Optimization of the Tribological Behavior of TiO₂ Nanolubricants: Experimental Design and RSM-Based Analysis

Optimization of the Tribological Behavior of TiO₂ Nanolubricants: Experimental Design and RSM-Based Analysis | 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 Optimization of the Tribological Behavior of TiO₂ Nanolubricants: Experimental Design and RSM-Based Analysis Mohammad Khazaliyan, Esmaeil Salahi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8690627/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 15 You are reading this latest preprint version Abstract This study optimizes the tribological performance of ductile cast iron lubricated with SAE 10W-40 engine oil infused with TiO2 nanoparticles. Nanoparticles were synthesized via the sol-gel technique and dispersed at 0.1-0.4 wt.% concentrations without surfactants. A pin-on-disk (ASTM G99) test rig was used to evaluate the influence of nanoparticle concentration, applied load (13.83-124.15 N), and sliding speed (0.05-0.26 m/s) on the coefficient of friction (COF) and disc weight loss. Response Surface Methodology (RSM) with a Central Composite Design (CCD) was employed for experimental design, and ANOVA was used to evaluate parameter significance4. The results indicated an optimal concentration of ~0.2 wt.% TiO2, achieving up to a 42% reduction in weight loss and a 36% decrease in COF relative to the base oil. Applied load exhibited the most significant effect on both responses. Nanoparticle characterization (FESEM, XRD, EDS) confirmed their nanostructure, crystallinity, and purity. Surface analysis of worn specimens indicated smoother wear tracks and tribofilm formation, demonstrating the efficacy of TiO2 nanolubricants for friction and wear reduction in ductile cast iron under boundary and mixed lubrication regimes. Physical sciences/Engineering Physical sciences/Materials science Physical sciences/Nanoscience and technology TiO₂ nanoparticles Nanolubricant Ductile cast iron Wear Reduction Response Surface Methodology (RSM) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 1. Introduction Friction and wear have been regarded as the primary contributors to energy loss and component failure in mechanical systems, accounting for nearly one-third of global energy consumption in industry [1]. Conventional lubricants serve a crucial function in reducing surface interactions; however, their effectiveness faces limitations under severe conditions like boundary and mixed lubrication regimes. To overcome these challenges, nanoparticle-based additives have attracted considerable interest for their capacity to form protective tribofilms, acting as nano/micro-rolling elements, and filling surface asperities, thereby improving the tribological performance of base oils [2,3]. Ductile cast iron is widely utilized in automotive engine components, including crankshafts, cylinder blocks, and piston rings, because of excellent tensile strength, toughness, fatigue resistance, and inherent wear resistance. These properties make it a key material in manufacturing modern internal combustion engines [4]. Nevertheless, prolonged operation under severe loads and boundary or mixed lubrication regimes still leads to progressive wear and increased friction [5]. Although ductile cast iron exhibits excellent mechanical strength and wear resistance, its tribological behavior depends strongly on load, sliding speed, and lubrication. In the absence of lubrication, adhesive and abrasive wear processes dominate, while boundary lubrication can reduce friction through graphite layer formation. Besides, composition, especially nickel content, and lubricant type further influence scuffing resistance. Understanding these factors is essential for predicting component lifespan and optimizing mechanical performance [6,7]. However, compared to steels and gray cast irons, systematic investigations of ductile cast iron in the presence of nanoparticle-enhanced engine oils remain scarce, despite its extensive industrial significance. Among various nanoparticles, titanium dioxide (TiO₂) has emerged as a promising additive offering chemical stability, cost-effectiveness, environmental compatibility, and multifunctional properties [8]. Recent reviews have underscored the ability of TiO₂ nanomaterials to significantly enhance tribological outcomes—such as friction and wear reduction—through various mechanisms like rolling, polishing, surface asperity filling, and tribofilm formation [9,10]. TiO 2 is recognized as an effective additive for improving not only tribological performance but also the mechanical and thermal stability of the interacting surfaces. Studies have demonstrated that the synergistic combination of anatase and rutile phases in TiO₂ improves lubrication. Nevertheless, excessive nanoparticle concentrations may cause agglomeration and higher wear rates, even if the coefficient of friction (COF) decreases [11,12]. Therefore, careful control over phase composition, surface chemistry, and nanoparticle concentration is essential for optimizing nanolubricant performance. Furthermore, the phase distribution and interfacial interactions between anatase and rutile phases significantly affect dispersion stability, lubrication performance, and multifunctional behavior, underscoring their importance for practical tribological applications [13]. Nonetheless, the effectiveness of TiO₂ nanolubricants is highly influenced by several factors, including nanoparticle concentration, applied load, and sliding speed, which collectively govern dispersion stability and lubrication mechanisms [14]. Recent studies have further highlighted that intrinsic nanoparticle properties, including hardness and concentration, significantly influence wear mechanisms. Response Surface Methodology (RSM) has been widely adopted as a robust statistical and optimization tool to model lubrication parameters and enhance the anti-wear performance of nanolubricants [15]. RSM enables efficient analysis and prediction of optimal conditions by establishing empirical relationships between operational variables and tribological responses. This approach has been successfully applied across various studies investigating different nanoparticle-based lubricants. For instance, researchers have optimized ligand-functionalized nanolubricants to improve long-term tribological stability through enhanced nanoparticle surface chemistry and colloidal dispersion [16]. In TiO₂ nanoparticle-based lubricants, RSM has been used to predict the influence of operational factors such as speed, load, and nanoparticle concentration on the coefficient of friction (COF) [17]. Similarly, research on TiO₂/MWCNT hybrid nanolubricants has demonstrated that nanoparticle concentration and temperature significantly affect rheological behavior, with RSM offering reliable optimization and prediction capabilities [18]. Beyond TiO₂-based systems, notable improvements in tribological performance have also been reported for copper oxide and graphene-based hybrid nanolubricants, further highlighting the versatility of nanoparticle additives and the robustness of RSM in tribological responses optimization [19,20]. Nevertheless, despite the industrial relevance of ductile cast iron, systematic investigations integrating TiO₂-based nanolubricants with RSM to evaluate its tribological characteristics remain scarce. The present study addresses this gap by investigating the tribological behavior of ductile cast iron lubricated with TiO₂ nanoparticle-enhanced SAE 10W-40 engine oil. TiO₂ nanoparticle synthesis was performed by the sol–gel technique, followed by characterizations through FESEM, XRD, and EDS. These nanoparticles were then incorporated into the base oil at varying concentrations (0.1–0.4 wt%) without surfactants. Pin-on-disk experiments were conducted under varying loads and sliding speeds, and the resulting responses (weight loss and COF) were modeled and optimized using RSM. Finally, worn surface morphologies were analyzed to elucidate the mechanisms of wear reduction. This integrated approach, combining experimental, statistical, and microstructural analyses, offers new insights into the optimal conditions and wear-reduction mechanisms through which TiO₂ nanolubricants enhance tribological performance, providing practical guidelines for their application across the automotive and industrial sectors. 2. Experimental Procedures 2.1. Materials and Specimen Preparation Titanium isopropoxide (TIP, 97% purity, Sigma-Aldrich) was used as the precursor for TiO₂ nanoparticle synthesis via the sol–gel method. Ethanol (99% purity, Merck) was used as the solvent, while nitric acid (96% purity, Merck) functioned as the acidic catalyst. SAE 10W-40 engine oil (SL grade, Pars Oil Company, Iran) acted as the base oil in the nanolubricant formulation. Table 1 presents the physicochemical characteristics of the base oil. Disc specimens were machined from ductile cast iron blocks (grade 3G40, DIN EN 1563) manufactured in Germany. The material grade was verified through chemical composition analysis and hardness testing. The blocks were then machined using wire-cut EDM into discs with a 50 mm diameter and 5 mm thickness, followed by surface grinding to achieve a dimensional tolerance of ±0.05 mm. Pin specimens comprised commercially available needle rollers (5 mm diameter, 50 mm length) typically used in rolling-element bearings. Each pin featured a hard chromium-coated surface with a Brinell hardness of 400–450 HB and an average surface roughness of 0.2–0.4 µm. The pin tips were hemispherical with a radius of 0.5 mm (Figure 1). 2.2. TiO₂ Nanoparticle Synthesis TiO₂ nanoparticles were prepared through the sol–gel technique at pH ≈ 3 using TIP, ethanol, deionized water, and nitric acid, following standard protocols reported in previous studies [9]. The molar ratio of reactants was maintained in a molar ratio of 1:3:1:0.3. First, HNO₃ was added to deionized water and thoroughly mixed at 30 °C for 10 min. Simultaneously, TIP was mixed with ethanol and stirred for 30 min, followed by the dropwise addition of the aqueous solution into the TIP–ethanol mixture while constantly stirring at 30 °C for 2 h. The obtained sol underwent 24-h aging in the dark at room temperature, after which it was dried at 100 °C for 1 hour and ground into a fine powder. The resulting powder underwent calcination at 450 °C for 2 hours in a muffle furnace with a 10 °C/min heating rate. 2.3. Nanolubricant Preparation The synthesized TiO₂ nanoparticles were dispersed into SAE 10W-40 engine oil at 0.1, 0.2, 0.3, and 0.4 wt.% without the use of surfactants. Accurate amounts of nanoparticles were calculated using a high-precision digital microbalance (±0.0001g), considering a fixed oil volume of 40 mL and a density of 0.856 g/cm³. The oil was preheated to 50 °C and stirred at 800 rpm for 20 minutes, followed by gradual nanoparticle addition to the oil and 2-hour stirring at 1200 rpm. The resulting mixture underwent sonication using a probe-type ultrasonic device (600 W, 40 kHz) for 15 minutes to achieve homogeneous dispersion (Figure 2). 2.4. Characterization Techniques The morphology of TiO₂ nanoparticles was characterized by FESEM, while EDX was employed to examine elemental composition. XRD was further utilized to determine crystalline phase and size using High Score Plus software. Surface wear tracks on the ductile cast iron discs were also examined by optical microscopy to assess wear mechanisms. 