To address these challenges, we develop a low-cost (< $ 800), portable nanofiber-based imaging technique (NFIT) using CsPbBr 3 @HPβCD luminescent nanofibers. NFIT achieves in-situ, multi-regional imaging with ultrahigh-resolution (1450 dpi) and micron-scale similarity (93.24 ± 4.6%), capturing intricate details from sweat pores to large skin areas. Its non-contact design eliminates chemical pre/post-treatments, ensuring safety, hygiene and ease of use. NFIT demonstrates robustness and reliability as it maintains clear imaging under extreme temperature (-50°C to + 50°C) and over extended periods (Level 3 ≥ 81 days, Level 2 ≥ 108 days ). An algorithm was developed to support 3D skin texture model reconstruction, offering a transformative solution for forensic evidence analysis, dermatological assessments, and personalized medicine. Physical sciences/Chemistry/Materials chemistry/Optical materials Physical sciences/Materials science/Nanoscale materials Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Skin, the human body's largest organ, harbors numerous secrets within its distinctive texture 1 – 6 , sweat gland distribution 7 , and biological properties 1 , awaiting precise capture and analysis 2 . 8 . For instance, fingerprints, as the most commonly used feature of the skin, are stable and unique for each individual due to the interplay of genetic and environmental factors during fetal development 5 , 6 . This makes them an excellent tool for personal identification 9 , crime scene investigations 7 , 10 , 11 , 12 , and security applications 12 . Thus, analytical techniques have been developed based on Raman spectroscopy 13 , mass spectrometry 14 , Fourier transform infrared spectroscopy (FTIR) 15 , luminescence imaging 16 – 18 and other techniques 19 . Among the materials applied in these imaging techniques, luminescent materials such as carbon dots 20 , 21 , perovskite quantum dots 22 , aggregation-induced emissive materials 23 and organic dyes 24 , 25 exhibit good imaging performance. However, on-site analysis requires exceptional stability, accuracy, and safety imaging materials, posing significant challenges for technological advancements 26 . Furthermore, traditional skin imaging techniques are constrained by hardware limitations 27 , lens quality, image processing algorithms 28 and shooting environments 29 , 30 , 31 , 32 , thereby impeding the attainment of high-resolution images of micrometer-scale skin textures 9 , 10 , 14 . Thus, a universal high-resolution skin imaging technique combined with a data analysis system for identity verification, forensic science and criminal investigations has not yet been fully developed. To address these issues, we have developed a low-cost, portable nanofiber-based imaging technique (NFIT) for human skin texture photocopying, using CsPbBr 3 @HPβCD luminescent nanofibers. This NFIT facilitates in situ , multi-regional imaging of skin microsurface morphology by harnessing a unique wavelength-dependent photoluminescence mapping technique, utilizing trace amounts of sweat residue. When benchmarked against real fingerprint tertiary feature data, the NFIT exhibits a remarkable micron-scale imaging similarity of 93.24 ± 4.6%, coupled with high-resolution fingerprint imaging (1450 dpi). This underscores its exceptional proficiency in capturing intricate skin texture details, ranging from the minute structure of individual sweat glands to extensive textures across the palm, sole, abdomen and dorsum of the hand. Notably, the NFIT adopts a non-contact imaging paradigm, eliminating chemical pre/post-treatment requirements. This attribute ensures compatibility with DNA evidence collection while minimizing chemical interference, thereby presenting a dependable and convenient tool for forensic and security applications. Moreover, NFIT maintains high-definition imaging across a broad temperature range of − 50°C to + 50°C and delivers excellent long-term imaging stability (level 3 ≥ 81 days, level 2 ≥ 108 days). This robustness ensures reliable operation under diverse harsh conditions, offering robust support for on-site analysis. Beyond its high precision, low cost (< $ 800), and portability (< 400 grams), the NFIT's extensive applicability enables users to extract and photocopy skin texture images in real-time, irrespective of location or time, thereby supporting 3D skin texture model reconstruction. Importantly, the entire digitization process necessitates minimal computational resources 33 , thereby reducing the complexity and cost associated with system development and maintenance. This functionality significantly enhances operational efficiency and brings unparalleled convenience and substantial contributions to high-precision 3D portrait construction, dermatology, regenerative medicine, forensic analysis, and other pertinent fields. Results Fingerprint Imaging Process and Morphological Characterization CsPbBr 3 @HPβCD nanocrystals were synthesized via grinding (see details in the Methods section). In this study, amphiphilic thermoplastic polyurethane (TPU) was selected as the electrospinning matrix because of its lypohydrophilic character compared with polystyrene (Supplementary Fig. 1). This characteristic ensures reliable extraction of fingerprint residues, primarily consisting of sweat and sebum, and potentially enhances the luminescence response. The CsPbBr 3 @HPβCD nanocrystals were then blended with TPU to form a mixed solution prepared as an electrospinning ink. Consequently, a handheld mini electrospinning device (ca. 10 cm in length) was used to spray CsPbBr 3 @HPβCD fibers onto the sample to form luminescent nanofibers for imaging. Herein, fingerprints were employed as a representative of detailed skin textures to examine the imaging capability of NFIT. As shown in Fig. 1 a and Supplementary Movie #1, high-definition Level 3 fingerprint imaging can be obtained efficiently within 10 seconds. The Level 3 fingerprints offer the most intricate details, such as ridge shapes, pore positions, incipient ridges and scars 5 . To evaluate the accuracy of NFIT, we captured a fingerprint luminescence image via NFIT and compared it to the same zone of an actual fingerprint photo for the same individual (Fig. 1 b). The luminescence image clearly revealed the sweat pore features, including the pore size, shape, location, distribution, frequency, and pore-to-pore interspacing (Fig. 1 c). Overlaying Fig. 1 b with 1c, NFIT evidently allows high-precision visualization of Level 3 fingerprint features, with a matching similarity of over 93.24 ± 4.6% compared to the real fingerprint (Fig. 1 d, Supplementary Figs. 2–3 and Supplementary Table 1.), which is the highest accuracy as reported for sweat pore imaging to date 16 , 19 , 23 , 24 . Notably, unlike traditional methods in which sweat pore information is indirectly obtained after epidermal imaging, NFIT both directly responds to sweat pore and epidermal texture characteristics, providing a more precise and direct representation (Supplementary Fig. 4). Additionally, we compared the fingerprint images extracted by NFIT with those obtained via traditional ink-based fingerprinting and commercial capacitive fingerprint sensors. It can be seen that NFIT produces higher-quality fingerprint images with more abundant fingerprint features (Supplementary Fig. 5). Notably, NFIT employs a fully noncontact approach throughout the skin texture extraction process, allowing users to press their skin on any substrate and lift them without any contact with chemical reagents. This ensures both chemical safety and hygiene. In addition, the operational safety of the imaging process was thoroughly evaluated. The exposure dose per fingerprint area (ca. 4 cm 2 ) was limited to DMF ≤ 4 µL (3.8 mg) and DMSO ≤ 0.48 µL (0.5 mg) (Supplementary Table 2), which are well below the 8-hour weighted average exposure limits set by the Occupational Safety and Health Administration (OSHA) 34 . ICP-MS analysis revealed that Pb concentration leached during each fingerprint imaging process was 0.003 mg/L (Supplementary Table 3). This value is significantly lower than the 0.01 mg/L drinking water standard in the Guidelines for Drinking-water Quality published by World Health Organization (WHO) 35 , indicating negligible risk to human health 36 . To elucidate the mechanism of the CsPbBr 3 @HPβCD nanofibers’ response to sweat residues, we investigated their morphology via scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM) and energy dispersive spectroscopy (EDS) mapping. The TPU polymer forms a fibrous scaffold that effectively holds the CsPbBr 3 @HPβCD nanocrystals (Supplementary Figs. 6 and 7). SEM images of real fingerprints and latent fingerprints (LFPs) obtained via NFIT are shown in Supplementary Fig. 8. In the absence of CsPbBr 3 @HPβCD nanofibers, the LFPs exhibit distinct regional contrast between the light and dark areas (Supplementary Fig. 6a). EDS mapping reveals that the darker regions correspond to organic components primarily composed of carbon, which is predominantly concentrated in the fingerprint ridges, except for at the sweat pores (Supplementary Fig. 9). In contrast, after electrospinning, the CsPbBr 3 @HPβCD nanofibers (diameter ~ 27.8 ± 10.2 nm) are uniformly distributed across the entire surface, without preferential accumulation in the luminescence-intense regions, namely sweat pores and ridges (Supplementary Fig. 8b-d). The crystalline nature of the CsPbBr 3 @HPβCD on TPU fibers was confirmed by HRTEM (Supplementary Fig. 8e and 8f). The crystalline regions display distinct lattice fringes, with an interplanar spacing of 0.210 nm, corresponding to the (110) crystal plane towards highly crystalline CsPbBr 3 37 . Excitingly, EDS analysis demonstrates that NFIT not only accurately maps the real fingerprint features but also reveals the sodium chloride (NaCl) distribution in the fingerprint sweat (Fig. 1 e-g, and Supplementary Figs. 10–12), represented as the dark regions in the luminescence image (Fig. 1 c). In contrast, in the EDS mapping of the corresponding fingerprint residues without CsPbBr 3 @HPβCD fibers, the Na and Cl contents are below the detection limit (Supplementary Fig. 9). We hypothesize that the capillary action of the CsPbBr 3 @HPβCD nanofibers allows rapid adsorption and enrichment of NaCl from sweat. To validate this hypothesis, we sprayed a sodium chloride aqueous solution onto the surface of the CsPbBr 3 @HPβCD fibers. TEM and EDS reveal Na and Cl distributions along the fibers, confirming that NaCl can be adsorbed onto the surface of the CsPbBr 3 @HPβCD nanofibers (Supplementary Fig. 13). Furthermore, the addition of NaCl significantly affects the crystalline quality of CsPbBr 3 (Supplementary Fig. 14), potentially quenching its luminescence. The selective response to fingerprint residues enables the distinction between real and forged fingerprints, thus enhancing the security and reliability of fingerprint recognition. For example, when we prepared fake fingerprints using silicone molds, NFIT did not reveal any significant fingerprint features (Supplementary Fig. 15). Additionally, this noncontact approach addresses several issues associated with touch-based fingerprint collection, such as the nonlinear distortion caused by pressing fingers onto sensor plates and the need for regular sensor surface cleaning 38 . More importantly, NFIT achieves fingerprint image resolutions of up to 1450 dpi (Supplementary Fig. 16) without soaking, heating, or adding reagents for pre- or post-treatment. Furthermore, the fingerprint features obtained by NFIT belong to Level 3. This significantly improves the precision of fingerprint feature capture and recognition, offering promising prospects for practical applications. Selective spectral response and Chemical interactions of CsPbBr@HPβCD nanofibers to sweat components Given that CsPbBr 3 @HPβCD nanofibers enable high-definition fingerprint imaging through a selective response to sweat residues, an in-depth study of their spectral response is essential. HPβCD enhances the photoluminescence (PL) intensity of CsPbBr 3 (Supplementary Fig. 17). HRTEM images reveal that the CsPbBr 3 nanocrystals without HPβCD exhibit irregular morphologies (Supplementary Fig. 18). In contrast, the addition of HPβCD improves the crystal quality of the CsPbBr 3 nanocrystals (Supplementary Fig. 8e and 8f), which was further confirmed by X-ray diffraction results (Supplementary Fig. 19). This finding suggests that HPβCD molecules effectively passivate the defects in CsPbBr 3 , leading to enhanced PL performance. The luminescence property of the CsPbBr 3 @HPβCD fibers, coupled with their specific interactions with NaCl, prompted us to explore their potential for selective response to fingerprint residues. Sweat residues are primarily composed of sweat and sebum. Among these components, sweat contains various chlorides, such as sodium chloride (NaCl), magnesium chloride (MgCl 2 ) and potassium chloride (KCl), along with organic compounds, such as glucose, ascorbic acid, uric acid and urea 39 – 42 . Sebum, in contrast, primarily comprises triglycerides, squalene and other lipid-based compounds 43 . Therefore, we performed spectroscopic analysis to investigate the response mechanism of the CsPbBr 3 @HPβCD nanofibers to representative components (NaCl, KCl, MgCl 2 , laurostearin, ascorbic acid, urea, uric acid and squalene) of sweat residues. The ultraviolet-visible absorption (UV-Vis) spectra indicate that the addition of various components has little effect on the bandgap of the CsPbBr 3 fibers without HPβCD. However, in the presence of HPβCD, the bandgap of the CsPbBr 3 @HPβCD fibers is affected to varying degrees by these components (Supplementary Figs. 20a and 20b). Correspondingly, the PL intensities of the CsPbBr 3 fibers and CsPbBr 3 @HPβCD fibers exposed to the above components were characterized (Supplementary Figs. 20c and 20d). The patterns of their PL peak shifts are consistent with those for the UV-Vis spectra. A decrease in intensity accompanies this blueshift of the PL peaks. Owing to the good color purity of CsPbBr 3 @HPβCD (full width at half maximum = 20.86 nm), the color change upon the addition of chloride salts is highly noticeable and can be distinguished by the naked eye (Supplementary Fig. 21). In comparison, the CsPbBr 3 fibers without HPβCD typically exhibit PL quenching and minimal PL peak shifts upon the addition of chlorides (Supplementary Figs. 22). Furthermore, exposure of the CsPbBr 3 fibers to organic components (laurostearin, ascorbic acid, urea, uric acid and squalene) generally results in an increase or decrease in the PL intensity without regular changes (Supplementary Figs. 23). In contrast, for the CsPbBr 3 @HPβCD fibers, almost all, the aforementioned organic components cause a decrease in the PL intensity. Interestingly, glucose is an exception: trace amounts of glucose (mass ratio of glucose: CsPbBr 3 @HPβCD = 6×10⁻ 5 : 1) increase the PL intensity (Supplementary Fig. 24). When the concentration is increased to 50 times, glucose still produces in a detectable PL intensity. The above PL performance suggests that HPβCD plays a dual role: it enhances the interaction of CsPbBr 3 with ionic species and selectively modulates the response to specific organic components, which facilitates the analysis of extracted fingerprints. Considering the individual differences in sweat composition that could affect the specific response of the CsPbBr 3 @HPβCD nanofibers for imaging, we systematically analyzed the concentration-dependent PL intensity responses for nine fingerprint residue components (Supplementary Figs. 25–27 and Supplementary Tables 4–12). The relationship between these representative components and the PL peak shifts of the CsPbBr 3 @HPβCD fibers are summarized in the box plot in Fig. 2 a and Supplementary Table 13. The data indicate that introducing NaCl, KCl, and MgCl 2 causes a blueshift in the PL peak, accompanied by a reduction in the PL intensity. In contrast, upon exposure to organic compounds, their influence on the PL peak wavelength of the CsPbBr 3 @HPβCD fibers is negligible, whereas a general decrease in the PL intensity was observed. Glucose, as an exception, increases the PL intensity at low concentrations but causes PL quenching at higher concentrations. The luminescence properties of the CsPbBr 3 @HPβCD fiber response to sweat residue components can be better understood via time-resolved photoluminescence (TRPL) spectra. As shown in Fig. 2 b and Supplementary Table 14, glucose is the only component that significantly extends the average PL lifetime, whereas the other components reduce the lifetime to varying degrees. To further investigate the