International Journal of Mechanical and Materials Engineering最新文献

MoS₂-derived carbon nanomaterials have garnered significant interest as anode materials for lithium-ion batteries (LIBs). MoS₂-based carbon nanomaterials are synthesized using a two-step or multi-step method. Herein, we report a simple one-step arc-discharge technique for the synthesis of MoS₂ nanoparticles loaded on S-doped carbon nanohorns (MoS₂/SCNHs). The synthesized MoS₂/SCNHs serve as an anode material for LIBs, demonstrating a substantial reversible capacity of 480.4 mAh g⁻¹ at a current density of 1.0 A g⁻¹ after 550 cycles. The elevated specific capacity and extended lifespan are primarily ascribed to a distinctive bud-type morphology of SCNHs. The microporous structure of the SCNHs significantly reduces charge-transfer resistance and effectively prevents the aggregation of MoS₂ nanoparticles. The MoS₂/SCNHs hybrid material synthesized via the arc-discharge method is a promising anode for LIBs, and this method offers a novel approach for producing other transition metal sulfides supported on carbonaceous substrates.

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The growing emphasis on sustainability and environmental impact has driven increased demand for eco-friendly tyres. Tyre components are usually subjected to substantial static and dynamic load and often fail due to crack initiation and crack propagation. Understanding of the deformation mechanism of tyre components under fatigue loading is essential for enhancing the safety and reliability of tyres. In recent years, advanced tools for predicting fatigue and wear have been introduced, improving the accuracy of virtual prototyping and enabling more extensive evaluation of design concepts at early stages. This paper reviews recent advancements in the use of numerical methods for predicting fatigue failure and damage in tyre design. Given the limited research on numerical modelling for fatigue and fracture, there is a need for further investigation to develop reliable simulations for predicting tyre behaviour under fatigue loads. This review summarises the current applications of numerical fatigue modelling, providing engineers with a systematic overview of the literature, highlighting key achievements, and promoting further development in the field. The paper begins by discussing tyre components, followed by an exploration of material modelling techniques. It then addresses numerical modelling strategies for full-scale tyres under real-life loading conditions. Challenges in predicting fatigue failure using finite element (FE) modelling are examined, along with the issue of potential damage accumulation. Finally, the paper outlines recommendations for future research on FE modelling techniques, offering insights into current approaches and encouraging further investigation in the field.

The development of efficient and stable photocatalysts for hydrogen (H₂) generation is crucial for sustainable energy applications. This study addresses the limitations of pristine zinc oxide (ZnO), its wide bandgap (~ 3.37 eV), and rapid charge recombination by synthesizing aluminum (Al) and cerium (Ce) co-doped ZnO nanocomposites (ACZO) via a scalable hydrothermal method. Structural and optical characterizations confirmed successful dopant incorporation, reduced crystallite size, and enhanced light absorption, with a narrowed bandgap of 2.64 eV. Further, these modifications suppress electron–hole recombination, as evidenced by a 70% reduction in photoluminescence intensity for ACZO compared to ZnO. Under simulated solar irradiation, the optimized ACZO nanocomposite achieved an H₂ generation rate of 1474 μmol/g.h, a 2.8-fold increase over pristine ZnO, outperforming single-doped counterparts (AZO: 1.25-fold; and CZO: 1.84-fold). The optimal catalyst dosage was determined to be 1.5 g/L, balancing dispersion and light absorption. Furthermore, ACZO exhibited excellent photostability over multiple cycles, demonstrating its potential for long-term applications. This study highlights the effectiveness of dual doping in enhancing ZnO’s photocatalytic efficiency, positioning ACZO as a promising candidate for scalable solar-driven hydrogen production.

Nanomaterials have emerged as pivotal components in advancing technologies, particularly in energy production and storage. This paper explores their unique properties, with a specific focus on magnetic nanomaterials for hydrogen generation through water splitting. As the global demand for clean and sustainable energy intensifies, hydrogen has been identified as a promising energy carrier due to its zero-emission profile and high energy density. The integration of magnetic fields with nanomaterials enhances reaction kinetics and mass transport during electrolysis, thereby significantly improving efficiency. This study reviews strategies for harnessing magnetic nanomaterials, such as ferrites, to optimize catalytic activity in water electrolysis. The mechanisms through which magnetic fields influence reaction dynamics, including enhanced charge transfer and reduced electron–hole recombination, are examined. Challenges, such as the stability of magnetic materials under operational conditions and the scalability of production methods, are also discussed. The findings underscore the transformative potential of magnetic nanomaterials in accelerating the transition to a hydrogen economy, offering critical insights for future research in renewable energy technologies.