2.5. Tribological Testing (Pin-on-Disk Method) A standard pin-on-disk wear test was conducted according to ASTM G99-17 to evaluate tribological behavior [21]. Prior to testing, disc and pin specimens underwent ultrasonic cleaning in acetone for 10 minutes, followed by drying. Specimens were weighed under identical conditions using a high-precision balance. A pin-on-disk configuration was selected rather than a pin-on-plate to ensure more consistent wear volume measurements during the initial transient phase [22]. During testing, the disc was securely mounted to prevent displacement or vibration, while the pin was vertically applied via a lever arm with suspended loads. The sliding path was established by operating the apparatus without load to mark a circular wear track (38 mm diameter). Sliding speeds were controlled by adjusting the rotational frequency of the disk (10, 20, 30, 40, and 50 Hz), corresponding to linear sliding speeds of 0.05–0.26 m/s. The sliding distance was regulated at 1000 m, resulting in test durations between 333 and 64 minutes (the lowest and highest speeds, respectively). Normal loads of 13.83, 41.38, 68.94, 96.60, and 124.15 N were applied using suspended masses of 1–9 kg, considering lever arm ratios (fixed length: 64 cm, variable length: 45.5 cm). The contact area of the hemispherical pin tip was 19.63 mm². 2.6. Experimental Design Using RSM Tribological experiments were designed and analyzed using RSM [23]. A Central Composite Design (CCD) was utilized to explore the effects of three independent variables: TiO₂ nanoparticle concentration (wt.%), applied load (N), and sliding speed (m/s). Design-Expert software (version 12, Stat-Ease Inc., USA) was used to implement the experimental design and analyze the data. Table 2 summarizes the coded and actual levels of the independent variables, while Table 3 presents the corresponding response variables, including the coefficient of friction (COF) and weight loss (WL). 3. Results and discussion 3.1. TiO₂ Nanoparticle Morphology, Structure, and Phase Composition FESEM micrographs (Figure 3) revealed that TiO₂ nanoparticles prepared via the sol–gel technique would exhibit a nearly spherical morphology with smooth surfaces and limited agglomeration. The particles showed a relatively narrow size distribution, with a 20–25 nm average size. This geometry and uniform size distribution are highly advantageous for tribological applications, since spherical particles can function as “rolling elements,” partially transforming sliding motion into rolling and thereby reducing direct asperity–asperity contact and friction. These observations are consistent with previous studies reporting that spherical TiO₂ nanoparticles enhance lubrication by third-body rolling mechanisms and contribute to wear reduction when well-dispersed in base oils [24,25]. EDS analyses revealed that the nanoparticles consisted of 66.00 wt% Ti and 33.92 wt% O, closely consistent with the stoichiometric composition of TiO₂. The absence of impurity elements confirms the high purity of the prepared nanoparticles. This is particularly important, as impurity phases or contaminant elements have been reported to negatively affect the tribological behavior of nanolubricants by destabilizing the lubricating film or promoting abrasive wear [26]. Thus, the tribological improvements observed in this work can be attributed to TiO₂ itself rather than to secondary phases. XRD analyses (Figure 4) further highlighted the coexistence of anatase and rutile phases, with approximate fractions of 89% and 11%, respectively. The characteristic peaks at 2θ = 25.27° and 27.37° correspond to the (101) plane of anatase and the (110) plane of rutile. Crystallite sizes, estimated using the Scherrer equation, were ~19 nm for anatase and ~32 nm for rutile. The dual-phase composition offers complementary advantages for tribological behavior. Anatase, with its smaller crystallite size and higher surface reactivity, enhances adhesion to sliding surfaces and facilitates uniform tribofilm formation. On the other hand, rutile contributes higher density, hardness, and thermal stability under elevated contact stresses. Synergistic effects between anatase and rutile have been reported in tribological studies of TiO₂ P25 powders, where the mixed-phase structure improved both friction reduction and wear resistance [27]. This synergy between surface activity (anatase) and structural robustness (rutile) aligns with broader mechanisms reported for TiO₂ nanolubricants, such as rolling, film formation, and patching, which collectively enhance tribological performance. Beyond tribology, mixed-phase TiO₂ nanoparticles have also demonstrated superior functional properties in other fields, such as photocatalysis, due to enhanced charge separation at anatase/rutile interfaces. Although photocatalysis operates through different mechanisms from tribological behavior, analogous interfacial phenomena—such as efficient energy dissipation and improved film stability—may similarly facilitate friction and wear reduction in sliding contacts [11,13]. 3.2. Statistical Modeling of Tribological Responses The experimental observations from CCD-designed pin-on-disk tests (Table 4) were analyzed using ANOVA to evaluate the influence of TiO₂ concentration, applied load, and sliding speed on two responses: (i) weight loss and (ii) the average COF. 3.2.1. Weight loss The quadratic model demonstrated excellent adequacy and predictive reliability for weight loss, with close agreement between predicted and experimental values. ANOVA (Table 5) indicated that TiO₂ concentration (A), applied load (B), sliding speed (C), their interaction BC, and the quadratic terms A² and B² were statistically significant, while other terms were either marginally significant or non-significant. The initial full quadratic equation (1a) included all terms, whereas the reduced equation (1b) retained only those that were statistically (p < 0.05) or marginally (p-values 0.05-0.1) significant. Equation 1a: Full model Weight Loss = +0.454035- 6.40489 A + 0.127663 B +0.007989 C- 0.012500 AB + 0.0027500 AC - 0.003000 BC + 16.16848 A ² + 0.006671 B² - 0.000071 C² To enhance predictive accuracy, statistically non-significant terms were excluded, resulting in the reduced regression model presented in Equation (1b). Equation 1b: Reduced model Weight Loss = +0.454035- 6.40489 A + 0.127663 B +0.007989 C - 0.003000 BC + 16.16848 A ² + 0.006671 B² 3.2.2. Coefficient of friction (COF) Similarly, the quadratic model provided an excellent fit for COF, with strong model adequacy and reliable predictive performance (Table 6). ANOVA confirmed that applied load (B), sliding speed (C), and quadratic terms A² and C² were the most statistically significant contributors, while other terms demonstrated marginal or negligible effects. The full quadratic equation (2a) was initially generated, followed by a reduced equation (2b) that excluded non-significant terms. Equation 2a: Full model Average coefficient of friction = +0.311451- 0.881304 A - 0.004082 B -0.007395 C+ 0.023750 AB + 0.004250 AC + 0.000225 BC + 1.50326 A ² - 0.000304 B² + 0.000075 C² According to the ANOVA results, non-significant terms were removed, and the final regression model was presented in Equation (2b). Equation 2b: Reduced model Average coefficient of friction = +0.311451- 0.881304 A - 0.004082 B -0.007395 C+ 0.023750 AB + 0.004250 AC + 0.000225 BC + 1.50326 A ² + 0.000075 C² The diagnostic plots presented in Figure 5 validate the adequacy and robustness of the developed quadratic models for both response variables (weight loss and COF). The predicted versus actual plot (Figure 5a and b) highlights close alignment of the data points with the 45° reference line, demonstrating a substantial correlation between experimental and predicted values and confirming the high predictive reliability of the models. As supported by the normal probability plot of residuals (Figure 5c and d), the residuals closely align with a straight-line trend, suggesting that the assumption of normality is satisfied. Finally, the residuals versus predicted values plot (Figure 5e and f) reveals the random distribution of the residuals around zero, with no noticeable patterns or trends, confirming homogeneity of variance and the absence of model bias. Overall, these plots provide strong evidence of the statistical robustness of the models, supporting their suitability for describing and optimizing the tribological behavior of TiO₂-based nanolubricants. Contour and 3D surface plots further clarified the interaction effects among the factors. For the weight loss response (Figure 6a-f), increasing TiO₂ concentration reduced wear up to an optimum level of approximately 0.2 wt%, after which a considerable increase was observed. This trend can be associated with nanoparticle agglomeration at greater concentrations, where clustered particles acted as abrasive third bodies that disrupted the uniform tribofilm, and accelerated material removal. Applied load remained the dominant factor, consistent with conventional wear mechanisms, where higher normal forces promote material loss. For the COF response (Figure 7a-f), the plots illustrate that moderate TiO₂ concentrations (~0.2 wt%) combined with higher sliding speeds effectively minimized COF, whereas increasing load generally led to higher friction. These findings confirm that TiO₂ concentration and sliding speed are the primary factors influencing COF, while applied load exerts a more pronounced effect on wear. Overall, statistical analyses confirmed that applied load was the primary contributor to weight loss, whereas sliding speed and nanoparticle concentration were more decisive for COF. The incorporation of TiO₂ nanoparticles, particularly at ~0.2 wt%, substantially reduced both wear and friction. These observations align with several recently conducted studies that underscore the dominant influence of applied load on wear mechanisms and the beneficial effect of optimized nanoparticle concentrations on lubrication efficiency [28-31]. The successful application of RSM in this study further demonstrates its effectiveness in optimizing tribological systems while reducing the need for extensive experimental trials. 3.3. Multi-response Optimization of Tribological Behavior Multi-response optimization of tribological performance was performed using the RSM technique with a CCD in Design-Expert 12. In contrast to the single-response models discussed earlier, this stage focused on simultaneously minimizing both the weight loss of ductile cast iron discs and the average COF. Numerical optimization produced desirability ramp plots (Figure 8), which identified the optimal operating point at a TiO₂ nanoparticle concentration of 0.206 wt%, a 1-kg applied load, and a 36.4-Hz rotational speed. The overall desirability score approached unity, highlighting the robustness of the optimization process. Contour and 3D surface plots (Figure 9a-f) further illustrated factor interactions. As indicated, across the design space, the optimum consistently emerged under low applied load, moderate sliding speed, and TiO₂ concentrations close to 0.2 wt%. Under these conditions, both responses were minimized simultaneously. Mechanistically, moderate nanoparticle loadings facilitate third-body lubrication and promote the formation of a stable tribofilm, whereas excessive concentrations encourage agglomeration, where clustered particles behave as abrasive third bodies, disrupt film continuity, and diminish lubrication efficiency. Conversely, low nanoparticle concentrations fail to effectively form a uniform and stable protective film between the interacting frictional surfaces [32,33]. These findings highlight the advantage of balanced nanoparticle addition when both wear and friction must be controlled simultaneously. These optimization outcomes are consistent with prior reports indicating that moderate nanoparticle concentrations (~0.2–0.3 wt%) result in the best balance between dispersion stability and tribofilm formation [34,35,15]. The application of RSM for multi-response optimization has likewise proven robust in tribological research involving lubricants and coatings [15,17-20]. Notably, the identified optimum conditions not only validate the experimental findings but also offer practical guidance for the formulation of nanolubricants in automotive and industrial applications, where simultaneous reduction of wear and friction is essential for extending component lifetime and improving energy efficiency. 