Search Results (2,983)

Tri-reforming of methane (TRM) has emerged as a promising pathway for low-carbon syngas production by integrating steam reforming, dry reforming, and partial oxidation within a single process. This coupling enables simultaneous CH₄ utilization and CO₂ valorization while enabling internal heat generation and flexible adjustment of the H₂/CO ratio for downstream synthesis. However, TRM performance cannot be adequately evaluated using conversion or energy efficiency alone, because the process involves complex interactions among competing reaction pathways, transport phenomena, catalyst stability, and thermodynamic irreversibility. This review provides a multiscale critical assessment of TRM from both first-law energy and second-law exergy perspectives, linking reaction-network fundamentals to reactor-level behavior and system-level performance. The literature evidence shows that although high temperatures and near-autothermal operation can enhance CH₄ conversion and reduce external heat demand, these conditions may simultaneously intensify deep oxidation, hotspot formation, carbon-forming tendencies, and exergy destruction. While equilibrium analyses help define feasible operating windows, they are insufficient without kinetic modeling and reactor-scale studies that capture spatial non-uniformities and pathway competition. Across reported TRM systems, exergy destruction is consistently concentrated within the reformer, identifying the reacting core as the dominant thermodynamic bottleneck. Accordingly, the key challenge in TRM is not simply to maximize conversion but to preserve chemical work potential while maintaining syngas quality and operational stability. Viewed from this perspective, TRM is better understood as an irreversibility-aware multiscale design problem in which optimal performance depends on the integrated optimization of catalyst functionality, reactor architecture, heat management, and system-level operation. Full article

Although interior-point methods (IPMs) have transformed mathematical programming since 1984, the original projective Karmarkar algorithm is rarely documented step by step on reproducible engineering examples that combine algorithmic transparency with real resource allocation constraints. This article therefore does not propose a new variant of Karmarkar’s algorithm; rather, its scientific contribution is the reproducible MATLAB implementation, canonical-form conversion, and comparative validation of the original projective method against the revised Simplex method and Barnes’ affine scaling variant in two engineering settings. The case studies are (i) the minimum-weight plastic design of a rigid frame with seven candidate plastic hinge locations and six collapse mechanisms and (ii) the optimal allocation of crop patterns in the Caplina Valley (Tacna, Southern Peru), an arid irrigated system with an irrigated command area of 1253 ha, monthly labor availability of 22,239 jornales, and water availability derived from Caplina River discharges at 75% persistence. For Case I, the algorithm reached F = 1.001 in the normalized dual space, which corresponds to F = 4.251 in the original structural objective after applying the scaling factor 17/4; relative to the analytical optimum F* = 4.25, this gives |4.251 − 4.25|/4.25 = 2.4 × 10⁻⁴ after 20 iterations. For Case II, the model yielded the maximum net production value of USD 703,135.92, allocating 948.47 ha among 12 crops while satisfying water, labor, market, and land constraints. The double validation confirms the algorithm’s strictly interior trajectory, polynomial-time rationale, and transparent internal parameters (α = 0.7968, ε = 10⁻⁸), making the implementation a reproducible benchmark for educational use and for future AI–operations research hybrid solvers in regions with limited access to commercial optimization software. Full article

Tool wear significantly impacts the productivity and efficiency of sheet metal stamping operations, particularly in high-volume progressive die applications. This study presents an iterative calibration framework for Archard’s wear model, tailored to industrial stamping processes. The proposed methodology integrates finite element simulations with experimentally measured wear data obtained from production components, enabling data-driven calibration of the wear coefficient $K_{sim}$. The framework achieves high predictive accuracy, with deviations of 1.4–3.7% between simulated and optically measured wear depths and localization, after more than 15 million strokes. Rapid convergence is obtained within two to three calibration cycles, significantly reducing computational effort while maintaining physical fidelity. The simulation setup incorporates detailed modelling of contact pressure, sliding velocity, and stress distribution, validated using optical surface measurement systems and coordinate-based metrology. Beyond the specific industrial case, the framework demonstrates transferability to other sheet metal forming processes, such as bending, blanking, and coining, by leveraging physically based parameter adaptation across comparable pressure–velocity regimes. The approach enables predictive wear modeling in data-scarce environments and supports early-stage tool design workflows. Overall, the proposed methodology bridges the gap between empirical calibration and generalized simulation, contributing both methodological rigour and practical applicability to manufacturing science. Full article

