Journal of Materials Science最新文献

Poly(m-phenylene isophthalamide) (PMIA)-based insulating paper exhibits excellent electrical insulation and mechanica l properties, including higher breakdown strength (E_b) than conventional cellulose insulating paper. However, its intrinsically low thermal conductivity limits heat dissipation in oil-paper insulation systems, causing Joule heat accumulation, insulation degradation, and thermal breakdown. Herein, we report PMIA-based composite papers prepared by binary multidimensional doping the small-size 0D sphere-like aluminum nitride (AlN) filler with large-size 3D sphere-like, 2D lamellar-like, and 1D wire-like AlN fillers, respectively. At the same total filler volume fraction, large-size fillers with different morphologies show distinct advantages. For electrical insulation, the 2D lamellar-like filler most effectively enhances E_b by optimizing trap characteristics and mitigating electric field distortion, reaching 284.3 kV/mm, 29.5% higher than that of the 0D-only doped sample (N15). For thermal conduction, 3D sphere-like filler is most effective in enhancing the out-of-plane thermal conductivity (k_⊥) by reducing thermal resistance, reaching 0.282 W/(m·K) and representing a 14.5% improvement over N15. In contrast, 1D wire-like and 2D lamellar-like fillers are more favorable for constructing in-plane heat transfer pathways, yielding in-plane thermal conductivity (k_//) values of 0.546 W/(m·K) and 0.386 W/(m·K), respectively. Moreover, finite element analysis further reveals the morphology-dependent electric and thermal field distributions in the composites.

Epoxy resins are widely used, but their inherent flammability and the release of copious smoke and toxic gases during combustion severely limit their application in high-end sectors. To overcome the drawbacks of conventional DOPO-based flame retardants—namely poor compatibility, high required loadings, and significant degradation of mechanical properties, we synthesized a novel DOPO-derived ionic liquid flame retardant, [DMoam]Ps, by incorporating aminopropylmorpholine (which bears reactive amino groups) into the DOPO skeleton, and confirmed the successful formation of the target product via FTIR, NMR, and mass spectrometry. Upon introducing this flame retardant into the epoxy/DDM curing system, we systematically evaluated the flame retardancy, thermal stability, and mechanical performance of the composites; results showed that at 10 phr loading, the limiting oxygen index increased from 22.7 to 30.8% with a UL-94 V-0 rating, while cone calorimetry revealed reductions of 35.7% in peak heat release rate and 38.4% in total heat release, and at 8 phr, the tensile strength, flexural modulus, and impact strength were enhanced by 52.93%, 64.36%, and 95.13%, respectively. Mechanistic investigations elucidated that [DMoam]Ps acts through a synergistic phosphorus–nitrogen–sulfur effect, scavenging free radicals and diluting combustible volatiles in the gas phase, while promoting the formation of a compact intumescent char layer in the condensed phase, thereby establishing a dual “gas-phase quenching and condensed-phase barrier” protection mechanism. This study offers a new approach to epoxy composites with high flame retardancy and excellent mechanical properties.

Activating peroxymonosulfate (PMS) with metal-free carbon catalysts represents a promising and environmentally benign strategy for water purification, which has recently attracted widespread research interest. Nevertheless, practical implementation in real waters remains challenged by matrix complexity and limited accessible active sites. Herein, a three-dimensional hierarchical phosphorus-doped porous carbon (3DHPC) was synthesized from renewable glucose, where manganese nitrate was used to construct mesopores, while sodium hypophosphite served as the phosphorus source and assisted in regulating the hierarchical pore structure. The 3DHPC-0.2 delivered a micro-/mesoporous architecture and showed rapid BPA degradation via PMS activation, achieving 99.5% removal within 5 min at 0.05 g L⁻¹ catalyst and 0.1 g L⁻¹ PMS. XPS and FTIR analyses revealed the presence of C–P and O–P functionalities, providing strong evidence for phosphorus-related surface chemistry that plays a crucial role in promoting PMS activation. EPR spectroscopy combined with quenching assays revealed that both radical-mediated and nonradical pathways were operative, with singlet oxygen (¹O₂) being efficiently generated. Meanwhile, the 3DHPC-0.2/PMS process sustained robust performance across pH 3.0–11.0, at 25–35 °C, and in a variety of water chemistries. Notably, it preserved a high BPA removal efficiency after six consecutive cycles, underscoring its excellent reusability and structural robustness. This work demonstrates a scalable strategy for constructing biomass-derived carbon catalysts with integrated hierarchical porosity and phosphorus functionalities for PMS-based advanced oxidation processes.

