Search Results (25,810)

With the increasing deployment of lithium iron phosphate (LiFePO₄) batteries in electric vehicles and energy storage systems, the recycling of these materials has become an urgent necessity. Specifically, the reclamation of lithium iron phosphate cathode materials presents a significant challenge in the recycling process. In this study, we proposed an efficient low-temperature hydrothermal direct regeneration method aimed at repairing lithium vacancies and Fe/Li inversion defects in spent lithium iron phosphate resulting from prolonged cycling. By using this method, spent lithium iron phosphate was successfully regenerated through a hydrothermal process conducted at 80 °C for 6 h, utilizing hydrazine hydrate (N₂H₄·H₂O) as a potent reducing agent and lithium hydroxide (LiOH·H₂O) as the lithium source. X-ray diffraction (XRD) analysis, coupled with Rietveld refinement, revealed a substantial reduction in the concentration of Fe/Li anti-site defects in the spent material, decreasing from 8.8% to 3.3% following regeneration. Consequently, the electrochemical performance was significantly restored. The initial specific discharge capacity increased from 118.0 mAh·g⁻¹ to 150.3 mAh·g⁻¹, and the capacity retention after 100 cycles (at 1 C) improved from 67.5% to 90.7%. The hydrothermal regeneration process introduced in this work effectively repairs the material structure and restores the active valence state of iron, thereby significantly enhancing lithium-ion diffusion and electron transport capabilities. This approach constitutes a technically viable solution for the efficient, environmentally friendly, and cost-effective recycling of spent lithium-ion batteries. Full article

The utilization of recycled steel is essential for achieving carbon neutrality and sustainable engineering, yet repeated recycling inevitably leads to the accumulation of residual elements that are difficult to remove during conventional refining. Among them, copper (Cu) readily enriches in scrap-based steels and is a primary cause of surface hot shortness during high-temperature processing due to its segregation at the oxide/steel interface. While the compositional effects of Cu have been extensively studied, the influence of thermo-history associated with different industrial processing routes remains poorly understood. In this work, Cu enrichment during high-temperature oxidation was systematically investigated under thermo-histories representative of conventional hot rolling, thin slab continuous casting and rolling (TSCR), and strip casting. Plain carbon steels containing 0.05–0.30 wt.% Cu were oxidized at 1000–1200 °C, and interfacial microstructures were characterized using SEM–EDS. The results show that Cu enrichment is highly sensitive to both temperature and thermal exposure time, with a critical temperature range of 1100–1150 °C promoting the formation of continuous Cu-rich liquid films. Prolonged thermo-history in conventional hot rolling markedly enhances Cu enrichment, TSCR partially suppresses interfacial segregation, whereas strip casting effectively inhibits Cu enrichment even at elevated Cu contents. These findings highlight thermo-history as a dominant factor controlling Cu-induced surface hot shortness and provide guidance for process optimization in recycled steels. Full article

This work proposes new architecture, supported by analytical modelling and computer-aided design (CAD) simulations, for a highly sensitive monolayer graphene-gated AlGaN/GaN HEMT terahertz (THz) detector operating at room temperature (RT). The monolayer graphene gate acts as a surface plasmon absorber for the incident THz radiation. The carrier density perturbation caused by incident THz energy on the monolayer graphene surface is then capacitively coupled to the two-dimensional electron gas (2DEG) channel of the HEMT structure underneath. The channel is partially depleted for increased mobility and nonlinearity with potential asymmetry across the channel for consistent photogeneration. The Drude absorption of THz radiation initiates intraband transitions in monolayer graphene, thereby reducing phonon losses. These reduced phonon losses enable RT THz detection. Based on our simulations, the proposed detector architecture can generate a responsivity of 2.12 × 10⁶ V/W at 1 THz with a broadband bandwidth of 2 THz. Full article