chemical interactions between CsPbBr 3 @HPβCD and fingerprint residues, X-ray photoelectron spectroscopy (XPS), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and 1 H nuclear magnetic resonance ( 1 H-NMR) spectroscopy were used. Compared with pristine CsPbBr 3 fibers, introducing various sweat components results in the Cs 3 d , Pb 4 f , and Br 3 d peaks shifting to lower binding energies (Supplementary Figs. 28–30). In contrast, CsPbBr 3 @HPβCD exhibits a more systematic specific response upon exposure to fingerprint residues. For example, when ascorbic acid, laurostearin and squalene are introduced to CsPbBr 3 @HPβCD fibers, the binding energy of the Pb 4 f peak further decreases by 0.40, 0.50 and 0.40 eV, respectively, compared with that of pure CsPbBr 3 fibers. This shift suggests a reduction in the electron affinity and an increase in the electron cloud density around the Cs, Pb, and Br atoms, which can be attributed to electron donation from the additive molecules, likely forming coordination bonds 36 . Conversely, the introduction of various chlorides to CsPbBr 3 @HPβCD fibers causes the Pb 4 f and Br 3 d peaks to shift to higher binding energies (Fig. 2 c and Supplementary Fig. 31). This phenomenon may be ascribed to the partial incorporation of chloride ions (Cl⁻) into the CsPbBr 3 lattice, facilitated by the presence of HPβCD (Supplementary Fig. 20) 44 . Interestingly, the introduction of glucose to CsPbBr 3 @HPβCD increases the binding energies of the Pb 4 f and Br 3 d peaks (Supplementary Tables 15 and 16). This finding may be attributed to glucose synergistically strengthening hydrogen bonding interactions with CsPbBr 3 through multiple hydroxyl groups 45 and HPβCD. As a result, the local environment of CsPbBr 3 is altered, and its electron density decreases. The above XPS results indicate that HPβCD plays a critical role in modulating the chemical interactions between CsPbBr 3 @HPβCD and fingerprint residues, particularly upon exposure to glucose and chlorides, thereby altering the photophysical properties of the material. Owing to the ionic nature of CsPbBr 3 , which arises from the strong ionic interactions inherent to its crystal structure, the material exhibits distinctive characteristics when interacting with other species 46 . The incorporation of HPβCD further enhances these interactions, as its polar internal cavity and hydrophilic exterior provide an ideal microenvironment for interactions with metal ions and stabilizing agents 47 . Specifically, the ionic species interact with the hydroxyl and other functional groups on the HPβCD surface, altering the local electron density. This interaction, in turn, may affect the shielding of nearby protons, as reflected in the chemical shifts observed via 1 H-NMR spectroscopy. The introduction of CsPbBr 3 primarily causes more significant shifts in the exterior protons of HPβCD (H1, H2 and H7) than in the inner cavity protons (H4 and H6), indicating that the interaction predominantly occurs on the external surface of HPβCD 48 . Furthermore, the addition of chloride salts (NaCl, KCl, and MgCl 2 ) to CsPbBr 3 @HPβCD results in distinct shifts in the exterior protons of HPβCD (Supplementary Tables 17 and 18 and Fig. 32). When chloride salts compete with CsPbBr 3 for active sites on the HPβCD surface, the strong electronegativity of chloride ions may disrupt the original electrostatic field, leading to changes in the chemical environment of the exterior protons. Moreover, HPβCD can assist in capturing chloride ions from the system, thus promoting halogen exchange between the chloride ions and the perovskite. In contrast, when glucose is introduced to the CsPbBr 3 @HPβCD complex, the chemical shifts of the exterior protons remain largely unchanged, indicating that glucose does not compete with CsPbBr 3 for the active binding sites of HPβCD. The multiple hydroxyl groups of glucose may provide additional active sites to stabilize CsPbBr 3 , further suppressing the exposure of CsPbBr 3 defects 41 , 49 . Given the above findings, we investigated the interactions between chlorides, glucose and CsPbBr 3 @HPβCD via ATR-FTIR spectroscopy. When CsPbBr 3 is added to HPβCD, the -OH stretching frequency of HPβCD slightly increases, shifting from 3343 cm⁻ 1 to 3350 cm⁻ 1 . Upon the addition of NaCl to CsPbBr 3 @HPβCD, the -OH stretching frequency increases dramatically to 3398 cm⁻ 1 , suggesting that NaCl has a significant influence on the CsPbBr 3 @HPβCD complex (Fig. 2 d). Similarly, the introduction of KCl and MgCl 2 leads to an increase in the intensity and a blueshift of the -OH vibrational band (~ 3343 cm⁻ 1 ) of HPβCD, accompanied by a narrowing of the peak width. This phenomenon may arise from the alteration of the hydrogen bonding network of HPβCD by chloride salts through electrostatic interactions 50 , which affects the electron density distribution of HPβCD 51 , 52 . The impact of glucose can be observed in its interaction with CsPbBr 3 (Fig. 2 e), in which the -OH stretching frequency of glucose increases from 3243 cm⁻ 1 to 3264 cm⁻ 1 upon the introduction of CsPbBr 3 . This result suggests the formation of hydrogen bonds between the CsPbBr 3 and -OH groups. Similarly, the introduction of CsPbBr 3 causes a blueshift in the -OH stretching band of HPβCD, from 3343 cm⁻ 1 to 3350 cm⁻ 1 , indicating a similar interaction of HPβCD with CsPbBr 3 and glucose with CsPbBr 3 . The characteristic peaks of CsPbBr 3 @HPβCD and glucose@HPβCD are almost identical. However, the –OH stretching band of the CsPbBr 3 @HPβCD/glucose complex blueshifts from 3343 cm⁻ 1 to 3318 cm⁻ 1 , accompanied by peak width broadening. This is likely due to the addition of glucose expanding the hydrogen bonding network of HPβCD and further enhancing the synergistic interaction between HPβCD and glucose acting on CsPbBr 3 . To further elucidate the molecular-level interactions of the CsPbBr 3 @HPβCD fibers with NaCl, KCl, and MgCl 2 , we performed density functional theory (DFT) calculations 53 – 55 . First, we investigated Na + , K + , and Mg 2+ doping at the Cs + and Pb 2+ sites, along with halogen exchange, and their effects on the CsPbBr 3 bandgap (Supplementary Tables 19–21). The results indicate that doping Na + and K + at the Pb 2+ site, and Cl⁻ substituted by Br⁻, produces a bandgap that closely matches the experimental results. This observation can be attributed to the ionic radii of Na + (1.02Å) and K + (1.38 Å) being closer to that of Pb 2+ (1.19 Å) than the ionic radius of Cs + (1.67 Å), making them better suited for doping at Pb 2+ sites 56,57 . Additionally, doping at the Pb 2+ site introduces local charge imbalances, which are compensated by lattice defect mechanisms, thereby maintaining the overall material stability. Conversely, Cs + , as a large alkali metal ion, occupies the A-site in the octahedral perovskite structure, where it exhibits high chemical stability. Replacing Cs + with smaller ions such as Na + and K + often destabilizes the structure, leading to collapse 58 . However, based on the aforementioned UV-Vis spectra, the transient surface adsorption of Na + and K + ions, along with halogen exchange, has a minimal effect on the band gap of CsPbBr 3 , suggesting that such processes are unlikely to occur without additional external treatment. Compared to CsPbBr 3 , the CsPbBr 3 @HPβCD fibers demonstrate a stronger response to NaCl, KCl, and MgCl 2 , suggesting that HPβCD plays a crucial role in this system. We calculated the adsorption energies ( E abs ) with and without HPβCD, revealing that HPβCD enhances the E abs of NaCl (–6.42 eV), KCl (–6.64 eV), and MgCl 2 (–6.01 eV) to − 7.27 eV, − 7.16 eV, and − 7.14 eV, respectively (Fig. 2 f and Supplementary Tables 22) 46 . The enhanced E abs values indicate stronger interactions between chloride salts and the CsPbBr 3 @HPβCD complex, particularly through Na + and K + doping at the Pb 2+ site and halogen exchange, significantly influencing the PL properties. For comparison, we synthesized CsPbBr 3 @HPβCD, CsPbBr 3 @K-βCD, and CsPbBr 3 @Cl-βCD fibers, using HPβCD, potassium-enriched β-cyclodextrin (K-βCD), and chloride-enriched β-cyclodextrin (Cl-βCD), respectively (see Methods for details). The results further confirm that the halide exchange effect is more prominent as the emission peak of CsPbBr 3 @Cl-βCD blueshifts to ~ 475 nm (Supplementary Fig. 33). The above computational and experimental results demonstrate that ion-dipole or electrostatic interactions between HPβCD and inorganic chloride salts facilitate halide exchange with CsPbBr 3 . In the case of glucose, the coexisting HPβCD and glucose may synergistically interact with surface defect sites on CsPbBr 3 , potentially inhibiting exposure of CsPbBr 3 and thereby enhancing its fluorescence lifetime. Conversely, organic components other than glucose may undergo stronger interactions with HPβCD, acting as guests that compete with CsPbBr 3 . This competition could increase the exposure of CsPbBr 3 , leading to further quenching of the PL emission. The differential response of CsPbBr 3 @HPβCD fibers to fingerprint residue components is critical for achieving high-precision fiber-based imaging, as illustrated in the mechanism diagram (Fig. 2 f). Photoluminescence characterization and in situ imaging Building on the above comprehensive characterization, we further conducted an in-depth study on the effects of NaCl, KCl, MgCl 2 and glucose on the photophysical properties of CsPbBr 3 @HPβCD fibers via temperature-dependent PL spectroscopy, in situ PL mapping, and in situ fluorescence lifetime imaging microscopy (FLIM). During the temperature-dependent PL analysis, the PL intensities of the CsPbBr 3 fibers, CsPbBr 3 @HPβCD fibers, and CsPbBr 3 @HPβCD fibers with added NaCl or glucose progressively decrease with increasing temperature (Fig. 3 a and Supplementary Fig. 34). The reduction in the PL intensity can be attributed to the increased thermal energy, which induces exciton dissociation and promotes electron-phonon interactions, resulting in substantial PL quenching 59 , 60 . Notably, the temperature-dependent PL intensity of CsPbBr 3 @HPβCD/NaCl shows a more pronounced decline than that of CsPbBr 3 @HPβCD (Supplementary Fig. 35), which may be related to the lattice phase transition of CsPbBr 3 , the loss of surface HPβCD during heating 61 and the defect formation induced by NaCl doping. The PL intensity of CsPbBr 3 @HPβCD/glucose exhibits a more gradual decline with increasing temperature, maintaining a detectable PL signal even at 350 K (Supplementary Fig. 34). Based on the earlier mechanistic investigations, we infer that glucose contributes to passivation effects, mitigating exciton dissociation and electron-phonon interactions under high thermal stress, thereby increasing the stability of CsPbBr 3 perovskites. The exciton binding energy ( E b ) was calculated from the Arrhenius plot via the following Eq. 6 2 : where I 0 is the integrated PL intensity at 0 K, K B is the Boltzmann constant, and A is the Arrhenius coefficient. The CsPbBr 3 @HPβCD/glucose fibers exhibit the highest E b (74.9 meV) compared to CsPbBr 3 fibers (50.8 meV) and CsPbBr 3 @HPβCD fibers (63.4 meV) (Supplementary Fig. 36), which suggests a more effective inhibition of exciton dissociation due to the synergistic effects of glucose and HPβCD. Given the impact of chlorides and glucose on the emission wavelength and lifetime of CsPbBr 3 @HPβCD fibers, we further employed in situ PL mapping to investigate their potential for imaging the spatial distribution of specific components. Wavelength-dependent PL mapping reveals that the emission peaks of the CsPbBr 3 @HPβCD fibers on LFPs range from 490 nm to 520 nm, with distinct regional characteristics (Fig. 3 b and 3 c). The PL emission at 520 nm is predominantly concentrated in the furrows and sweat pores of the fingerprint. The distribution of the 500 nm luminescence accurately outlines the edges of ridges and pores. In comparison, the peak wavelength observed at the ridges surrounding the sweat pore, which corresponds to the region enriched with Na + and Cl⁻, gradually blueshifts to 490 nm (Fig. 1 g and Supplementary Figs. 10–12). Thus, FLIM was performed at PL emission wavelengths of 520 nm and 490 nm. Using the lifetime of the CsPbBr 3 @HPβCD fibers as a reference, a distinct spatial distribution of the relative lifetime was observed (Fig. 3 d). At 520 nm, the long-lifetime regions are primarily concentrated around the pores and fingerprint valleys, corresponding to the areas of stronger emission. Conversely, chloride salts lead to a reduced lifetime, which is evident in the shorter lifetime of 490 nm compared to 520 nm. FLIM at various wavelengths provides additional details for Level 3 fingerprint imaging (Supplementary Fig. 37a-d). Consistent with the PL mapping and EDS results, FLIM indicates that chlorides are primarily distributed around the outer edge of the sweat pores on the ridges, where the emission undergoes a blueshift with a shortened lifetime. Regions with strong emission intensity and a relative lifetime exceeding 100% may provide clues for the distribution of glucose (Supplementary Fig. 37e and 38 and Table 23). Thus, FLIM can effectively visualize fingerprints and potentially provide glucose distribution. Due to precise measurements of sweat glucose concentrations can be utilized to estimate blood glucose levels 63 , there is potential for this NFIT to be integrated with sensing technology 64 in the future, further promoting its application in biomedical diagnostics. Evaluation of the universality, stability, and nondestructiveness of NFIT In light of the high luminescence imaging performance of NFIT, we conducted skin texture extraction experiments under various environmental conditions to evaluate its stability, adaptability and broad applicability systematically. Specifically, clear and high-contrast visualization of LFPs on common substrates, including tinfoil, quartz, iron, glass and plastic, (relatively clear Level-2 fingerprint imaging can be achieved on leather and paper), was achieved with a 10-second electrospinning process. (Fig. 4 a and Supplementary Figs. 39–41). These results demonstrate that NFIT can rapidly acquire high-resolution fingerprint information on a wide range of substrate surfaces, thus meeting the demands for swift, high-definition extraction of fingerprints on typical crime scene items (Supplementary Fig. 42). We further investigated the performance of NFIT in extracting Level 3 features under various finger pressures. As shown in Supplementary Figs. 43 and 44, an increase in pressure caused a reduction in the diameter of the sweat pores, consistent with previously reported results 10 . This finding suggests that NFIT can efficiently capture changes in the sweat pore diameter, providing insights into the force exerted by the individual and offering valuable forensic clues. The temporal stability and imaging consistency of NFIT in fingerprint extraction were also evaluated. Experiments demonstrate that even for aged LFPs left for 37 days, NFIT can still deliver clear Level 3 fingerprint features (Supplementary Figs. 45 and Fig. 46). This result indicates that NFIT significantly outperforms traditional humidity-responsive fingerprint imaging techniques, which often struggle to extract complete Level 3 fingerprint information once the moisture in the fingerprint evaporates. Moreover, fingerprint imaging generated via CsPbBr 3 @HPβCD nanofibers exhibits impressive long-term stability (Level 3 ≥ 81 days, Level 2 ≥ 108 days) see Supplementary Fig. 47. The CsPbBr 3 @HPβCD nanofibers also demonstrate strong resistance to photodegradation. Under continuous high frequency laser (20 MHz, 405 nm) irradiation at a single point, the PL intensity remains stable, with an estimated half-life of 158 minutes (Supplementary Fig. 48). The NFIT performance was further assessed under extreme environmental conditions with temperatures ranging from + 50°C to − 50°C. At PL mapping wavelengths of 520 nm and 490 nm, NFIT consistently captures clear Level 3 features (Fig. 4 b and 4 c). Combined with its portable design, it is suitable for on-site collection and analysis under extreme temperature conditions. Moreover, we expanded the extraction area from fingerprints to the entire palm to evaluate the ability of NFIT to capture the full ridge patterns. As shown in Fig. 4 d and 4 e, NFIT successfully captures whole palm print information, providing high-resolution details for sweat pores (Supplementary Fig. 49). This highlights the potential of NFIT for applications involving photocopying whole-body skin textures. In actual forensic and criminal investigation scenarios, using nondestructive techniques