Aminated Carbon Nanofiber-Mediated Nanoconfined Liquid Phase Nanoextraction Coupled with Py-GC/MS for Sensitive Determination of Polystyrene Nanoplastics

Aminated Carbon Nanofiber-Mediated Nanoconfined Liquid Phase Nanoextraction Coupled with Py-GC/MS for Sensitive Determination of Polystyrene Nanoplastics | 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 Research Article Aminated Carbon Nanofiber-Mediated Nanoconfined Liquid Phase Nanoextraction Coupled with Py-GC/MS for Sensitive Determination of Polystyrene Nanoplastics Jin-Chi Jiang, Zixuan Zhang, Long-Yue Meng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8650715/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Apr, 2026 Read the published version in Microchimica Acta → Version 1 posted 9 You are reading this latest preprint version Abstract Nanoplastics pose severe ecological and human health risks due to their high reactivity and bioaccumulation potential, but their efficient extraction and precise detection remain challenging. Herein, a novel integrated method combining nanoconfined liquid phase nanoextraction (NLPNE) based on aminated carbon nanofibers/ carbon fibers (NH 2 -CNFs/CFs) with pyrolysis-gas chromatography-mass spectrometry (Py/GC-MS) was developed for the sensitive determination of polystyrene (PS) nanoplastics in aqueous samples. NLPNE plays a pivotal role: the nanoconfined spaces formed by entangled CNFs accelerate PS mass transfer via short-range diffusion, while amino groups enhance specific electrostatic interactions with negatively charged PS, achieving rapid and selective pre-enrichment. Optimized with acetonitrile as the nanoconfined solvent, the method reaches extraction equilibrium quickly, following pseudo-first-order kinetics and Langmuir monolayer adsorption. Direct Py-GC/MS analysis using styrene trimer (m/z=312) as the marker yields a low detection limit of 0.56 μg/L. The method provided a novel technical solution for the detection of nanoplastics in complex matrices and facilitating future studies on their environmental behaviors. Polystyrene nanoplastics Aminated carbon nanofibers Nanoconfined liquid phase nanoextraction Pyrolysis-gas chromatography-mass spectrometry Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction In 2004, Thompson et al. pioneered the term "microplastics" in the prestigious journal Science , highlighting the potential ecological risks and bringing the issue of microplastic pollution to the forefront of environmental awareness [ 1 ]. As a ubiquitous byproduct of microplastic degradation or unintended release during manufacturing, nanoplastics (typically defined as plastic particles with a particle size < 100 nm) even more diminutive and possess a remarkably higher specific surface area-to-volume ratio [ 2 , 3 ]. This unique structural feature endows them with distinctive physicochemical properties, such as enhanced surface reactivity, superior colloidal stability, and strong interfacial interaction capabilities, and biological activities that differ fundamentally from their microscale counterparts. Consequently, nanoplastics are more prone to being adsorbed, ingested, and accumulated by organisms across trophic levels, readily infiltrating biological systems and participating in food chain transfer. Worse still, they can act as carriers for hazardous substances (e.g., heavy metals, persistent organic pollutants) through surface adsorption, posing synergistic and composite risks to ecological integrity and human health [ 4 ]. Against this backdrop, investigations into the environmental occurrence, migration and transformation pathways, and ecological effect assessments of nanoplastics have emerged as pivotal research hotspots in the field of environmental science. Among these core research thrusts, the efficient separation, extraction, and precise detection of nanoplastics constitute the indispensable prerequisite for all subsequent studies. Only by effectively isolating nanoplastics from complex environmental matrices and achieving accurate detection can reliable data support be furnished for elucidating their environmental behaviors, evaluating ecological risks, and developing targeted pollution control technologies. However, nanoplastics' inherent characteristics, including their ultra-small size, chemical heterogeneity, and intricate interactions with environmental components-pose formidable technical challenges to their extraction and detection [ 5 ]. Conventional extraction methods, such as liquid-liquid extraction and solid-phase extraction, suffer from inherent limitations: liquid-liquid extraction is plagued by emulsion formation and low enrichment efficiency for nano-sized analytes, while solid-phase extraction often exhibits insufficient adsorption capacity and poor selectivity for nanoplastics [ 6 – 8 ]. Although innovative approaches like density-based separation, enzymatic digestion, and surfactant assisted extraction show promising application prospects, they still face practical bottlenecks, including low extraction efficiency, high operational costs, and cumbersome procedures-that hinder their widespread adoption. To address these limitations, our research team previously leveraged the size effect and interfacial properties of nanomaterials, coupled with precision synthesis technology of carbon nanofibers (CNFs), to develop a novel extraction method: nanoconfined liquid phase nanoextraction (NLPNE) [ 9 ]. NLPNE employs the three dimensions (3D) porous channels of CNFs as the extraction support unit, distinguishing itself from traditional methods through higher sensitivity, faster extraction kinetics, and superior enrichment efficiency. Notably, the CNFs matrix enables the capture of nanoplastics via physical interception effects, while the nanoconfined space within the fiber channels significantly enhances intermolecular interactions, including hydrogen bonding, π-π stacking, and electrostatic interactions, between target nanoplastics and the nanoconfined solvent [ 10 ]. Furthermore, the nanoscale pores restrict the orientation and mobility of nanomaterials, modifying their interaction with the nanoconfined solvent and thereby improving the selectivity and efficiency of the extraction process [ 11 ]. Efficient extraction techniques lay a solid foundation for the precise analysis of nanoplastics, and the selection of appropriate detection methods directly determines the sensitivity, accuracy, and specificity of the analytical results, forming a synergistic "extraction-detection" technical chain that is critical for overcoming nanoplastics analysis challenges. Currently, nanoplastics detection has evolved into a diversified system centered on spectroscopy and mass spectrometry (MS), complemented by microscopy and electrochemical techniques [ 12 – 14 ]. Spectroscopic methods, such as Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopy, are widely used for rapid screening of large batches of samples due to their simplicity of operation and rapid response [ 15 – 17 ]. However, they suffer from insufficient sensitivity for low-concentration nanoplastics and are highly susceptible to matrix interference, often requiring complex pretreatment to avoid signal masking. Microscopy techniques enable visual observation and particle size characterization of nanoplastics but are limited by low detection efficiency and difficulties in quantitative analysis. In contrast, MS, particularly pyrolysis gas chromatography-mass spectrometry (Py/GC-MS), stands out for its exceptional sensitivity and specificity, synergizing the efficient separation capability of gas chromatography with the detection of MS to enable accurate identification of multiple polymer types in complex samples [ 18 , 19 ]. Its pyrolysis step directly converts polymeric nanoplastics into characteristic small-molecule fragments, eliminating the need for cumbersome sample pretreatment, extraction, or derivatization, and this inherent advantage aligns perfectly with the high-efficiency enrichment provided by NLPNE, forming an integrated "sample-to-answer" workflow that minimizes sample loss and maximizes analytical throughput, thereby rendering it particularly suitable for the precise analysis of diverse nanoplastics in complex environmental matrices. Building on the aforementioned technical advances, this study for the first time employs NLPNE based on aminated carbon nanofibers (NH 2 -CNFs/CFs) for the extraction of polystyrene (PS) nanoplastics from aqueous samples, followed by characterization and quantification via Py/GC-MS. This integrated method achieves the enrichment, extraction, and separation of PS nanoplastics from water samples within a short timeframe. The superior performance is attributed not only to the enhanced capture of nanoplastics by the nanoconfined solvent but also to the key role of positively charged NH 2 -CNFs/CFs in pre-enrichment-facilitated by electrostatic interactions between the amine-functionalized fibers and negatively charged PS nanoplastics. In the subsequent Py/GC-MS analysis, characteristic signal peaks corresponding to styrene monomer, dimer, and trimer were successfully detected, confirming the reliability of the method. This work provides a novel technical approach and innovative insights for the rapid qualitative and quantitative detection of nanoplastics in complex matrices, as well as for future investigations into their environmental behaviors and ecological effects. 2. Experimental 2.1. Chemicals and instruments Ethylenediamine (C 2 H 8 N 2 ), 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide hydrochloride (EDC), acetonitrile (ACN) were purchased from Innochem (Beijing, China). Polystyrene nanoplastics (PS) were monodispersed in deionized water (Janus New Materials Co., LTD. Nanjing, China). 