In precision gear manufacturing, longitudinal crowning on tooth flanks is commonly produced by applying diagonal feed in worm-type generating processes using tools such as variable-tooth-thickness hobs and dressable grinding worms. However, precise twist control remains difficult because the geometric parameters of the generating tool are strongly coupled with the machine feed settings in the underlying generating kinematics. In addition, direct numerical optimization becomes unreliable near the standard tool state, where the sensitivity of the diagonal-feed coefficient degenerates and conventional linearized solvers may lose effectiveness. To address these issues, this study proposes a multi-variable optimization framework for twist-constrained worm-type gear generation. An iterative singular value decomposition (SVD) scheme is developed to construct and update the sensitivity matrix, while a warm-start continuation strategy is introduced to overcome the local singularity and improve numerical robustness. Two closed-form expressions for the diagonal-feed coefficient are also proposed as practically useful initial estimates, corresponding respectively to the minimum SVD topographic residual and the minimum tooth-flank twist. Numerical validation over a 60-case parameter sweep shows maximum relative errors below 1.6% within the tested range. The proposed framework coordinates the tool-geometry design and diagonal-feed selection to generate tooth flanks with prescribed crowning characteristics while satisfying a specified twist requirement and limiting the required diagonal shift. Numerical examples show that the iterative framework reduces the root-mean-square (RMS) topographic error from 1.14 μm to 0.027 μm relative to the analytical setting of Hsu and Fong. These results indicate that the proposed method provides a reliable computational basis for twist control and process-parameter design in advanced CNC gear generation. From a manufacturing standpoint, because the three design criteria are accessed by adjusting only the diagonal-feed ratio on the machine, a single generating-tool design can serve a range of crowning and twist requirements without retooling, reducing setup and tooling efforts in production. Full article

For agricultural films, spectral matching, UV protection, and environmental durability are essential for efficient crop production. A self-cleaning silane-crosslinked red/blue dual-emission carbon dot/polyvinyl alcohol composite film (KH/RB-CQDs/PVA) was fabricated via a covalent anchoring strategy. RB-CQDs were synthesized by a two-step hydrothermal method using o-phenylenediamine: initial blue-emitting carbon cores formed, then phosphoric acid-assisted secondary treatment covalently bridged residual precursor-derived red fluorophores onto cores through pyrophosphate bonds, as evidenced by TEM, XPS, ³¹P NMR, HPLC-MS and DFT. This rigid bridging suppressed excessive core growth and energy transfer while spatially separating dual emission, endowing excellent photostability (>95% fluorescence retention after 50 min UV and 30 d storage). Subsequently, KH-560 was employed to construct a robust covalent crosslinked network anchoring RB-CQDs in PVA and forming rough Si-O-Si surface structures, confirmed by SEM and XPS. The resulting film exhibited 16.16% quantum yield, 291% tensile strength enhancement, 95% UV shielding, and <1% contaminant residue. Chlorophyll fluorescence kinetics, gas-exchange analyses, and photosynthetic response curves demonstrated that KH/RB-CQDs/PVA increased the potato net photosynthetic rate by 55.46% and tuber yield by 76% through synergistic optimization of photosystem II electron transport and RuBisCO-mediated carbon assimilation. This work provides a molecular design principle for high-performance intelligent agricultural films. Full article