for DNA is crucial. Therefore, we investigated the impact of NFIT on DNA identification to ensure its applicability to nondestructive analysis. Based on short tandem repeat (STR) analysis of the data of extracted DNA with or without electrospun CsPbBr 3 @HPβCD nanofibers, NFIT has no negative effects on STR analysis, as the two samples yield consistent results (Supplementary Figs. 50 and 51). This confirms the effectiveness of NFIT in extracting fingerprints without damaging DNA evidence. In summary, NFIT demonstrates adaptability across a wide range of extreme environments. Whether under the scorching heat of the Sahara or the freezing temperatures of polar regions, this technology can be easily applied to various substrate surfaces via a portable electrospinning device, enabling rapid, convenient and high-resolution onsite fingerprint imaging. Portable high-resolution fingerprint imaging and data analysis system Leveraging the high-resolution imaging capability and broad applicability of NFIT, we self-developed a micro-image algorithm that integrates portable fingerprint imaging devices with rapid data analysis. This integrated system consists of a handheld mini-electrospinning device and a smartphone (Supplementary Fig. 52). The fingerprint analysis program can be embedded in a smartphone or a computer, which serves as the data processing platform (Fig. 5 a and Supplementary Fig. 53). The high resolution of the extracted images ensures precise capture of fingerprint features. Coupled with the user-friendly program, the entire extraction and analysis process becomes highly efficient, allowing collection and storage of 100 fingerprints within only 1 hour. As a proof-of-concept, we used this system for fingerprint extraction and analysis, with the results shown in Fig. 5 b. The images can then be imported into the program (see Methods) for image processing. This program can accurately extract grayscale values from multiple fingerprint regions within the image (Supplementary Fig. 54). The analysis regions can be user-defined, and the number of sampling points can be adjusted (Supplementary Movie #2). Unlike traditional methods that rely on "drawing lines to take points", our integrated NFIT system directly converts large areas of image information into grayscale values. Additionally, depending on the number of sampling points, images of various resolutions can be generated (Supplementary Fig. 55). Owing to the efficiency of the integrated NFIT system, extensive computational resources are not required, even when managing large datasets. For example, the data from the four charts in Fig. 5 a occupy only 894 K bytes after processing by the integrated NFIT system. This substantial reduction in computational and storage demands significantly lowers operational complexity and maintenance costs. Simultaneously, the system converts digitized grayscale data into 2D/3D images, enabling swift visualization and comparison of fine fingerprint features. The integrated NFIT system can directly capture data and construct models from a photograph of a real fingerprint, allowing the obtainment of a 3D model that accurately aligns with the model generated through NFIT, thus validating the precision of the entire extraction and modeling process (Fig. 5 c, Supplementary Fig. 56 and Supplementary Movie #3). Further comparisons reveal that the 3D reconstruction models obtained via NFIT provide more detailed fingerprint features, which is attributable to the high contrast achieved in fingerprint luminescence imaging (Supplementary Fig. 57–59). Additionally, the finger surface morphology can be reconstructed through mirroring inversion of the 3D fingerprint model obtained by the integrated NFIT system (Supplementary Fig. 60). This mirroring model provides clear information on the ridge patterns and more details, making it valuable for forensic identification and high-precision authentication applications. Thus, this integrated NFIT system provides comprehensive functionalities, including fingerprint extraction and imaging, image conversion and storage, data analysis and 3D model reconstruction. It has significant advantages over existing fingerprint collection techniques (Supplementary Table 24): 1. The device is compact, lightweight (< 400 g) and easy to assemble, reducing the complexity and operational requirements compared with traditional laboratory instruments; 2. The entire system is low-cost (< $ 800, Supplementary Table 25), making it highly suitable for field operations and large-scale deployment; 3. The system is optimized for an efficient integrated workflow that encompasses fingerprint extraction, imaging, data storage, and analysis (Supplementary Movie #4); 4. The system employs a 3D reconstruction algorithm, thus providing high-precision features and a visually presented fingerprint morphology for forensic and identity authentication applications. Integrated NFIT System for Body Skin Photocopying and 3D model construction Utilizing the NFIT system, we have achieved rapid, high-precision photocopying of skin textures from diverse body regions, including the forehead, abdomen, handbacks, and soles of the feet. This process consistently delivers high-definition skin texture images within just 5 minutes and it overcomes the challenges posed by areas with minimal sweat secretion, such as the hand back. Our system employs CsPbBr 3 @HPβCD as a luminescent imaging medium, uniquely responding to sweat secretions. By using an electrospinning mechanism, we enable swift and precise imaging without reliance on intricate feedback systems or chemical pre- or post-processing, ensuring operational simplicity and efficiency. Moreover, our NFIT system excels in generating 3D models from these high-resolution skin texture images (Fig. 6 and Supplementary Fig. 61). This capability extends even to regions like the hand back, where sweat secretion is limited, demonstrating the system’s exceptional sensitivity and adaptability for the whole human body skin. These 3D skin texture datasets have significantly enhanced the fidelity and detail optimization in 3D modeling and rendering. This advancement supports the creation of hyper-realistic works in game development, animation production, and film special effects, providing realism. Beyond creative applications, the system has propelled innovations in virtual try-on and personalized customization technologies. By enabling the accurate reproduction of individual skin textures, consumers can experience tailored services with unprecedented precision and convenience. Additionally, the system offers potential in medical diagnostics and health monitoring, providing a non-invasive approach to capturing skin textures for analysis of dermatological conditions, even in areas of the traditionally challenging for imaging. These advancements underscore the NFIT system as a transformative tool in high-resolution skin imaging and 3D modeling, redefining possibilities across industries. Discussion We developed an innovative nanofiber-based imaging technique (NFIT) using CsPbBr 3 @HPβCD luminescent nanofibers, achieving real-time, multidimensional and multiregional imaging of human skin textures with unprecedented precision. The NFIT system utilizes unique chloride and glucose recognition mechanisms, enabling accurate sweat pore imaging with a similarity of 93.24 ± 4.6%. It supports large-area imaging across diverse materials while maintaining high-resolution (1450 dpi) image quality under extended storage (Level 3 ≥ 81 days, Level 2 ≥ 108 days) and extreme temperatures (–50°C to + 50°C). Beyond capturing detailed 2D skin surface features, NFIT facilitates the construction of high-precision 3D skin morphology models. These data revolutionize biometric security systems, offering enhanced fingerprint and palm print recognition accuracy. Furthermore, the data serve as invaluable resources for educational and research purposes in biology and anthropology while advancing personalized medicine and dermatology. This technology sets a benchmark in human skin photocopying, addressing critical challenges in precision, safety, and usability and unlocking transformative applications across diverse fields. Methods Materials Cesium bromide (CsBr, 99.9%) and lead bromide (PbBr 2 , 99.9%) were purchased from Advanced Election technology Co., Ltd. The N , N -dimethylformamide (DMF, AR),and Dimethyl sulfoxide (DMSO, AR) were purchased from Sinopharm Chemical Reagent Co., Ltd. Hydroxypropyl-β-cyclodextrin (HPβCD) and deuterated dimethyl sulfoxide (DMSO–d 6 ) were purchased from Shanghai Macklin Biochemical Co., Ltd. Thermoplastic Polyurethanes (TPU) was purchased from Qingdao Nuokang Environmental Protection Technology Co., Ltd. Sodium chloride (NaCl, AR), magnesium chloride (MgCl 2 , AR), potassium chloride (KCl, AR) and glucose were purchased from Sinopharm Chemical Reagent Co., Ltd., Lauro stearin (98%) and squalene (95%) were purchased from Shanghai Macklin Biochemical Co., Ltd. Ascorbic acid (99%) and uric acid (99%) were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd. Preparation of electrospinning solution and LFPs recognition process CsBr (0.0213 g), PbBr 2 (0.0367 g), and HPβCD (0.05 g) were combined and ground using a mortar and pestle for 1 minute. DMF (0.25 ml) and DMSO (0.25 ml) were then added to the mixture, which was shaken and allowed to sit at room temperature for 1 hour. Subsequently, 100 µl of this solution was mixed with 1 ml of a 16% TPU solution (the solvent is DMF) and stirred for 10 seconds to fabricate the electrospinning solution. The final solution was loaded into a handheld electrospinning device, allowing for the rapid generation of LFP images, with complete imaging achievable in approximately 10 seconds. Preparation of K-βCD To prepare K-βCD, a mixture of β-CD (0.68 g, 0.6 mmol) and KOH (0.269 g, 4.8 mmol) was dissolved in H 2 O (12 ml) in a beaker and sonicated for 5 minutes to ensure homogeneous dispersion. Methanol (12 ml) was subsequently added, and the solution was stirred continuously for 1 hour. The mixture was then subjected to microwave irradiation at 100 W for 4 minutes and 30 seconds to facilitate crystal growth. Following this step, the reactant was carefully added dropwise to a large volume of hot methanol, which acted as a size-controlling agent. The resulting crystals were collected by centrifugation at 7000 rpm and washed three times with methanol. Finally, the crystals were dried under vacuum at 50°C for 12 hours. The dried product, K-βCD, was obtained by gentle grinding of the crystals. Preparation of Cl-βCD To synthesize Cl-βCD, a mixture of β-CD (1.9 g, 1.5 mmol) and imidazole (1.5 g, 22.5 mmol) was dissolved in DMF (60 ml) under a nitrogen atmosphere. Anhydrous phenylsulfonyl chloride (3.9 g, 22.5 mmol) was then added, and the reaction mixture was stirred at room temperature for 2 hours. Subsequently, the reaction was heated to 70°C and maintained at this temperature for 24 hours. After completion, the solvent was removed by distillation, and 200 ml of water was added. The pH was adjusted by the addition of 2 mol L − 1 NaOH solution until the solution was fully alkaline. The resulting mixture was stirred for an additional 2 hours, and the precipitate was collected by filtration, washed thoroughly with H 2 O and acetone, and then recrystallized to yield purified Cl-βCD. Characterization A custom-built fluorescence microscopy system was employed to observe LFPs fluorescence imaging. The microscope used was a DO-BX53 (Olympus) equipped with a mercury lamp as the excitation source (300–500 nm) and 2.5 ×-100 ×objective lens. The morphological images were captured using a Regulus 8230 (Hitachi) cold-field emission scanning electron microscope (SEM) which was equipped with a X flash 5060F (Bruker) detector for energy dispersive X-ray spectra and mapping (EDS). The high-resolution transition electron microscopy (HRTEM) images were captured with a Tecnai G2 F30 (S-TWIN) transition electron microscope at an accelerating voltage of 300 kV, which was equipped with an X Flash (STEM-HAADF) detector for EDS mapping and Gatan Ultrascan CCD camera for high-resolution imaging. The binding energy was characterized on an ESCALAB 250Xi+ (Thermo Fischer) X-ray Photoelectron Spectroscopy (XPS). Fourier-transform infrared (FTIR) spectra were obtained by Cary 610/670 (Agilent). The nuclear magnetic resonance (NMR) was performed on Quantum-I plus 600 (Oxford). A FLS1000 fluorescence spectrometer (Edinburgh Instruments) was used to test the (PL spectra and TRPL. The temperature-dependent measurement was conducted with DN Optical Cryostats (Oxford Instruments) as an apparatus on FLS1000. Fluorescent lifetime imaging microscopy (FLIM) was performed on an ECLIPSE Ni-U microscope (Nikon) with a 5× -10 ×objective lens, which was coupled with FLS1000 via optical fibers. A 405 nm picosecond pulsed diode laser was used as the excitation source for TRPL analysis and FLIM. The detailed parameters were as follows: a spatial resolution of 10 µm, a dwell time of 2 seconds per point, using the time-correlated single photon counting technique. PL mapping was performed on inVia Qontor (REINISHAW) with a 40× objective lens. The sample was excited by a 325 nm laser and the spatial resolution was 10 µm. Temperature-dependent PL mapping was conducted with a THMS600 temperature control stage equipped on inVia Qontor. The solid-state UV-Vis absorption spectra were conducted on Shimadzu with an integrating sphere. The LFP was spun using a hand-held electrospinning device of E-01 (Foshan Qingzi Precision Measurement and Control Technology Co., Ltd). Evaluation of the effect of CsPbBr 3 @HPβCD electrospinning treatment on the identification of DNA Blood samples were collected from a volunteer. Samples were prepared by depositing blood drops onto filter paper, with or without electrospun CsPbBr 3 @HPβCD nanofibers. DNA was extracted from these blood samples using the QIA amp DNA Blood Mini Kit (Qiagen, Hilden, Germany). The final concentration of DNA was 3 ng per PCR. STR analysis was performed using the Goldeneye DNA Identification System 20A (peoplespot, Beijing, China). The PCR products were analyzed using ABI 3130xl Genetic Analyzer (Applied Biosystems). Fluorescence was quantified, and the precise size of the DNA fragments was calculated with Genemapper software 3.2 (Applied Biosystems). Computational details First-principles density functional theory (DFT) calculations were performed using the Vienna abinitio Simulation Package (VASP) 47 with the projector augmented wave (PAW) method 48 . The exchange-functional was treated within the generalized gradient approximation (GGA) employing the Perdew-Burke-Ernzerhof (PBE) functiona 49 . The long-range van der Waals interactions are accounted for through the DFT-D3 approach. A plane wave basis set with an energy cutoff of 500 eV was employed, and the geometry relaxation was performed until the forces on each atom were below 0.03 eV Å⁻ 1 . The Brillouin zone was sampled using 1 × 1 × 1 k-point grid. Self-consistent calculations were conducted with an energy convergence threshold of 10⁻ 5 eV. A vacuum region of 15 Å was added along the z direction to prevent interactions between periodic structures. Self-developed skin texture processing analysis program The self-developed Level 3 fingerprint analysis program (see Supplementary Data 1) provides a comprehensive two-step data processing workflow, optimized for efficient analysis and visualization of high-resolution fingerprint data. In the first step, the software converts color images to grayscale, allowing for region-specific intensity analysis within user-defined regions of interest (ROI). The grayscale intensity data, including pixel coordinates and values, is exported as structured CSV or Excel files, ensuring compatibility with subsequent analysis stages. In the second step, this exported grayscale data is treated as point cloud input to generate detailed 2D grayscale images and 3D models, enhancing visualization and supporting interactive exploration of fingerprint features. The program’s graphical user interface (GUI) enables real-time processing and immediate feedback, improving usability across both analysis steps. Core implementation technologies include NumPy for efficient numerical computation, OpenCV and Pillow (PIL) for robust image manipulation, PyVista for 3D visualization, and Pandas for managing data exports. The program also employs Matplotlib to render 2D distribution charts and OpenPyXL to facilitate formatted Excel outputs with embedded visualizations. By ensuring smooth data flow between steps, the system minimizes manual data handling and enhances accuracy, reducing the risk of errors and enabling researchers to focus on analytical outcomes. This integrated approach supports a range of forensic and research applications, with potential future expansions to include automated data pipelines for even more efficient transitions from image processing to 3D visualization. Data availability The data that support the findings of this study are available. Code availability The code used in this study is openly available on GitHub 65 , 66 without any access restrictions. Declarations Ethics Approval Statement: This study was approved by the Institutional Review Board (IRB)/Ethics Committee of the School of Chemical Engineering and Technology, Instrumental Analysis & Research Center, First Affiliated Hospital of Sun Yat-sen University, and the School of Chemistry and Chemical Engineering, Yangzhou University. Participant Consent Statement: Written informed consent was obtained from all participants prior to their enrollment in the study. Data availability The data that support the findings of this study are available. Code availability The code used in this study is openly available on GitHub 65,66 without any access restrictions. Acknowledgement This work is financially supported by the National Natural Science Foundation of China (22305215, 52402203), Jiangsu Province Youth Fund Project (BK20240893) and the State Key Laboratory of Coordination Chemistry. Special thanks to Mu-Zi Yang and Xiao-Ning Cheng from the Instrumental Analysis and Research Center of Sun Yat-sen University for their support in PL mapping and SEM analysis, Gangfeng Ouyang's instrumental support in TEM and NMR analysis. The authors express their gratitude to Mr. Shuai Yuan (from Yangzhou Xuntu Network Technology Co., Ltd.) for his valuable assistance in developing the Level 3 fingerprint analysis program. Author contributions Tian Tian, Yu-Xin Chen and Huan Pang designed the experiments. Tian Tian, Huixuan Han and Xinyi Lin carried out the fabrication of CsPbBr 3 @HPβCD nanofibers. Huixuan Han, Xinyi Lin, Tian Tian and Huan Pang carried out DFT calculations. The STR analysis was performed by Chao Wu. The characterizations were carried out by Hui Kang, Meifang Yang, Zihao Chen, Yuansheng Jiang, Wen-Guang Li, Xueqing Chang, Qin Xu and Yu-Xin Chen. Tian Tian, Yizhou Zhang and Yu-Xin Chen completed photoluminescence and DNA experiments. 