3.4. Morphological and EDS Analysis of Worn Disc Surfaces Worn surface analyses demonstrated the influence of TiO₂ nanoparticles in modifying wear and friction mechanisms. Under the base oil conditions, the wear track (Figure 10) exhibited deep grooves and significant material removal, while EDS confirmed only the base alloying elements (Fe, C, Si), indicating the absence of protective layers. In contrast, lubrication with 0.2 wt% TiO₂ produced noticeably smoother surfaces (Figure 11), with distinct Ti and O peaks in the EDS spectra confirming nanoparticle retention and tribofilm formation. At higher concentrations (0.4 wt%), FESEM observations (Figure 12) revealed partial improvements over the base oil condition, but also clear signs of nanoparticle agglomeration, which limited uniform film formation. Quantitative wear data demonstrated that, although the average COF faced a slight reduction (0.162 → 0.152), weight loss increased (1.0 → 1.3 mg), confirming that agglomerated particles functioned as abrasive third bodies. This dual effect highlights the balance between cavity filling/tribofilm stabilization and abrasion due to clustering. In addition, the EDS-Mapping analyses offered further insights into TiO₂ nanoparticle impacts on the worn disc surfaces. At a concentration of 0.2 wt% (Figure 13a), only a small number of nanoparticles was detected, distributed relatively uniformly across the surface. This limited detection can be partly attributed to the ultrasonic cleaning procedure applied prior to weighing. This process likely removed a substantial fraction of the nanoparticles constituting the protective tribofilm, thereby reducing their visibility in the mapping analysis. In contrast, despite a similar cleaning process, a more noticeable presence of Ti was observed for the 0.4 wt% TiO₂ sample (Figure 13b), which may be associated with the greater number of surface cavities caused by higher wear or initial surface roughness, facilitating localized nanoparticle entrapment. Such entrapment exhibits a dual effect: on one hand, the filling of cavities contributes to smoother contact surfaces; on the other hand, nanoparticle agglomeration at higher concentrations promotes the formation of larger abrasive clusters, thereby accelerating wear. Hence, the mapping results not only confirm the positive role of nanoparticles in pore filling and tribofilm formation but also underscore the detrimental influence of agglomeration at elevated concentrations [36]. The friction–distance responses and corresponding surface morphologies collectively substantiate the beneficial, yet concentration-dependent, role of TiO₂ nano-additives. Under fixed load and speed conditions (5 kg, 30 Hz), the concentration sweep (Figure 14a) reveals a clear transition from higher and noisier friction in the base oil to a lower and more stable friction trace at 0.2 wt% TiO₂. The 0.4 wt% curve remains below that of the base oil but exhibits occasional irregularities, consistent with intermittent third-body activity. The reduced mean friction level and narrowed fluctuation band at 0.2 wt% indicate a rapid running-in period followed by a quasi-steady regime, consistent with the formation and stabilization of a protective tribofilm and the partial “polishing/rolling” action of well-dispersed nanoparticles. In contrast, the residual spikes at 0.4 wt% suggest local film disruption events, in line with agglomerate-assisted micro-ploughing. These trends are mirrored in the optical micrographs (Figure 15a), revealing pronounced grooves for the base oil, smoother, more uniformly burnished tracks for the 0.2 wt% sample, and localized damage consistent with clustered debris and asperity-level abrasion for the 0.4 wt% sample. The load series (Figure 14b) highlights the dominant role of normal force. As shown, increasing the load from 1 to 9 kg elevates the mean COF and amplifies its temporal fluctuations, reflecting more frequent stick–slip and transient film breakdown under higher contact stress. Mechanistically, higher loads intensify asperity deformation and promote both third-body entrainment and expulsion, resulting in a dynamic competition between film repair and removal. The corresponding micrographs (Figure 15b) confirm this interpretation. Accordingly, shallow, finer tracks at 1 kg evolve into wider grooves and locally delaminated patches at 9 kg, indicating a transition from mixed polishing/mild abrasion toward more severe micro-cutting and micro-fracture. Speed effects (Figure 14c) exhibit a Stribeck-like response. At 10 Hz, insufficient lubricant entrainment and limited nanoparticle mobility maintain the contact in a predominantly boundary regime, defined by a higher COF and irregular transients. Increasing the speed to ~30 Hz stabilizes the trace and lowers COF, consistent with improved lubricant replenishment, enhanced third-body circulation, and a more continuous tribofilm. At 50 Hz, however, the friction curve demonstrates renewed fluctuations, plausibly due to shear-heating-induced softening of near-surface material and intermittent film scission under elevated tangential stresses. The surface evidence aligns with this interpretation (Figure 15c): the 30 Hz condition presents the smoothest morphology, while both lower and higher speeds exhibit features consistent with either under-supplied films (10 Hz) or thermally aggravated micro-ploughing (50 Hz). According to these observations, the optimal operating window emerges at ~0.2 wt% TiO₂, low–moderate load, and moderate speed (~30 Hz). Under these conditions, the friction trace rapidly converges to a low, stable plateau, and the wear track displays uniform burnishing with minimal groove depth—characteristics of a sustained tribofilm supported by well-dispersed nanoparticles acting as mobile, load-sharing third bodies. Departures from this window degrade performance through two principal routes: (i) excessive load, which accelerates asperity damage and destabilizes the film; and (ii) excessive nanoparticle concentration, which promotes agglomeration, producing larger, abrasive clusters that increase wear by intensifying micro-ploughing and debris-mediated abrasion, although sometimes reducing average COF through partial smoothing/valley filling. Thus, the combined friction–distance and imaging evidence provides converging, mechanism-level support for the RSM/ANOVA findings and the microstructural narratives of tribofilm formation, pore filling, and controlled third-body lubrication. Similar dual roles of nanoparticles in tribology have also been reported in recent studies [37, 38 , 39], where moderate nanoparticle concentrations enhance tribofilm formation and reduce friction and wear, whereas excessive concentrations or agglomeration led to abrasive effects. 4. Conclusions This study comprehensively evaluated the tribological performance of ductile cast iron lubricated with TiO₂-based nanolubricants by integrating nanoparticle characterization, pin-on-disk tribological testing, statistical modeling, and worn surface analyses. A summary of the main research findings is presented below: Nanoparticle morphology and structure: TiO₂ nanoparticles synthesized via the sol–gel method exhibited a nearly spherical morphology with a relatively narrow particle size distribution (20–25 nm) and high chemical purity. XRD analysis confirmed the coexistence of anatase (≈89%) and rutile (≈11%) phases with crystallite sizes of ~19 nm and ~32 nm, respectively. This dual-phase structure provided a synergistic effect through which anatase facilitated tribofilm formation due to its high surface reactivity, while rutile offered mechanical hardness and thermal stability. Tribological performance and statistical modeling: RSM analysis of pin-on-disk tests demonstrated that applied load was the dominant factor influencing weight loss, whereas sliding speed and nanoparticle concentration contributed more significantly to controlling the coefficient of friction (COF). Quadratic regression models exhibited excellent predictive reliability (R² > 0.97) with non-significant lack-of-fit, validating their robustness for both response variables. Multi-response optimization: Optimization results identified ~0.2 wt% TiO₂, a low applied load (≈1 kg), and moderate sliding speed (~36 Hz) as the optimal operating conditions, simultaneously minimizing both wear and COF. At higher nanoparticle concentrations (≥0.4 wt%), agglomeration effects led to increased wear despite a reduction in COF, underscoring the necessity of controlling dispersion stability to maintain performance. Microstructural mechanisms: FESEM, EDS, and mapping analyses confirmed two synergistic mechanisms contributing to wear reduction: (i) nanoparticle filling of surface cavities, which smoothed contact areas and mitigated ploughing, and (ii) tribofilm formation, which enhanced load-bearing capacity and reduced direct asperity contact. At higher concentrations, however, nanoparticle agglomerates acted as abrasive third bodies, accelerating wear even under reduced COF. Practical implications: Within the concentration range of 0.1–0.3 wt%, TiO₂ nanolubricants consistently improved wear resistance and frictional stability, with optimum performance at 0.2 wt%. The combined statistical and microstructural evidence demonstrates the potential of TiO₂ nanoparticles as effective additives for improving lubrication efficiency in ductile cast iron components, particularly in boundary and mixed lubrication regimes. These findings provide practical guidelines for the formulation of nanoparticle-enhanced lubricants in automotive and industrial applications. Declarations 5. Data Availability declaration The data supporting the findings of this study are available from the corresponding author upon reasonable request. 6. Declaration of interests 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. 7. Funding The authors did not receive support from any organization for the submitted work. References Holmberg, K., Erdemir, A., 2017. Influence of tribology on global energy consumption, costs and emissions. Friction 5, 263–284. https://doi.org/10.1007/s40544-017-0183-5 Zhao, J., Huang, Y., He, Y., & Shi, Y. (2020). Nanolubricant additives: A review. Friction, 9(5), 891–917. https://doi.org/10.1007/s40544-020-0450-8. Waqas, M., Zahid, R., Bhutta, M. U., Khan, Z. A., & Saeed, A. (2021). 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Lubricants, 12(4), 134. https://doi.org/10.3390/lubricants12040134. Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response surface methodology: Process and product optimization using designed experiments (4th ed.). Wiley. Wu, H., Zhao, J., Cheng, X., Xia, W., He, A., Yun, J.