Hydrogenation reactor shells are safety-critical thick-section pressure-bearing components in petrochemical hydroprocessing equipment. Long-term exposure to elevated temperature, high pressure, and hydrogen-bearing media requires not only adequate strength, but also toughness, tempering stability, hydrogen-damage resistance, and through-thickness property uniformity. 12Cr2Mo1V steel, a Chinese Cr-Mo-V reactor steel closely related to vanadium-modified 2.25Cr-1Mo-0.25V steels, is widely used for large-shell forgings because its alloy design supports bainitic transformation, carbide stability, and elevated-temperature performance. This review critically synthesizes studies on 12Cr2Mo1V shell forgings, related Cr-Mo-V reactor steels, and heavy free-forged products. The discussion is organized around alloy design, ingot-derived defect inheritance, defect closure during free forging, bainite–grain–carbide evolution during forging and heat treatment, and the resulting strength, toughness, and hydrogen-service performance. Particular emphasis is placed on the process–defect–microstructure–property linkage in super-thick sections. The review shows that free forging is not merely a forming route, but a decisive metallurgical operation for densification, strain penetration, and precursor-structure conditioning. Future work should integrate casting, free forging, and heat treatment with multiscale characterization and data-enhanced predictive quality control. To further reduce descriptive comparison, this review summarizes standardized quantitative indicators for evaluating forging-route design, heat-treatment response, and prediction-method reliability. Full article

The quantitative prediction of the equilibrium gibbsite content in alkaline liquors of alumina production is a key parameter for controlling precipitation kinetics and ensuring product quality. Unlike Bayer alumina refineries, sintering alumina refineries use different alkali and impurity content ranges; moreover, they are characterized by the presence of significant amounts of potassium in aluminate liquors that are not considered in the existing gibbsite equilibrium models. This paper presents an extended mathematical model, which is based on the Rosenberg–Healey methodology and incorporates sodium (Na₂O) and potassium (K₂O) components into the total alkaline system. Model coefficients were optimized using 18 tests designed by the D-optimal method at temperatures of 50–85 °C and a total alkali content of [R₂O_k] = 40–80 g/L, which contains up to 30% of potassium alkali K₂O, as well as the impurities in the form of soda [Na₂CO₃] = 0–58 g/L and sodium sulfate [Na₂SO₄ ]= 0–25 g/L. The fine-tuned model was verified using the composition of actual refinery liquors and provides RMSE = 0.71 g/L Al₂O₃, thus demonstrating satisfactory solubility prediction accuracy. The presented model can be used to calculate aluminate liquor productivity at existing sintering refineries with a sodium–potassium system. Full article

Punching is a fundamental and extensively employed process in the field of cold forming, prized for its operational simplicity, high performance, and ability to produce components of superior quality. However, the process is inherently complex, as the selection of optimal punching parameters remains a challenging endeavor. Achieving a high-quality punched product is critically dependent on the precise and validated choice of these parameters, which directly influence the mechanical and geometrical integrity of the final component. In this study, the shear zone height, a key indicator of punched part quality, is systematically investigated. The finite element method (FEM), integrated with the Johnson-Cook material model, is employed to simulate and analyze the influence of various punching parameters on the shear zone height, with particular emphasis on the effect of different punch shaft shapes. The Johnson-Cook model, renowned for its accuracy in capturing material behavior under high strain rates and temperatures, enables a robust and reliable simulation framework. The results of this investigation reveal that punch tools featuring a pointed shaft shape exhibit an almost constant distribution of shear zone height across a range of punching parameters. This consistency suggests that such designs are less sensitive to parameter variations, thereby offering a more stable and predictable performance. Consequently, the pointed punch shape is identified as the optimal configuration for achieving superior punched part quality, minimizing defects, and enhancing process reliability. This work contributes to the advancement of cold forming technology by providing insights into the relationship between punch geometry and shear zone characteristics, ultimately facilitating the selection of punching parameters for improved product quality and process efficiency. Full article