Vanadium dioxide (VO₂) is a highly promising material for infrared laser protection due to the pronounced optical switching effect during its metal–insulator transition (MIT). However, due to the relatively high MIT temperature of VO₂ and the low transmittance contrast before and after the MIT, practical applications face challenges in modulation depth and response time. In this study, we address these issues using a wafer-scale VO₂/GaN/Al₂O₃ heterostructure fabricated by oxide molecular beam epitaxy. The conductive GaN interlayer enables local Joule heating of the VO₂ film, permitting direct control of the MIT via an external bias with a threshold of 4.7 V. This structure exhibits a substantial resistance change of four orders of magnitude and enables adaptive limiting of a 3.7 μm laser, reducing transmittance from 60% to 10%. Our work demonstrates a practical, wafer-scale laser-protection device and introduces a pre-excitation strategy via external biasing to enhance response performance. Full article

Semiconductor manufacturing equipment such as vacuum pumps, wafer handling mechanisms, etching machines, and deposition systems operates for a long time under high vacuum, high temperature, strong electromagnetic, and high-precision continuous production environments. Its reliability is directly related to the yield and stability of the production line. During equipment operation, the fault signals are often weak, the noise is strong, and the working conditions are variable, so traditional methods are difficult to achieve high-precision recognition. To solve this problem, this paper proposes a fault diagnosis and health monitoring method for semiconductor manufacturing equipment based on deep learning and subspace transfer. Firstly, considering the cyclostationary characteristics of the operating signals of key equipment, the cyclic spectral analysis technology is used to obtain the cyclic spectral coherence map, which effectively reveals the feature differences under different health states. Then, a deep fault diagnosis model based on the convolutional neural network (CNN) is constructed to extract deep feature representations. Furthermore, the subspace transfer learning technology is introduced, and group normalization and correlation alignment unsupervised adaptation layers are designed to achieve automatic alignment and enhancement of the statistical characteristics of deep features between the source domain and the target domain, which effectively improves the generalization and adaptability of the model. Finally, simulation experiments based on the public bearing dataset verify that the proposed method has strong feature representation ability and high classification accuracy under different working conditions and different loads. Because the key components and experimental scenarios of semiconductor manufacturing equipment have similar signal characteristics, this method can be directly transferred to the early fault diagnosis and health monitoring of semiconductor production line equipment, which has important engineering application value. Full article

This study presents an integrated, open-source process simulation for converting agricultural biogas into high-purity liquid hydrogen using DWSIM (Distillation, Water, Separation and Inorganic Modules), an open-source sequential-modular simulator. The model simulates a farm-scale biogas feed and is optimised to enhance liquid hydrogen yield while reducing specific energy consumption under set operating conditions. The proposed model links biogas upgrading via dual pressure swing adsorption, steam–methane reforming, two-stage water–gas shift, hydrogen purification, and cryogenic liquefaction within a single optimisation framework. Using a representative farm-scale feed (103.7 kg h⁻¹ biogas containing 60 mol% CH₄), the optimised process produces 16.5 kg h⁻¹ of liquid hydrogen with 99.2% para-hydrogen purity while simultaneously capturing 104 kg h⁻¹ of CO₂ at 98% purity and 16 bar. Optimal operating conditions include SMR at 909 °C and 16 bar with a steam-to-carbon ratio of 3.0, followed by high- and low-temperature water–gas shifts at 413 °C and 210 °C, respectively. The overall cold-gas efficiency (LHV basis, excluding liquefaction electricity) reaches 78%, and the specific electricity demand for liquefaction is 32.4 kWh per kg of liquid hydrogen, which is consistent with reported values for small-scale hydrogen liquefiers. Sensitivity analysis over a methane content range of 40–75% confirms near-linear scalability of hydrogen output (R² = 0.998), demonstrating feedstock flexibility without re-parameterisation. The developed process in this work provides a transparent and extensible digital twin for early-stage design and optimisation of decentralised biogas-to-hydrogen systems. Using the open-source DWSIM platform ensures full transparency, reproducibility, and accessibility compared with proprietary simulators. Full article