-H., Huang, S., Wang, L., Huang, H., Jiao, S., & Jiang, Z. (2018). Friction and wear characteristics of TiO 2 nano-additive water-based lubricant on ferritic stainless steel. Tribology International, 117, 24–38. https://doi.org/10.1016/j.triboint.2017.08.011. Jason, Y. J. J., How, H. G., Teoh, Y. H., & Chuah, H. G. (2020). A Study on the Tribological Performance of Nanolubricants. Processes, 8(11), 1372. https://doi.org/10.3390/pr8111372. Ali, M. K. A., Ezzat, F. M. H., El-Gawwad, K. A. A., & Salem, M. M. M. (2017). Effect of Lubricant Contaminants on Tribological Characteristics During Boundary Lubrication Reciprocating Sliding (Version 1). arXiv. https://doi.org/10.48550/ARXIV.1710.04448. Ingole, S., Charanpahari, A., Kakade, A., Umare, S. S., Bhatt, D. V., & Menghani, J. (2013). Tribological behavior of nano TiO2 as an additive in base oil. Wear, 301(1–2), 776–785. https://doi.org/10.1016/j.wear.2013.01.037. Patil, H. H., Pawar, G. B., Mali, P. V., Ballal, Y. P., & Gondkar, V. S. (2022). Enhancement of tribological properties by adding titanium dioxide (TiO2) nanoparticles in mineral-based SN-500 oil. Materials Today: Proceedings, 59, 128–133. https://doi.org/10.1016/j.matpr.2021.10.270. Noble, N., Akhil, U. V., Aravind Krishna, S., Radhika, N., & Ramu, M. (2023). Effect of Nano-Additives on Tribological Behaviour of Hazelnut Oil and Sunflower Oil. Tribology in Industry, 45(3), 457–471. https://doi.org/10.24874/ti.1464.03.23.05. Ahmed Ali, M. K., Xianjun, H., Turkson, R. F., Peng, Z., & Chen, X. (2016). Enhancing the thermophysical properties and tribological behaviour of engine oils using nano-lubricant additives. RSC Advances, 6(81), 77913–77924. https://doi.org/10.1039/c6ra10543b. BIRLEANU, C., PUSTAN, M., CIOAZA, M., MOLEA, A., POPA, F., & CONTIU, G. (2021). Experimental Analyses of the Additive Effect of TiO2 Nanoparticles on the Tribological Properties of Lubricating Oil. Research Square Platform LLC. https://doi.org/10.21203/rs.3.rs-1123984/v1. Jazaa, Y., Lan, T., Padalkar, S., & Sundararajan, S. (2018). The Effect of Agglomeration Reduction on the Tribological Behavior of WS2 and MoS2 Nanoparticle Additives in the Boundary Lubrication Regime. Lubricants, 6(4), 106. https://doi.org/10.3390/lubricants6040106. Jason, Y. J. J., How, H. G., Teoh, Y. H., & Chuah, H. G. (2020). A Study on the Tribological Performance of Nanolubricants. Processes, 8(11), 1372. https://doi.org/10.3390/pr8111372. Pourpasha, H., Zeinali Heris, S., & Asadi, A. (2019). Experimental investigation of nano-TiO2/turbine meter oil nanofluid. Journal of Thermal Analysis and Calorimetry, 138(1), 57–67. https://doi.org/10.1007/s10973-019-08155-2. Bogunovic, L., Zuenkeler, S., Toensing, K., & Anselmetti, D. (2015). An Oil-Based Lubrication System Based on Nanoparticular TiO2 with Superior Friction and Wear Properties. Tribology Letters, 59(2). https://doi.org/10.1007/s11249-015-0557-7. Demas, N. G., Erck, R. A., Lorenzo-Martin, C., Ajayi, O. O., & Fenske, G. R. (2017). Experimental Evaluation of Oxide Nanoparticles as Friction and Wear Improvement Additives in Motor Oil. Journal of Nanomaterials, 2017, 1–12. https://doi.org/10.1155/2017/8425782 . Ali, M. K. A., Xianjun, H., Mai, L., Qingping, C., Turkson, R. F., & Bicheng, C. (2016). Improving the tribological characteristics of piston ring assembly in automotive engines using Al2O3 and TiO2 nanomaterials as nano-lubricant additives. Tribology International, 103, 540–554. https://doi.org/10.1016/j.triboint.2016.08.011. Uniyal, P., Gaur, P., Yadav, J., Khan, T., & Ahmed, O. S. (2024). A Review on the Effect of Metal Oxide Nanoparticles on Tribological Properties of Biolubricants. ACS Omega. https://doi.org/10.1021/acsomega.3c08279 . Choudhury , N. D., Bhaumik, S., Saha, N., & Kataki, R. (2024). Investigating the tribological properties of TiO2 nanoparticles added Thevetia peruviana and Cucurbita pepo L. blend oils. Tribology International, 197, 109769. https://doi.org/10.1016/j.triboint.2024.109769. Tables Tables 1 to 6 are available in the supplementary files section Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 06 Apr, 2026 Reviews received at journal 04 Apr, 2026 Reviewers agreed at journal 04 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Editor invited by journal 01 Apr, 2026 Reviews received at journal 20 Feb, 2026 Reviews received at journal 20 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers agreed at journal 10 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers invited by journal 09 Feb, 2026 Editor assigned by journal 04 Feb, 2026 Submission checks completed at journal 27 Jan, 2026 First submitted to journal 27 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. 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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-8690627","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":589824025,"identity":"b7459a41-8c1a-4395-9a4f-2b164aac3f9f","order_by":0,"name":"Mohammad Khazaliyan","email":"","orcid":"","institution":"Materials and Energy Research Center","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Khazaliyan","suffix":""},{"id":589824026,"identity":"d529778c-6e8b-462a-8259-e241b1931913","order_by":1,"name":"Esmaeil Salahi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYLCCBwwHePjhPGZitCQAtUg2kKqFweAAsW7iZ2B/+CGh5o6M8bXDxz78YLCTZ2DnfYBXi2QDj7FEwrFnPGa305Jn9jAkGzYwsxvg1WJw/w2DRALbYaCWHGOgL5gTGJjZ8DvM/gD74x8J/w7zGM/O/wzUUk9YC9ANZhKJbYd5DKRzmIFaDhPWInGAx8wise8wj8TtNGPGHoPjhm2EtPA3sD++8eHbYXv+2cmPGX5UVMvz8x/DrwXTnQTsGAWjYBSMglFADAAA8vQ5TKNVmuwAAAAASUVORK5CYII=","orcid":"","institution":"Materials and Energy Research Center","correspondingAuthor":true,"prefix":"","firstName":"Esmaeil","middleName":"","lastName":"Salahi","suffix":""}],"badges":[],"createdAt":"2026-01-25 06:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8690627/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8690627/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102532945,"identity":"8722fcff-d1ce-470b-b3b0-82221f46e541","added_by":"auto","created_at":"2026-02-12 16:47:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":535117,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental setup and materials: (a) Pin-on-disk wear test apparatus; (b) Close-up of the pin-on-disk contact configuration; (c) Ductile cast iron disc specimens; (d) Needle roller pin specimens.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/f7067b71921b2ac23790a330.png"},{"id":102532900,"identity":"0004c5d2-0e27-4e85-b34d-d3f88176b1aa","added_by":"auto","created_at":"2026-02-12 16:47:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":220845,"visible":true,"origin":"","legend":"\u003cp\u003ePreparation process of TiO₂-based nanolubricants at various concentrations\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/0f45106f5f2d01f41dfa9f7e.png"},{"id":102746400,"identity":"bf10f69b-7e1a-407f-82f7-8989b6617a06","added_by":"auto","created_at":"2026-02-16 08:57:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":234479,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterization of synthesized TiO\u003csub\u003e2\u003c/sub\u003e nanoparticles: (a) FESEM micrograph at 100kX magnification showing particle distribution; (b) High-magnification (200kX) FESEM image illustrating quasi-spherical morphology and average particle size; (c) Low-magnification (2.00kX) FESEM image showing nanoparticle agglomerates; (d) EDS spectrum and corresponding elemental analysis confirming the high purity of the TiO\u003csub\u003e2\u003c/sub\u003e powder.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/fd63a89221a19b6255c57f87.png"},{"id":102532927,"identity":"13955430-8a6d-4ee3-bb46-61734b1284d7","added_by":"auto","created_at":"2026-02-12 16:47:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":40083,"visible":true,"origin":"","legend":"\u003cp\u003eXRD analysis of TiO₂ nanoparticles exhibiting anatase and rutile phases.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/6aeeed956cdef9c69d29fa9b.png"},{"id":102746771,"identity":"d0898ee3-1449-40bb-bb24-dddec933c608","added_by":"auto","created_at":"2026-02-16 09:01:12","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":149058,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic plots validating the quadratic RSM models. Plots (a), (c), and (e) correspond to the Weight Loss model; plots (b), (d), and (f) correspond to the Average Friction Coefficient model. (a, b) Predicted vs. Actual values, confirming high correlation and model reliability. (c, d) Normal probability plots of residuals, demonstrating that the error terms are normally distributed. (e, f) Residuals vs. Predicted values, showing a random scatter that confirms homogeneity of variance.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/218ee77d5715f3b8fbf16228.png"},{"id":102746360,"identity":"3194100d-bc88-43ba-bcd7-bf7dfbe37d68","added_by":"auto","created_at":"2026-02-16 08:57:01","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":420035,"visible":true,"origin":"","legend":"\u003cp\u003eContour plots (left column) and 3D surface plots (right column) illustrating the interaction effects of the independent variables on Weight Loss (mg). (a, b) Interaction effect of TiO\u003csub\u003e2\u003c/sub\u003e Concentration and Applied Load (at fixed Sliding Speed). (c, d) Interaction effect of TiO\u003csub\u003e2\u003c/sub\u003e Concentration and Sliding Speed (at fixed Applied Load). (e, f) Interaction effect of Sliding Speed and Applied Load (at fixed TiO\u003csub\u003e2\u003c/sub\u003e Concentration).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/ba002cb741365fa3b06a4769.png"},{"id":102746783,"identity":"d721c941-0ffb-4330-af7d-bfe8815a0531","added_by":"auto","created_at":"2026-02-16 09:01:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":367774,"visible":true,"origin":"","legend":"\u003cp\u003eContour plots (left column) and 3D surface plots (right column) illustrating the interaction effects of the independent variables on the average Coefficient of Friction (COF). (a, b) Interaction effect of TiO\u003csub\u003e2\u003c/sub\u003e Concentration and Applied Load (at fixed Sliding Speed). (c, d) Interaction effect of TiO\u003csub\u003e2\u003c/sub\u003e Concentration and Sliding Speed (at fixed Applied Load). (e, f) Interaction effect of Sliding Speed and Applied Load (at fixed TiO\u003csub\u003e2\u003c/sub\u003e Concentration).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/da8588b98d1d3bd7cb088dfd.png"},{"id":102532904,"identity":"93fb9c85-d6b3-495f-8f36-0000d22fe16c","added_by":"auto","created_at":"2026-02-12 16:47:08","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":31878,"visible":true,"origin":"","legend":"\u003cp\u003eDesirability ramp plots from the multi-response optimization of weight loss and COF using RSM.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/4d181af0538bf0b685d2c07c.png"},{"id":102532944,"identity":"08a2ad16-e1da-4596-8874-715d1a6593fd","added_by":"auto","created_at":"2026-02-12 16:47:09","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":354829,"visible":true,"origin":"","legend":"\u003cp\u003e3D surface plots (left column) and corresponding contour plots (right column) for the multi-response Desirability, showing the combined effects of factor interactions on optimizing both weight loss and COF. (a, b) Interaction effect of TiO\u003csub\u003e2\u003c/sub\u003e Concentration and Applied Load (at fixed Sliding Speed). (c, d) Interaction effect of TiO\u003csub\u003e2\u003c/sub\u003e Concentration and Sliding Speed (at fixed Applied Load). (e, f) Interaction effect of Sliding Speed and Applied Load (at fixed TiO\u003csub\u003e2\u003c/sub\u003e Concentration).\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/d3889d568a04f3e74ec3e7db.png"},{"id":102532903,"identity":"fdefe253-7644-4d58-a409-66875b2cb902","added_by":"auto","created_at":"2026-02-12 16:47:08","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":262375,"visible":true,"origin":"","legend":"\u003cp\u003eSurface analysis of the worn ductile cast iron disc lubricated with the base oil (0 wt.% TiO\u003csub\u003e2\u003c/sub\u003e) under a 5 kg applied load and 30 Hz rotational speed: (a) FESEM micrographs at low and high magnification, revealing a severe wear track dominated by deep abrasive grooves and material removal; (b) EDS spectrum and corresponding elemental analysis, confirming the absence of a protective tribofilm as only the base alloy elements (Fe, Si, C) are detected.