2.2 Synthesis of CNFs/CFs CNFs/CFs were prepared following the method reported by Meng et al. with the following modifications applied [ 20 ]: the tube furnace was operated at 600 ℃, the N 2 flow rate was set 150 mL min − 1 , and H 2 was used instead of 5% H 2 /Ar at a flow rate of 20 mL min − 1 for 30 min. All the other experimental conditions remained unchanged. 2.3 Synthesis of amino-functionalized carbon nanofibres (NH 2 -CNFs/CFs) CNFs/CFs were ultrasonically mixed with 60 mL of deionised water, 0.5 mL of C 2 H 8 N 2 for 5 min, then added with an appropriate amount of 5 mM of EDC and continued to be ultrasonicated for 30 min, then stirred for 12 h at room temperature. Finally, the product was dried at 40 ℃ to obtain NH 2 -CNFs/CFs. 2.4 Characterization The morphological and structural features of the samples were characterized by scanning electron microscopy (SEM; SU8000, Hitachi, Japan). 2.5 Nanoconfined liquid phase nanoextraction procedure The liquid-phase nano-extraction process can be divided into three stages: (a) pretreatment stage: 0.5×3 cm NH 2 -CNFs/CFs were ultrasonically pretreated in a nanoconfined solvent for 3 min; (b) nanoconfined solvent loading stage: 500 µL of nanoconfined solvent was uniformly added dropwise on the surface of NH 2 -CNFs/CFs; and (c) extraction stage: the NH 2 -CNFs/CFs were immersed in the solution containing polystyrene nanoplastics for a period of time for extraction. Finally, there is no desorption stage, the extracted NH 2 -CNFs/CFs were at room temperature and sent to Py/GC-MS for for analysis. Meanwhile, the concentration of the remaining polystyrene nanoplastics was determined using a UV spectrophotometer. 2.5 Py/GC-MS analysis Polystyrene nanoplastics were analysed via a Frontier EGA/PY-3030D pyrolyser coupled to a gas chromatography-mass spectrometry (GC/MS) system. Following the extraction of PS, the NH 2 -CNFs/CFs composites were air-dried at room temperature and then directly introduced into the Py/GC-MS instrument for analysis. Helium was adopted as the carrier gas for the Py-GC/MS analysis, with the pyrolyzer oven temperature set at 590°C and the interface temperature maintained at 300°C. GC separation was conducted on a Thermo Trace 1300 system fitted with a DB-5MS capillary column (30 m × 0.25 mm, 0.25 µm film thickness), which was hyphenated to a Thermo ISQLT quadrupole mass spectrometer. The GC oven temperature program was set as follows: an initial isothermal hold at 50 ℃ for 2 min, followed by a linear ramp to 320 ℃ at a rate of 10 ℃ min − 1 , and a final hold at this temperature for 3 min. For mass spectrometry (MS), the operating parameters were configured as below: ion source temperature of 230 ℃, MS transfer line temperature of 280 ℃, quadrupole temperature of 150 ℃, and electron impact (EI) ionization mode with an electron energy of 70 eV at 200 ℃. MS was operated in full scan mode throughout the analysis. 3. Results and Discussion 3.1 Material characterization Using the chemical vapor deposition method, CNFs were grown in situ on the surface of flexible carbon fibers (CFs), and the as-prepared CNFs/CFs composite was further subjected to amino-functionalization to obtain NH 2 -CNFs/CFs. Subsequently, this functionalized composite material was employed to treat PS via NPLNE. The SEM images in Fig. 1 a-h comprehensively present the morphological characteristics of the samples at each stage of this process. Specifically, Fig. 1 a displays the overall morphology of pristine CFs, confirming their diameter of ~ 7.4 µm. The high-magnification view in Fig. 1 b further reveals that the surface of CFs is not smooth but decorated with numerous continuous longitudinal grooves: these structures not only enhance the surface roughness of CFs but also serve as effective anchoring sites for metal catalysts, thereby providing favorable nucleation conditions for the subsequent in situ growth of CNFs. For the CNFs/CFs composite, Fig. 1 c demonstrates that CNFs coat the CFs matrix uniformly and densely, forming a complete encapsulating layer on the CFs surface. The high-resolution details in Fig. 1 d show that the as-grown CNFs exhibit a size distribution concentrated in the range of 10–50 nm, presenting a curled and cross-linked tangled state. The interwoven structure between CNFs naturally forms abundant nanoscale spaces, which can act as reservoirs to accommodate nanoplastics. In contrast, the overall structural framework of NH 2 -CNFs/CFs after amino functionalization (Fig. 1 e-f) is similar to that of CNFs/CFs. However, there are subtle differences in details: the texture becomes more brittle and harder, the entanglement degree slightly decreases, and the structural rigidity has a slight increase compared to the original CNFs/CFs. Regarding the NH 2 -CNFs/CFs sample that underwent NPLNE treatment without subsequent desorption (Fig. 1 g-h), the high magnification SEM images clearly show that polystyrene nanoplastics are tightly filled in the nanospace of the composite, rather than simply adsorbed on the surface of CNFs. This phenomenon is attributed to the mechanism of NPLNE: after the nanoconfined solvent extracts the nanoplastics, the solvent evaporates gradually during the post-treatment process, leaving the nanoplastics retained in the confined nanospace of the composite. 3.2 NLPNE kinetics and isotherm To clarify the adsorption mechanism of NH 2 -CNFs/CFs in the NPLNE of PS, a promising technology for mitigating PS contamination, systematic kinetic and isothermal adsorption analyses were performed. The fitting curves and corresponding model parameters are presented in Fig. 2 and Table 1 – 2 , respectively. Figure 2 a presents the kinetic fitting curve of the NPLNE process, clearly revealing a distinctive two-stage adsorption profile. In the initial rapid-uptake stage, occurring within the first ~ 2 min, the adsorption capacity (q e ) exhibits a steep increase, which is not merely a result of high surface area or functional group availability, but rather a direct manifestation of the nanoconfined liquid-phase extraction mechanism intrinsic to NPLNE [ 21 ]. To quantify this kinetic behavior, the pseudo-first-order and pseudo-second-order models were employed for fitting. As summarized in Table 1 , the pseudo-first-order model yields a fitted equilibrium q e of 14.79 mg/g, a rate constant (k 1 ) of 1.40 min − 1 , and a determination coefficient (R 2 ) of 0.996; in contrast, the pseudo-second-order model gives a q e of 16.28 mg/g, a rate constant (k 2 ) of 0.129 g·mg − 1 ·min − 1 , and an R 2 of 0.979. Notably, the q e of the pseudo-first-order model is more consistent with the equilibrium adsorption capacity reflected by experimental data (Fig. 1 a), and its higher R 2 value indicates that the NPLNE process of PS by NH 2 -CNFs/CFs is better described by the pseudo-first-order kinetic model [ 22 ]. This result aligns with the intrinsic nature of NPLNE: the rate-controlling step of the process is the diffusion of PS within the nanoconfined spaces, rather than the surface reaction process in traditional adsorption systems. Unlike conventional bulk-phase adsorption systems where target analytes must traverse relatively large diffusion distances through stagnant or slow-moving liquid layers, NPLNE leverages the nanoconfined solvent environments formed within the interwoven networks of CNFs (cellulose nanofibers) on the NH 2 -CNFs/CFs substrate. These nanoconfined regions, with characteristic dimensions on the order of tens to hundreds of nanometers, act as micro-reactors that fundamentally alter the mass transfer regime [ 9 ]. Within these nanospaces, the nanoconfined solvent molecules exhibit anomalous transport behaviors, including reduced viscosity, enhanced molecular mobility, and elevated local concentration gradients, due to the breakdown of bulk-phase hydrodynamic assumptions. This enables ultrafast short-range diffusion of PS molecules toward the amino-functionalized binding sites embedded on the CNFs surfaces [ 10 , 23 ]. The amino groups serve not only as chemoselective ligands that form hydrogen bonds and electrostatic interactions with the negatively charged head groups of PS, but also as spatial anchors that help maintain the structural integrity of the nanoconfined domains under wet conditions [ 24 ]. As the extraction proceeds, these nanoconfined solvent domains gradually become saturated with PS molecules, leading to a competitive occupancy effect, where incoming PS molecules must displace already-bound species or find increasingly scarce free binding sites. This transition marks the onset of the second, slower stage of the adsorption curve. Here, the rate-limiting step shifts from nanoconfined diffusion to surface site saturation and intermolecular repulsion, resulting in a pronounced decrease in the adsorption rate until thermodynamic equilibrium is established. Crucially, the NPLNE mechanism does not rely on external agitation, temperature gradients, or pressure-driven flow to enhance mass transfer. Instead, it exploits nanoscale solvation dynamics to achieve high-efficiency extraction at ambient conditions [ 9 , 10 ]. This makes NPLNE particularly advantageous for processing trace-level biomolecules in complex matrices, where preserving structural integrity and minimizing sample loss are paramount. The initial rapid uptake observed in Fig. 2 a is a direct consequence of the nanoconfined liquid-phase extraction mechanism, where the synergy between geometric confinement, enhanced nanoscale diffusion, and chemoselective surface functionalization enables rapid, selective, and high-capacity extraction of PS, an effect unattainable in traditional bulk-phase systems [ 10 , 25 ]. The kinetic modeling further validates that this process is governed