In this work, a series of defective Co₃O₄ catalysts (Al@Co₃O₄₋x, x = 4, 6, 8 mmol/L, representing the NaOH concentration) were prepared by Al doping and NaOH etching via hydrothermal method for ethyl acetate degradation. The results indicated that the Al@Co₃O₄-6 catalyst presented the optimal catalytic performance for ethyl acetate degradation (T₉₀ = 207 °C). The results of many characterizations, such as X-ray diffraction (XRD), scanning electron microscope (SEM), Fourier transform infrared (FT-IR) spectra, Raman, and temperature-programmed H₂ reduction (H₂-TPR), etc., showed that the Al doping and NaOH etching induced the production of defects and oxygen vacancies in the catalyst, improved the surface area, boosted the low-temperature reducibility, and promoted the low-temperature oxygen species desorption, which enhanced ethyl acetate oxidation over Al@Co₃O₄-6. Importantly, the possible ethyl acetate degradation pathway was revealed by in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), in the sense that the adsorbed ethyl acetate was gradually oxidized to ethanol and acetaldehyde, acetic acid, formate, and finally to CO₂ and H₂O. Full article

Combining with the wheel–rail rolling contact models and extended finite element method (XFEM), this study systematically analyses the influence of wheel thermal expansion induced by braking thermal load on the tread cracking behavior of railway freight trains during the emergency braking process. Unlike the well-documented effect of material softening at elevated temperatures, the key contribution of this work lies in identifying and elucidating the dominant role of thermally induced geometrical changes in the contact conditions. The results demonstrate that wheel thermal expansion significantly alters the shape of the contact spot and the stress distribution, thereby reconstructing the mechanical driving force at the crack tip. Specifically, thermal expansion effectively suppresses Mode I cracking. Although it slightly reduces the magnitude of ΔK_II, the primary and critical outcome is a distinct shift in the location of the maximum ΔK_II from the deep interior of the crack to its superficial outer tip, driven by the altered contact geometry. This shift intensifies the crack propagation trend along the length direction near the surface. Therefore, although the nominal contact stress decreases when considering braking heat, the risk of surface-initiated damage increases, which needs to be paid attention to during operations and maintenance. Full article

Bio-based bismaleimide (BMI) resins can reduce environmental impact and impart intrinsic flame retardancy, but achieving a high glass transition temperature (Tg) remains challenging. Here, we replace the conventional petrochemical co-monomer O,O′-diallyl bisphenol A (DABPA) with a synthesized tri-allyl derivative of curcumin (AEC) in 4,4′-bismaleimidodiphenylmethane (BDM)-based resins. The AEC monomer, synthesized via exhaustive O- and C-alkylation of curcumin, acts as a trifunctional crosslinker. By systematically varying the imide:allyl molar ratio, we optimized the network properties. We optimize the network’s thermal and fire-safety properties. The optimized formulation (BDM: AEC = 1:0.87, denoted BA-0.87) yields 43.06% char at 800 °C and reduces the peak heat release rate (PHRR) by 13.2% compared to the conventional BDM/DABPA control (BD-0.87). Meanwhile, BA-0.87 passes UL-94 V-0 with no dripping and attains a Tg above 400 °C—nearly 100 °C higher than BD-0.87. These enhancements arise from curcumin’s rigid conjugated structure, which increases crosslink density and promotes char formation during decomposition. Our work demonstrates a viable, bio-derived pathway to engineer BMI resins that simultaneously improve thermal stability and intrinsic flame retardancy. Such resins are promising for demanding aerospace and high-temperature electronic applications that require both fire safety and stability. Full article

