Weak interfacial adhesion between carbon fibers and epoxy matrices remains a critical limitation for achieving high-performance carbon fiber reinforced polymer composites. In this work, a bioinspired hierarchical interphase was constructed on carbon fibers via tannic acid-Fe3+ assisted by graphene (GR) and graphene oxide (GO). Owing to π-π interactions, the MPN-GR and MPN-GO hybrid coatings were well distributed onto the fiber surface, introducing abundant oxygen-containing functional groups and a multiscale roughened architecture without compromising the intrinsic tensile strength of the fibers. Compared with pristine composites, the interfacial and mechanical properties were markedly improved, particularly for the CF-MPN/GO system, which exhibited a maximum increase of 95.7% in interlaminar shear strength and 117.6% in flexural strength. Fracture morphology analysis revealed a transition from interfacial debonding to matrix-dominated failure, indicating significantly improved load transfer and interfacial toughness. The superior performance of the MPN/GO interphase is attributed to the synergistic effects of metal-ligand coordination, π-π stacking, hydrogen bonding, and enhanced mechanical interlocking. This study provides a facile and environmentally friendly strategy for constructing well-defined hybrid interphases in carbon fiber reinforced polymer composites.

In this work, we present a metamaterial perfect absorber (MPA) for the far-infrared band that leverages the phase transition in vanadium dioxide (VO2) to achieve a dynamically switchable response, alternating between broadband and narrowband absorption. The structure, from bottom to top, consists of a Ti substrate, a Si dielectric layer, a two-dimensional graphene (GE) layer, and a patterned VO2 layer. When VO2 is in the metallic state, the structure exhibits broadband absorption, covering 16.7 to 28.7 THz with an average absorption rate of 96.1%. We analyze its physical mechanism through the distribution of electromagnetic fields. When VO2 is in the insulating phase, the proposed MPA exhibits nine distinct absorption peaks, each exceeding 90% absorption, and demonstrates excellent sensing characteristics, with the highest sensitivity reaching 3.978 THz/RIU. Our design offers the advantages of numerous narrowband absorption peaks, high sensitivity, and wide bandwidth. Additionally, this MPA can be tuned to achieve functional switching over a small range of conductivity changes. Therefore, our design has important applications in sensing, optical switching, energy harvesting, and remote sensing.

Molecular dynamics (MD) simulations were employed to unravel the atomistic mechanisms responsible for the selective permeation of cobalt (Co2+) and mercury (Hg2+) ions through chemically functionalized nanoporous graphene (GRA) membranes. The computational framework consisted of nanoporous GRA membranes functionalized with electronegative fluorine (-F) and chlorine (-Cl) moieties and immersed in mixed aqueous nitrate environments. An external electric field applied along the membrane normal induced directed ionic migration across the pores. Detailed structural and dynamical analyses reveal that ion transport is dictated by a delicate balance among hydration free energy, ion-pore electrostatic interactions, and interfacial polarization effects. The F-functionalized nanoporous GRA membranes have been shown to promote enhanced ion transport when subjected to an external electric field. Notably, Co2+ ions exhibit preferential permeation through F-functionalized pores, whereas Hg2+ ions demonstrate higher permeation efficiency in Cl-functionalized pores. These findings provide a fundamental molecular-level understanding of how functional group chemistry and applied electric fields modulate ion selectivity and transport energetics in GRA-based membranes with tailored pore diameters, offering predictive insights for the rational design of next-generation nanofiltration and electroseparation systems.

The rapid detection of organophosphorus (OP) compounds is crucial for safeguarding human health and ensuring food safety. This study presents a novel wearable electrochemical biosensor that integrates miniaturized screen-printed electrodes with wearable devices to achieve real-time, on-site OP detection. The biosensor was fabricated by constructing a screen-printed carbon electrode (SPCE) on a thermoplastic polyurethane (TPU) substrate, sequentially modified with graphene (GR), gold nanoparticles (AuNPs), and organophosphorus hydrolase (OPH), and finally encapsulated with Nafion. This SPCE/GR/AuNPs/OPH/Nafion configuration yields a highly flexible and portable device. The detection principle relies on the enzymatic hydrolysis of methyl paraoxon (MPOX) by OPH, generating p-nitrophenol (PNP), which is quantitatively measured via square wave voltammetry (SWV). The sensor exhibits a broad linear detection range (30-400 μM) with a strong linear correlation (R2 = 0.995) and a low detection limit (0.321 μM). It demonstrates excellent selectivity against common interfering substances, including urea, sucrose, and various metal ions. Application to real-world samples such as cabbage and tap water yielded high recoveries (107.2% for cabbage and 101.2% for tap water), with relative standard deviations (RSDs) below 8%. Furthermore, the biosensor maintains robust flexibility and mechanical resilience, with less than 5% signal loss after 100 bending cycles, confirming its suitability for wearable applications and reliable operation under mechanical stress. This innovative, flexible electrochemical biosensor provides a powerful and reliable platform for rapid OP detection, particularly in complex testing environments.