Current research on the development of biomaterials aims at reducing bacterial colonization and increasing cell adhesion on the surface of implantable devices for regenerative medicine. Equally noteworthy is the growing interest in using materials from renewable sources and biodegradable in medical devices. In this study, femtosecond laser surface texturing was applied to PLA/PHBV polymer blends nanocomposites with and without cellulose nanocrystals (CNCs) and carbon nanotubes (CNTs) fillings. Micro-pillar structures were developed using a femtosecond laser. The textured samples were characterized by SEM, profilometry, and contact angle measurements. The effect of texturing on cytotoxicity, cell adhesion and proliferation were evaluated by MTT assay and confocal fluorescence microscopy by using L929 fibroblasts cell line. The results showed that laser texturing led to a significant increase in surface roughness and caused the material to change from hydrophilic to hydrophobic behavior, a phenomenon explained by the Wenzel model. The polymers showed higher cell viability and directional growth after laser treatment, especially in the samples containing 0.5–1.5 wt% CNT and up to 5 wt% CNC. However, it was observed that at high concentrations of nanofillers the biocompatibility was compromised, which could be attributed to particle agglomeration and percolation effects. Overall, this study highlights the synergistic role of laser-induced microstructures and functionalization with nanomaterials in modulating the surface properties of biopolymers to promote biocompatibility, offering a promising approach for the development of bioactive surfaces for high-performance implants.

Nerve agents are highly toxic organophosphorus compounds due to their irreversible inhibition of mechanisms that are critical in neural signalling. Early identification of such molecules is extremely challenging. Dimethyl methylphosphonate (DMMP), a simulant for G-series Sarin, is detected here using a Complementary Split Ring Resonator (CSRR) platform, functionalized with (3-aminopropyl) triethoxysilane (APTES) and gold nanoparticles (AuNPs) forming AuNPs–APTES. Two material platforms were investigated, namely rigid ({text{F}text{R}}_{4}) (a fibreglass-reinforced epoxy-based PCB material) and a flexible paper test strip. The CSRR sensor was fabricated on a ({text{F}text{R}}_{4}) substrate at a resonance frequency of 428 MHz with an attenuation of − 22.38 dB. After due functionalization with AuNPs–APTES layer, the resonant frequency shifted from 419 MHz. Upon subjecting the surface to DMMP (0–500 ppm), it further shifted to 381 MHz, showing a sensitivity of 76 kHz/ppm. CSRR with test strip exhibited a shift from to 410 MHz (~18 kHz/ppm), for the same range of DMMP variation. The AuNPs–APTES layer enables strong affinity towards phosphoryl groups of DMMP, leading to pronounced dielectric perturbation near the CSRR resonator gap. The synergy between surface chemistry-driven selectivity and radio-frequency (RF) resonator field confinement produces quantifiable resonance signatures as a function of analyte concentration, without the need for heating or electrolytes. A low power, miniaturized and substrate adaptable RF chemical sensor for nerve agent warning is proposed.