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Supplementary Files SupplementaryData.docx Dataset 1 SupplementaryMovie1.mp4 Luminescence imaging of latent fingerprints by NFIT SupplementaryMovie2.mp4 Data Conversion from fingerprint images to grayscale value data SupplementaryMovie3.mp4 Data Conversion from grayscale value data to reconstruct 3D finger surface SupplementaryMovie4.mp4 LFPs extraction by NFIT SupplementaryInformation.docx Supplementary Information Cite Share Download PDF Status: Published Journal Publication published 04 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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University","correspondingAuthor":false,"prefix":"","firstName":"Yuansheng","middleName":"","lastName":"Jiang","suffix":""},{"id":502553085,"identity":"52153c76-3fbc-44b2-b498-d9a652c5c4ad","order_by":9,"name":"Wen-Guang Li","email":"","orcid":"","institution":"Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Wen-Guang","middleName":"","lastName":"Li","suffix":""},{"id":502553086,"identity":"b867ebc8-ff2d-45a3-a833-7de5a9585e11","order_by":10,"name":"Xueqing Chang","email":"","orcid":"","institution":"Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xueqing","middleName":"","lastName":"Chang","suffix":""},{"id":502553087,"identity":"e15dad77-2629-4a9c-9e5c-20d31325356d","order_by":11,"name":"Yi-Zhou Zhang","email":"","orcid":"https://orcid.org/0000-0001-9154-0085","institution":"King Abdullah University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Yi-Zhou","middleName":"","lastName":"Zhang","suffix":""},{"id":502553088,"identity":"99c76af9-cb3b-42b8-b4c9-f9fb2cace10f","order_by":12,"name":"Qin Xu","email":"","orcid":"","institution":"Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Qin","middleName":"","lastName":"Xu","suffix":""},{"id":502553089,"identity":"2904e049-ed29-4b0e-8d38-f66468f6b004","order_by":13,"name":"Yu-Xin Chen","email":"","orcid":"https://orcid.org/0009-0000-4790-6123","institution":"Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Yu-Xin","middleName":"","lastName":"Chen","suffix":""},{"id":502553090,"identity":"7449d6af-42f0-47f1-ac5f-86b0a2ef712b","order_by":14,"name":"Gangfeng Ouyang","email":"","orcid":"https://orcid.org/0000-0002-0797-6036","institution":"Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Gangfeng","middleName":"","lastName":"Ouyang","suffix":""}],"badges":[],"createdAt":"2024-12-17 06:05:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5658648/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5658648/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-64703-5","type":"published","date":"2025-11-04T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90894864,"identity":"37e77ed6-9c66-4919-b5f7-1d2b0256149b","added_by":"auto","created_at":"2025-09-09 11:31:21","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1861110,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic illustration of the fingerprint imaging process and morphological characterization.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e Schematic diagram of the preparation of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD nanofibers on LFPs\u003cstrong\u003e. b \u003c/strong\u003eImage of a real fingerprint.\u003cstrong\u003e c \u003c/strong\u003eLuminescence image obtained via NFIT for a real fingerprint marked with Level 3 fingerprint characteristics. \u003cstrong\u003ed \u003c/strong\u003eOverlay of the fingerprint luminescence image obtained via NFIT and the real fingerprint image. \u003cstrong\u003ee \u003c/strong\u003eSEM image of the LFP with electrospun CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD nanofibers. \u003cstrong\u003ef \u003c/strong\u003eMagnified SEM image of the LFP with electrospun CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD nanofibers. \u003cstrong\u003eg\u003c/strong\u003e SEM-EDS mapping of the distribution of sodium.\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/630d4ba8184e4c879ab0cd5c.jpeg"},{"id":90894860,"identity":"2e6ce10f-c187-49c4-933b-45cbd52cdf3f","added_by":"auto","created_at":"2025-09-09 11:31:21","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1233500,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpectral response and chemical interactions of CsPbBr\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e@HPβCD to sweat residue components. a \u003c/strong\u003eBox plots of the dependence of the PL peak shift in CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD fibers on the concentration variation of sweat residue. \u003cstrong\u003eb\u003c/strong\u003e TRPL spectra of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD fibers exposed to sweat components. \u003cstrong\u003ec \u003c/strong\u003eXPS spectra of Pb 4\u003cem\u003ef\u003c/em\u003e for CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD fibers with the sweat residue. ATR-FTIR spectra of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD with the addition of (\u003cstrong\u003ed\u003c/strong\u003e) chloride and (\u003cstrong\u003ee\u003c/strong\u003e) glucose.\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ef\u003c/strong\u003e Adsorption energy simulation model of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD with the addition of chloride. \u003cstrong\u003eg\u003c/strong\u003e Illustration of the response mechanism of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD fibers to sweat residues.\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/b1c56de74c225da9cd411070.jpeg"},{"id":90894859,"identity":"30ef094c-2d36-4e1b-ab0c-28e52900d731","added_by":"auto","created_at":"2025-09-09 11:31:21","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1984009,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePL characterization of and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein situ\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e fingerprint PL imaging with CsPbBr\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e@HPβCD nanofibers. a \u003c/strong\u003eTemperature-dependent PL of CsPbBr\u003csub\u003e3\u003c/sub\u003e, CsPbBr\u003csub\u003e3 \u003c/sub\u003e@HPβCD, CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD/glucose and CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD/NaCl fibers. \u003cstrong\u003eb \u003c/strong\u003eBright field image and peak wavelength distribution for CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD\u003csub\u003e \u003c/sub\u003efiber fingerprint imaging, scale bar: 500 µm. \u003cstrong\u003ec\u003c/strong\u003e Wavelength-dependent PL mapping at 520 nm, 510 nm, 500 nm and 490 nm of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD\u003csub\u003e \u003c/sub\u003efibers in response to fingerprint residues, scale bar: 500 µm. \u003cstrong\u003ed\u003c/strong\u003e FLIM at 520 nm and 490 nm, scale bar: 1 mm.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/d4d262e81f77b6b4671fa1ff.jpeg"},{"id":90897067,"identity":"301000b4-5b4c-4f83-8103-9f1d3d725796","added_by":"auto","created_at":"2025-09-09 11:39:22","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2494712,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eǀ Universality and stability characterization of NFIT. a \u003c/strong\u003eNFIT images of LFPs on various substrates, scale bar: 1 cm. Temperature-dependent PL mapping of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD nanofiber-based fingerprint images at (\u003cstrong\u003eb\u003c/strong\u003e) 520 nm and (\u003cstrong\u003ec\u003c/strong\u003e) 490 nm. \u003cstrong\u003ed\u003c/strong\u003e Real palm image. \u003cstrong\u003ee\u003c/strong\u003e The palm imaging by NFIT.\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/2674da787515918191ff521c.jpeg"},{"id":90894863,"identity":"1fa05c2a-6a8e-413d-aeff-e40c9f52eaea","added_by":"auto","created_at":"2025-09-09 11:31:21","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1071375,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntegrated NFIT system for fingerprint data extraction and processing.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea \u003c/strong\u003eIntegrated NFIT system for fingerprint extraction and imaging.\u003cstrong\u003e b\u003c/strong\u003e Conversion and storage from fingerprint image to grayscale data. \u003cstrong\u003ec\u003c/strong\u003eGrayscale value distributions and the corresponding 3D models.\u003c/p\u003e","description":"","filename":"image5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/a8f7b202c924745a04bf5385.jpg"},{"id":90897656,"identity":"28f4a479-0ae5-404d-9c28-f857d524c951","added_by":"auto","created_at":"2025-09-09 11:47:21","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1022425,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe workflow of integrated NFIT system for body skin photocopying and 3D model construction. \u003c/strong\u003eIntegrated NFIT system for forehead, abdomen, hand backs, and soles of feet texture photocopying and 3D modeling, the scale bar: 1 cm.\u003c/p\u003e","description":"","filename":"image6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/67cc0750378f80489eafde93.jpeg"},{"id":95179741,"identity":"be0a19c0-123b-4841-b627-2b928b41b7ae","added_by":"auto","created_at":"2025-11-05 08:09:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10973823,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/6736c1bd-5617-457f-a547-b0d5be95f1c4.pdf"},{"id":90897061,"identity":"43a6fe08-21e2-46e7-a280-7d45b73f364a","added_by":"auto","created_at":"2025-09-09 11:39:21","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29787,"visible":true,"origin":"","legend":"Dataset 1","description":"","filename":"SupplementaryData.docx","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/716ed3fc05cc12eb9c9f0326.docx"},{"id":90897062,"identity":"1f755272-64e6-4dc8-acf4-3446fb70644f","added_by":"auto","created_at":"2025-09-09 11:39:21","extension":"mp4","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4433391,"visible":true,"origin":"","legend":"Luminescence imaging of latent fingerprints by NFIT","description":"","filename":"SupplementaryMovie1.mp4","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/b6735ab2b1ced25ec395377b.mp4"},{"id":90897655,"identity":"81de1a64-249f-4c3e-8bc4-4c4d934777f7","added_by":"auto","created_at":"2025-09-09 11:47:21","extension":"mp4","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1350135,"visible":true,"origin":"","legend":"Data Conversion from fingerprint images to grayscale value data","description":"","filename":"SupplementaryMovie2.mp4","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/7aa3ae5e3388572bd3d01f3b.mp4"},{"id":90897064,"identity":"2756172b-4d70-480b-93cc-1854cb152fc8","added_by":"auto","created_at":"2025-09-09 11:39:21","extension":"mp4","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":4513467,"visible":true,"origin":"","legend":"Data Conversion from grayscale value data to reconstruct 3D finger surface","description":"","filename":"SupplementaryMovie3.mp4","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/d2c04dcf9c4025fb518d3d57.mp4"},{"id":90897131,"identity":"d775e563-35f5-4345-b2e1-0046af983745","added_by":"auto","created_at":"2025-09-09 11:39:27","extension":"mp4","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":8015580,"visible":true,"origin":"","legend":"LFPs extraction by NFIT","description":"","filename":"SupplementaryMovie4.mp4","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/e0513f1b9ba631a42c8bdfc2.mp4"},{"id":90897078,"identity":"f781d3cc-3ec5-4a45-9096-c6622b2a2d28","added_by":"auto","created_at":"2025-09-09 11:39:22","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":34345554,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-5658648/v1/47005ae60bd6afa907e5b563.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Luminescent Nanofibers for Human Skin Textures Photocopying","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSkin, the human body's largest organ, harbors numerous secrets within its distinctive texture\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, sweat gland distribution\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, and biological properties\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, awaiting precise capture and analysis\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e.\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. For instance, fingerprints, as the most commonly used feature of the skin, are stable and unique for each individual due to the interplay of genetic and environmental factors during fetal development\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This makes them an excellent tool for personal identification\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, crime scene investigations\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, and security applications\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Thus, analytical techniques have been developed based on Raman spectroscopy\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, mass spectrometry\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, Fourier transform infrared spectroscopy (FTIR)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, luminescence imaging\u003csup\u003e\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and other techniques\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Among the materials applied in these imaging techniques, luminescent materials such as carbon dots\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, perovskite quantum dots\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, aggregation-induced emissive materials\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and organic dyes\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e exhibit good imaging performance. However, on-site analysis requires exceptional stability, accuracy, and safety imaging materials, posing significant challenges for technological advancements\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Furthermore, traditional skin imaging techniques are constrained by hardware limitations\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, lens quality, image processing algorithms\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e and shooting environments\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, thereby impeding the attainment of high-resolution images of micrometer-scale skin textures\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Thus, a universal high-resolution skin imaging technique combined with a data analysis system for identity verification, forensic science and criminal investigations has not yet been fully developed.