Density functional theory was utilized to investigate the adsorption strength, electronic characteristics, and solvent effects between Nitrosourea (NU) and pristine Graphene (GP) and Boron Nitride (BN) nanosheets and their two heterostructures, such as BN/GP (heterostructure-1, H1) and GP/BN (heterostructure-2, H2), in both air and water media. Our results showed that NU was physically adsorbed on pristine GP and BN surfaces, with adsorption energies ranging from −0.59 to −0.34 eV and minimal charge transfer of about 0.006–0.021 e, indicating stable non-covalent interactions. The incorporation of GP or BN heterostructures significantly enhanced sensitivity, with adsorption energies up to −1.09 eV in water and −0.61 eV in air, while maintaining the structural integrity of selected complexes. The adsorption of NU decreased the energy gap of the nanosheets, for example, from 4.38 to 2.36 eV in BN and from 1.85 to 1.51 eV in GP/BN (H2), indicating increased conductivity and reactivity. Quantum descriptors such as chemical potential and electrophilicity indicate higher reactivity while maintaining stability for drug delivery. Furthermore, after NU adsorption, the increase in dipole moments and changes in work function, especially in water media, indicate enhanced polarity and solubility. This study emphasizes the potential of GP and BN nanosheets as efficient carriers for anticancer drugs, especially in their heterostructure forms. Among all the nanosheets examined, the GP/BN(H2) nanosheet exhibited the strongest adsorption, good structural stability, and enhanced dipole moment, suggesting it is a promising candidate for NU delivery.

Carbon-based nanodevices for bioactive molecular recognition are crucial for biochemical engineering and novel probe development. This is heavily dependent on the surface interaction between the carbon-based nanomaterials (CNMs) and bioactive molecules. However, CNMs with variable topological structures and curvatures can undoubtedly affect the interaction with bioactive molecules such as nucleic acid bases, and the mechanism of carbon surface curvature-mediated electronic fingerprints for nucleic acid base identification has not yet been revealed. This study employs first-principles calculations combined with nonequilibrium Green's function method to investigate the electron transport properties and recognition mechanisms for five bases (A, C, G, T, U) adsorbed onto four CNMs: graphene (GR), graphdiyne (GDY), fullerene C60, and carbon nanotube (CNT). The transport characteristics modulated by carbon surface curvature, including current-voltage curves, transmission spectra, density of states, and band structures, are systematically analyzed. Distinct curvature-sensitivity relationship and voltage-dependent recognition capability are revealed from a material-specific view. It is found that GR can distinguish C/U, and CNTs distinguish C/G and C/T in the high bias range, while GDY and C60 exhibit significant current differences (>1000-2000 μA) at specific voltages (2.5-2.9 V for GDY and ∼2.8 V for C60). The recognition mechanism showed that the curvature-induced band structure modulation in GDY and C60 creates unique transmission channels essential for biochemical identification. GR provides the strongest binding stability of base primarily via dispersion interactions (-13.58 to -18.65 kcal/mol). This study establishes substrate curvature and voltage-tunable electronic signatures as key design parameters for nucleic acid base recognition, providing guidelines for bioactive molecule identification.