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/7617bb1f523bd0829795bdc9.png"},{"id":102532910,"identity":"ea24e446-0296-4584-8655-79cb500aa589","added_by":"auto","created_at":"2026-02-12 16:47:08","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":288561,"visible":true,"origin":"","legend":"\u003cp\u003eSurface analysis of the worn ductile cast iron disc lubricated with the optimal 0.2 wt% TiO\u003csub\u003e2\u003c/sub\u003e nanolubricant under a 5 kg applied load and 30 Hz rotational speed: (a) FESEM micrographs at low and high magnification, revealing a significantly smoother wear track with fewer and shallower abrasive grooves compared to the base oil (Fig. 10); (b) EDS spectrum and elemental analysis, where the detection of Ti and O peaks confirms the incorporation of TiO\u003csub\u003e2\u003c/sub\u003e nanoparticles into the surface, providing evidence of tribofilm formation.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/bec53fe1111c59ee76cec0c0.png"},{"id":102532908,"identity":"088a8cb0-a094-4537-b680-415e23de000b","added_by":"auto","created_at":"2026-02-12 16:47:08","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":353319,"visible":true,"origin":"","legend":"\u003cp\u003eSurface analysis of the worn ductile cast iron disc lubricated with the high-concentration 0.4 wt% TiO\u003csub\u003e2\u003c/sub\u003e nanolubricant under a 5 kg applied load and 30 Hz rotational speed: (a) FESEM micrographs at progressively higher magnifications, clearly illustrating the formation of nanoparticle agglomerates (clusters) on the wear track; (b) EDS spectrum and elemental analysis confirming a strong presence of Ti and O in these agglomerated regions. As discussed in the text, these clusters are linked to an increase in abrasive wear.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/45ebefb8394f4efa191c3782.png"},{"id":102532907,"identity":"8ecd72b5-cd3b-49be-ac74-11bda30e041b","added_by":"auto","created_at":"2026-02-12 16:47:08","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eEDS elemental mapping analysis of the worn ductile cast iron disc surface (tested under 5 kg load and 30 Hz speed), comparing nanolubricant concentrations: (a) Lubricated with 0.2 wt% TiO\u003csub\u003e2\u003c/sub\u003e, showing a sparse, relatively uniform distribution of Titanium (Ti). (b) Lubricated with 0.4 wt% TiO\u003csub\u003e2\u003c/sub\u003e, showing a much more noticeable and localized co-presence of Titanium (Ti) and Oxygen (O), which corresponds to the nanoparticle agglomeration sites seen in Figure 12\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/3a1ebc422e232b7fa67911ad.png"},{"id":102532916,"identity":"a126e659-1937-431c-9e5f-0501ce64eac1","added_by":"auto","created_at":"2026-02-12 16:47:08","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eFriction–distance curves of ductile cast iron disc under different operating conditions: (a) effect of TiO₂ concentration at a 5 kg applied load and 30 Hz rotational speed (0.0, 0.2, and 0.4 wt%), (b) effect of applied load at 0.2 wt% TiO₂ and 30 Hz (1, 5, and 9 kg), and (c) effect of rotational speed at 0.2 wt% TiO₂ and 5 kg load (10, 30, and 50 Hz)\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/266c797404a31c10be6c8369.png"},{"id":102746390,"identity":"90b6e91d-8f81-4e02-af25-bca213064e5e","added_by":"auto","created_at":"2026-02-16 08:57:18","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eOptical micrographs of the worn surface of the ductile cast iron disc under different operating conditions. Effect of TiO\u003csub\u003e2\u003c/sub\u003e Concentration (at 5 kg load, 30 Hz): (a) 0.0 wt% (Base Oil), (b) 0.2 wt% and (c) 0.4 wt%. Effect of Applied Load (at 0.2 wt% TiO\u003csub\u003e2\u003c/sub\u003e, 30 Hz): (d) 1 kg, (e) 5 kg and (f) 9 kg. Effect of Rotational Speed (at 0.2 wt% TiO\u003csub\u003e2\u003c/sub\u003e, 5 kg load): (g) 10 Hz, (h) 30 Hz and (i) 50 Hz.\u003c/p\u003e","description":"","filename":"15.png","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/02d4107fccabfa3a7c625608.png"},{"id":102750708,"identity":"93467413-f705-417e-a6f2-298603216eb5","added_by":"auto","created_at":"2026-02-16 09:21:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4243578,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/c38f8214-f6b1-4e6e-9d84-b5a241af17c5.pdf"},{"id":102746518,"identity":"3444dd25-10aa-4ea7-82b5-e7c264cec7b0","added_by":"auto","created_at":"2026-02-16 08:58:01","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":25638,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8690627/v1/ee79576b07d3701add3ae2d7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimization of the Tribological Behavior of TiO₂ Nanolubricants: Experimental Design and RSM-Based Analysis","fulltext":[{"header":" 1. Introduction","content":"\u003cp\u003eFriction and wear have been regarded as the primary contributors to energy loss and component failure in mechanical systems, accounting for nearly one-third of global energy consumption in industry [1]. Conventional lubricants serve a crucial function in reducing surface interactions; however, their effectiveness faces limitations under severe conditions like boundary and mixed lubrication regimes. To overcome these challenges, nanoparticle-based additives have attracted considerable interest for their capacity to form protective tribofilms, acting as nano/micro-rolling elements, and\u0026nbsp;filling surface asperities, thereby improving the tribological performance of base oils [2,3]. Ductile cast iron is widely utilized in automotive engine components, including crankshafts, cylinder blocks, and piston rings, because of excellent tensile strength, toughness, fatigue resistance, and inherent wear resistance. These properties make it a key material in manufacturing modern internal combustion engines [4]. Nevertheless, prolonged operation under severe loads and boundary or mixed lubrication regimes still leads to progressive wear and increased friction [5]. Although ductile cast iron exhibits excellent mechanical strength and wear resistance, its tribological behavior depends strongly on load, sliding speed, and lubrication. In the absence of lubrication, adhesive and abrasive wear processes dominate, while boundary lubrication can reduce friction through graphite layer formation. Besides, composition, especially nickel content, and lubricant type further influence scuffing resistance. Understanding these factors is essential for predicting component lifespan and optimizing mechanical performance [6,7]. However, compared to steels and gray cast irons, systematic investigations of ductile cast iron in the presence of nanoparticle-enhanced engine oils remain scarce, despite its extensive industrial significance. Among various nanoparticles, titanium dioxide (TiO₂) has emerged as a promising additive offering chemical stability, cost-effectiveness, environmental compatibility, and multifunctional properties [8]. Recent reviews have underscored the ability of TiO₂ nanomaterials to significantly enhance tribological outcomes\u0026mdash;such as friction and wear reduction\u0026mdash;through various mechanisms like rolling, polishing, surface asperity filling, and tribofilm formation [9,10]. TiO\u003csub\u003e2\u003c/sub\u003e is recognized as an effective additive for improving not only tribological performance but also the mechanical and thermal stability of the interacting surfaces. Studies have demonstrated that the synergistic combination of anatase and rutile phases in TiO₂ improves lubrication. Nevertheless, excessive nanoparticle concentrations may cause agglomeration and higher wear rates, even if the coefficient of friction (COF) decreases [11,12]. Therefore, careful control over phase composition, surface chemistry, and nanoparticle concentration is essential for optimizing nanolubricant performance. Furthermore, the phase distribution and interfacial interactions between anatase and rutile phases significantly affect dispersion stability, lubrication performance, and multifunctional behavior, underscoring their importance for practical tribological applications [13].\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eNonetheless, the effectiveness of TiO₂ nanolubricants is highly influenced by several factors, including nanoparticle concentration, applied load, and sliding speed, which collectively govern dispersion stability and lubrication mechanisms [14].\u003cspan dir=\"RTL\"\u003e\u0026nbsp;Recent studies have further highlighted that intrinsic nanoparticle properties, including hardness and concentration, significantly influence wear mechanisms. Response Surface Methodology (RSM) has been widely adopted as a robust statistical and optimization tool to model lubrication parameters and enhance the anti-wear performance of nanolubricants\u0026nbsp;\u003c/span\u003e[15]. RSM enables efficient analysis and prediction of optimal conditions by establishing empirical relationships between operational variables and tribological responses. This approach has been successfully applied across various studies investigating different nanoparticle-based lubricants. For instance, researchers have optimized ligand-functionalized nanolubricants to improve long-term tribological stability through enhanced nanoparticle surface chemistry and colloidal dispersion [16]. In TiO₂ nanoparticle-based lubricants, RSM has been used to predict the influence of operational factors such as speed, load, and nanoparticle concentration on the coefficient of friction (COF) [17]. Similarly, research on TiO₂/MWCNT hybrid nanolubricants has demonstrated that nanoparticle concentration and temperature significantly affect rheological behavior, with RSM offering reliable optimization and prediction capabilities [18]. Beyond TiO₂-based systems, notable improvements in tribological performance have also been reported for copper oxide and graphene-based hybrid nanolubricants, further highlighting the versatility of nanoparticle additives and the robustness of RSM in tribological responses optimization [19,20].\u003c/p\u003e\n\u003cp\u003eNevertheless,\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003edespite the industrial relevance of ductile cast iron, systematic investigations integrating TiO₂-based nanolubricants with RSM to evaluate its tribological characteristics remain scarce. The present study addresses this gap by investigating the tribological behavior of ductile cast iron lubricated with TiO₂ nanoparticle-enhanced SAE 10W-40 engine oil. TiO₂ nanoparticle synthesis was performed by the sol\u0026ndash;gel technique, followed by characterizations through FESEM, XRD, and EDS. These nanoparticles were then incorporated into the base oil at varying concentrations (0.1\u0026ndash;0.4 wt%) without surfactants. Pin-on-disk experiments were conducted under varying loads and sliding speeds, and the resulting responses (weight loss and COF) were modeled and optimized using RSM. Finally, worn surface morphologies were analyzed to elucidate the mechanisms of wear reduction. This integrated approach, combining experimental, statistical, and microstructural analyses, offers new insights into the optimal conditions and wear-reduction mechanisms through which TiO₂ nanolubricants enhance tribological performance, providing practical guidelines for their application across the automotive and industrial sectors.\u003c/p\u003e"},{"header":"2. Experimental Procedures","content":"\u003cp\u003e\u003cstrong\u003e2.1. Materials and Specimen Preparation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTitanium isopropoxide (TIP, 97% purity, Sigma-Aldrich) was used as the precursor for TiO₂ nanoparticle synthesis via the sol\u0026ndash;gel method. Ethanol (99% purity, Merck) was used as the solvent, while nitric acid (96% purity, Merck) functioned as the acidic catalyst. SAE 10W-40 engine oil (SL grade, Pars Oil Company, Iran) acted as the base oil in the nanolubricant formulation. Table 1 presents the physicochemical characteristics of the base oil.