\u003c/p\u003e\u003cp\u003eTo address these issues, we have developed a low-cost, portable nanofiber-based imaging technique (NFIT) for human skin texture photocopying, using CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD luminescent nanofibers. This NFIT facilitates \u003cem\u003ein situ\u003c/em\u003e, multi-regional imaging of skin microsurface morphology by harnessing a unique wavelength-dependent photoluminescence mapping technique, utilizing trace amounts of sweat residue. When benchmarked against real fingerprint tertiary feature data, the NFIT exhibits a remarkable micron-scale imaging similarity of 93.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6%, coupled with high-resolution fingerprint imaging (1450 dpi). This underscores its exceptional proficiency in capturing intricate skin texture details, ranging from the minute structure of individual sweat glands to extensive textures across the palm, sole, abdomen and dorsum of the hand. Notably, the NFIT adopts a non-contact imaging paradigm, eliminating chemical pre/post-treatment requirements. This attribute ensures compatibility with DNA evidence collection while minimizing chemical interference, thereby presenting a dependable and convenient tool for forensic and security applications. Moreover, NFIT maintains high-definition imaging across a broad temperature range of \u0026minus;\u0026thinsp;50\u0026deg;C to +\u0026thinsp;50\u0026deg;C and delivers excellent long-term imaging stability (level 3\u0026thinsp;\u0026ge;\u0026thinsp;81 days, level 2\u0026thinsp;\u0026ge;\u0026thinsp;108 days). This robustness ensures reliable operation under diverse harsh conditions, offering robust support for on-site analysis.\u003c/p\u003e\u003cp\u003eBeyond its high precision, low cost (\u0026lt; \u003cspan\u003e$\u003c/span\u003e800), and portability (\u0026lt;\u0026thinsp;400 grams), the NFIT's extensive applicability enables users to extract and photocopy skin texture images in real-time, irrespective of location or time, thereby supporting 3D skin texture model reconstruction. Importantly, the entire digitization process necessitates minimal computational resources\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, thereby reducing the complexity and cost associated with system development and maintenance. This functionality significantly enhances operational efficiency and brings unparalleled convenience and substantial contributions to high-precision 3D portrait construction, dermatology, regenerative medicine, forensic analysis, and other pertinent fields.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eFingerprint Imaging Process and Morphological Characterization\u003c/h2\u003e\n \u003cp\u003eCsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanocrystals were synthesized via grinding (see details in the Methods section). In this study, amphiphilic thermoplastic polyurethane (TPU) was selected as the electrospinning matrix because of its lypohydrophilic character compared with polystyrene (Supplementary Fig.\u0026nbsp;1). This characteristic ensures reliable extraction of fingerprint residues, primarily consisting of sweat and sebum, and potentially enhances the luminescence response. The CsPbBr\u003csub\u003e3\u003c/sub\u003e @HP\u0026beta;CD nanocrystals were then blended with TPU to form a mixed solution prepared as an electrospinning ink. Consequently, a handheld mini electrospinning device (ca. 10 cm in length) was used to spray CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers onto the sample to form luminescent nanofibers for imaging. Herein, fingerprints were employed as a representative of detailed skin textures to examine the imaging capability of NFIT. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea and Supplementary Movie #1, high-definition Level 3 fingerprint imaging can be obtained efficiently within 10 seconds. The Level 3 fingerprints offer the most intricate details, such as ridge shapes, pore positions, incipient ridges and scars\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. To evaluate the accuracy of NFIT, we captured a fingerprint luminescence image via NFIT and compared it to the same zone of an actual fingerprint photo for the same individual (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb). The luminescence image clearly revealed the sweat pore features, including the pore size, shape, location, distribution, frequency, and pore-to-pore interspacing (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec). Overlaying Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb with 1c, NFIT evidently allows high-precision visualization of Level 3 fingerprint features, with a matching similarity of over 93.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6% compared to the real fingerprint (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ed, Supplementary Figs.\u0026nbsp;2\u0026ndash;3 and Supplementary Table\u0026nbsp;1.), which is the highest accuracy as reported for sweat pore imaging to date\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Notably, unlike traditional methods in which sweat pore information is indirectly obtained after epidermal imaging, NFIT both directly responds to sweat pore and epidermal texture characteristics, providing a more precise and direct representation (Supplementary Fig.\u0026nbsp;4). Additionally, we compared the fingerprint images extracted by NFIT with those obtained via traditional ink-based fingerprinting and commercial capacitive fingerprint sensors. It can be seen that NFIT produces higher-quality fingerprint images with more abundant fingerprint features (Supplementary Fig.\u0026nbsp;5). Notably, NFIT employs a fully noncontact approach throughout the skin texture extraction process, allowing users to press their skin on any substrate and lift them without any contact with chemical reagents. This ensures both chemical safety and hygiene. In addition, the operational safety of the imaging process was thoroughly evaluated. The exposure dose per fingerprint area (ca. 4 cm\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e) was limited to DMF\u0026thinsp;\u0026le;\u0026thinsp;4 \u0026micro;L (3.8 mg) and DMSO\u0026thinsp;\u0026le;\u0026thinsp;0.48 \u0026micro;L (0.5 mg) (Supplementary Table\u0026nbsp;2), which are well below the 8-hour weighted average exposure limits set by the Occupational Safety and Health Administration (OSHA)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. ICP-MS analysis revealed that Pb concentration leached during each fingerprint imaging process was 0.003 mg/L (Supplementary Table\u0026nbsp;3). This value is significantly lower than the 0.01 mg/L drinking water standard in the Guidelines for Drinking-water Quality published by World Health Organization (WHO)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, indicating negligible risk to human health\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. To elucidate the mechanism of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers\u0026rsquo; response to sweat residues, we investigated their morphology via scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM) and energy dispersive spectroscopy (EDS) mapping. The TPU polymer forms a fibrous scaffold that effectively holds the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanocrystals (Supplementary Figs.\u0026nbsp;6 and 7). SEM images of real fingerprints and latent fingerprints (LFPs) obtained via NFIT are shown in Supplementary Fig.\u0026nbsp;8. In the absence of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers, the LFPs exhibit distinct regional contrast between the light and dark areas (Supplementary Fig.\u0026nbsp;6a). EDS mapping reveals that the darker regions correspond to organic components primarily composed of carbon, which is predominantly concentrated in the fingerprint ridges, except for at the sweat pores (Supplementary Fig.\u0026nbsp;9). In contrast, after electrospinning, the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers (diameter\u0026thinsp;~\u0026thinsp;27.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2 nm) are uniformly distributed across the entire surface, without preferential accumulation in the luminescence-intense regions, namely sweat pores and ridges (Supplementary Fig.\u0026nbsp;8b-d). The crystalline nature of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD on TPU fibers was confirmed by HRTEM (Supplementary Fig.\u0026nbsp;8e and 8f). The crystalline regions display distinct lattice fringes, with an interplanar spacing of 0.210 nm, corresponding to the (110) crystal plane towards highly crystalline CsPbBr\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e37\u003c/sup\u003e. Excitingly, EDS analysis demonstrates that NFIT not only accurately maps the real fingerprint features but also reveals the sodium chloride (NaCl) distribution in the fingerprint sweat (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ee-g, and Supplementary Figs. 10\u0026ndash;12), represented as the dark regions in the luminescence image (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec). In contrast, in the EDS mapping of the corresponding fingerprint residues without CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers, the Na and Cl contents are below the detection limit (Supplementary Fig.\u0026nbsp;9). We hypothesize that the capillary action of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers allows rapid adsorption and enrichment of NaCl from sweat. To validate this hypothesis, we sprayed a sodium chloride aqueous solution onto the surface of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers. TEM and EDS reveal Na and Cl distributions along the fibers, confirming that NaCl can be adsorbed onto the surface of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers (Supplementary Fig.\u0026nbsp;13). Furthermore, the addition of NaCl significantly affects the crystalline quality of CsPbBr\u003csub\u003e3\u003c/sub\u003e (Supplementary Fig. 14), potentially quenching its luminescence. The selective response to fingerprint residues enables the distinction between real and forged fingerprints, thus enhancing the security and reliability of fingerprint recognition. For example, when we prepared fake fingerprints using silicone molds, NFIT did not reveal any significant fingerprint features (Supplementary Fig. 15). Additionally, this noncontact approach addresses several issues associated with touch-based fingerprint collection, such as the nonlinear distortion caused by pressing fingers onto sensor plates and the need for regular sensor surface cleaning\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. More importantly, NFIT achieves fingerprint image resolutions of up to 1450 dpi (Supplementary Fig. 16) without soaking, heating, or adding reagents for pre- or post-treatment. Furthermore, the fingerprint features obtained by NFIT belong to Level 3. This significantly improves the precision of fingerprint feature capture and recognition, offering promising prospects for practical applications.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSelective spectral response and Chemical interactions of CsPbBr@HP\u0026beta;CD nanofibers to sweat components\u003c/h3\u003e\n\u003cp\u003eGiven that CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers enable high-definition fingerprint imaging through a selective response to sweat residues, an in-depth study of their spectral response is essential. HP\u0026beta;CD enhances the photoluminescence (PL) intensity of CsPbBr\u003csub\u003e3\u003c/sub\u003e (Supplementary Fig. 17). HRTEM images reveal that the CsPbBr\u003csub\u003e3\u003c/sub\u003e nanocrystals without HP\u0026beta;CD exhibit irregular morphologies (Supplementary Fig. 18). In contrast, the addition of HP\u0026beta;CD improves the crystal quality of the CsPbBr\u003csub\u003e3\u003c/sub\u003e nanocrystals (Supplementary Fig. 8e and 8f), which was further confirmed by X-ray diffraction results (Supplementary Fig. 19). This finding suggests that HP\u0026beta;CD molecules effectively passivate the defects in CsPbBr\u003csub\u003e3\u003c/sub\u003e, leading to enhanced PL performance. The luminescence property of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers, coupled with their specific interactions with NaCl, prompted us to explore their potential for selective response to fingerprint residues.\u003c/p\u003e\n\u003cp\u003eSweat residues are primarily composed of sweat and sebum. Among these components, sweat contains various chlorides, such as sodium chloride (NaCl), magnesium chloride (MgCl\u003csub\u003e2\u003c/sub\u003e) and potassium chloride (KCl), along with organic compounds, such as glucose, ascorbic acid, uric acid and urea\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Sebum, in contrast, primarily comprises triglycerides, squalene and other lipid-based compounds\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Therefore, we performed spectroscopic analysis to investigate the response mechanism of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers to representative components (NaCl, KCl, MgCl\u003csub\u003e2\u003c/sub\u003e, laurostearin, ascorbic acid, urea, uric acid and squalene) of sweat residues. The ultraviolet-visible absorption (UV-Vis) spectra indicate that the addition of various components has little effect on the bandgap of the CsPbBr\u003csub\u003e3\u003c/sub\u003e fibers without HP\u0026beta;CD. However, in the presence of HP\u0026beta;CD, the bandgap of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers is affected to varying degrees by these components (Supplementary Figs.\u0026nbsp;20a and 20b). Correspondingly, the PL intensities of the CsPbBr\u003csub\u003e3\u003c/sub\u003e fibers and CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers exposed to the above components were characterized (Supplementary Figs.\u0026nbsp;20c and 20d). The patterns of their PL peak shifts are consistent with those for the UV-Vis spectra. A decrease in intensity accompanies this blueshift of the PL peaks. Owing to the good color purity of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD (full width at half maximum\u0026thinsp;=\u0026thinsp;20.86 nm), the color change upon the addition of chloride salts is highly noticeable and can be distinguished by the naked eye (Supplementary Fig.\u0026nbsp;21). In comparison, the CsPbBr\u003csub\u003e3\u003c/sub\u003e fibers without HP\u0026beta;CD typically exhibit PL quenching and minimal PL peak shifts upon the addition of chlorides (Supplementary Figs. 22). Furthermore, exposure of the CsPbBr\u003csub\u003e3\u003c/sub\u003e fibers to organic components (laurostearin, ascorbic acid, urea, uric acid and squalene) generally results in an increase or decrease in the PL intensity without regular changes (Supplementary Figs. 23). In contrast, for the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers, almost all, the aforementioned organic components cause a decrease in the PL intensity. Interestingly, glucose is an exception: trace amounts of glucose (mass ratio of glucose: CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD\u0026thinsp;=\u0026thinsp;6\u0026times;10⁻\u003csup\u003e5\u003c/sup\u003e: 1) increase the PL intensity (Supplementary Fig.\u0026nbsp;24). When the concentration is increased to 50 times, glucose still produces in a detectable PL intensity. The above PL performance suggests that HP\u0026beta;CD plays a dual role: it enhances the interaction of CsPbBr\u003csub\u003e3\u003c/sub\u003e with ionic species and selectively modulates the response to specific organic components, which facilitates the analysis of extracted fingerprints.\u003c/p\u003e\n\u003cp\u003eConsidering the individual differences in sweat composition that could affect the specific response of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers for imaging, we systematically analyzed the concentration-dependent PL intensity responses for nine fingerprint residue components (Supplementary Figs.