Chitosan (CS), a linear polysaccharide derived from chitin (Ch), is known for its excellent biocompatibility, biodegradability, and high chemical resistance, making it suitable for environmental and biomedical applications. However, its relatively low mechanical strength limits its performance in demanding applications. To address this limitation, this study explores the reinforcement of chitosan with chitin via electrospinning, a technique that effectively incorporates chitin as a reinforcing agent. Specifically, electrospun nanofibers were composed of hydrolyzed chitosan (hCS), hydrolyzed chitin (hCh), and polyvinyl alcohol (PVA) as carrier polymer. To evaluate their structural and thermal performance, the nanofibers were characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). SEM images revealed uniform and interconnected fibers, with diameters ranging from 231 to 317 nm, exhibiting a strong correlation between fiber diameter and chitin concentration. FTIR analysis indicated increased hydroxyl and amine group availability in hCS, further enhancing hydrogen bonding, which led to a crystallinity increase from 37.87% to 39.08% after chitosan hydrolysis, as revealed by XRD. Hydrolyzed chitin exhibited a higher crystallinity index of 64.52%. XRD studies showed that increasing hCh content in nanofibers improved crystallinity, with the highest crystallinity index of 51.21% observed in the sample containing 80% hCh. TGA demonstrated that nanofibers with higher chitin content exhibited superior thermal stability, with decomposition temperatures increasing from 317 °C (0% hCh) to 345 °C (100% hCh). This enhancement is attributed to the highly ordered crystalline structure and strong intermolecular hydrogen bonding of hCh. The findings underscore that the integration of chitin into chitosan-based nanofibers significantly improves their structural integrity, thermal resistance, and crystallinity. These optimized nanofibers hold promise for advanced applications in environmental remediation, biomedicine, and sustainable material development.

This study explores the optimization of multi-walled carbon nanotube (MWCNT) concentration in nylon-based nanocomposites to enhance the performance of triboelectric nanogenerators (TENGs). Nylon/MWCNT nanocomposite films were fabricated using the spin-coating method, and their electrical output was systematically evaluated as a function of MWCNT concentration. Results show that the open-circuit voltage (Voc) and short-circuit current (Isc) increase with MWCNT loading up to 0.05 wt%, reaching a peak of 29.7 V and 3.0 μA, respectively, compared to 17.5 V and 1.8 μA for pristine nylon-based TENGs. However, a decline in output was observed at 0.1 wt% due to MWCNT agglomeration, which disrupts charge transfer and introduces charge leakage. The enhancement at optimal concentration is attributed to improved charge trapping and increased dielectric constant, while excessive CNT loading reduces the effective contact area and limits triboelectric charge generation. These findings underscore the crucial role of nanomaterial dispersion in optimizing TENG performance and offer valuable insights for the development of high-efficiency triboelectric energy harvesting systems.

Low-cycle fatigue is a common failure mode of stud connectors in bridges. Accurate prediction of their life is crucial for material design and engineering applications. However, traditional theoretical formulas and experimental methods suffer from limitations such as low accuracy and individual variability. This study aims to develop a high-precision prediction model for low-cycle fatigue life using machine learning methods, providing a new approach for material performance evaluation. Firstly, through literature analysis and correlation analysis, key feature variables were identified: f_u, ln(τ_max), ln(Δτ). Secondly, the predictive performance of nine machine learning models was compared by combining cross-validation and hyperparameter optimization. Based on the principle of complementary advantages, an ensemble model was established using Random Forest (RF) and Extreme Gradient Boosting Tree (XGBoost) as the basis. Finally, the SHAP tool was introduced to explain the model’s decision-making process. The results showed that compared to individual models, the integrated model reduced the MAPE by 8.91% and the RMSE by 14.83%, while increasing the R² by 7.32%. The main factor affecting the low-cycle fatigue life of studs is ln (τ _max). The interaction between ln (τ _max) and ln (Δ τ) has the greatest impact on the low-cycle fatigue life of the stud. These findings not only enhance the understanding of fatigue mechanisms in stud connectors but also provide a robust framework for optimizing material selection and design in steel–concrete composite structures.