by diffusion within nanoconfined environments, rather than surface reaction kinetics, reinforcing the uniqueness of the NPLNE paradigm. Figure 1 b presents the isothermal extraction isotherm of the NPLNE system. Because the PS capture event occurs inside a nanometre-thick liquid film rather than on a solid surface, the plateau value reflects the solubility limit of PS in the nanoconfined solvent phase, not the surface-site exhaustion typical of adsorption [ 10 ]. The Langmuir fit (q m = 8.79 mg g − 1 , K L = 0.85 L mg − 1 , R 2 = 0.992) vastly outperforms the Freundlich fit (R 2 = 0.920), corroborating the kinetic conclusion that the fibre scaffold presents a spatially uniform array of amino-functionalised nanospaces. Within these domains, PS molecules undergo rapid, diffusion-controlled uptake until the nanophase solvent is saturated, giving rise to the Langmuirian “monolayer” plateau [ 26 ]. Thus, the isotherm is quantitative proof that NPLNE operates via homogeneous, single-stage partitioning into a nanoconfined liquid layer, seamlessly extending the fast, diffusion-limited regime observed in the kinetic profile to the thermodynamic limit. Taken together, the kinetic and thermodynamic signatures depict NPLNE as a single, homogeneous liquid-liquid partitioning event: PS is rapidly delivered by nanoscale diffusion into a thin, amino-lined solvent layer, where it remains until the nanophase is saturated. The result is an extraction that is complete within minutes, operates at ambient temperature without external energy, and yields a PS-rich nanoconfined phase ready for downstream analysis or disposal. 3.3 Condition optimization of NLPNE The nanoconfined space environment and associated process parameters directly determine the efficiency of NLPNE. In this study, we focused on investigating the effects of key factors, including the preparation temperature of CNFs/CFs, dosage of NH 2 -CNFs/CFs, type of nanoconfined solvent, and dosage of nanoconfined solvent, and tracked their influence on PS removal (Fig. 3 a-d). 3.3.1 Effect of CNFs/CFs preparation temperature Figure 3 a depicts the variation in PS removal rate with the preparation temperature of CNFs/CFs. As the temperature increased from 500 ℃ to 750 ℃, the removal rate rose continuously, reaching a maximum of ~ 80% at 750 ℃. This trend is attributed to the temperature-dependent growth of CNFs: higher calcination temperatures not only promotes the dense and uniform growth of CNFs on the surface of CFs, but also expands the nanoscale confined space between entangled CNFs, this structural feature creates more sufficient space conditions for the filling of nanoconfined solvents. 3.3.2 Effect of NH 2 -CNFs/CFs dosage The influence of NH 2 -CNFs/CFs dosage on the PS removal rate is shown in Fig. 3 b. The removal rate increased gradually with increasing dosage, reaching ~ 60% at 15 mg. This phenomenon is explained by the positive correlation between adsorbent dosage and active sites: a higher dosage of NH 2 -CNFs/CFs provides more nanoconfined spaces and amino-functionalized binding sites, thereby enhancing the probability of contact and interaction between the composite and PS. 3.3.3 Effect of nanoconfined solvent type Selecting an appropriate nanoconfined solvent is a core optimization step for NLPNE efficiency. Here, we compared the PS removal rates of three polar nanoconfined solvents, methanol, ethanol and acetonitrile, as shown in Fig. 3 c. All three nanoconfined solvents can interact with the polar groups on the PS surface, but their removal efficiencies differ significantly: the removal rates of methanol and ethanol are ~ 70%, while that of acetonitrile reaches ~ 85%. This advantage of acetonitrile originates from its dual interaction mechanism with PS: the cyano group (-CN) in acetonitrile not only forms strong dipole-dipole interactions with the polar segments of PS but also engages in π-π stacking interactions with the aromatic ring structure of styrene, thus strengthening the nanoconfined solvent-PS binding force [ 5 ]. Therefore, acetonitrile was selected as the optimal nanoconfined solvent for subsequent experiments. 3.3.4 Effect of nanoconfined solvent dosage Figure 3 d illustrates the relationship between acetonitrile dosage and PS removal rate. The removal rate increased sharply when the dosage was raised from 0.25 mL to 0.5 mL, but decreased slightly with further dosage elevation to 0.75 mL. This trend can be rationalized by the nanoconfined space matching principle: insufficient nanoconfined solvent cannot fully fill the nanoconfined spaces of NH 2 -CNFs/CFs, leading to incomplete contact with PS. Excessive nanoconfined solvent, however, overfills the confined spaces and dilutes the effective concentration of PS in the nanoscale region, thereby weakening the extraction efficiency. Thus, 0.5 mL was determined as the optimal nanoconfined solvent dosage. Collectively, the data demonstrate that NLPNE is governed by the amount, uniformity and chemical identity of the nanoconfined liquid phase. Under the selected conditions (750°C growth temperature, 15 mg NH 2 -CNFs/CFs, 0.5 mL acetonitrile), PS removal reaches ~ 85%, a performance that scales directly with the quantity and quality of the nanoconfined extractor rather than with classical surface adsorption sites. 3.4 Determination of PS in water by Py/GC-MS Py-GC/MS was employed to perform on-line cleavage analysis of PS loaded on NH 2 -CNFs/CFs, yielding the total ion current (TIC) profile and characteristic mass spectral patterns of PS pyrolysis products, as presented in Fig. 4 . Notably, no solvent peak was observed in the TIC profile (Fig. 4 a), which can be attributed to the complete evaporation of trace acetonitrile, used as the nanoconfined solvent, during the sample injection process, leaving only the pyrolysis products of the extracted PS for analysis. The composition and content of PS pyrolysis products are highly dependent on pyrolysis temperature and duration: polystyrene undergoes pyrolysis in the 300–600 ℃ range, generating typical products including styrene monomers, dimers, and trimers. Specifically, at 300–350 ℃, the pyrolysis rate is relatively slow, and trimers dominate the product distribution; as the temperature rises to 350–450 ℃, the pyrolysis rate accelerates sharply, elevating the proportion of monomers; within 450–600 ℃, the pyrolysis proceeds at a high rate, further increasing the monomer fraction while the trimer proportion decreases significantly [ 27 ]. For this study, the optimal pyrolysis parameters were determined by referencing relevant thermal decomposition data from prior works, which fall within the conventional operating range and are adapted to the target NH 2 -CNFs/CFs-PS sample system [ 28 , 29 ]. As shown in the TIC profile and extracted ion chromatograms (EICs) in Fig. 4 a, the PS pyrolysis products were sequentially separated with good resolution: the styrene monomer eluted at ~ 5 min and the trimer at ~ 23.16 min. These peaks exhibited high response intensities with no overlap, though slight tailing was observed, this phenomenon is likely ascribed to the retention of pyrolysis components by the chromatographic column's stationary phase during separation [ 30 , 31 ]. Figure 4 b displays the MS of the pyrolysis products: the styrene monomer is characterized by prominent fragment ions, for example, m/z = 51, 78, 104, with m/z = 104 as the molecular ion peak, while the styrene trimer shows characteristic ions including m/z = 91,117, 207, and m/z = 312 (molecular ion peak) [ 32 ]. PS pyrolysis products were successfully identified via mass spectral database matching. Considering the high specificity and abundance of the styrene trimer (m/z = 312), it was selected as the target indicator compound for PS after thermal cleavage; qualitative confirmation was performed based on its retention time and the abundance ratio of fragment ions, with m/z = 117 and 207 serving as supplementary qualifying ions [ 29 ]. Meanwhile, based on the calculation standard of detection limit, the limit of detection (LOD) for PS by this method can reach 0.56 µg/L, demonstrating the excellent sensitivity of this method in the trace analysis of PS. 4. Conclusions This study constructed a sensitive analytical platform for trace PS by coupling NH 2 -CNFs/CFs-based NLPNE with Py-GC/MS. The NH 2 -CNFs/CFs prepared at 750 ℃ features abundant nanoconfined spaces and surface amino groups, which synergistically enhance PS capture via accelerated mass transfer and specific interactions, dipole-dipole and π-π stacking. Optimized NLPNE parameters achieved a PS removal rate of ~ 85% with minimal nanoconfined solvent usage. The Py-GC/MS system using styrene trimer as the indicator exhibited a low detection limit of 0.56 µg/L without nanoconfined solvent interference. This method integrates high extraction efficiency, strong selectivity, and environmental friendliness, providing a practical solution for PS monitoring in environmental samples. Future work will focus on complex matrix adaptation and material regeneration to expand its application scope. Declarations Funding : This study was supported by grants from the National Natural Science Foundation of China (22166034). Conflicts of Interest : The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. CRediT authorship contribution statement : Jin-Chi Jiang: Writing-original draft, Data curation, Formal analysis; Zixuan Zhang: Methodology, Investigation, Writing-review and editing Long-Yue Meng: Project administration, Funding acquisition. Availability of data and material : Data sharing not applicable to this article as no datasets were generated or analysed during the current study. Code availability : Not applicable. Ethics approval : Not applicable. References R.C. Thompson, Y. Olsen, R.P. Mitchell, A. Davis, S.J. Rowland, A.W.G. John, D. McGonigle, A.E. Russell, (2004) Lost at sea: Where is all the plastic? 