\u0026nbsp;25\u0026ndash;27 and Supplementary Tables\u0026nbsp;4\u0026ndash;12). The relationship between these representative components and the PL peak shifts of the CsPbBr\u003csub\u003e3\u003c/sub\u003e @HP\u0026beta;CD fibers are summarized in the box plot in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea and Supplementary Table\u0026nbsp;13. The data indicate that introducing NaCl, KCl, and MgCl\u003csub\u003e2\u003c/sub\u003e causes a blueshift in the PL peak, accompanied by a reduction in the PL intensity. In contrast, upon exposure to organic compounds, their influence on the PL peak wavelength of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers is negligible, whereas a general decrease in the PL intensity was observed. Glucose, as an exception, increases the PL intensity at low concentrations but causes PL quenching at higher concentrations. The luminescence properties of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fiber response to sweat residue components can be better understood via time-resolved photoluminescence (TRPL) spectra. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb and Supplementary Table\u0026nbsp;14, glucose is the only component that significantly extends the average PL lifetime, whereas the other components reduce the lifetime to varying degrees.\u003c/p\u003e\n\u003cp\u003eTo further investigate the chemical interactions between CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD and fingerprint residues, X-ray photoelectron spectroscopy (XPS), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH nuclear magnetic resonance (\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH-NMR) spectroscopy were used. Compared with pristine CsPbBr\u003csub\u003e3\u003c/sub\u003e fibers, introducing various sweat components results in the Cs 3\u003cem\u003ed\u003c/em\u003e, Pb 4\u003cem\u003ef\u003c/em\u003e, and Br 3\u003cem\u003ed\u003c/em\u003e peaks shifting to lower binding energies (Supplementary Figs. 28\u0026ndash;30). In contrast, CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD exhibits a more systematic specific response upon exposure to fingerprint residues. For example, when ascorbic acid, laurostearin and squalene are introduced to CsPbBr\u003csub\u003e3\u003c/sub\u003e @HP\u0026beta;CD fibers, the binding energy of the Pb 4\u003cem\u003ef\u003c/em\u003e peak further decreases by 0.40, 0.50 and 0.40 eV, respectively, compared with that of pure CsPbBr\u003csub\u003e3\u003c/sub\u003e fibers. This shift suggests a reduction in the electron affinity and an increase in the electron cloud density around the Cs, Pb, and Br atoms, which can be attributed to electron donation from the additive molecules, likely forming coordination bonds\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Conversely, the introduction of various chlorides to CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers causes the Pb 4\u003cem\u003ef\u003c/em\u003e and Br 3\u003cem\u003ed\u003c/em\u003e peaks to shift to higher binding energies (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec and Supplementary Fig.\u0026nbsp;31). This phenomenon may be ascribed to the partial incorporation of chloride ions (Cl⁻) into the CsPbBr\u003csub\u003e3\u003c/sub\u003e lattice, facilitated by the presence of HP\u0026beta;CD (Supplementary Fig. 20)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Interestingly, the introduction of glucose to CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD increases the binding energies of the Pb 4\u003cem\u003ef\u003c/em\u003e and Br 3\u003cem\u003ed\u003c/em\u003e peaks (Supplementary Tables 15 and 16). This finding may be attributed to glucose synergistically strengthening hydrogen bonding interactions with CsPbBr\u003csub\u003e3\u003c/sub\u003e through multiple hydroxyl groups\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and HP\u0026beta;CD. As a result, the local environment of CsPbBr\u003csub\u003e3\u003c/sub\u003e is altered, and its electron density decreases. The above XPS results indicate that HP\u0026beta;CD plays a critical role in modulating the chemical interactions between CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD and fingerprint residues, particularly upon exposure to glucose and chlorides, thereby altering the photophysical properties of the material.\u003c/p\u003e\n\u003cp\u003eOwing to the ionic nature of CsPbBr\u003csub\u003e3\u003c/sub\u003e, which arises from the strong ionic interactions inherent to its crystal structure, the material exhibits distinctive characteristics when interacting with other species\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. The incorporation of HP\u0026beta;CD further enhances these interactions, as its polar internal cavity and hydrophilic exterior provide an ideal microenvironment for interactions with metal ions and stabilizing agents\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Specifically, the ionic species interact with the hydroxyl and other functional groups on the HP\u0026beta;CD surface, altering the local electron density. This interaction, in turn, may affect the shielding of nearby protons, as reflected in the chemical shifts observed via \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH-NMR spectroscopy. The introduction of CsPbBr\u003csub\u003e3\u003c/sub\u003e primarily causes more significant shifts in the exterior protons of HP\u0026beta;CD (H1, H2 and H7) than in the inner cavity protons (H4 and H6), indicating that the interaction predominantly occurs on the external surface of HP\u0026beta;CD\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Furthermore, the addition of chloride salts (NaCl, KCl, and MgCl\u003csub\u003e2\u003c/sub\u003e) to CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD results in distinct shifts in the exterior protons of HP\u0026beta;CD (Supplementary Tables\u0026nbsp;17 and 18 and Fig.\u0026nbsp;32). When chloride salts compete with CsPbBr\u003csub\u003e3\u003c/sub\u003e for active sites on the HP\u0026beta;CD surface, the strong electronegativity of chloride ions may disrupt the original electrostatic field, leading to changes in the chemical environment of the exterior protons. Moreover, HP\u0026beta;CD can assist in capturing chloride ions from the system, thus promoting halogen exchange between the chloride ions and the perovskite. In contrast, when glucose is introduced to the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD complex, the chemical shifts of the exterior protons remain largely unchanged, indicating that glucose does not compete with CsPbBr\u003csub\u003e3\u003c/sub\u003e for the active binding sites of HP\u0026beta;CD. The multiple hydroxyl groups of glucose may provide additional active sites to stabilize CsPbBr\u003csub\u003e3\u003c/sub\u003e, further suppressing the exposure of CsPbBr\u003csub\u003e3\u003c/sub\u003e defects\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eGiven the above findings, we investigated the interactions between chlorides, glucose and CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD via ATR-FTIR spectroscopy. When CsPbBr\u003csub\u003e3\u003c/sub\u003e is added to HP\u0026beta;CD, the -OH stretching frequency of HP\u0026beta;CD slightly increases, shifting from 3343 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e to 3350 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Upon the addition of NaCl to CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD, the -OH stretching frequency increases dramatically to 3398 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, suggesting that NaCl has a significant influence on the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD complex (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed). Similarly, the introduction of KCl and MgCl\u003csub\u003e2\u003c/sub\u003e leads to an increase in the intensity and a blueshift of the -OH vibrational band (~\u0026thinsp;3343 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e) of HP\u0026beta;CD, accompanied by a narrowing of the peak width. This phenomenon may arise from the alteration of the hydrogen bonding network of HP\u0026beta;CD by chloride salts through electrostatic interactions\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, which affects the electron density distribution of HP\u0026beta;CD\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. The impact of glucose can be observed in its interaction with CsPbBr\u003csub\u003e3\u003c/sub\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ee), in which the -OH stretching frequency of glucose increases from 3243 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e to 3264 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e upon the introduction of CsPbBr\u003csub\u003e3\u003c/sub\u003e. This result suggests the formation of hydrogen bonds between the CsPbBr\u003csub\u003e3\u003c/sub\u003e and -OH groups. Similarly, the introduction of CsPbBr\u003csub\u003e3\u003c/sub\u003e causes a blueshift in the -OH stretching band of HP\u0026beta;CD, from 3343 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e to 3350 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, indicating a similar interaction of HP\u0026beta;CD with CsPbBr\u003csub\u003e3\u003c/sub\u003e and glucose with CsPbBr\u003csub\u003e3\u003c/sub\u003e. The characteristic peaks of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD and glucose@HP\u0026beta;CD are almost identical. However, the \u0026ndash;OH stretching band of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD/glucose complex blueshifts from 3343 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e to 3318 cm⁻\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, accompanied by peak width broadening. This is likely due to the addition of glucose expanding the hydrogen bonding network of HP\u0026beta;CD and further enhancing the synergistic interaction between HP\u0026beta;CD and glucose acting on CsPbBr\u003csub\u003e3\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eTo further elucidate the molecular-level interactions of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers with NaCl, KCl, and MgCl\u003csub\u003e2\u003c/sub\u003e, we performed density functional theory (DFT) calculations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. First, we investigated Na\u003csup\u003e+\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, and Mg\u003csup\u003e2+\u003c/sup\u003e doping at the Cs\u003csup\u003e+\u003c/sup\u003e and Pb\u003csup\u003e2+\u003c/sup\u003e sites, along with halogen exchange, and their effects on the CsPbBr\u003csub\u003e3\u003c/sub\u003e bandgap (Supplementary Tables 19\u0026ndash;21). The results indicate that doping Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e at the Pb\u003csup\u003e2+\u003c/sup\u003e site, and Cl⁻ substituted by Br⁻, produces a bandgap that closely matches the experimental results. This observation can be attributed to the ionic radii of Na\u003csup\u003e+\u003c/sup\u003e (1.02\u0026Aring;) and K\u003csup\u003e+\u003c/sup\u003e (1.38 \u0026Aring;) being closer to that of Pb\u003csup\u003e2+\u003c/sup\u003e (1.19 \u0026Aring;) than the ionic radius of Cs\u003csup\u003e+\u003c/sup\u003e (1.67 \u0026Aring;), making them better suited for doping at Pb\u003csup\u003e2+\u003c/sup\u003e sites\u003csup\u003e56,57\u003c/sup\u003e. Additionally, doping at the Pb\u003csup\u003e2+\u003c/sup\u003e site introduces local charge imbalances, which are compensated by lattice defect mechanisms, thereby maintaining the overall material stability. Conversely, Cs\u003csup\u003e+\u003c/sup\u003e, as a large alkali metal ion, occupies the A-site in the octahedral perovskite structure, where it exhibits high chemical stability. Replacing Cs\u003csup\u003e+\u003c/sup\u003e with smaller ions such as Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e often destabilizes the structure, leading to collapse\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. However, based on the aforementioned UV-Vis spectra, the transient surface adsorption of Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e ions, along with halogen exchange, has a minimal effect on the band gap of CsPbBr\u003csub\u003e3\u003c/sub\u003e, suggesting that such processes are unlikely to occur without additional external treatment. Compared to CsPbBr\u003csub\u003e3\u003c/sub\u003e, the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers demonstrate a stronger response to NaCl, KCl, and MgCl\u003csub\u003e2\u003c/sub\u003e, suggesting that HP\u0026beta;CD plays a crucial role in this system. We calculated the adsorption energies (\u003cem\u003eE\u003c/em\u003e\u003csub\u003eabs\u003c/sub\u003e) with and without HP\u0026beta;CD, revealing that HP\u0026beta;CD enhances the \u003cem\u003eE\u003c/em\u003e\u003csub\u003eabs\u003c/sub\u003e of NaCl (\u0026ndash;6.42 eV), KCl (\u0026ndash;6.64 eV), and MgCl\u003csub\u003e2\u003c/sub\u003e (\u0026ndash;6.01 eV) to \u0026minus;\u0026thinsp;7.27 eV, \u0026minus;\u0026thinsp;7.16 eV, and \u0026minus;\u0026thinsp;7.14 eV, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef and Supplementary Tables\u0026nbsp;22)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. The enhanced \u003cem\u003eE\u003c/em\u003e\u003csub\u003eabs\u003c/sub\u003e values indicate stronger interactions between chloride salts and the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD complex, particularly through Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e doping at the Pb\u003csup\u003e2+\u003c/sup\u003e site and halogen exchange, significantly influencing the PL properties. For comparison, we synthesized CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD, CsPbBr\u003csub\u003e3\u003c/sub\u003e@K-\u0026beta;CD, and CsPbBr\u003csub\u003e3\u003c/sub\u003e @Cl-\u0026beta;CD fibers, using HP\u0026beta;CD, potassium-enriched \u0026beta;-cyclodextrin (K-\u0026beta;CD), and chloride-enriched \u0026beta;-cyclodextrin (Cl-\u0026beta;CD), respectively (see Methods for details). The results further confirm that the halide exchange effect is more prominent as the emission peak of CsPbBr\u003csub\u003e3\u003c/sub\u003e@Cl-\u0026beta;CD blueshifts to ~\u0026thinsp;475 nm (Supplementary Fig.\u0026nbsp;33).\u003c/p\u003e\n\u003cp\u003eThe above computational and experimental results demonstrate that ion-dipole or electrostatic interactions between HP\u0026beta;CD and inorganic chloride salts facilitate halide exchange with CsPbBr\u003csub\u003e3\u003c/sub\u003e. In the case of glucose, the coexisting HP\u0026beta;CD and glucose may synergistically interact with surface defect sites on CsPbBr\u003csub\u003e3\u003c/sub\u003e, potentially inhibiting exposure of CsPbBr\u003csub\u003e3\u003c/sub\u003e and thereby enhancing its fluorescence lifetime. Conversely, organic components other than glucose may undergo stronger interactions with HP\u0026beta;CD, acting as guests that compete with CsPbBr\u003csub\u003e3\u003c/sub\u003e. This competition could increase the exposure of CsPbBr\u003csub\u003e3\u003c/sub\u003e, leading to further quenching of the PL emission. The differential response of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers to fingerprint residue components is critical for achieving high-precision fiber-based imaging, as illustrated in the mechanism diagram (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhotoluminescence characterization and\u003c/strong\u003e \u003cstrong\u003ein situ\u003c/strong\u003e \u003cstrong\u003eimaging\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBuilding on the above comprehensive characterization, we further conducted an in-depth study on the effects of NaCl, KCl, MgCl\u003csub\u003e2\u003c/sub\u003e and glucose on the photophysical properties of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers via temperature-dependent PL spectroscopy, \u003cem\u003ein situ\u003c/em\u003e PL mapping, and \u003cem\u003ein situ\u003c/em\u003e fluorescence lifetime imaging microscopy (FLIM). During the temperature-dependent PL analysis, the PL intensities of the CsPbBr\u003csub\u003e3\u003c/sub\u003e fibers, CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers, and CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers with added NaCl or glucose progressively decrease with increasing temperature (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea and Supplementary Fig.\u0026nbsp;34). The reduction in the PL intensity can be attributed to the increased thermal energy, which induces exciton dissociation and promotes electron-phonon interactions, resulting in substantial PL quenching\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Notably, the temperature-dependent PL intensity of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD/NaCl shows a more pronounced decline than that of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD (Supplementary Fig.\u0026nbsp;35), which may be related to the lattice phase transition of CsPbBr\u003csub\u003e3\u003c/sub\u003e, the loss of surface HP\u0026beta;CD during heating\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e and the defect formation induced by NaCl doping. The PL intensity of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD/glucose exhibits a more gradual decline with increasing temperature, maintaining a detectable PL signal even at 350 K (Supplementary Fig.