Accurate prediction of the full stress–strain curve, rather than a few isolated scalar metrics, is essential for understanding deformation behavior and optimizing thermomechanical processing in steels. However, this task remains challenging because the mechanical response is jointly affected by processing history and microstructural heterogeneity. In this work, a multimodal mechanical response network (MMR-Net) is proposed to predict the complete true stress–strain curves of GCr15 high-carbon chromium bearing steel by combining thermomechanical process parameters with segmented scanning electron microscopy (SEM) images. The framework uses dual encoders to extract features from process descriptors and microstructural images, fuses them through cross-attention, and generates the stress sequence within the uniform deformation regime using a physically constrained sequence decoder. MMR-Net achieved an average R² of 0.976 ± 0.009 and an MAE of 15.01 ± 2.92 MPa on the validation sets, and an R² of 0.964 ± 0.013 and an MAE of 21.90 ± 4.78 MPa on the test set, consistently outperforming the single-modality baselines and ablated model variants. Interpretability analysis shows that the contributions of process parameters and microstructural features vary along the deformation sequence, while latent feature visualization reveals clustering behavior associated with key thermal processing conditions. Beyond direct curve prediction, the reconstructed true stress–strain curves are further used to derive deformation-related macroscopic quantities within the uniform deformation regime, including (varepsilon_{{{text{end}}}}), (sigma_{{{text{end}}}}), (W_{{{text{total}}}}), (W_{{text{p}}}), and (overline{n}). For the AT and At scanning groups, the predicted variation of these quantities is consistent with the corresponding SEM fracture morphologies, especially the changes in dimple size and uniformity, indicating that the predicted curves preserve physically meaningful information relevant to the pre-fracture deformation stage. These results demonstrate that MMR-Net can capture the process–microstructure–mechanical response relationship in a physically interpretable manner and that the predicted curves can further support the analysis of deformation behavior preceding fracture. The proposed framework provides an effective data-driven approach for the prediction and interpretation of mechanical behavior in high-performance steels.

Phenolic resin-based composites, featuring excellent ablative thermal insulation, mechanical stability, and convenient formability, serve as core candidate materials for the thermal protection systems of hypersonic vehicles in the aerospace field. In the present work, different from traditional 1D chopped fibers, 2D fiber fabrics and 2.5D woven fabrics, and SiO₂ fiber aerogels with a 3D micro/nano dual-scale fiber network were used as reinforcement to further enhance the mechanical properties, thermal insulation, and ablation resistance of phenolic resin-based composites. By optimizing the micro/nano fiber ratio to 2:2, micro/nano dual-scale SiO₂ fiber network/phenolic resin composites exhibit higher compressive strength, lower thermal conductivity, and ablation rate. The synergistic effect of the micro/nano dual-scale fiber network is the core of performance enhancement. Microfibers dissipate strain energy through pull-out, while nanofibers enhance resin continuity and inhibit crack propagation. In terms of ablation resistance, the 3D micro/nano dual-scale fiber network can anchor the carbonized layer and decrease heat conduction through the infinite path effect and phonon scattering effect, thereby providing synergistic thermal protection. This study not only develops a novel micro/nano dual-scale SiO₂ fiber network/phenolic resin composite but also provides insight into the design of a new generation of lightweight and high-efficiency thermal protection materials for aerospace applications.

Multifunctional bimetallic nanocomposites of silver and copper, in which the supported particles are on reduced graphene oxide (AgCu@rGO), were prepared by a hydrothermal-assisted chemical reduction procedure. Monometallic Ag@rGO and Cu@rGO nanocomposites were also prepared for comparison. The reduction of GO, the formation of metal–oxygen–carbon (M–O–C) bonds, and the interfacial effective bonding between the metal NPs and rGO sheets were successfully characterized through comprehensive analyses using FTIR, XRD, XPS, Raman spectroscopy, UV–Vis, SEM-EDX, TGA, and BET. XRD confirmed the presence of mixed Ag–Cu phases, indicating alloy formation and lattice distortion, which contributed to increased electronic interactions and charge transfer. The resulting AgCu@rGO nanocomposite had a mesoporous structure with a specific surface area of 44.15 m² g⁻¹ and a uniform distribution of NPs, which provided plenty of active sites for the catalyzed reaction. Photocatalytic studies showed that AgCu@rGO exhibited strong catalytic activity. In hydrogen evolution from the dehydrogenation of formic acid (FA), the Ag₂₀Cu₈₀@rGO was optimized to achieve a high turnover frequency (TOF) of 5572.4 h⁻¹ at 60 °C with total hydrogen selectivity, exceeding that of the monometallic and noble metal counterparts, Pt/C and Pd/C. Similarly, AgCu@rGO exhibited photocatalytic activity with remarkable visible-light superiority, degrading methylene blue (MB) by more than 95% in 60 minutes under pseudo-first-order conditions. The improved activity has been explained by synergistic interfacial charge transfer among Ag, Cu, and rGO, localized surface plasmon resonance (LSPR), and increased separation of photoinduced charge carriers. The catalyst was highly robust in practice, exhibiting high structural stability and reusability across repeated cycles.