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Veres, (2023) Surface-enhanced raman spectroscopy for the detection of microplastics Applied Surface Science 608: 155239. https://doi.org/10.1016/j.envres.2022.113583. X.-x. Zhou, L.-t. Hao, H.-y.-z. Wang, Y.-j. Li, J.-f. Liu, (2019) Cloud-point extraction combined with thermal degradation for nanoplastic analysis using pyrolysis gas chromatography–mass spectrometry Analytical Chemistry 91: 1785-1790. https://doi.org/10.1021/acs.analchem.8b04729. B.Z. Wang, Y.A. Piao, Z.X. Zhang, T. Han, B. Jin, L.Y. Meng, (2024) Enrichment of nanoplastics in waters using magnetic solid phase extraction with magnetic biochar adsorbents and their determination by pyrolysis gas chromatography-mass spectrometry Journal of Separation Science 47: e70045. https://doi.org/10.1002/jssc.70045. Z.-Y. Feng, R. Liu, J.-C. Jiang, L.-Y. Meng, (2024) Villous 3D nanoconfined flexible carbon fibers-based electrode toward dopamine electrochemical detection Diamond and Related Materials 141: 110695. https://doi.org/10.1016/j.diamond.2023.110695. J.-C. Jiang, D.-D. Cui, Z.-Y. Feng, B. Jin, L.-Y. Meng, (2026) Nanoconfined effect mediated NH 2 -CNFs/CFs assisted dispersive solid phase extraction coupled with Py-GC/MS for the analysis of polyethylene nanoplastics/bisphenols aggregates Inorganic Chemistry Communications 184: 116035. https://doi.org/10.1016/j.inoche.2025.116035. J. Du, J. Li, R. Yin, S. Liu, T. Deng, X. Du, (2025) Study on selective adsorption of organic pollutants in environmental water samples by solid-phase microextraction based on MOF-derived coatings RSC Advances 15: 37570-37578. https://doi.org/10.1039/D5RA02456K. B. Li, C. Zou, H. Liang, W. Chen, S. Lin, Y. Liao, (2021) Mass transfer from nanofluid single drops in low interfacial tension liquid–liquid extraction process Chemical Physics Letters 771: 138530. https://doi.org/10.1016/j.cplett.2021.138530. S. Wang, C. Fu, Z. Lin, Y. Lin, Y. Xu, Z. Gao, F. Zhang, L. Fang, X. Li, J. Fu, (2025) One-pot quick preparation of a magnetic nanocomposite based on aminated/fluorinated carbon nanotubes for the efficient capture of fluoroquinolones in aqueous samples Journal of Molecular Liquids 437: 128577. https://doi.org/10.1016/j.molliq.2025.128577. J. Kamp, G. Dierkes, P.N. Schweyen, A. Wick, T.A. Ternes, (2023) Quantification of poly(vinyl chloride) microplastics via pressurized liquid extraction and combustion ion chromatography Environmental Science & Technology 57: 4806-4812. https://doi.org/10.1021/acs.est.2c06555. N. Wang, Y. Wei, H. Sun, N. Wang, Y. Liu, Y. Li, (2025) Mechanistic insights into simultaneous adsorption of contaminants in dyeing wastewater using polyurethane-based hierarchical porous adsorbents Carbon Letters 35: 2197-2213. https://doi.org/10.1007/s42823-025-00915-5. K.E. Grafinger, C. Ochiai, H.-X. Zhou, T. Hettich, A. Büttler, R. Álvarez Troncoso, A. Zenker, S. Gaugler, (2024) Towards quantitative microplastic analysis using pyrolysis-gas chromatography coupled with mass spectrometry Polymer Testing 140: 108620. https://doi.org/10.1016/j.polymertesting.2024.108620. F. Hasager, Þ.N. Björgvinsdóttir, S.F. Vinther, A. Christofili, E.R. Kjærgaard, S.S. Petters, M. Bilde, M. Glasius, (2024) Development and validation of an analytical pyrolysis method for detection of airborne polystyrene nanoparticles Journal of Chromatography A 1717: 464622. https://doi.org/10.1016/j.chroma.2023.464622. Z. Zhang, J.-C. Jiang, Z.-Y. Feng, B. Jin, Y. Liu, L.-Y. Meng, (2024) ACFs-NH 2 developed for dispersive solid phase extraction combined with Py-GC/MS for nanoplastic analysis in ambient water samples Journal of Chromatography A 1736: 465382. https://doi.org/10.1016/j.chroma.2024.465382. A. Martín de la Fuente, F.C. Marhuenda-Egea, M. Ros, J.A. Pascual, J.A. Saez-Tovar, E. Martinez-Sabater, R. Peñalver, (2022) Thermogravimetry coupled with mass spectrometry successfully used to quantify polyethylene and polystyrene microplastics in organic amendments Environmental Research 213: 113583. https://doi.org/10.1016/j.envres.2022.113583. X.-y. Sheng, Y.-j. Lai, S.-j. Yu, Q.-c. Li, Q.-x. Zhou, J.-f. Liu, (2023) Quantitation of atmospheric suspended polystyrene nanoplastics by active sampling prior to pyrolysis–gas chromatography–mass spectrometry Environmental Science & Technology 57: 10754-10762. https://doi.org/10.1021/acs.est.3c02299. L. Hou, B. Pan, Y. Fan, S. Xu, Z. Huang, H. Liu, J. Yu, (2025) Analysis of micro/nanoplastics on the surface of polystyrene foam lunch boxes by pyrolysis-gas chromatography/mass spectrometry Journal of Analytical and Applied Pyrolysis 190: 107161. https://doi.org/10.1016/j.jaap.2025.107161. Tables Table 1 Pseudo-first order and pseudo-second order parameters for NLPNE of PS by NH 2 -CNFs/CFs. Pseudo-first order Pseudo-second order PS q e (mg/g) k 1 (min − 1 ) R 2 q e (mg/g) k 2 (g·mg − 1 ·min) −1 R 2 14.79 1.40 0.996 16.28 0.129 0.979 Table 2 Langmuir and Freundlich parameters for NLPNE of PS by NH 2 -CNFs/CFs. Langmuir Freundlich q m (mg/g) K L (L/mg) R 2 n K F (m/mg) R 2 PS 8.79 0.85 0.992 3.33 3.94 0.920 Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstracts.docx Cite Share Download PDF Status: Published Journal Publication published 09 Apr, 2026 Read the published version in Microchimica Acta → Version 1 posted Editorial decision: Revision requested 24 Feb, 2026 Reviews received at journal 24 Feb, 2026 Reviews received at journal 22 Feb, 2026 Reviewers agreed at journal 22 Feb, 2026 Reviewers agreed at journal 10 Feb, 2026 Reviewers invited by journal 26 Jan, 2026 Editor assigned by journal 21 Jan, 2026 Submission checks completed at journal 21 Jan, 2026 First submitted to journal 20 Jan, 2026 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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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8650715","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581607023,"identity":"2bdde35b-f220-4169-b7a2-dceece3af99b","order_by":0,"name":"Jin-Chi Jiang","email":"","orcid":"","institution":"Yanbian University","correspondingAuthor":false,"prefix":"","firstName":"Jin-Chi","middleName":"","lastName":"Jiang","suffix":""},{"id":581607024,"identity":"6aed1041-0c19-40bf-bbd5-de308adea665","order_by":1,"name":"Zixuan Zhang","email":"","orcid":"","institution":"Yanbian University","correspondingAuthor":false,"prefix":"","firstName":"Zixuan","middleName":"","lastName":"Zhang","suffix":""},{"id":581607025,"identity":"d0b8bfca-56f5-41b6-bcb4-a4a00b7bae04","order_by":2,"name":"Long-Yue Meng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACPghlw2AAoniI0cIGodJI13KYFC0S2YmPC36dT9wukcD44G0bg7w5YS25m41n9t1O3DkjgdlwbhuD4c4Gwlq2SfP23E7ccCOBTZq3jSHB4ABhLdt/8/acA2lh/02slm3MPD8OgG1hJk4Lz9vN0rwNycY7ex42S845J2G4gZAWfvbcjZ95/tjJbmdPPvjhTZmNPEFbGAQSGBgY2xgcGxgYG4BcCULqQdaADP3DYE+E0lEwCkbBKBipAAC+wEAfJ5kpFAAAAABJRU5ErkJggg==","orcid":"","institution":"Yanbian University","correspondingAuthor":true,"prefix":"","firstName":"Long-Yue","middleName":"","lastName":"Meng","suffix":""}],"badges":[],"createdAt":"2026-01-20 15:38:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8650715/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8650715/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00604-026-08024-4","type":"published","date":"2026-04-09T15:57:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":101435339,"identity":"1e523a7d-be17-41bd-94cc-2a5b99f73357","added_by":"auto","created_at":"2026-01-29 16:12:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":547384,"visible":true,"origin":"","legend":"\u003cp\u003eSEM images of CFs (a-b), CNFs/CFs (c-d), NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs (e-f) and NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs after NLPNE (g-h).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8650715/v1/b8fbb6c169125d986cbc3113.png"},{"id":101435331,"identity":"456addd4-95ee-4e11-aa1c-2f2753d9981f","added_by":"auto","created_at":"2026-01-29 16:12:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":80751,"visible":true,"origin":"","legend":"\u003cp\u003eThe adsorption kinetics curves of the pseudo-first-order and the pseudo-second-order (a), and the isothermal adsorption fitting curves of Langmuir and Freundlich (b).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8650715/v1/b6e20f5260056623b6d351a4.png"},{"id":101435281,"identity":"57236e7a-55cc-4010-9546-a0eceef697a8","added_by":"auto","created_at":"2026-01-29 16:12:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":139431,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of growth temperature of CNFs/CFs (a), dosage of CNFs/CFs (b), type of nanoconfined solvent (c), and dosage of nanoconfined solvent on the NLPNE of PS.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8650715/v1/70d3f38eb1c5ba322a49b583.png"},{"id":101435328,"identity":"9c51ca29-5255-4fb9-89bc-8cbd64391c3b","added_by":"auto","created_at":"2026-01-29 16:12:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48817,"visible":true,"origin":"","legend":"\u003cp\u003ePy-GC/MS spectrum of the NLPNE of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs for PS.