The glass transition temperature (Tg) is a critical parameter that defines the thermal and mechanical functional limits of poly(vinyl chloride) (PVC) and its nanocomposites. The influence of graphene (GN) and curcumin noncovalent-modified graphene (GN@CU), on the glass transition behavior and molecular dynamics of unplasticized PVC was investigated. A comprehensive set of thermal, mechanical, dielectric, and spectroscopic techniques, including differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), dielectric loss measurements, and solid-state 1H nuclear magnetic resonance (NMR) spectroscopy, was applied to investigate both local and segmental chain mobility in PVC-based nanocomposites. Spin-lattice relaxation times (T1), obtained from NMR measurements, provided molecular-level insights into chain dynamics associated with the glass transition. The results demonstrate that both GN and GN@CU restrict the mobility of the PVC chain, resulting in an increased Tg and composite stiffness. Especially, curcumin modification occurring according to the π-π interaction mechanism enhances filler dispersion and polymer-filler interfacial interactions, thereby further amplifying these effects. This work highlights the importance of integrating thermal, mechanical, dielectric, and NMR techniques to elucidate polymer-nanofiller interactions at the molecular level, which is crucial for designing PVC-based nanocomposites with improved thermal stability and mechanical properties suitable for demanding industrial applications.

Estradiol (E2) is a steroid hormone that has garnered widespread global attention as an emerging pollutant due to its potential to cause endocrine disruption in organisms upon concentration changes. This experiment achieves highly efficient detection of estradiol based on screen-printed electrodes (SPEs) and a graphene (GPE)/MIL-100(Fe) composite material. The GPE/MIL- 100(Fe) composite, characterized by a rich porous structure, was synthesized via a hydrothermal method, and the modified electrode was prepared using the drop-coating technique. The GPE/MIL-100(Fe) composite was characterized by SEM, XRD, FTIR, and XPS to confirm its structure, composition, and properties. Cyclic voltammetry (CV), differential pulse voltammetry (DPV), and chronoamperometry (CA) were employed to enable continuous monitoring of estradiol in liquid environments. The modified electrode demonstrated significant electrocatalytic activity, exhibiting high sensitivity within a linear range of 2.0 nmol/ mL to 140 nmol/mL, with a practical detection limit (LOD) of 0.002 μmol/mL. The innovation of this study lies in leveraging the synergistic effect of GPE/MIL-100(Fe) to enhance the detection performance for estradiol. In the detection of actual samples such as urine (spiked recovery rate: 103.3% -110.9%) and pond water (spiked recovery rate: 96.7% -110.0%), clear characteristic peaks and good sensitivity for estradiol were observed.

Abstract The development of multifunctional polymer nanocomposites has attracted significant attention due to their potential applications in advanced electronics, thermal management, and structural materials. In the present work, a novel ternary composite of acrylonitrile butadiene styrene (ABS) nanocomposites reinforced with hybrid fillers of graphene (GR) and multi-walled carbon nanotubes (MWCNTs) has been fabricated by using a solvent blending technique. Chloroform was employed as the primary solvent to dissolve ABS and ensure dispersion of nanofillers. The effect of varying the composition of GR/MWCNTs (Pure Polymer, 0.5, 1.0, and 2.0 wt%) on the resulting composite’s electrical conductivity and mechanical performance has been systematically investigated. The synergetic interaction of GR and MWCNTs with ABS significantly increases the current conduction and reduces the resistance. The electrical performance enhances progressively with fillers, attaining optimal conductivity at 2 wt% of GR/MWCNTs loading, showing nearly a 10 times increment in conductivity than unfilled ABS. Nanoindentation results show improved hardness and elastic modulus of the composite. A significant rise of 22% and 30% has been observed in modulus and hardness, respectively. These outcomes demonstrate that the combined use of GR and CNTs in ABS can simultaneously tailor both mechanical and electrical properties, making the composites promising candidates for applications in flexible electronics, electromagnetic shielding, and thermal interface materials.

Multifunctional performance enhancement of polypropylene nanocomposites via dual filler hybridization: Mechanical, viscoelastic, creep, aging, and repairability analysis