\u003c/p\u003e\n\u003cp\u003eDisc specimens were machined from ductile cast iron blocks (grade 3G40, DIN EN 1563) manufactured in Germany. The material grade was verified through chemical composition analysis and hardness testing. The blocks were then machined using wire-cut EDM into discs with a 50 mm diameter and 5 mm thickness, followed by surface grinding to achieve a dimensional tolerance of \u0026plusmn;0.05 mm. Pin specimens comprised commercially available needle rollers (5 mm diameter, 50 mm length) typically used in rolling-element bearings. Each pin featured a hard chromium-coated surface with a Brinell hardness of 400\u0026ndash;450 HB and an average surface roughness of 0.2\u0026ndash;0.4 \u0026micro;m. The pin tips were hemispherical with a radius of 0.5 mm (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. TiO₂ Nanoparticle Synthesis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTiO₂ nanoparticles were prepared through the sol\u0026ndash;gel technique at pH \u0026asymp; 3 using TIP, ethanol, deionized water, and nitric acid, following standard protocols reported in previous studies\u0026nbsp;[9].\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe molar ratio of reactants was maintained in a molar ratio of 1:3:1:0.3. First, HNO₃ was added to deionized water and thoroughly mixed at 30 \u0026deg;C for 10 min. Simultaneously, TIP was mixed with ethanol and stirred for 30 min, followed by the dropwise addition of the aqueous solution into the TIP\u0026ndash;ethanol mixture while constantly stirring at 30 \u0026deg;C for 2 h. The obtained sol underwent 24-h aging in the dark at room temperature, after which it was dried at 100 \u0026deg;C for 1 hour and ground into a fine powder. The resulting powder underwent calcination at 450 \u0026deg;C for 2 hours in a muffle furnace with a 10 \u0026deg;C/min heating rate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Nanolubricant Preparation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe synthesized TiO₂ nanoparticles were dispersed into SAE 10W-40 engine oil at 0.1, 0.2, 0.3, and 0.4 wt.% without the use of surfactants. Accurate amounts of nanoparticles were calculated using a high-precision digital microbalance (\u0026plusmn;0.0001g), considering a fixed oil volume of 40 mL and a density of 0.856 g/cm\u0026sup3;. The oil was preheated to 50 \u0026deg;C and stirred at 800 rpm for 20 minutes, followed by gradual nanoparticle addition to the oil and 2-hour stirring at 1200 rpm. The resulting mixture underwent sonication using a probe-type ultrasonic device (600 W, 40 kHz) for 15 minutes to achieve homogeneous dispersion (Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Characterization Techniques\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe morphology of TiO₂ nanoparticles was characterized by FESEM, while EDX was employed to examine elemental composition. XRD was further utilized to determine crystalline phase and size using High Score Plus software. Surface wear tracks on the ductile cast iron discs were also examined by optical microscopy to assess wear mechanisms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5. Tribological Testing (Pin-on-Disk Method)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA standard pin-on-disk wear test was conducted according to ASTM G99-17 to evaluate tribological behavior\u0026nbsp;[21]. Prior to testing, disc and pin specimens underwent ultrasonic cleaning in acetone for 10 minutes, followed by drying. Specimens were weighed under identical conditions using a high-precision balance. A pin-on-disk configuration was selected rather than a pin-on-plate to ensure more consistent wear volume measurements during the initial transient phase\u0026nbsp;[22]. During testing, the disc was securely mounted to prevent displacement or vibration, while the pin was vertically applied via a lever arm with suspended loads. The sliding path was established by operating the apparatus without load to mark a circular wear track (38 mm diameter). Sliding speeds were controlled by adjusting the rotational frequency of the disk (10, 20, 30, 40, and 50 Hz), corresponding to linear sliding speeds of 0.05\u0026ndash;0.26 m/s. The sliding distance was regulated at 1000 m, resulting in test durations between 333 and 64 minutes (the lowest and highest speeds, respectively). Normal loads of 13.83, 41.38, 68.94, 96.60, and 124.15 N were applied using suspended masses of 1\u0026ndash;9 kg, considering lever arm ratios (fixed length: 64 cm, variable length: 45.5 cm). The contact area of the hemispherical pin tip was 19.63 mm\u0026sup2;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6. Experimental Design Using RSM\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTribological experiments were designed and analyzed using RSM [23]. A Central Composite Design (CCD) was utilized to explore the effects of three independent variables: TiO₂ nanoparticle concentration (wt.%), applied load (N), and sliding speed (m/s). Design-Expert software (version 12, Stat-Ease Inc., USA) was used to implement the experimental design and analyze the data. Table 2 summarizes the coded and actual levels of the independent variables, while Table 3 presents the corresponding response variables, including the coefficient of friction (COF) and weight loss (WL).\u003c/p\u003e"},{"header":"3. Results and discussion","content":"\u003cp\u003e\u003cstrong\u003e3.1. TiO₂ Nanoparticle Morphology, Structure, and Phase Composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFESEM micrographs (Figure 3) revealed that TiO₂ nanoparticles prepared via the sol\u0026ndash;gel technique would exhibit a nearly spherical morphology with smooth surfaces and limited agglomeration. The particles showed a relatively narrow size distribution, with a 20\u0026ndash;25 nm average size. This geometry and uniform size distribution are highly advantageous for tribological applications, since spherical particles can function as \u0026ldquo;rolling elements,\u0026rdquo; partially transforming sliding motion into rolling and thereby reducing direct asperity\u0026ndash;asperity contact and friction. These observations are consistent with previous studies reporting that spherical TiO₂ nanoparticles enhance lubrication by third-body rolling mechanisms and contribute to wear reduction when well-dispersed in base oils\u0026nbsp;[24,25].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEDS analyses revealed that the nanoparticles consisted of 66.00 wt% Ti and 33.92 wt% O, closely consistent with the stoichiometric composition of TiO₂. The absence of impurity elements confirms the high purity of the prepared nanoparticles. This is particularly important, as impurity phases or contaminant elements have been reported to negatively affect the tribological behavior of nanolubricants by destabilizing the lubricating film or promoting abrasive wear\u0026nbsp;[26]. Thus, the tribological improvements observed in this work can be attributed to TiO₂ itself rather than to secondary phases. XRD analyses (Figure 4) further highlighted the coexistence of anatase and rutile phases, with approximate fractions of 89% and 11%, respectively. The characteristic peaks at 2\u0026theta; = 25.27\u0026deg; and 27.37\u0026deg; correspond to the (101) plane of anatase and the (110) plane of rutile. Crystallite sizes, estimated using the Scherrer equation, were ~19 nm for anatase and ~32 nm for rutile.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The dual-phase composition offers complementary advantages for tribological behavior. Anatase, with its smaller crystallite size and higher surface reactivity, enhances adhesion to sliding surfaces and facilitates uniform tribofilm formation. On the other hand, rutile contributes higher density, hardness, and thermal stability under elevated contact stresses. Synergistic effects between anatase and rutile have been reported in tribological studies of TiO₂ P25 powders, where the mixed-phase structure improved both friction reduction and wear resistance [27]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis synergy between surface activity (anatase) and structural robustness (rutile) aligns with broader mechanisms reported for TiO₂ nanolubricants, such as rolling, film formation, and patching, which collectively enhance tribological performance. Beyond tribology, mixed-phase TiO₂ nanoparticles have also demonstrated superior functional properties in other fields, such as photocatalysis, due to enhanced charge separation at anatase/rutile interfaces. Although photocatalysis operates through different mechanisms from tribological behavior, analogous interfacial phenomena\u0026mdash;such as efficient energy dissipation and improved film stability\u0026mdash;may similarly facilitate friction and wear reduction in sliding contacts\u0026nbsp;[11,13].\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Statistical Modeling of Tribological Responses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental observations from CCD-designed pin-on-disk tests (Table 4) were analyzed using ANOVA to evaluate the influence of TiO₂ concentration, applied load, and sliding speed on two responses: (i) weight loss and (ii) the average COF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.1. Weight loss\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe quadratic model demonstrated excellent adequacy and predictive reliability for weight loss, with close agreement between predicted and experimental values. ANOVA (Table 5) indicated that TiO₂ concentration (A), applied load (B), sliding speed (C), their interaction BC, and the quadratic terms A\u0026sup2; and B\u0026sup2; were statistically significant, while other terms were either marginally significant or non-significant. The initial full quadratic\u0026nbsp;equation (1a)\u0026nbsp;included all terms, whereas the reduced\u0026nbsp;equation (1b)\u0026nbsp;retained only those that were statistically (p \u0026lt; 0.05) or marginally (p-values 0.05-0.1) significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 1a:\u003c/strong\u003e Full model\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWeight Loss\u003c/strong\u003e = +0.454035-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e6.40489 A\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e+ 0.127663 B +0.007989\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eC-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.012500 AB +\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.0027500 AC\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.003000 BC\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e16.16848 A\u003csup\u003e\u0026sup2;\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/sup\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.006671 B\u0026sup2; -\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.000071 C\u0026sup2;\u003c/p\u003e\n\u003cp\u003eTo enhance predictive accuracy, statistically non-significant terms were excluded, resulting in the reduced regression model presented in\u0026nbsp;Equation (1b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 1b:\u003c/strong\u003e Reduced model\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWeight Loss\u003c/strong\u003e = +0.454035-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e6.40489 A\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e+ 0.127663 B +0.007989\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eC -\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.003000 BC\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e16.16848 A\u003csup\u003e\u0026sup2;\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/sup\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.006671 