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8650715/v1/245d1a5c26bbbf0f555af881.png"},{"id":106809102,"identity":"aa5dbd50-f391-47af-827d-5bee2e871ba3","added_by":"auto","created_at":"2026-04-13 16:06:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1544031,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8650715/v1/f778f5a8-d659-4c3f-acce-9bfe5188d746.pdf"},{"id":101435302,"identity":"70958368-68ef-4e60-a96d-e4fa4d9034af","added_by":"auto","created_at":"2026-01-29 16:12:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":278869,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstracts.docx","url":"https://assets-eu.researchsquare.com/files/rs-8650715/v1/859fc7c7d95643dea0bbd3d5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Aminated Carbon Nanofiber-Mediated Nanoconfined Liquid Phase Nanoextraction Coupled with Py-GC/MS for Sensitive Determination of Polystyrene Nanoplastics","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn 2004, Thompson \u003cem\u003eet al.\u003c/em\u003e pioneered the term \"microplastics\" in the prestigious journal \u003cem\u003eScience\u003c/em\u003e, highlighting the potential ecological risks and bringing the issue of microplastic pollution to the forefront of environmental awareness [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As a ubiquitous byproduct of microplastic degradation or unintended release during manufacturing, nanoplastics (typically defined as plastic particles with a particle size\u0026thinsp;\u0026lt;\u0026thinsp;100 nm) even more diminutive and possess a remarkably higher specific surface area-to-volume ratio [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This unique structural feature endows them with distinctive physicochemical properties, such as enhanced surface reactivity, superior colloidal stability, and strong interfacial interaction capabilities, and biological activities that differ fundamentally from their microscale counterparts. Consequently, nanoplastics are more prone to being adsorbed, ingested, and accumulated by organisms across trophic levels, readily infiltrating biological systems and participating in food chain transfer. Worse still, they can act as carriers for hazardous substances (e.g., heavy metals, persistent organic pollutants) through surface adsorption, posing synergistic and composite risks to ecological integrity and human health [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Against this backdrop, investigations into the environmental occurrence, migration and transformation pathways, and ecological effect assessments of nanoplastics have emerged as pivotal research hotspots in the field of environmental science.\u003c/p\u003e \u003cp\u003eAmong these core research thrusts, the efficient separation, extraction, and precise detection of nanoplastics constitute the indispensable prerequisite for all subsequent studies. Only by effectively isolating nanoplastics from complex environmental matrices and achieving accurate detection can reliable data support be furnished for elucidating their environmental behaviors, evaluating ecological risks, and developing targeted pollution control technologies. However, nanoplastics' inherent characteristics, including their ultra-small size, chemical heterogeneity, and intricate interactions with environmental components-pose formidable technical challenges to their extraction and detection [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Conventional extraction methods, such as liquid-liquid extraction and solid-phase extraction, suffer from inherent limitations: liquid-liquid extraction is plagued by emulsion formation and low enrichment efficiency for nano-sized analytes, while solid-phase extraction often exhibits insufficient adsorption capacity and poor selectivity for nanoplastics [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Although innovative approaches like density-based separation, enzymatic digestion, and surfactant assisted extraction show promising application prospects, they still face practical bottlenecks, including low extraction efficiency, high operational costs, and cumbersome procedures-that hinder their widespread adoption. To address these limitations, our research team previously leveraged the size effect and interfacial properties of nanomaterials, coupled with precision synthesis technology of carbon nanofibers (CNFs), to develop a novel extraction method: nanoconfined liquid phase nanoextraction (NLPNE) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. NLPNE employs the three dimensions (3D) porous channels of CNFs as the extraction support unit, distinguishing itself from traditional methods through higher sensitivity, faster extraction kinetics, and superior enrichment efficiency. Notably, the CNFs matrix enables the capture of nanoplastics via physical interception effects, while the nanoconfined space within the fiber channels significantly enhances intermolecular interactions, including hydrogen bonding, π-π stacking, and electrostatic interactions, between target nanoplastics and the nanoconfined solvent [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Furthermore, the nanoscale pores restrict the orientation and mobility of nanomaterials, modifying their interaction with the nanoconfined solvent and thereby improving the selectivity and efficiency of the extraction process [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEfficient extraction techniques lay a solid foundation for the precise analysis of nanoplastics, and the selection of appropriate detection methods directly determines the sensitivity, accuracy, and specificity of the analytical results, forming a synergistic \"extraction-detection\" technical chain that is critical for overcoming nanoplastics analysis challenges. Currently, nanoplastics detection has evolved into a diversified system centered on spectroscopy and mass spectrometry (MS), complemented by microscopy and electrochemical techniques [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Spectroscopic methods, such as Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopy, are widely used for rapid screening of large batches of samples due to their simplicity of operation and rapid response [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, they suffer from insufficient sensitivity for low-concentration nanoplastics and are highly susceptible to matrix interference, often requiring complex pretreatment to avoid signal masking. Microscopy techniques enable visual observation and particle size characterization of nanoplastics but are limited by low detection efficiency and difficulties in quantitative analysis. In contrast, MS, particularly pyrolysis gas chromatography-mass spectrometry (Py/GC-MS), stands out for its exceptional sensitivity and specificity, synergizing the efficient separation capability of gas chromatography with the detection of MS to enable accurate identification of multiple polymer types in complex samples [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Its pyrolysis step directly converts polymeric nanoplastics into characteristic small-molecule fragments, eliminating the need for cumbersome sample pretreatment, extraction, or derivatization, and this inherent advantage aligns perfectly with the high-efficiency enrichment provided by NLPNE, forming an integrated \"sample-to-answer\" workflow that minimizes sample loss and maximizes analytical throughput, thereby rendering it particularly suitable for the precise analysis of diverse nanoplastics in complex environmental matrices.\u003c/p\u003e \u003cp\u003eBuilding on the aforementioned technical advances, this study for the first time employs NLPNE based on aminated carbon nanofibers (NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs) for the extraction of polystyrene (PS) nanoplastics from aqueous samples, followed by characterization and quantification via Py/GC-MS. This integrated method achieves the enrichment, extraction, and separation of PS nanoplastics from water samples within a short timeframe. The superior performance is attributed not only to the enhanced capture of nanoplastics by the nanoconfined solvent but also to the key role of positively charged NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs in pre-enrichment-facilitated by electrostatic interactions between the amine-functionalized fibers and negatively charged PS nanoplastics. In the subsequent Py/GC-MS analysis, characteristic signal peaks corresponding to styrene monomer, dimer, and trimer were successfully detected, confirming the reliability of the method. This work provides a novel technical approach and innovative insights for the rapid qualitative and quantitative detection of nanoplastics in complex matrices, as well as for future investigations into their environmental behaviors and ecological effects.\u003c/p\u003e"},{"header":"2. Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Chemicals and instruments\u003c/h2\u003e \u003cp\u003eEthylenediamine (C\u003csub\u003e2\u003c/sub\u003eH\u003csub\u003e8\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003e), 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide hydrochloride (EDC), acetonitrile (ACN) were purchased from Innochem (Beijing, China). Polystyrene nanoplastics (PS) were monodispersed in deionized water (Janus New Materials Co., LTD. Nanjing, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Synthesis of CNFs/CFs\u003c/h2\u003e \u003cp\u003eCNFs/CFs were prepared following the method reported by Meng \u003cem\u003eet al.\u003c/em\u003e with the following modifications applied [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]: the tube furnace was operated at 600 ℃, the N\u003csub\u003e2\u003c/sub\u003e flow rate was set 150 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and H\u003csub\u003e2\u003c/sub\u003e was used instead of 5% H\u003csub\u003e2\u003c/sub\u003e/Ar at a flow rate of 20 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for 30 min. All the other experimental conditions remained unchanged.