Graphene (GR) demonstrates significant potential in enhancing the mechanical performance of titanium matrix composites (TMCs), particularly by improving their tensile strength, fracture toughness, and fatigue resistance, thereby optimizing the overall structural integrity and durability of the composites; however, their practical implementation confronts two fundamental challenges: achieving uniform dispersion and mitigating excessive interfacial TiC formation, which compromises mechanical properties. This review comprehensively explores progress in the fabrication, interfacial design, and mechanical optimization of TMCs reinforced with graphene-based materials. Various processing techniques, such as powder metallurgy (PM) and spark plasma sintering (SPS), are critically analyzed in terms of their advantages and limitations for producing high-performance TMCs. This article analyzes how key parameters in processes like PM and SPS affect graphene structure, dispersion, and interfacial reactions. It outlines strategies-including surface modification, 3D structural design, and multiscale interface engineering-that enhance both strength and toughness. While progress has been made in microscale performance, challenges remain in engineering stability and long-term reliability. Future work should focus on intelligent process optimization and architectured composite manufacturing. By systematically synthesizing existing research findings, this article clarifies the advantages and limitations of current technological approaches, providing a theoretical foundation and technical roadmap for the subsequent development of graphene-reinforced TMCs that exhibit high strength, high toughness, and excellent reliability.

The deterioration of soil health due to salinization, acidification, and heavy metal pollution represents a critical environmental challenge threatening sustainable agriculture and ecosystem functions worldwide. Conventional remediation strategies often face limitations in efficiency, cost, and long-term stability. Carbon-based nanomaterials (CNMs), including nanobiochar (NBCs), graphene (GNs), carbon nanotubes (CNTs), and carbon dots (CDs) have emerged as promising alternatives due to their distinctive surface characteristics and nanoscale effects. This systematic review critically examines the dual role of CNMs in improving key soil properties (e.g., pH, cation exchange capacity, organic carbon content, and porosity) while also addressing their concentration-dependent effects and potential ecological risks. We analyze the mechanisms underlying CNMs-soil interactions, highlighting material-specific and concentration-dependent behaviors as well as their environmental implications, including effects on microbial communities and long-term fate. Based on mechanistic comparison, integration, and risk-benefit evaluation, this review combines field and laboratory research to identify the most promising CNMs for field application. It further proposes a synergistic framework integrating multi‑omics and field studies to guide the design of eco-friendly CNMs composites and standardized application protocols. This work provides a comprehensive foundation for applying CNMs in sustainable soil management while emphasizing the importance of ensuring ecological safety.

Strain sensors play a critical role in flexible electronics; however, conventional devices are often constrained by a narrow sensing range, low sensitivity, and intrinsic brittleness, which limit their practical applicability. In this study, a novel intelligent silicone rubber–based strain sensor was developed based on a force–electric coupling mechanism. The sensor incorporates a three-carbon topological conductive network (MCGVM), composed of carbon black (CB), graphene (GR), and multi-walled carbon nanotubes (MWCNTs) embedded in a silicone rubber (SR) matrix. The synergistic interaction among the three carbonaceous fillers promotes uniform dispersion within the matrix, resulting in a remarkably low percolation threshold (0.52 wt%) and enhanced interfacial interactions. Consequently, the MCGVM sensor exhibits an ultrawide strain sensing range of 342.62%, an exceptionally high gauge factor (GF = 43,207.05), and a stable, shoulder-effect-free resistance–strain response over 10,000 loading–unloading cycles. Furthermore, the underlying force–electric coupling behavior is systematically interpreted using a tunneling effect–based theoretical model. These results demonstrate the strong potential of MCGVM for high-performance, wide-range strain sensing applications in flexible electronics.

ABSTRACT Polyamide 6 (PA6) is inherently flammable and prone to severe melt‐dripping, which severely restricts its application in aerospace, rail transit, and public safety sectors. To address this, we developed a complementary flame‐retardant system by incorporating electrochemically exfoliated graphene (GR), melamine polyphosphate (MPP), and aluminum diethylphosphinate (ADP) into PA6 via in situ polymerization. The thermal stability and interactions among the three components were thoroughly investigated. The results indicate that the optimized formulations exhibit significant flame‐retardant enhancement. Specifically, the GR/MPP/ADP/PA6‐012 and GR/MPP/ADP/PA6‐75 composites achieved limiting oxygen index (LOI) values of 35% and 29%, respectively, and both passed the vertical burning test and achieved V‐0 rating, without any dripping. In cone calorimetry, the GR/MPP/ADP/PA6‐57 composite demonstrated the most effective heat‐release suppression, with the peak heat release rate (pHRR) and total heat release (THR) significantly reduced to 76.3 kW m −2 and 37.7 MJ m −2 , respectively. Mechanistic analysis reveals that GR forms a continuous, compact physical barrier during combustion, effectively hindering heat transfer. MPP promotes the formation of an expanded char layer, enhancing condensed‐phase protection. Meanwhile, ADP releases PO · radicals in the gas phase to quench flame‐active species and simultaneously promotes char formation. The three components work complementarily, establishing a multi‐level “barrier–charring–quenching” flame‐retardant network. This study proposes an efficient and environmentally friendly flame‐retardant strategy for PA6. By optimizing the ratio of each flame retardant, the resulting composites exhibit superior flame‐retardant performance, offering new insights into the flame‐retardant modification of engineering plastics and the design of multi‐component systems.