\u0026nbsp;34). Based on the earlier mechanistic investigations, we infer that glucose contributes to passivation effects, mitigating exciton dissociation and electron-phonon interactions under high thermal stress, thereby increasing the stability of CsPbBr\u003csub\u003e3\u003c/sub\u003e perovskites. The exciton binding energy (\u003cem\u003eE\u003c/em\u003e\u003csub\u003eb\u003c/sub\u003e) was calculated from the Arrhenius plot via the following Eq.\u0026nbsp;6\u003csup\u003e2\u003c/sup\u003e:\u003c/p\u003e\n\u003ch3\u003e\u003cimg 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\"\u003e\u003c/h3\u003e\n\u003cp\u003ewhere \u003cem\u003eI\u003c/em\u003e\u003csub\u003e0\u003c/sub\u003e is the integrated PL intensity at 0 K, \u003cem\u003eK\u003c/em\u003e\u003csub\u003eB\u003c/sub\u003e is the Boltzmann constant, and \u003cem\u003eA\u003c/em\u003e is the Arrhenius coefficient. The CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD/glucose fibers exhibit the highest \u003cem\u003eE\u003c/em\u003e\u003csub\u003eb\u003c/sub\u003e (74.9 meV) compared to CsPbBr\u003csub\u003e3\u003c/sub\u003e fibers (50.8 meV) and CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers (63.4 meV) (Supplementary Fig.\u0026nbsp;36), which suggests a more effective inhibition of exciton dissociation due to the synergistic effects of glucose and HP\u0026beta;CD.\u003c/p\u003e\n\u003cp\u003eGiven the impact of chlorides and glucose on the emission wavelength and lifetime of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers, we further employed \u003cem\u003ein situ\u003c/em\u003e PL mapping to investigate their potential for imaging the spatial distribution of specific components. Wavelength-dependent PL mapping reveals that the emission peaks of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers on LFPs range from 490 nm to 520 nm, with distinct regional characteristics (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec). The PL emission at 520 nm is predominantly concentrated in the furrows and sweat pores of the fingerprint. The distribution of the 500 nm luminescence accurately outlines the edges of ridges and pores. In comparison, the peak wavelength observed at the ridges surrounding the sweat pore, which corresponds to the region enriched with Na\u003csup\u003e+\u003c/sup\u003e and Cl⁻, gradually blueshifts to 490 nm (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eg and Supplementary Figs.\u0026nbsp;10\u0026ndash;12). Thus, FLIM was performed at PL emission wavelengths of 520 nm and 490 nm. Using the lifetime of the CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD fibers as a reference, a distinct spatial distribution of the relative lifetime was observed (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed). At 520 nm, the long-lifetime regions are primarily concentrated around the pores and fingerprint valleys, corresponding to the areas of stronger emission. Conversely, chloride salts lead to a reduced lifetime, which is evident in the shorter lifetime of 490 nm compared to 520 nm. FLIM at various wavelengths provides additional details for Level 3 fingerprint imaging (Supplementary Fig. 37a-d). Consistent with the PL mapping and EDS results, FLIM indicates that chlorides are primarily distributed around the outer edge of the sweat pores on the ridges, where the emission undergoes a blueshift with a shortened lifetime. Regions with strong emission intensity and a relative lifetime exceeding 100% may provide clues for the distribution of glucose (Supplementary Fig. 37e and 38 and Table 23). Thus, FLIM can effectively visualize fingerprints and potentially provide glucose distribution. Due to precise measurements of sweat glucose concentrations can be utilized to estimate blood glucose levels\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e, there is potential for this NFIT to be integrated with sensing technology\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e in the future, further promoting its application in biomedical diagnostics.\u003c/p\u003e\n\u003ch3\u003eEvaluation of the universality, stability, and nondestructiveness of NFIT\u003c/h3\u003e\n\u003cp\u003eIn light of the high luminescence imaging performance of NFIT, we conducted skin texture extraction experiments under various environmental conditions to evaluate its stability, adaptability and broad applicability systematically. Specifically, clear and high-contrast visualization of LFPs on common substrates, including tinfoil, quartz, iron, glass and plastic, (relatively clear Level-2 fingerprint imaging can be achieved on leather and paper), was achieved with a 10-second electrospinning process. (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea and Supplementary Figs.\u0026nbsp;39\u0026ndash;41). These results demonstrate that NFIT can rapidly acquire high-resolution fingerprint information on a wide range of substrate surfaces, thus meeting the demands for swift, high-definition extraction of fingerprints on typical crime scene items (Supplementary Fig.\u0026nbsp;42). We further investigated the performance of NFIT in extracting Level 3 features under various finger pressures. As shown in Supplementary Figs.\u0026nbsp;43 and 44, an increase in pressure caused a reduction in the diameter of the sweat pores, consistent with previously reported results\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. This finding suggests that NFIT can efficiently capture changes in the sweat pore diameter, providing insights into the force exerted by the individual and offering valuable forensic clues. The temporal stability and imaging consistency of NFIT in fingerprint extraction were also evaluated. Experiments demonstrate that even for aged LFPs left for 37 days, NFIT can still deliver clear Level 3 fingerprint features (Supplementary Figs.\u0026nbsp;45 and Fig.\u0026nbsp;46). This result indicates that NFIT significantly outperforms traditional humidity-responsive fingerprint imaging techniques, which often struggle to extract complete Level 3 fingerprint information once the moisture in the fingerprint evaporates. Moreover, fingerprint imaging generated via CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers exhibits impressive long-term stability (Level 3\u0026thinsp;\u0026ge;\u0026thinsp;81 days, Level 2\u0026thinsp;\u0026ge;\u0026thinsp;108 days) see Supplementary Fig.\u0026nbsp;47. The CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers also demonstrate strong resistance to photodegradation. Under continuous high frequency laser (20 MHz, 405 nm) irradiation at a single point, the PL intensity remains stable, with an estimated half-life of 158 minutes (Supplementary Fig. 48). The NFIT performance was further assessed under extreme environmental conditions with temperatures ranging from +\u0026thinsp;50\u0026deg;C to \u0026minus;\u0026thinsp;50\u0026deg;C. At PL mapping wavelengths of 520 nm and 490 nm, NFIT consistently captures clear Level 3 features (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb and \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec). Combined with its portable design, it is suitable for on-site collection and analysis under extreme temperature conditions. Moreover, we expanded the extraction area from fingerprints to the entire palm to evaluate the ability of NFIT to capture the full ridge patterns. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ed and \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ee, NFIT successfully captures whole palm print information, providing high-resolution details for sweat pores (Supplementary Fig.\u0026nbsp;49). This highlights the potential of NFIT for applications involving photocopying whole-body skin textures. In actual forensic and criminal investigation scenarios, using nondestructive techniques for DNA is crucial. Therefore, we investigated the impact of NFIT on DNA identification to ensure its applicability to nondestructive analysis. Based on short tandem repeat (STR) analysis of the data of extracted DNA with or without electrospun CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD nanofibers, NFIT has no negative effects on STR analysis, as the two samples yield consistent results (Supplementary Figs.\u0026nbsp;50 and 51). This confirms the effectiveness of NFIT in extracting fingerprints without damaging DNA evidence. In summary, NFIT demonstrates adaptability across a wide range of extreme environments. Whether under the scorching heat of the Sahara or the freezing temperatures of polar regions, this technology can be easily applied to various substrate surfaces via a portable electrospinning device, enabling rapid, convenient and high-resolution onsite fingerprint imaging.\u003c/p\u003e\n\u003ch3\u003ePortable high-resolution fingerprint imaging and data analysis system\u003c/h3\u003e\n\u003cp\u003eLeveraging the high-resolution imaging capability and broad applicability of NFIT, we self-developed a micro-image algorithm that integrates portable fingerprint imaging devices with rapid data analysis. This integrated system consists of a handheld mini-electrospinning device and a smartphone (Supplementary Fig. 52). The fingerprint analysis program can be embedded in a smartphone or a computer, which serves as the data processing platform (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea and Supplementary Fig. 53). The high resolution of the extracted images ensures precise capture of fingerprint features. Coupled with the user-friendly program, the entire extraction and analysis process becomes highly efficient, allowing collection and storage of 100 fingerprints within only 1 hour. As a proof-of-concept, we used this system for fingerprint extraction and analysis, with the results shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb. The images can then be imported into the program (see Methods) for image processing. This program can accurately extract grayscale values from multiple fingerprint regions within the image (Supplementary Fig. 54). The analysis regions can be user-defined, and the number of sampling points can be adjusted (Supplementary Movie #2). Unlike traditional methods that rely on \u0026quot;drawing lines to take points\u0026quot;, our integrated NFIT system directly converts large areas of image information into grayscale values. Additionally, depending on the number of sampling points, images of various resolutions can be generated (Supplementary Fig. 55). Owing to the efficiency of the integrated NFIT system, extensive computational resources are not required, even when managing large datasets. For example, the data from the four charts in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea occupy only 894 K bytes after processing by the integrated NFIT system. This substantial reduction in computational and storage demands significantly lowers operational complexity and maintenance costs. Simultaneously, the system converts digitized grayscale data into 2D/3D images, enabling swift visualization and comparison of fine fingerprint features.\u003c/p\u003e\n\u003cp\u003eThe integrated NFIT system can directly capture data and construct models from a photograph of a real fingerprint, allowing the obtainment of a 3D model that accurately aligns with the model generated through NFIT, thus validating the precision of the entire extraction and modeling process (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ec, Supplementary Fig. 56 and Supplementary Movie #3). Further comparisons reveal that the 3D reconstruction models obtained via NFIT provide more detailed fingerprint features, which is attributable to the high contrast achieved in fingerprint luminescence imaging (Supplementary Fig. 57\u0026ndash;59). Additionally, the finger surface morphology can be reconstructed through mirroring inversion of the 3D fingerprint model obtained by the integrated NFIT system (Supplementary Fig. 60). This mirroring model provides clear information on the ridge patterns and more details, making it valuable for forensic identification and high-precision authentication applications. Thus, this integrated NFIT system provides comprehensive functionalities, including fingerprint extraction and imaging, image conversion and storage, data analysis and 3D model reconstruction. It has significant advantages over existing fingerprint collection techniques (Supplementary Table 24): 1. The device is compact, lightweight (\u0026lt;\u0026thinsp;400 g) and easy to assemble, reducing the complexity and operational requirements compared with traditional laboratory instruments; 2. The entire system is low-cost (\u0026lt; \u003cspan\u003e$\u003c/span\u003e 800,\u003c/p\u003e\n\u003cp\u003eSupplementary Table\u0026nbsp;25), making it highly suitable for field operations and large-scale deployment; 3. The system is optimized for an efficient integrated workflow that encompasses fingerprint extraction, imaging, data storage, and analysis (Supplementary Movie #4); 4. The system employs a 3D reconstruction algorithm, thus providing high-precision features and a visually presented fingerprint morphology for forensic and identity authentication applications.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eIntegrated NFIT System for Body Skin Photocopying and 3D model construction\u003c/h2\u003e\n \u003cp\u003eUtilizing the NFIT system, we have achieved rapid, high-precision photocopying of skin textures from diverse body regions, including the forehead, abdomen, handbacks, and soles of the feet. This process consistently delivers high-definition skin texture images within just 5 minutes and it overcomes the challenges posed by areas with minimal sweat secretion, such as the hand back. Our system employs CsPbBr\u003csub\u003e3\u003c/sub\u003e@HP\u0026beta;CD as a luminescent imaging medium, uniquely responding to sweat secretions. By using an electrospinning mechanism, we enable swift and precise imaging without reliance on intricate feedback systems or chemical pre- or post-processing, ensuring operational simplicity and efficiency. Moreover, our NFIT system excels in generating 3D models from these high-resolution skin texture images (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and Supplementary Fig. 61). This capability extends even to regions like the hand back, where sweat secretion is limited, demonstrating the system\u0026rsquo;s exceptional sensitivity and adaptability for the whole human body skin. These 3D skin texture datasets have significantly enhanced the fidelity and detail optimization in 3D modeling and rendering. This advancement supports the creation of hyper-realistic works in game development, animation production, and film special effects, providing realism. Beyond creative applications, the system has propelled innovations in virtual try-on and personalized customization technologies. By enabling the accurate reproduction of individual skin textures, consumers can experience tailored services with unprecedented precision and convenience. Additionally, the system offers potential in medical diagnostics and health monitoring, providing a non-invasive approach to capturing skin textures for analysis of dermatological conditions, even in areas of the traditionally challenging for imaging. These advancements underscore the NFIT system as a transformative tool in high-resolution skin imaging and 3D modeling, redefining possibilities across industries.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe developed an innovative nanofiber-based imaging technique (NFIT) using CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD luminescent nanofibers, achieving real-time, multidimensional and multiregional imaging of human skin textures with unprecedented precision. The NFIT system utilizes unique chloride and glucose recognition mechanisms, enabling accurate sweat pore imaging with a similarity of 93.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6%. It supports large-area imaging across diverse materials while maintaining high-resolution (1450 dpi) image quality under extended storage (Level 3\u0026thinsp;\u0026ge;\u0026thinsp;81 days, Level 2\u0026thinsp;\u0026ge;\u0026thinsp;108 days) and extreme temperatures (\u0026ndash;50\u0026deg;C to +\u0026thinsp;50\u0026deg;C). Beyond capturing detailed 2D skin surface features, NFIT facilitates the construction of high-precision 3D skin morphology models. These data revolutionize biometric security systems, offering enhanced fingerprint and palm print recognition accuracy. Furthermore, the data serve as invaluable resources for educational and research purposes in biology and anthropology while advancing personalized medicine and dermatology. This technology sets a benchmark in human skin photocopying, addressing critical challenges in precision, safety, and usability and unlocking transformative applications across diverse fields.