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Synthesis of amino-functionalized carbon nanofibres (NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs)\u003c/h2\u003e \u003cp\u003eCNFs/CFs were ultrasonically mixed with 60 mL of deionised water, 0.5 mL of C\u003csub\u003e2\u003c/sub\u003eH\u003csub\u003e8\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003e for 5 min, then added with an appropriate amount of 5 mM of EDC and continued to be ultrasonicated for 30 min, then stirred for 12 h at room temperature. Finally, the product was dried at 40 ℃ to obtain NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Characterization\u003c/h2\u003e \u003cp\u003eThe morphological and structural features of the samples were characterized by scanning electron microscopy (SEM; SU8000, Hitachi, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Nanoconfined liquid phase nanoextraction procedure\u003c/h2\u003e \u003cp\u003eThe liquid-phase nano-extraction process can be divided into three stages: (a) pretreatment stage: 0.5\u0026times;3 cm NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs were ultrasonically pretreated in a nanoconfined solvent for 3 min; (b) nanoconfined solvent loading stage: 500 \u0026micro;L of nanoconfined solvent was uniformly added dropwise on the surface of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs; and (c) extraction stage: the NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs were immersed in the solution containing polystyrene nanoplastics for a period of time for extraction. Finally, there is no desorption stage, the extracted NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs were at room temperature and sent to Py/GC-MS for for analysis. Meanwhile, the concentration of the remaining polystyrene nanoplastics was determined using a UV spectrophotometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Py/GC-MS analysis\u003c/h2\u003e \u003cp\u003ePolystyrene nanoplastics were analysed via a Frontier EGA/PY-3030D pyrolyser coupled to a gas chromatography-mass spectrometry (GC/MS) system. Following the extraction of PS, the NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs composites were air-dried at room temperature and then directly introduced into the Py/GC-MS instrument for analysis. Helium was adopted as the carrier gas for the Py-GC/MS analysis, with the pyrolyzer oven temperature set at 590\u0026deg;C and the interface temperature maintained at 300\u0026deg;C. GC separation was conducted on a Thermo Trace 1300 system fitted with a DB-5MS capillary column (30 m \u0026times; 0.25 mm, 0.25 \u0026micro;m film thickness), which was hyphenated to a Thermo ISQLT quadrupole mass spectrometer. The GC oven temperature program was set as follows: an initial isothermal hold at 50 ℃ for 2 min, followed by a linear ramp to 320 ℃ at a rate of 10 ℃ min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and a final hold at this temperature for 3 min. For mass spectrometry (MS), the operating parameters were configured as below: ion source temperature of 230 ℃, MS transfer line temperature of 280 ℃, quadrupole temperature of 150 ℃, and electron impact (EI) ionization mode with an electron energy of 70 eV at 200 ℃. MS was operated in full scan mode throughout the analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Material characterization\u003c/h2\u003e \u003cp\u003eUsing the chemical vapor deposition method, CNFs were grown in situ on the surface of flexible carbon fibers (CFs), and the as-prepared CNFs/CFs composite was further subjected to amino-functionalization to obtain NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs. Subsequently, this functionalized composite material was employed to treat PS via NPLNE. The SEM images in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-h comprehensively present the morphological characteristics of the samples at each stage of this process. Specifically, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea displays the overall morphology of pristine CFs, confirming their diameter of ~\u0026thinsp;7.4 \u0026micro;m. The high-magnification view in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb further reveals that the surface of CFs is not smooth but decorated with numerous continuous longitudinal grooves: these structures not only enhance the surface roughness of CFs but also serve as effective anchoring sites for metal catalysts, thereby providing favorable nucleation conditions for the subsequent in situ growth of CNFs. For the CNFs/CFs composite, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec demonstrates that CNFs coat the CFs matrix uniformly and densely, forming a complete encapsulating layer on the CFs surface. The high-resolution details in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed show that the as-grown CNFs exhibit a size distribution concentrated in the range of 10\u0026ndash;50 nm, presenting a curled and cross-linked tangled state. The interwoven structure between CNFs naturally forms abundant nanoscale spaces, which can act as reservoirs to accommodate nanoplastics. In contrast, the overall structural framework of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs after amino functionalization (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee-f) is similar to that of CNFs/CFs. However, there are subtle differences in details: the texture becomes more brittle and harder, the entanglement degree slightly decreases, and the structural rigidity has a slight increase compared to the original CNFs/CFs. Regarding the NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs sample that underwent NPLNE treatment without subsequent desorption (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg-h), the high magnification SEM images clearly show that polystyrene nanoplastics are tightly filled in the nanospace of the composite, rather than simply adsorbed on the surface of CNFs. This phenomenon is attributed to the mechanism of NPLNE: after the nanoconfined solvent extracts the nanoplastics, the solvent evaporates gradually during the post-treatment process, leaving the nanoplastics retained in the confined nanospace of the composite.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 NLPNE kinetics and isotherm\u003c/h2\u003e \u003cp\u003eTo clarify the adsorption mechanism of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs in the NPLNE of PS, a promising technology for mitigating PS contamination, systematic kinetic and isothermal adsorption analyses were performed. The fitting curves and corresponding model parameters are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, respectively.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea presents the kinetic fitting curve of the NPLNE process, clearly revealing a distinctive two-stage adsorption profile. In the initial rapid-uptake stage, occurring within the first\u0026thinsp;~\u0026thinsp;2 min, the adsorption capacity (q\u003csub\u003ee\u003c/sub\u003e) exhibits a steep increase, which is not merely a result of high surface area or functional group availability, but rather a direct manifestation of the nanoconfined liquid-phase extraction mechanism intrinsic to NPLNE [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. To quantify this kinetic behavior, the pseudo-first-order and pseudo-second-order models were employed for fitting. As summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the pseudo-first-order model yields a fitted equilibrium q\u003csub\u003ee\u003c/sub\u003e of 14.79 mg/g, a rate constant (k\u003csub\u003e1\u003c/sub\u003e) of 1.40 min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and a determination coefficient (R\u003csup\u003e2\u003c/sup\u003e) of 0.996; in contrast, the pseudo-second-order model gives a q\u003csub\u003ee\u003c/sub\u003e of 16.28 mg/g, a rate constant (k\u003csub\u003e2\u003c/sub\u003e) of 0.129 g\u0026middot;mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and an R\u003csup\u003e2\u003c/sup\u003e of 0.979. Notably, the q\u003csub\u003ee\u003c/sub\u003e of the pseudo-first-order model is more consistent with the equilibrium adsorption capacity reflected by experimental data (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), and its higher R\u003csup\u003e2\u003c/sup\u003e value indicates that the NPLNE process of PS by NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs is better described by the pseudo-first-order kinetic model [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This result aligns with the intrinsic nature of NPLNE: the rate-controlling step of the process is the diffusion of PS within the nanoconfined spaces, rather than the surface reaction process in traditional adsorption systems.