Polymer-based materials offer advantages in thermal management, including easy processing, low density, and excellent flexibility. However, their limited thermal conductivity and poor interfacial compatibility hinder efficient heat dissipation. Herein, highly thermally conductive aramid nanofiber (ANF) composite films are reported, prepared by incorporating liquid crystal-assisted carbon nanotubes (M&OH-CNTs) as thermal fillers via facile vacuum-assisted filtration followed by hot pressing. The rod-like liquid crystal 4′-hydroxy-[1,1′-biphenyl]-4-yl 4-(allyloxy) benzoate (M) not only promotes uniform dispersion of OH-CNTs within the ANF matrix but also enables a unique “defect-healing” mechanism during hot-pressing in the liquid crystalline state, where M molecules flow into and fill microscopic gaps at the filler–matrix interface. This synergistic strategy, combining enhanced dispersion with interfacial defect repair, facilitates efficient phonon transport through a well-constructed thermal network. Consequently, an outstanding in-plane thermal conductivity of 23.70 W m⁻¹ K⁻¹ is achieved at 55 wt% M&OH-CNTs loading, representing an 879% enhancement over pristine ANF film. Moreover, the resulting composite films exhibit excellent thermal stability and, benefiting from the interconnected conductive network, deliver superior electromagnetic interference (EMI) shielding (29.5 dB) with an exceptional specific shielding effectiveness (SSE/t) of 4273 dB cm² g⁻¹ at a thickness of just 78 μm. This work provides a novel and effective strategy for fabricating high-performance polymer-based thermal management materials through liquid crystal-mediated filler engineering.

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Two-dimensional (2D) transition metal carbides (MXenes) show promising properties in a vast range of applications due to their unique properties, including 2D layered structure, large physical surface area, high electronic conductivity, and tailorable surface properties. The layered structure with weak physical forces between the layers poses a significant challenge due to the restacking tendency, resulting in a substantial decrease in the surface area. The electronic properties of 2D materials can be tuned by introducing heteroatoms into the layers. Herein, we designed novel electronic materials with a three-dimensional structure via a facile post-treatment of 2D V₂CT_x MXene layers. Then, nitrogen (N) and sulfur (S) atoms were used to tune the electronic properties of 3D V₂CT_x MXenes. The electronic properties of heteroatom-doped 3D MXenes were exploited as interlayer materials between a silicon wafer and aluminum to develop Schottky-type self-powered UV–Vis–NIR photodetector devices. Our results indicated that the MXene nanocomposite had excellent semiconductor behavior, confirming its potential for optoelectronic applications. Electrical parameters such as ideality factor and barrier height were efficiently estimated using various machine learning models, including linear regression and artificial neural networks. The MXene/n-Si device demonstrated superior performance under zero-bias operation, achieving a peak photocurrent of 3.78×10⁻⁶ A, responsivity of 13.18 mA/W, and detectivity up to 6.53×10¹⁰ Jones in the visible region (600 nm). In the UV range (351 nm), the device maintained reliable detection with photocurrents up to 5.97×10⁻⁷ A, responsivity of 3.80 mA/W, and detectivity of 1.88×10¹⁰ Jones. Even in the NIR region (1000 nm), it sustained strong performance with detectivity above 5.55×10¹⁰ Jones. These results highlight the MXene/n-Si heterojunction’s potential for high-sensitivity, broadband, and energy-efficient photodetection across the UV–VIS–NIR spectrum.

Graphical abstract