Thallium is one of the most toxic elements on the planet, and one alternative method for its precipitation is through jarosite-type compounds. Therefore, in this work, the kinetics of thallium jarosite were evaluated in an alkaline medium (NaOH and Ca(OH)₂). Experiments were conducted to assess the effect of medium concentration from 0.03 M to 5.5 × 10⁻⁴ M and the effect of temperature from 20 °C to 60 °C. The sigmoidal curves showed an induction period, during which there was no release of sulfur or thallium ions into the solution, nor the formation of solid byproducts, according to the X ray diffraction (XRD) results. Similarly, a progressive conversion period was observed, evidenced by the release of sulfur and thallium ions into the solution and the formation of amorphous solids. Finally, a stability zone is reached, indicating that the decomposition reaction has ended, as there are no changes in the concentration of sulfur and thallium ions in the solution. The reaction was monitored by determining S using Inductively Coupled Plasma (ICP). The experimental results for the progressive conversion period show a better fit to the chemically controlled shrinking core kinetic model. The reaction order for the kinetics in NaOH medium is 1.09 for the induction period and 0.89 for the progressive conversion period, while for Ca(OH)₂ medium it is 0.78 for the induction period and 0.47 for the progressive conversion period. The activation energies for the progressive conversion period in the two proposed media are 91.87 kJ mol⁻¹ in NaOH and 71.14 kJ mol⁻¹ in Ca(OH)₂, indicating that the controlling mechanism in both systems is the chemical reaction. For the induction period, the activation energies are 101.52 kJ mol⁻¹ and 79.45 kJ mol⁻¹, respectively, indicating that the chemical reaction also controls the initiation of the reactions. The high activation energy in both reaction media suggests that high concentrations of OH⁻ and high temperatures are required to initiate the decomposition reaction. Thallium jarosite precipitates a large amount of thallium and requires high energy to decompose, so it could be a viable alternative in thallium retention. Full article

This study addresses the issue of missing basic data and insufficient accuracy in predicting runoff and non-point-source pollution in the Heilongjiang region of China using the Soil and Water Assessment Tool (SWAT) model. Based on the China Ground Climate Data Daily Dataset (V3.0) and SPAW soil characteristic calculation formula, and assisted by the Python V3.0 language for data processing and computation, new high-precision weather generators and soil attribute databases suitable for the Heilongjiang region of China were established. The weather generator is based on daily data and contains detailed meteorological parameters such as temperature, humidity, wind speed, rainfall, etc., used to characterize the periodic changes in meteorological elements. And the differences and fluctuations outside this change curve were also retained in the basic construction of the weather generator. The soil database covers various parameters, such as soil type, texture, structure, nutrient content, organic matter content, etc., enabling the SWAT model to better simulate hydrological and pollutant transport processes in the soil. Additionally, point-source input data, including various industrial and domestic wastewater discharge situations, were collected and organized to improve data quality. Furthermore, a series of agricultural management measures were developed based on the use of fertilizers and pesticides for simulation, providing an important basis for analyzing non-point-source pollution using the SWAT model. By comparing the different results of the simulation using optimized databases, it is shown that the above work improved the simulation accuracy of the SWAT model in predicting runoff and pollution load in Heilongjiang, China. The NSE of runoff simulation increased from 0.923 to 0.988, and the NSE of ammonia nitrogen and CBOD simulation increased from 0.852 and 0.758 to 0.930 and 0.902, respectively. It is expected that these efforts will provide strong data support for subsequent research and provide a theoretical basis for government decision-makers to build scientifically rigorous and effective pollution control strategies. Full article

This study presents a techno-economic assessment of a modular, solar-assisted methane pyrolysis pilot plant designed for sustainable hydrogen production in Nigeria using concentrated solar power (CSP). Driven by the need to convert flare gas into value and reduce emissions, the work evaluates a hypothetical 100 kg/day hydrogen system by integrating a methane pyrolysis reactor with a solar heliostat–receiver field. Process modelling was carried out in DWSIM, while solar concentration behavior was represented using Tonatiuh. The mass–energy balance results show a hydrogen output of 3.95 kg/h accompanied by 12.30 kg/h of carbon black, with the reactor demanding roughly 44 kW of high-temperature heat at 900 °C. The total capital cost of the ≈50 kW pilot plant is approximately USD 1.5 million, with heliostat and receiver technologies forming the bulk of the investment. Annual operating costs are estimated at USD 69,580, alongside feedstock expenses of USD 43,566. Using annualized cost and discounted cash flow approaches, the resulting levelized cost of hydrogen (LCOH) is USD 5.87/kg, which is competitive with off-grid electrolysis in the region, though still above blue and gray hydrogen benchmarks. The results indicate that hydrogen cost is primarily driven by solar field capital expenditure and carbon by-product valorization. Financial indicators reveal a positive NPV, a 13% IRR, and a 13-year discounted payback period, highlighting the promise of solar-assisted methane pyrolysis as a transitional hydrogen pathway for Nigeria. Full article