\u003c/p\u003e \u003cp\u003eUnlike conventional bulk-phase adsorption systems where target analytes must traverse relatively large diffusion distances through stagnant or slow-moving liquid layers, NPLNE leverages the nanoconfined solvent environments formed within the interwoven networks of CNFs (cellulose nanofibers) on the NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs substrate. These nanoconfined regions, with characteristic dimensions on the order of tens to hundreds of nanometers, act as micro-reactors that fundamentally alter the mass transfer regime [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Within these nanospaces, the nanoconfined solvent molecules exhibit anomalous transport behaviors, including reduced viscosity, enhanced molecular mobility, and elevated local concentration gradients, due to the breakdown of bulk-phase hydrodynamic assumptions. This enables ultrafast short-range diffusion of PS molecules toward the amino-functionalized binding sites embedded on the CNFs surfaces [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The amino groups serve not only as chemoselective ligands that form hydrogen bonds and electrostatic interactions with the negatively charged head groups of PS, but also as spatial anchors that help maintain the structural integrity of the nanoconfined domains under wet conditions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. As the extraction proceeds, these nanoconfined solvent domains gradually become saturated with PS molecules, leading to a competitive occupancy effect, where incoming PS molecules must displace already-bound species or find increasingly scarce free binding sites. This transition marks the onset of the second, slower stage of the adsorption curve. Here, the rate-limiting step shifts from nanoconfined diffusion to surface site saturation and intermolecular repulsion, resulting in a pronounced decrease in the adsorption rate until thermodynamic equilibrium is established. Crucially, the NPLNE mechanism does not rely on external agitation, temperature gradients, or pressure-driven flow to enhance mass transfer. Instead, it exploits nanoscale solvation dynamics to achieve high-efficiency extraction at ambient conditions [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This makes NPLNE particularly advantageous for processing trace-level biomolecules in complex matrices, where preserving structural integrity and minimizing sample loss are paramount. The initial rapid uptake observed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea is a direct consequence of the nanoconfined liquid-phase extraction mechanism, where the synergy between geometric confinement, enhanced nanoscale diffusion, and chemoselective surface functionalization enables rapid, selective, and high-capacity extraction of PS, an effect unattainable in traditional bulk-phase systems [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The kinetic modeling further validates that this process is governed by diffusion within nanoconfined environments, rather than surface reaction kinetics, reinforcing the uniqueness of the NPLNE paradigm.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb presents the isothermal extraction isotherm of the NPLNE system. Because the PS capture event occurs inside a nanometre-thick liquid film rather than on a solid surface, the plateau value reflects the solubility limit of PS in the nanoconfined solvent phase, not the surface-site exhaustion typical of adsorption [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The Langmuir fit (q\u003csub\u003em\u003c/sub\u003e= 8.79 mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, K\u003csub\u003eL\u003c/sub\u003e= 0.85 L mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.992) vastly outperforms the Freundlich fit (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.920), corroborating the kinetic conclusion that the fibre scaffold presents a spatially uniform array of amino-functionalised nanospaces. Within these domains, PS molecules undergo rapid, diffusion-controlled uptake until the nanophase solvent is saturated, giving rise to the Langmuirian \u0026ldquo;monolayer\u0026rdquo; plateau [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Thus, the isotherm is quantitative proof that NPLNE operates via homogeneous, single-stage partitioning into a nanoconfined liquid layer, seamlessly extending the fast, diffusion-limited regime observed in the kinetic profile to the thermodynamic limit.\u003c/p\u003e \u003cp\u003eTaken together, the kinetic and thermodynamic signatures depict NPLNE as a single, homogeneous liquid-liquid partitioning event: PS is rapidly delivered by nanoscale diffusion into a thin, amino-lined solvent layer, where it remains until the nanophase is saturated. The result is an extraction that is complete within minutes, operates at ambient temperature without external energy, and yields a PS-rich nanoconfined phase ready for downstream analysis or disposal.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Condition optimization of NLPNE\u003c/h2\u003e \u003cp\u003eThe nanoconfined space environment and associated process parameters directly determine the efficiency of NLPNE. In this study, we focused on investigating the effects of key factors, including the preparation temperature of CNFs/CFs, dosage of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs, type of nanoconfined solvent, and dosage of nanoconfined solvent, and tracked their influence on PS removal (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-d).\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Effect of CNFs/CFs preparation temperature\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea depicts the variation in PS removal rate with the preparation temperature of CNFs/CFs. As the temperature increased from 500 ℃ to 750 ℃, the removal rate rose continuously, reaching a maximum of ~\u0026thinsp;80% at 750 ℃. This trend is attributed to the temperature-dependent growth of CNFs: higher calcination temperatures not only promotes the dense and uniform growth of CNFs on the surface of CFs, but also expands the nanoscale confined space between entangled CNFs, this structural feature creates more sufficient space conditions for the filling of nanoconfined solvents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Effect of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs dosage\u003c/h2\u003e \u003cp\u003eThe influence of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs dosage on the PS removal rate is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb. The removal rate increased gradually with increasing dosage, reaching\u0026thinsp;~\u0026thinsp;60% at 15 mg. This phenomenon is explained by the positive correlation between adsorbent dosage and active sites: a higher dosage of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs provides more nanoconfined spaces and amino-functionalized binding sites, thereby enhancing the probability of contact and interaction between the composite and PS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3 Effect of nanoconfined solvent type\u003c/h2\u003e \u003cp\u003eSelecting an appropriate nanoconfined solvent is a core optimization step for NLPNE efficiency. Here, we compared the PS removal rates of three polar nanoconfined solvents, methanol, ethanol and acetonitrile, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec. All three nanoconfined solvents can interact with the polar groups on the PS surface, but their removal efficiencies differ significantly: the removal rates of methanol and ethanol are ~\u0026thinsp;70%, while that of acetonitrile reaches\u0026thinsp;~\u0026thinsp;85%. This advantage of acetonitrile originates from its dual interaction mechanism with PS: the cyano group (-CN) in acetonitrile not only forms strong dipole-dipole interactions with the polar segments of PS but also engages in π-π stacking interactions with the aromatic ring structure of styrene, thus strengthening the nanoconfined solvent-PS binding force [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, acetonitrile was selected as the optimal nanoconfined solvent for subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.3.4 Effect of nanoconfined solvent dosage\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed illustrates the relationship between acetonitrile dosage and PS removal rate. The removal rate increased sharply when the dosage was raised from 0.25 mL to 0.5 mL, but decreased slightly with further dosage elevation to 0.75 mL. This trend can be rationalized by the nanoconfined space matching principle: insufficient nanoconfined solvent cannot fully fill the nanoconfined spaces of NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs, leading to incomplete contact with PS. Excessive nanoconfined solvent, however, overfills the confined spaces and dilutes the effective concentration of PS in the nanoscale region, thereby weakening the extraction efficiency. Thus, 0.5 mL was determined as the optimal nanoconfined solvent dosage.\u003c/p\u003e \u003cp\u003eCollectively, the data demonstrate that NLPNE is governed by the amount, uniformity and chemical identity of the nanoconfined liquid phase. Under the selected conditions (750\u0026deg;C growth temperature, 15 mg NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs, 0.5 mL acetonitrile), PS removal reaches\u0026thinsp;~\u0026thinsp;85%, a performance that scales directly with the quantity and quality of the nanoconfined extractor rather than with classical surface adsorption sites.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Determination of PS in water by Py/GC-MS\u003c/h2\u003e \u003cp\u003ePy-GC/MS was employed to perform on-line cleavage analysis of PS loaded on NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs, yielding the total ion current (TIC) profile and characteristic mass spectral patterns of PS pyrolysis products, as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Notably, no solvent peak was observed in the TIC profile (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), which can be attributed to the complete evaporation of trace acetonitrile, used as the nanoconfined solvent, during the sample injection process, leaving only the pyrolysis products of the extracted PS for analysis.