Textile-based temperature sensors often suffer from signal distortion due to strain interference in practical applications, severely limiting their reliability in dynamic environments. To address this challenge, this study developed a strain-insensitive resistive temperature-sensing yarn with a helical structure, named CNAS. The yarn utilizes aramid fiber as the substrate. After modification with polydopamine (PDA), single-walled carbon nanotubes (SWCNTs) were loaded onto the substrate through five cycles of dipping and drying. Subsequently, a uniform nickel oxide (NiO) sensitive layer was constructed on its surface via electrodeposition followed by thermal decomposition. The sensitive yarn (CNA) was then helically wrapped onto a prestretched Spandex core yarn to form the CNAS composite yarn. Experimental results demonstrate that CNAS exhibits a resistance variation below 4% within a strain range of 0–93% and maintains stable performance after 500 stretching cycles. It displays a significant negative temperature coefficient (NTC) behavior within a temperature range of −20 to 70 °C, with its sensitivity markedly superior to that of pure carbon nanotube (CNT) or graphene (GR) yarns. Human wear trials further confirmed that the yarn can effectively distinguish temperature changes from strain interference induced by joint movements. An alarm system built using CNAS enables reliable visual alerts for ambient temperature changes. This research provides an innovative and practical solution for anti-interference wearable temperature sensors.

ABSTRACTIn pursuit of high‐performance flexible strain sensors, achieving an optimal trade‐off among linearity, sensitivity, and strain sensing range remains a critical challenge. Inspired by the wrinkled‐leaf viburnum, we develop a Janus sensor that replicates its asymmetric structure. It comprises a dense, micro‐wrinkled natural rubber (NR)/graphene (GRs) top layer and a loose NR/carbon nanotubes (CNTs) bottom layer, fabricated via facile layer‐by‐layer filtration and pre‐stretching strategy. This bio‐inspired design enables the sensor with a synergistic sensing mechanism: wrinkle‐guided microcrack ensures highly sensitive linear response at low strains; strain‐phase division maintains signal continuity at medium strains; and parallel conductive circuits provide robustness at high strains. As a result, the sensor achieves an exceptional combination of ultra‐high linearity (R2 > 0.999) and sensitivity (gauge factors, GF > 14) across 0–100% strain, with a wide sensing range (> 400%) and fast response (0.16 s). We demonstrate its practical value in human motion detection, physiological signal monitoring, and an intelligent glove system for gesture recognition and human‐machine interaction, highlighting its promising potential for advanced wearable devices and human‐machine interactive systems.

ABSTRACT To design high performance of organic/inorganic thermoelectric composite materials by molecular simulation, composite materials (PPy/NG) are constructed by incorporating graphene (GE) modified with N atoms (NG) into the Polypyrrole (PPy) matrix. For different GE doping concentrations and different concentration N atoms modified in GE (mod‐Ns), the thermoelectric properties of PPy/ n ‐NG composite materials ( n represents different N atoms modified concentration) is systematically investigated using the non‐equilibrium molecular dynamics (NEMD) and density functional theory (DFT). It is found that N‐modification on GE has a significant influence on the reduction on the thermal conductivity of composites with 7.06 wt.% graphene concentration. Moreover, when the mod‐Ns concentration reached 3.66%, the thermal conductivity of the PPy/NG composite material is decreased by 49.19%. Additionally, the electron properties of PPy/ n ‐NG are studied. It is found that the energy differences between the HOMO of n ‐NG and the LUMO of PPy decrease with the increase of mod‐Ns concentration in NG. Overall, this study reveals that n ‐NG reduces the thermal conductivity of PPy/ n ‐NG composites and promotes the transfer of electrons between n ‐NG and PPy. It establishes a theoretical foundation for designing high‐performance organic/ inorganic thermoelectric materials.