B\u0026sup2;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.2. Coefficient of friction (COF)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSimilarly, the quadratic model provided an excellent fit for COF, with strong model adequacy and reliable predictive performance (Table 6). ANOVA confirmed that applied load (B), sliding speed (C), and quadratic terms A\u0026sup2; and C\u0026sup2; were the most statistically significant contributors, while other terms demonstrated marginal or negligible effects. The full quadratic\u0026nbsp;equation (2a)\u0026nbsp;was initially generated, followed by a reduced\u0026nbsp;equation (2b)\u0026nbsp;that excluded non-significant terms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 2a:\u003c/strong\u003e Full model\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAverage\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecoefficient of friction\u003c/strong\u003e =\u0026nbsp;+0.311451-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.881304 A\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.004082 B -0.007395\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eC+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.023750 AB +\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.004250 AC\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.000225 BC\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e1.50326 A\u003csup\u003e\u0026sup2;\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/sup\u003e-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.000304 B\u0026sup2; +\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.000075 C\u0026sup2;\u003c/p\u003e\n\u003cp\u003eAccording to the ANOVA results, non-significant terms were removed, and the final regression model was presented in\u0026nbsp;Equation (2b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 2b:\u003c/strong\u003e Reduced model\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAverage\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecoefficient of friction\u003c/strong\u003e =\u0026nbsp;+0.311451-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.881304 A\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e-\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.004082 B -0.007395\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eC+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.023750 AB +\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.004250 AC\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.000225 BC\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e1.50326 A\u003csup\u003e\u0026sup2;\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/sup\u003e+\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e0.000075 C\u0026sup2;\u003c/p\u003e\n\u003cp\u003eThe diagnostic plots presented in Figure 5 validate the adequacy and robustness of the developed quadratic models for both response variables (weight loss and COF).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe predicted versus actual plot (Figure 5a and b) highlights close alignment of the data points with the 45\u0026deg; reference line, demonstrating a substantial correlation between experimental and predicted values and confirming the high predictive reliability of the models. As supported by the normal probability plot of residuals (Figure 5c\u0026nbsp;and\u0026nbsp;d), the residuals closely align with a straight-line trend, suggesting that the assumption of normality is satisfied. Finally, the residuals versus predicted values plot (Figure 5e\u0026nbsp;and\u0026nbsp;f) reveals the random distribution of the residuals around zero, with no noticeable patterns or trends, confirming homogeneity of variance and the absence of model bias. Overall, these plots provide strong evidence of the statistical robustness of the models, supporting their suitability for describing and optimizing the tribological behavior of TiO₂-based nanolubricants.\u003c/p\u003e\n\u003cp\u003eContour and 3D surface plots further clarified the interaction effects among the factors. For the weight loss response (Figure 6a-f), increasing TiO₂ concentration reduced wear up to an optimum level of approximately 0.2 wt%, after which a considerable increase was observed. This trend can be associated with nanoparticle agglomeration at greater concentrations, where clustered particles acted as abrasive third bodies that disrupted the uniform tribofilm, and accelerated material removal. Applied load remained the dominant factor, consistent with conventional wear mechanisms, where higher normal forces promote material loss.\u003c/p\u003e\n\u003cp\u003eFor the COF response (Figure 7a-f), the plots illustrate that moderate TiO₂ concentrations (~0.2 wt%) combined with higher sliding speeds effectively minimized COF, whereas increasing load generally led to higher friction. These findings confirm that TiO₂ concentration and sliding speed are the primary factors influencing COF, while applied load exerts a more pronounced effect on wear. Overall, statistical analyses confirmed that applied load was the primary contributor to weight loss, whereas sliding speed and nanoparticle concentration were more decisive for COF. The incorporation of TiO₂ nanoparticles, particularly at ~0.2 wt%, substantially reduced both wear and friction. These observations align with several recently conducted studies that underscore the dominant influence of applied load on wear mechanisms and the beneficial effect of optimized nanoparticle concentrations on lubrication efficiency [28-31]. The successful application of RSM in this study further demonstrates its effectiveness in optimizing tribological systems while reducing the need for extensive experimental trials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Multi-response Optimization of Tribological Behavior\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMulti-response optimization of tribological performance was performed using the RSM technique with a CCD in Design-Expert 12. In contrast to the single-response models discussed earlier, this stage focused on simultaneously minimizing both the weight loss of ductile cast iron discs and the average COF. Numerical optimization produced desirability ramp plots (Figure 8), which identified the optimal operating point at a TiO₂ nanoparticle concentration of 0.206 wt%, a 1-kg applied load, and a 36.4-Hz rotational speed. The overall desirability score approached unity, highlighting the robustness of the optimization process. Contour and 3D surface plots (Figure 9a-f) further illustrated factor interactions. As indicated, across the design space, the optimum consistently emerged under low applied load, moderate sliding speed, and TiO₂ concentrations close to 0.2 wt%. Under these conditions, both responses were minimized simultaneously. Mechanistically, moderate nanoparticle loadings facilitate third-body lubrication and promote the formation of a stable tribofilm, whereas excessive concentrations encourage agglomeration, where clustered particles behave as abrasive third bodies, disrupt film continuity, and diminish lubrication efficiency. Conversely, low nanoparticle concentrations fail to effectively form a uniform and stable protective film between the interacting frictional surfaces [32,33].\u003c/p\u003e\n\u003cp\u003eThese findings highlight the advantage of balanced nanoparticle addition when both wear and friction must be controlled simultaneously. These optimization outcomes are consistent with prior reports indicating that moderate nanoparticle concentrations (~0.2\u0026ndash;0.3 wt%) result in the best balance between dispersion stability and tribofilm formation\u0026nbsp;[34,35,15]. The application of RSM for multi-response optimization has likewise proven robust in tribological research involving lubricants and coatings\u0026nbsp;[15,17-20]. Notably, the identified optimum conditions not only validate the experimental findings but also offer practical guidance for the formulation of nanolubricants in automotive and industrial applications, where simultaneous reduction of wear and friction is essential for extending component lifetime and improving energy efficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Morphological and EDS Analysis of Worn Disc Surfaces\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWorn surface analyses demonstrated the influence of TiO₂ nanoparticles in modifying wear and friction mechanisms. Under the base oil conditions, the wear track (Figure 10) exhibited deep grooves and significant material removal, while EDS confirmed only the base alloying elements (Fe, C, Si), indicating the absence of protective layers. In contrast, lubrication with 0.2 wt% TiO₂ produced noticeably smoother surfaces (Figure 11), with distinct Ti and O peaks in the EDS spectra confirming nanoparticle retention and tribofilm formation.\u003c/p\u003e\n\u003cp\u003eAt higher concentrations (0.4 wt%), FESEM observations (Figure 12) revealed partial improvements over the base oil condition, but also clear signs of nanoparticle agglomeration, which limited uniform film formation. Quantitative wear data demonstrated that, although the average COF faced a slight reduction (0.162 \u0026rarr; 0.152), weight loss increased (1.0 \u0026rarr; 1.3 mg), confirming that agglomerated particles functioned as abrasive third bodies. This dual effect highlights the balance between cavity filling/tribofilm stabilization and abrasion due to clustering.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, the EDS-Mapping analyses offered further insights into TiO₂ nanoparticle impacts on the worn disc surfaces. At a concentration of 0.2 wt% (Figure 13a), only a small number of nanoparticles was detected, distributed relatively uniformly across the surface. This limited detection can be partly attributed to the ultrasonic cleaning procedure applied prior to weighing. This process likely removed a substantial fraction of the nanoparticles constituting the protective tribofilm, thereby reducing their visibility in the mapping analysis. In contrast, despite a similar cleaning process, a more noticeable presence of Ti was observed for the 0.4 wt% TiO₂ sample (Figure 13b), which may be associated with the greater number of surface cavities caused by higher wear or initial surface roughness, facilitating localized nanoparticle entrapment. Such entrapment exhibits a dual effect: on one hand, the filling of cavities contributes to smoother contact surfaces; on the other hand, nanoparticle agglomeration at higher concentrations promotes the formation of larger abrasive clusters, thereby accelerating wear. Hence, the mapping results not only confirm the positive role of nanoparticles in pore filling and tribofilm formation but also underscore the detrimental influence of agglomeration at elevated concentrations [36].\u003c/p\u003e\n\u003cp\u003eThe friction\u0026ndash;distance responses and corresponding surface morphologies collectively substantiate the beneficial, yet concentration-dependent, role of TiO₂ nano-additives. Under fixed load and speed conditions (5 kg, 30 Hz), the concentration sweep (Figure 14a) reveals a clear transition from higher and noisier friction in the base oil to a lower and more stable friction trace at 0.2 wt% TiO₂. The 0.4 wt% curve remains below that of the base oil but exhibits occasional irregularities, consistent with intermittent third-body activity. The reduced mean friction level and narrowed fluctuation band at 0.2 wt% indicate a rapid running-in period followed by a quasi-steady regime, consistent with the formation and stabilization of a protective tribofilm and the partial \u0026ldquo;polishing/rolling\u0026rdquo; action of well-dispersed nanoparticles. In contrast, the residual spikes at 0.4 wt% suggest local film disruption events, in line with agglomerate-assisted micro-ploughing. These trends are mirrored in the optical micrographs (Figure 15a), revealing pronounced grooves for the base oil, smoother, more uniformly burnished tracks for the 0.2 wt% sample, and localized damage consistent with clustered debris and asperity-level abrasion for the 0.4 wt% sample.