\u003c/p\u003e \u003cp\u003eThe composition and content of PS pyrolysis products are highly dependent on pyrolysis temperature and duration: polystyrene undergoes pyrolysis in the 300\u0026ndash;600 ℃ range, generating typical products including styrene monomers, dimers, and trimers. Specifically, at 300\u0026ndash;350 ℃, the pyrolysis rate is relatively slow, and trimers dominate the product distribution; as the temperature rises to 350\u0026ndash;450 ℃, the pyrolysis rate accelerates sharply, elevating the proportion of monomers; within 450\u0026ndash;600 ℃, the pyrolysis proceeds at a high rate, further increasing the monomer fraction while the trimer proportion decreases significantly [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. For this study, the optimal pyrolysis parameters were determined by referencing relevant thermal decomposition data from prior works, which fall within the conventional operating range and are adapted to the target NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs-PS sample system [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs shown in the TIC profile and extracted ion chromatograms (EICs) in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, the PS pyrolysis products were sequentially separated with good resolution: the styrene monomer eluted at ~\u0026thinsp;5 min and the trimer at ~\u0026thinsp;23.16 min. These peaks exhibited high response intensities with no overlap, though slight tailing was observed, this phenomenon is likely ascribed to the retention of pyrolysis components by the chromatographic column's stationary phase during separation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb displays the MS of the pyrolysis products: the styrene monomer is characterized by prominent fragment ions, for example, m/z\u0026thinsp;=\u0026thinsp;51, 78, 104, with m/z\u0026thinsp;=\u0026thinsp;104 as the molecular ion peak, while the styrene trimer shows characteristic ions including m/z\u0026thinsp;=\u0026thinsp;91,117, 207, and m/z\u0026thinsp;=\u0026thinsp;312 (molecular ion peak) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. PS pyrolysis products were successfully identified via mass spectral database matching. Considering the high specificity and abundance of the styrene trimer (m/z\u0026thinsp;=\u0026thinsp;312), it was selected as the target indicator compound for PS after thermal cleavage; qualitative confirmation was performed based on its retention time and the abundance ratio of fragment ions, with m/z\u0026thinsp;=\u0026thinsp;117 and 207 serving as supplementary qualifying ions [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Meanwhile, based on the calculation standard of detection limit, the limit of detection (LOD) for PS by this method can reach 0.56 \u0026micro;g/L, demonstrating the excellent sensitivity of this method in the trace analysis of PS.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eThis study constructed a sensitive analytical platform for trace PS by coupling NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs-based NLPNE with Py-GC/MS. The NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs prepared at 750 ℃ features abundant nanoconfined spaces and surface amino groups, which synergistically enhance PS capture via accelerated mass transfer and specific interactions, dipole-dipole and \u0026pi;-\u0026pi; stacking. Optimized NLPNE parameters achieved a PS removal rate of ~\u0026thinsp;85% with minimal nanoconfined solvent usage. The Py-GC/MS system using styrene trimer as the indicator exhibited a low detection limit of 0.56 \u0026micro;g/L without nanoconfined solvent interference. This method integrates high extraction efficiency, strong selectivity, and environmental friendliness, providing a practical solution for PS monitoring in environmental samples. Future work will focus on complex matrix adaptation and material regeneration to expand its application scope.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This study was supported by grants from the National Natural Science Foundation of China (22166034).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJin-Chi Jiang: Writing-original draft, Data curation, Formal analysis;\u003c/p\u003e\n\u003cp\u003eZixuan Zhang: Methodology, Investigation, Writing-review and editing\u003c/p\u003e\n\u003cp\u003eLong-Yue Meng: Project administration, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e: Data sharing not applicable to this article as no datasets were generated or analysed during the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e: Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eR.C. 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Yu, (2025) Analysis of micro/nanoplastics on the surface of polystyrene foam lunch boxes by pyrolysis-gas chromatography/mass spectrometry Journal of Analytical and Applied Pyrolysis 190: 107161. https://doi.org/10.1016/j.jaap.2025.107161. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePseudo-first order and pseudo-second order parameters for NLPNE of PS by NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePseudo-first order\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePseudo-second order\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eq\u003c/em\u003e\u003csub\u003e\u003cem\u003ee\u003c/em\u003e\u003c/sub\u003e (mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ek\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e (min\u0026thinsp;\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eq\u003c/em\u003e\u003csub\u003e\u003cem\u003ee\u003c/em\u003e\u003c/sub\u003e (mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ek\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e (g\u0026middot;mg\u0026thinsp;\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;min)\u003csup\u003e\u0026minus;1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLangmuir and Freundlich parameters for NLPNE of PS by NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eLangmuir\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFreundlich\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eq\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e (mg/g)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003eL\u003c/em\u003e\u003c/sub\u003e (L/mg)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003eF\u003c/em\u003e\u003c/sub\u003e (m/mg)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"microchimica-acta","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"miac","sideBox":"Learn more about [Microchimica Acta](https://link.springer.com/journal/604)","snPcode":"604","submissionUrl":"https://submission.springernature.com/new-submission/604/3","title":"Microchimica Acta","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Polystyrene nanoplastics, Aminated carbon nanofibers, Nanoconfined liquid phase nanoextraction, Pyrolysis-gas chromatography-mass spectrometry","lastPublishedDoi":"10.21203/rs.3.rs-8650715/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8650715/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNanoplastics pose severe ecological and human health risks due to their high reactivity and bioaccumulation potential, but their efficient extraction and precise detection remain challenging. Herein, a novel integrated method combining nanoconfined liquid phase nanoextraction (NLPNE) based on aminated carbon nanofibers/ carbon fibers (NH\u003csub\u003e2\u003c/sub\u003e-CNFs/CFs) with pyrolysis-gas chromatography-mass spectrometry (Py/GC-MS) was developed for the sensitive determination of polystyrene (PS) nanoplastics in aqueous samples. NLPNE plays a pivotal role: the nanoconfined spaces formed by entangled CNFs accelerate PS mass transfer via short-range diffusion, while amino groups enhance specific electrostatic interactions with negatively charged PS, achieving rapid and selective pre-enrichment. Optimized with acetonitrile as the nanoconfined solvent, the method reaches extraction equilibrium quickly, following pseudo-first-order kinetics and Langmuir monolayer adsorption. Direct Py-GC/MS analysis using styrene trimer (m/z=312) as the marker yields a low detection limit of 0.56 μg/L. The method provided a novel technical solution for the detection of nanoplastics in complex matrices and facilitating future studies on their environmental behaviors.\u003c/p\u003e","manuscriptTitle":"Aminated Carbon Nanofiber-Mediated Nanoconfined Liquid Phase Nanoextraction Coupled with Py-GC/MS for Sensitive Determination of Polystyrene Nanoplastics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 16:11:06","doi":"10.21203/rs.3.rs-8650715/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-24T07:57:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T06:59:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-23T03:16:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214537761315873311325641627374862456561","date":"2026-02-23T02:42:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105740963173175658806032388461831801731","date":"2026-02-10T05:03:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-26T20:46:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-22T01:49:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-22T01:49:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Microchimica Acta","date":"2026-01-20T13:18:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"microchimica-acta","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"miac","sideBox":"Learn more about [Microchimica Acta](https://link.springer.com/journal/604)","snPcode":"604","submissionUrl":"https://submission.springernature.com/new-submission/604/3","title":"Microchimica Acta","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"da0bb50e-c176-4db7-9f84-86bd4bdcc4b8","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:02:48+00:00","versionOfRecord":{"articleIdentity":"rs-8650715","link":"https://doi.org/10.1007/s00604-026-08024-4","journal":{"identity":"microchimica-acta","isVorOnly":false,"title":"Microchimica Acta"},"publishedOn":"2026-04-09 15:57:57","publishedOnDateReadable":"April 9th, 2026"},"versionCreatedAt":"2026-01-29 16:11:06","video":"","vorDoi":"10.1007/s00604-026-08024-4","vorDoiUrl":"https://doi.org/10.1007/s00604-026-08024-4","workflowStages":[]},"version":"v1","identity":"rs-8650715","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8650715","identity":"rs-8650715","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}