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMaterials\u003c/h2\u003e\u003cp\u003eCesium bromide (CsBr, 99.9%) and lead bromide (PbBr\u003csub\u003e2\u003c/sub\u003e, 99.9%) were purchased from Advanced Election technology Co., Ltd. The \u003cem\u003eN\u003c/em\u003e, \u003cem\u003eN\u003c/em\u003e-dimethylformamide (DMF, AR),and Dimethyl sulfoxide (DMSO, AR) were purchased from Sinopharm Chemical Reagent Co., Ltd. Hydroxypropyl-β-cyclodextrin (HPβCD) and deuterated dimethyl sulfoxide (DMSO\u0026ndash;d\u003csub\u003e6\u003c/sub\u003e) were purchased from Shanghai Macklin Biochemical Co., Ltd. Thermoplastic Polyurethanes (TPU) was purchased from Qingdao Nuokang Environmental Protection Technology Co., Ltd. Sodium chloride (NaCl, AR), magnesium chloride (MgCl\u003csub\u003e2\u003c/sub\u003e, AR), potassium chloride (KCl, AR) and glucose were purchased from Sinopharm Chemical Reagent Co., Ltd., Lauro stearin (98%) and squalene (95%) were purchased from Shanghai Macklin Biochemical Co., Ltd. Ascorbic acid (99%) and uric acid (99%) were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePreparation of electrospinning solution and LFPs recognition process\u003c/h2\u003e\u003cp\u003eCsBr (0.0213 g), PbBr\u003csub\u003e2\u003c/sub\u003e (0.0367 g), and HPβCD (0.05 g) were combined and ground using a mortar and pestle for 1 minute. DMF (0.25 ml) and DMSO (0.25 ml) were then added to the mixture, which was shaken and allowed to sit at room temperature for 1 hour. Subsequently, 100 \u0026micro;l of this solution was mixed with 1 ml of a 16% TPU solution (the solvent is DMF) and stirred for 10 seconds to fabricate the electrospinning solution. The final solution was loaded into a handheld electrospinning device, allowing for the rapid generation of LFP images, with complete imaging achievable in approximately 10 seconds.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePreparation of K-βCD\u003c/h2\u003e\u003cp\u003eTo prepare K-βCD, a mixture of β-CD (0.68 g, 0.6 mmol) and KOH (0.269 g, 4.8 mmol) was dissolved in H\u003csub\u003e2\u003c/sub\u003eO (12 ml) in a beaker and sonicated for 5 minutes to ensure homogeneous dispersion. Methanol (12 ml) was subsequently added, and the solution was stirred continuously for 1 hour. The mixture was then subjected to microwave irradiation at 100 W for 4 minutes and 30 seconds to facilitate crystal growth. Following this step, the reactant was carefully added dropwise to a large volume of hot methanol, which acted as a size-controlling agent. The resulting crystals were collected by centrifugation at 7000 rpm and washed three times with methanol. Finally, the crystals were dried under vacuum at 50\u0026deg;C for 12 hours. The dried product, K-βCD, was obtained by gentle grinding of the crystals.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003ePreparation of Cl-βCD\u003c/h2\u003e\u003cp\u003eTo synthesize Cl-βCD, a mixture of β-CD (1.9 g, 1.5 mmol) and imidazole (1.5 g, 22.5 mmol) was dissolved in DMF (60 ml) under a nitrogen atmosphere. Anhydrous phenylsulfonyl chloride (3.9 g, 22.5 mmol) was then added, and the reaction mixture was stirred at room temperature for 2 hours. Subsequently, the reaction was heated to 70\u0026deg;C and maintained at this temperature for 24 hours. After completion, the solvent was removed by distillation, and 200 ml of water was added. The pH was adjusted by the addition of 2 mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e NaOH solution until the solution was fully alkaline. The resulting mixture was stirred for an additional 2 hours, and the precipitate was collected by filtration, washed thoroughly with H\u003csub\u003e2\u003c/sub\u003eO and acetone, and then recrystallized to yield purified Cl-βCD.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eCharacterization\u003c/h2\u003e\u003cp\u003eA custom-built fluorescence microscopy system was employed to observe LFPs fluorescence imaging. The microscope used was a DO-BX53 (Olympus) equipped with a mercury lamp as the excitation source (300\u0026ndash;500 nm) and 2.5 \u0026times;-100 \u0026times;objective lens. The morphological images were captured using a Regulus 8230 (Hitachi) cold-field emission scanning electron microscope (SEM) which was equipped with a X flash 5060F (Bruker) detector for energy dispersive X-ray spectra and mapping (EDS). The high-resolution transition electron microscopy (HRTEM) images were captured with a Tecnai G2 F30 (S-TWIN) transition electron microscope at an accelerating voltage of 300 kV, which was equipped with an X Flash (STEM-HAADF) detector for EDS mapping and Gatan Ultrascan CCD camera for high-resolution imaging. The binding energy was characterized on an ESCALAB 250Xi+ (Thermo Fischer) X-ray Photoelectron Spectroscopy (XPS). Fourier-transform infrared (FTIR) spectra were obtained by Cary 610/670 (Agilent). The nuclear magnetic resonance (NMR) was performed on Quantum-I plus 600 (Oxford). A FLS1000 fluorescence spectrometer (Edinburgh Instruments) was used to test the (PL spectra and TRPL. The temperature-dependent measurement was conducted with DN Optical Cryostats (Oxford Instruments) as an apparatus on FLS1000. Fluorescent lifetime imaging microscopy (FLIM) was performed on an ECLIPSE Ni-U microscope (Nikon) with a 5\u0026times; -10 \u0026times;objective lens, which was coupled with FLS1000 via optical fibers. A 405 nm picosecond pulsed diode laser was used as the excitation source for TRPL analysis and FLIM. The detailed parameters were as follows: a spatial resolution of 10 \u0026micro;m, a dwell time of 2 seconds per point, using the time-correlated single photon counting technique. PL mapping was performed on inVia Qontor (REINISHAW) with a 40\u0026times; objective lens. The sample was excited by a 325 nm laser and the spatial resolution was 10 \u0026micro;m. Temperature-dependent PL mapping was conducted with a THMS600 temperature control stage equipped on inVia Qontor. The solid-state UV-Vis absorption spectra were conducted on Shimadzu with an integrating sphere. The LFP was spun using a hand-held electrospinning device of E-01 (Foshan Qingzi Precision Measurement and Control Technology Co., Ltd).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eEvaluation of the effect of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD electrospinning treatment on the identification of DNA\u003c/h2\u003e\u003cp\u003eBlood samples were collected from a volunteer. Samples were prepared by depositing blood drops onto filter paper, with or without electrospun CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD nanofibers. DNA was extracted from these blood samples using the QIA amp DNA Blood Mini Kit (Qiagen, Hilden, Germany). The final concentration of DNA was 3 ng per PCR. STR analysis was performed using the Goldeneye DNA Identification System 20A (peoplespot, Beijing, China). The PCR products were analyzed using ABI 3130xl Genetic Analyzer (Applied Biosystems). Fluorescence was quantified, and the precise size of the DNA fragments was calculated with Genemapper software 3.2 (Applied Biosystems).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eComputational details\u003c/h2\u003e\u003cp\u003eFirst-principles density functional theory (DFT) calculations were performed using the Vienna abinitio Simulation Package (VASP)\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e with the projector augmented wave (PAW) method\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. The exchange-functional was treated within the generalized gradient approximation (GGA) employing the Perdew-Burke-Ernzerhof (PBE) functiona\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. The long-range van der Waals interactions are accounted for through the DFT-D3 approach. A plane wave basis set with an energy cutoff of 500 eV was employed, and the geometry relaxation was performed until the forces on each atom were below 0.03 eV \u0026Aring;⁻\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The Brillouin zone was sampled using 1 \u0026times; 1 \u0026times; 1 k-point grid. Self-consistent calculations were conducted with an energy convergence threshold of 10⁻\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e eV. A vacuum region of 15 \u0026Aring; was added along the z direction to prevent interactions between periodic structures.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eSelf-developed skin texture processing analysis program\u003c/h2\u003e\u003cp\u003eThe self-developed Level 3 fingerprint analysis program (see Supplementary Data 1) provides a comprehensive two-step data processing workflow, optimized for efficient analysis and visualization of high-resolution fingerprint data. In the first step, the software converts color images to grayscale, allowing for region-specific intensity analysis within user-defined regions of interest (ROI). The grayscale intensity data, including pixel coordinates and values, is exported as structured CSV or Excel files, ensuring compatibility with subsequent analysis stages. In the second step, this exported grayscale data is treated as point cloud input to generate detailed 2D grayscale images and 3D models, enhancing visualization and supporting interactive exploration of fingerprint features. The program\u0026rsquo;s graphical user interface (GUI) enables real-time processing and immediate feedback, improving usability across both analysis steps. Core implementation technologies include NumPy for efficient numerical computation, OpenCV and Pillow (PIL) for robust image manipulation, PyVista for 3D visualization, and Pandas for managing data exports. The program also employs Matplotlib to render 2D distribution charts and OpenPyXL to facilitate formatted Excel outputs with embedded visualizations. By ensuring smooth data flow between steps, the system minimizes manual data handling and enhances accuracy, reducing the risk of errors and enabling researchers to focus on analytical outcomes. This integrated approach supports a range of forensic and research applications, with potential future expansions to include automated data pipelines for even more efficient transitions from image processing to 3D visualization.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eCode availability\u003c/h2\u003e\u003cp\u003eThe code used in this study is openly available on GitHub\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e without any access restrictions.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003eEthics Approval Statement: This study was approved by the Institutional Review Board (IRB)/Ethics Committee of the School of Chemical Engineering and Technology, Instrumental Analysis \u0026amp; Research Center, First Affiliated Hospital of Sun Yat-sen University, and the School of Chemistry and Chemical Engineering, Yangzhou University.\u003c/p\u003e\n \u003cp\u003eParticipant Consent Statement: Written informed consent was obtained from all participants prior to their enrollment in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe code used in this study is openly available on GitHub\u003csup\u003e65,66\u003c/sup\u003e without any access restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is financially supported by the National Natural Science Foundation of China (22305215, 52402203), Jiangsu Province Youth Fund Project (BK20240893) and the State Key Laboratory of Coordination Chemistry. Special thanks to Mu-Zi Yang and Xiao-Ning Cheng from the Instrumental Analysis and Research Center of Sun Yat-sen University for their support in PL mapping and SEM analysis, Gangfeng Ouyang's instrumental support in TEM and NMR analysis. The authors express their gratitude to Mr. Shuai Yuan (from Yangzhou Xuntu Network Technology Co., Ltd.) for his valuable assistance in developing the Level 3 fingerprint analysis program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTian Tian, Yu-Xin Chen and Huan Pang designed the experiments. Tian Tian, Huixuan Han and Xinyi Lin carried out the fabrication of CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD nanofibers. Huixuan Han, Xinyi Lin, Tian Tian and Huan Pang carried out DFT calculations. The STR analysis was performed by Chao Wu. The characterizations were carried out by Hui Kang, Meifang Yang, Zihao Chen, Yuansheng Jiang, Wen-Guang Li, Xueqing Chang, Qin Xu and Yu-Xin Chen. Tian Tian, Yizhou Zhang and Yu-Xin Chen completed photoluminescence and DNA experiments. Tian Tian, Yu-Xin Chen and Huan Pang wrote the manuscript. All the authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNusayhah Hudaa G et al (2024) A prenatal skin atlas reveals immune regulation of human skin morphogenesis. Nature 635:679\u0026ndash;689\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePissarenko A, Meyers MA (2020) The materials science of skin: Analysis, characterization, and modeling. Prog Mater Sci 110:100634\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou J et al (2024) Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4. 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Nat Commun 15:6589\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ehttps://\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003egithub.com/stefan-ysh/image-grayscale-converter\u003c/span\u003e\u003cspan address=\"http://github.com/stefan-ysh/image-grayscale-converter\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ehttps://\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003egithub.com/stefan-ysh/points2image\u003c/span\u003e\u003cspan address=\"http://github.com/stefan-ysh/points2image\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5658648/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5658648/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe domain of forensic science, dermatology, and regenerative medicine critically relies on the precise replication of human skin details. Nevertheless, conducting on-site analysis poses challenges due to the stringent requirements for stability, accuracy, and the use of safe imaging materials. Current skin imaging methodologies are hindered by the inherent limitations of their hardware components, particularly when it comes to capturing the intricate, micrometer-scale textures of human skin. To address these challenges, we develop a low-cost (\u0026lt; \u003cspan\u003e$\u003c/span\u003e800), portable nanofiber-based imaging technique (NFIT) using CsPbBr\u003csub\u003e3\u003c/sub\u003e@HPβCD luminescent nanofibers. NFIT achieves in-situ, multi-regional imaging with ultrahigh-resolution (1450 dpi) and micron-scale similarity (93.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6%), capturing intricate details from sweat pores to large skin areas. Its non-contact design eliminates chemical pre/post-treatments, ensuring safety, hygiene and ease of use. NFIT demonstrates robustness and reliability as it maintains clear imaging under extreme temperature (-50\u0026deg;C to +\u0026thinsp;50\u0026deg;C) and over extended periods (Level 3\u0026thinsp;\u0026ge;\u0026thinsp;81 days, Level 2\u0026thinsp;\u0026ge;\u0026thinsp;108 days ). An algorithm was developed to support 3D skin texture model reconstruction, offering a transformative solution for forensic evidence analysis, dermatological assessments, and personalized medicine.\u003c/p\u003e","manuscriptTitle":"Luminescent Nanofibers for Human Skin Textures Photocopying","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 11:31:16","doi":"10.21203/rs.3.rs-5658648/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"dd4ca941-78cc-4d87-8f4d-c172d8c0f67b","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":53384648,"name":"Physical sciences/Chemistry/Materials chemistry/Optical materials"},{"id":53384649,"name":"Physical sciences/Materials science/Nanoscale materials"}],"tags":[],"updatedAt":"2025-11-05T08:09:10+00:00","versionOfRecord":{"articleIdentity":"rs-5658648","link":"https://doi.org/10.1038/s41467-025-64703-5","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-11-04 05:00:00","publishedOnDateReadable":"November 4th, 2025"},"versionCreatedAt":"2025-09-09 11:31:16","video":"","vorDoi":"10.1038/s41467-025-64703-5","vorDoiUrl":"https://doi.org/10.1038/s41467-025-64703-5","workflowStages":[]},"version":"v1","identity":"rs-5658648","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5658648","identity":"rs-5658648","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}