Nitrogenated amorphous C (a-C:N) coatings with an intermediate sp³ C fraction of 30%–55% and N content of 0–5 at.% were deposited on single-crystal silicon wafer substrates via intermittent filtered cathode vacuum arc deposition. Some of the coated specimens were annealed at 300 and 600 °C for 4 h in a 5-Pa vacuum. The morphologies, microstructures, and the bonding structure of the specimens were characterized using scanning electron microscopy, X-ray photoelectron spectroscopy, and micro-Raman spectroscopy. The mechanical characteristics of the coatings, including the residual stress and hardness, were measured. Of the doped N content in the coatings, 60%–70% formed a pyridine- and pyrrole-like ring configuration of sp² C = N bonds. As the N content was increased, the fraction of pyridine-like bonds decreased, and the pyrrole-like configuration gradually became dominant. Compared to the N-free coatings, the thermally stable temperature of the nitrogenated coatings decreased to approximately 300 °C, and their surface roughness increased after annealing at 600 °C. The increase in the ratio of pyridine-like to pyrrole-like bonds (R_pyd-pyr) in the coatings increased the number of voids and pinholes in the surface layer. However, the top surface of the a-C:N coating with 3.4 at.% N annealed at 600 °C remained smooth almost without voids, which could be ascribed to its suitable R_pyd-pyr and high sp² C = C fraction.

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In this paper the Poly (aniline-co–o-methoxy aniline) (PAOMA) copolymer coatings, as well polyaniline (PANI) and poly (o-methoxy aniline) (POMA) individual polymer coatings, were synthesized on copper (Cu) substrates from an aqueous solution of sodium salicylate. A series of PAOMA copolymer coatings were deposited by electrochemical copolymerization of aniline (ANI) with o-methoxy aniline (OMA) using different monomer feed ratios under cyclic voltammetric conditions. A comparative analysis of the cyclic voltammograms (CVs) recorded during polymerization of aniline, o-methoxy aniline, and their copolymer clearly reveals the effect of the monomer ratio on the formation of the copolymer, polymer, and the quality of the coatings. All the resulting coatings were characterized by cyclic voltammetry, UV–visible absorption spectroscopy, scanning electron microscopy (SEM), nuclear magnetic resonance (NMR) spectroscopy, and Fourier transform infrared spectroscopy (FTIR). The synthesis of the copolymer, using a mixture of monomers in the aqueous sodium salicylate solution, was confirmed through a comparative study of the results obtained from the polymerizations, as well with the characterizations of the individual monomers, aniline and o-methoxy aniline. Corrosion resistant characteristics of resulting coatings were evaluated by potentiodynamic polarization measurement in aqueous solution of 3% NaCl solution. It extracts the values of corrosion potential (E_corr), corrosion rate (CR), porosity (P) and protection efficiency (%PE). The analysis of these results imply that the copolymer PAMOA-5 coating provides effective protection to Cu against corrosion in aqueous 3% NaCl as compared to that of the other copolymers and also than the corresponding homopolymers. For PAOMA-5 coated Cu it was found that the remarkable positive shift of 344 mV in E_corr, substantial reduction in corrosion rate 875 times lower than that observed for bare Cu, lowest value of porosity (0.44 × 10^–6) and highest protection efficiency of 99.9%.

The CuCo₂O₄ and CuCo₂O₄/MWCNT nanocomposites were synthesized using hydrothermal techniques as an electrode material for supercapacitor applications. Structural characterization, including XRD, SEM, and EDX, confirmed the successful fabrication of nanocomposites. Electrochemical analysis revealed that CuCo₂O₄/MWCNTs exhibit excellent oxygen (OER) and hydrogen (HER) evolution catalytic activity, with enhanced cyclic stability, high-rate capability, and better specific capacitance compared to pure CuCo₂O₄ electrodes. The synergistic interaction between CuCo₂O₄ and MWCNTs significantly improves electrochemical performance, highlighting the potential of these nanocomposites as an electrode material for energy storage and electrocatalytic applications.