Stimuli-responsive hydrogels are an emerging class of smart materials with immense potential across biomedical engineering, soft robotics, environmental systems, and advanced manufacturing. In this review, we present an in-depth exploration of their material design, classification, fabrication strategies, and real-world applications. We examine how a wide range of external stimuli—such as temperature, pH, moisture, ions, electricity, magnetism, redox conditions, and light—interact with polymer composition and crosslinking chemistry to shape the responsive behavior of hydrogels. Special attention is given to the growing field of 4D printing, where time-dependent shape and property changes enable dynamic, programmable systems. Unlike existing reviews that often treat materials, stimuli, or applications in isolation, this work introduces a multidimensional comparative framework that connects stimulus-response behavior with fabrication techniques and end-use domains. We also highlight key challenges that limit practical deployment—including mechanical fragility, slow actuation, and scale-up difficulties—and outline engineering solutions such as hybrid material design, anisotropic structuring, and multi-stimuli integration. Our aim is to offer a forward-looking perspective that bridges material innovation with functional design, serving as a resource for researchers and engineers working to develop next-generation adaptive systems. Full article

Superabsorbent polymers (SAPs) are materials that can absorb and retain water solutions with a mass of several hundred times greater than their own. This work aimed to synthesise and evaluate the effects of highly absorbent starch phosphate-g-poly(acrylic acid) copolymers on the microbiological activity of soils previously used for agriculture. The biopolymers studied were obtained by thermal and chemical oxidation of starch phosphates and copolymerized with potassium salts of acrylic acid. Basic physicochemical parameters were determined in the applied soil. Following SAP application, the basal respiration rate was measured at 22 °C with a constant soil moisture content of 60% WHC. The incubation time in constant temperature and moisture conditions was 78 days. After this period, their microbiological activity (microbial and organic phosphorus fractions) was assessed, thereby enabling the determination of the direction of change in the soil environment. The addition of SAP increases the soil’s water-holding capacity and respiration. The SP-g-PAA polymers serve as slow-release sources of potassium and phosphorus ions. These elements were bound to the polymer network by ionic and covalent bonds. Analysis of the results shows that within two weeks, 47–80% of the starch hydrogel undergoes microbial degradation. No differences were found in the content of labile forms of phosphorus in soils with SAP additions compared to soils without polymer additions. The use of modified starch reduces the consumption of vinyl monomers, while the resulting product is characterised by high absorbency and low water content, which reduces the amount of energy needed to obtain the finished product, thus contributing to sustainable development. Full article

This paper presents Sem4EDA, an ontology-driven and rule-based framework for automated fault diagnosis and energy-aware optimization in Electronic Design Automation (EDA) and Internet of Things (IoT) environments. The escalating complexity of modern hardware systems, particularly within IoT and embedded domains, presents formidable challenges for traditional EDA methodologies. While EDA tools excel at design and simulation, they often operate as siloed applications, lacking the semantic context necessary for intelligent fault diagnosis and system-level optimization. Sem4EDA addresses this gap by providing a comprehensive ontological framework developed in OWL 2, creating a unified, machine-interpretable model of hardware components, EDA design processes, fault modalities, and IoT operational contexts. We present a rule-based reasoning system implemented through SPARQL queries, which operates atop this knowledge base to automate the detection of complex faults such as timing violations, power inefficiencies, and thermal issues. A detailed case study, conducted via a large-scale trace-driven co-simulation of a smart city environment, demonstrates the framework’s practical efficacy: by analyzing simulated temperature sensor telemetry and Field-Programmable Gate Array (FPGA) configurations, Sem4EDA identified specific energy inefficiencies and overheating risks, leading to actionable optimization strategies that resulted in a 23.7% reduction in power consumption and 15.6% decrease in operating temperature for the modeled sensor cluster. This work establishes a foundational step towards more autonomous, resilient, and semantically-aware hardware design and management systems. Full article