Graphene (GRA) and graphene oxide (GO) have drawn significant attention in materials science, chemistry, and nanotechnology because of their tunable physicochemical properties and wide range of potential uses in biomedical and environmental applications. Building reliable, large-scale molecular models of GRA and GO is essential for molecular simulations of wetting, adsorption, and catalytic behavior. However, current methods often struggle to generate large, chemically consistent sheets at high oxidation levels. In addition, the resulting structures are frequently incompatible across different simulation packages. This work introduces a step-by-step protocol with custom Tool Command Language (Tcl) and modified Python version 3.12 scripts for building large-scale, AMBER-compatible GO structures with oxidation levels from 0% to 68%. The workflow applies a systematic surface modification strategy combined with post-processing and atom-type assignment routines to ensure chemical accuracy and force field consistency. The dataset includes fifteen MOL2 format files of 20 × 20 nm2 GO sheets, ranging from pristine to highly oxidized surfaces, each validated through oxidation-ratio analysis and structural integrity checks. Together, the dataset and protocol provide a design of scalable and chemically reliable GO molecular models for molecular dynamics simulations.

The composite of quantum dots (QDs) with graphene (GR) has significantly enhanced its potential for optoelectronic applications. Although existing research has experimentally confirmed the excellent optoelectronic properties of quantum dots-graphene (QD-GR) heterostructures, the underlying charge transfer mechanisms have not been fully elucidated. This study uses the Marcus theory to investigate the photoinduced charge transfer characteristics of QD-GR heterostructures under external electric field (Fext) modulation. We first constructed a lead sulfide quantum dots-graphene (PbS QD-GR) heterojunction model using a minimal-sized lead sulfide quantum dots (PbS QDs) cluster and a single-layer flake graphene. Next, we systematically analyzed the electronic state distribution at the interface and elucidated the essential mechanism underlying the heterojunction's structural stability. The excited state properties of the PbS QD-GR heterojunction under Fext modulation were systematically investigated. Finally, based on Marcus theory, the reorganization energy (λ), Gibbs free energy (ΔG) and electron coupling matrix element (Vda) were quantitatively calculated to reasonably predict the charge transfer rate (K). The study revealed that the charge separation rate significantly exceeds the charge recombination rate (KCS ≫ KCR), demonstrating the heterostructure's exceptional exciton dissociation capability. Our findings elucidate the trend of charge transfer parameters in specific PbS QD-graphene heterojunctions under external electric fields, thereby providing theoretical support for a deeper understanding of optoelectronic device performance.

Single-atom catalysts (SACs) have demonstrated great potential in the electrochemical nitrogen reduction reaction (NRR). However, the electronic regulation mechanism of intermediate adsorption on SACs remains unclear, and conventional density functional theory (DFT) calculations fail to establish a universal "structure-performance" relationship. This study is based on coordinated single-atom structures (M-NnCm-GN), anchored at defect sites of nitrogen-doped graphene (GN), and develops an AdaBoost-XGB integrated model (R 2 = 0.95) to analyze the interaction mechanisms between metal active sites and reaction intermediates (O, N, C and H). The results show that the doped metal in the MN4 structure and the adsorbed intermediates follow the 10-valence electron coupling rule, which is extended to different coordination environments. For the N intermediate, average electronegativity values less than 2.8, equal to 2.8 and greater than 2.8 correspond to the 11-, 10- and 10-valence electron coupling rules, respectively, while O follows the 10-valence electron coupling rule. In addition, we used this rule to guide the design of NRR (N2 → NNH) and OER (OH → O) catalysts. The three-dimensional descriptor of the adsorbate fitted by the SISSO algorithm achieved an R 2 of 0.97, further improving predictive accuracy. The metal valence electron number (Ne1) exhibits a positive correlation with adsorption energy, while the introduction of bond length features (d 1) enhances the model's predictive accuracy by approximately 17%. The electronegativity-regulated interfacial valence electron coupling rules established in this study successfully unravels the "structure-activity relationship black box" challenge of SAC catalysts, providing a quantifiable and transferable approach for the design of high-performance SACs.