\u003c/p\u003e\n\u003cp\u003eThe load series (Figure 14b) highlights the dominant role of normal force. As shown, increasing the load from 1 to 9 kg elevates the mean COF and amplifies its temporal fluctuations, reflecting more frequent stick\u0026ndash;slip and transient film breakdown under higher contact stress. Mechanistically, higher loads intensify asperity deformation and promote both third-body entrainment and expulsion, resulting in a dynamic competition between film repair and removal. The corresponding micrographs (Figure 15b) confirm this interpretation. Accordingly, shallow, finer tracks at 1 kg evolve into wider grooves and locally delaminated patches at 9 kg, indicating a transition from mixed polishing/mild abrasion toward more severe micro-cutting and micro-fracture. Speed effects (Figure 14c) exhibit a Stribeck-like response. At 10 Hz, insufficient lubricant entrainment and limited nanoparticle mobility maintain the contact in a predominantly boundary regime, defined by a higher COF and irregular transients. Increasing the speed to ~30 Hz stabilizes the trace and lowers COF, consistent with improved lubricant replenishment, enhanced third-body circulation, and a more continuous tribofilm. At 50 Hz, however, the friction curve demonstrates renewed fluctuations, plausibly due to shear-heating-induced softening of near-surface material and intermittent film scission under elevated tangential stresses. The surface evidence aligns with this interpretation (Figure 15c): the 30 Hz condition presents the smoothest morphology, while both lower and higher speeds exhibit features consistent with either under-supplied films (10 Hz) or thermally aggravated micro-ploughing (50 Hz). According to these observations, the optimal operating window emerges at ~0.2 wt% TiO₂, low\u0026ndash;moderate load, and moderate speed (~30 Hz).\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan dir=\"RTL\"\u003eUnder these conditions, the friction trace rapidly converges to a low, stable plateau, and the wear track displays uniform burnishing with minimal groove depth\u0026mdash;characteristics of a sustained tribofilm supported by well-dispersed nanoparticles acting as mobile, load-sharing third bodies. Departures from this window degrade performance through two principal routes: (i) excessive load, which accelerates asperity damage and destabilizes the film; and (ii) excessive nanoparticle concentration, which promotes agglomeration, producing larger, abrasive clusters that increase wear by intensifying micro-ploughing and debris-mediated abrasion, although sometimes reducing average COF through partial smoothing/valley filling. Thus, the combined friction\u0026ndash;distance and imaging evidence provides converging, mechanism-level support for the RSM/ANOVA findings and the microstructural narratives of tribofilm formation, pore filling, and controlled third-body lubrication.\u0026nbsp;Similar dual roles of nanoparticles in tribology have also been reported in recent studies\u0026nbsp;[37, 38\u003cspan dir=\"RTL\"\u003e,\u003c/span\u003e 39], where moderate nanoparticle concentrations enhance tribofilm formation and reduce friction and wear, whereas excessive concentrations or agglomeration led to abrasive effects.\u003c/span\u003e\u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eThis study comprehensively evaluated the tribological performance of ductile cast iron lubricated with TiO₂-based nanolubricants by integrating nanoparticle characterization, pin-on-disk tribological testing, statistical modeling, and worn surface analyses. A summary of the main research findings is presented below:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eNanoparticle morphology and structure: TiO₂ nanoparticles synthesized via the sol\u0026ndash;gel method exhibited a nearly spherical morphology with a relatively narrow particle size distribution (20\u0026ndash;25 nm) and high chemical purity. XRD analysis confirmed the coexistence of anatase (\u0026asymp;89%) and rutile (\u0026asymp;11%) phases with crystallite sizes of ~19 nm and ~32 nm, respectively. This dual-phase structure provided a synergistic effect through which anatase facilitated tribofilm formation due to its high surface reactivity, while rutile offered mechanical hardness and thermal stability.\u003c/li\u003e\n \u003cli\u003eTribological performance and statistical modeling: RSM analysis of pin-on-disk tests demonstrated that applied load was the dominant factor influencing weight loss, whereas sliding speed and nanoparticle concentration contributed more significantly to controlling the coefficient of friction (COF). Quadratic regression models exhibited excellent predictive reliability (R\u0026sup2; \u0026gt; 0.97) with non-significant lack-of-fit, validating their robustness for both response variables.\u003c/li\u003e\n \u003cli\u003eMulti-response optimization: Optimization results identified ~0.2 wt% TiO₂, a low applied load (\u0026asymp;1 kg), and moderate sliding speed (~36 Hz) as the optimal operating conditions, simultaneously minimizing both wear and COF. At higher nanoparticle concentrations (\u0026ge;0.4 wt%), agglomeration effects led to increased wear despite a reduction in COF, underscoring the necessity of controlling dispersion stability to maintain performance.\u003c/li\u003e\n \u003cli\u003eMicrostructural mechanisms: FESEM, EDS, and mapping analyses confirmed two synergistic mechanisms contributing to wear reduction: (i) nanoparticle filling of surface cavities, which smoothed contact areas and mitigated ploughing, and (ii) tribofilm formation, which enhanced load-bearing capacity and reduced direct asperity contact. At higher concentrations, however, nanoparticle agglomerates acted as abrasive third bodies, accelerating wear even under reduced COF.\u003c/li\u003e\n \u003cli\u003ePractical implications: Within the concentration range of 0.1\u0026ndash;0.3 wt%, TiO₂ nanolubricants consistently improved wear resistance and frictional stability, with optimum performance at 0.2 wt%. The combined statistical and microstructural evidence demonstrates the potential of TiO₂ nanoparticles as effective additives for improving lubrication efficiency in ductile cast iron components, particularly in boundary and mixed lubrication regimes. These findings provide practical guidelines for the formulation of nanoparticle-enhanced lubricants in automotive and industrial applications.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e5.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eData Availability declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDeclaration of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 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\u003e7. Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors did not receive support from any organization for the submitted work.\u003c/p\u003e"},{"header":" References","content":"\u003col\u003e\n\u003cli\u003e\u003cstrong\u003eHolmberg,\u003c/strong\u003e K., Erdemir, A., 2017. Influence of tribology on global energy consumption, costs and emissions. \u003cem\u003eFriction\u003c/em\u003e 5, 263\u0026ndash;284. https://doi.org/10.1007/s40544-017-0183-5\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eZhao, J., \u003c/strong\u003eHuang, Y., He, Y., \u0026amp; Shi, Y. (2020). Nanolubricant additives: A review. Friction, 9(5), 891\u0026ndash;917. https://doi.org/10.1007/s40544-020-0450-8.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eWaqas, M.,\u003c/strong\u003e Zahid, R., Bhutta, M. U., Khan, Z. A., \u0026amp; Saeed, A. (2021). A Review of Friction Performance of Lubricants with Nano Additives. 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Tribology International, 197, 109769. https://doi.org/10.1016/j.triboint.2024.109769.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 6 are available in the supplementary files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"TiO₂ nanoparticles, Nanolubricant, Ductile cast iron, Wear Reduction, Response Surface Methodology (RSM)","lastPublishedDoi":"10.21203/rs.3.rs-8690627/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8690627/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study optimizes the tribological performance of ductile cast iron lubricated with SAE 10W-40 engine oil infused with TiO2 nanoparticles. Nanoparticles were synthesized via the sol-gel technique and dispersed at 0.1-0.4 wt.% concentrations without surfactants. A pin-on-disk (ASTM G99) test rig was used to evaluate the influence of nanoparticle concentration, applied load (13.83-124.15 N), and sliding speed (0.05-0.26 m/s) on the coefficient of friction (COF) and disc weight loss. Response Surface Methodology (RSM) with a Central Composite Design (CCD) was employed for experimental design, and ANOVA was used to evaluate parameter significance4. The results indicated an optimal concentration of ~0.2 wt.% TiO2, achieving up to a 42% reduction in weight loss and a 36% decrease in COF relative to the base oil. Applied load exhibited the most significant effect on both responses. Nanoparticle characterization (FESEM, XRD, EDS) confirmed their nanostructure, crystallinity, and purity. Surface analysis of worn specimens indicated smoother wear tracks and tribofilm formation, demonstrating the efficacy of TiO2 nanolubricants for friction and wear reduction in ductile cast iron under boundary and mixed lubrication regimes.","manuscriptTitle":"Optimization of the Tribological Behavior of TiO₂ Nanolubricants: Experimental Design and RSM-Based Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 16:47:02","doi":"10.21203/rs.3.rs-8690627/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-06T08:16:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-04T06:22:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"236568701054712698432526843198452029641","date":"2026-04-04T06:05:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T08:33:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196255469450008231297502125445757107802","date":"2026-04-02T15:26:39+00:00","index":"hide","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-02T01:33:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-20T14:39:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-20T10:15:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308829062145522143137524020965336506672","date":"2026-02-11T18:44:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173563433218334073840378852882801783673","date":"2026-02-10T07:33:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279372767508767107003912796986145494188","date":"2026-02-09T18:09:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-09T17:54:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-04T06:13:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-27T17:01:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-01-27T16:56:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cd0fcae2-adc7-4f4c-a4c9-7a6304cd850a","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":62764101,"name":"Physical sciences/Engineering"},{"id":62764102,"name":"Physical sciences/Materials science"},{"id":62764103,"name":"Physical sciences/Nanoscience and technology"}],"tags":[],"updatedAt":"2026-04-06T08:26:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 16:47:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8690627","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8690627","identity":"rs-8690627","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}