Background: Overexpression of immune cell populations leads to self-amplifying cytokine loops, contributing to chronic inflammation in both allograft rejection and autoimmune conditions. Tacrolimus (TAC), despite being a potent immunosuppressant, has limitations; its systemic adverse effects include nephrotoxicity, neurotoxicity, and high variability in tissue exposure in patients. Currently available therapeutic options are limited by the lack of targeted and localized drug delivery systems, resulting in ineffective control over drug-release behavior. Moreover, TAC being highly lipophilic poses challenges for formulation development. To address these gaps, this study focuses on developing a thermoresponsive hydrogel platform comprising distinct nanocarriers for localized delivery of TAC. The nanocarriers include nanoemulsion (NE) and micelles as TAC carriers, and their particle sizes are specifically engineered at the nanoscale for differential release behavior and to support immune cell targeting (macrophages and T-cells). Incorporation into a thermoresponsive hydrogel matrix enables it to act as a local depot at the injection site and deliver TAC with a slow, extended-release profile. Methods: TAC was loaded into a coconut-rich lipid-phase-based NE via high-pressure microfluidization. Simultaneously, TAC-loaded micelles were optimized using a full-factorial design of experiments (DoE) and manufactured via the thin-film hydration method. Both nanocarriers were evaluated for long-term colloidal stability assessments. Hydrogels were produced maintaining aseptic conditions for sterile batch production. Rheological characterization was performed to assess sol-gel transition, thermoreversibility, and injectability, and in vitro release studies were conducted to evaluate TAC diffusion from the developed nanoformulations. Results: Developed nanocarriers resulted in distinct particle sizes in NE (80–85 nm) and micelles (15–17 nm) with successful TAC loading maintaining long-term colloidal stability. The developed TAC-loaded dual-nanocarrier hydrogel (Dual-HG) showed thermoresponsive behavior and gelation at 37 °C, forming as a local depot. In vitro release studies showed slow and extended tacrolimus release from hydrogels and demonstrated particle size-dependent release behavior between the NE and micelle. Conclusions: Therefore, our study highlights a novel dual nanocarrier hydrogel platform combining TAC-NE and TAC-micelle for localized delivery. The findings support that nanocarriers can be engineered to modulate drug diffusion behavior. Notably, the dual nanocarrier within a thermoresponsive hydrogel platform can be used to deliver one or multiple drugs locally, minimizing systemic exposure when sustained local immunosuppression is required. The 25 mL scale sterile batch production of hydrogels emphasizes their suitability for future translational applications. Full article

Developing high-quality and reliable solver code for the job shop scheduling problem (JSSP) remains a challenging and expertise-intensive task because generated code must stay executable, produce feasible schedules, and achieve strong scheduling results. This paper proposes a large language model (LLM)-driven multi-agent evolution framework for scheduling solver code generation, where LLMs act as hyper-heuristics for program-space search under external evaluation. The framework forms a closed-loop process with three collaborating agents. A seed heuristic generation agent uses a structured constraint template and a shared solver skeleton to synthesize, screen, and diversify seed programs to construct a competitive initial code pool. An evolutionary operator agent updates the pool through program-space crossover and best-so-far mutation. A code reflection agent analyzes solver code and maintains trajectory-aware reflective memory to generate structured guidance for later revision. Experiments on standard JSSP benchmarks show that the framework outperforms representative metaheuristics across heterogeneous instance families and scales while reaching best-known reference quality on a subset of instances. Ablation results further confirm the contributions of the initialization design and the reflection-guided revision mechanism. More broadly, the proposed framework helps reduce manual heuristic design effort and offers a practical approach to production scheduling optimization in intelligent manufacturing environments. Full article

Research and development of novel CO₂-selective membranes, called molecular gate membranes (MGMs), has been conducted. Unlike conventional CO₂-selective membranes, MGMs show exceptionally high CO₂ separation over H₂. The membranes and the membrane modules were developed for CO₂ separation at low energy consumption and low cost in pre-combustion processes such as integrated gasification combined cycle (IGCC) and hydrogen production. To date, two candidate membrane materials—poly(ethylene glycol) (PEG)-based and poly(vinyl alcohol) (PVA)-based membranes—have been used. As for PEG-based membrane materials, the effect of operating conditions, such as relative humidity in feed gas and sweep gas and operating pressure, on CO₂ separation performance were investigated. Both CO₂ permeance and selectivity increased with increasing relative humidity on both the feed and permeate sides. The CO₂ permeance increased from the 10⁻¹² to the 10⁻¹¹ order, while the selectivity increased from 2.8 to 25. In addition, it was found that the water vapor permeates from the high to the low relative humidity side with a permeance typically on the order of 10⁻⁸ m³(STP)m⁻²·s⁻¹·Pa⁻¹, regardless of the total pressure difference between the feed side and the permeate side. This finding is important in the design of membrane systems. However, we found that PVA-based membranes exhibited superior thin-film coating ability and higher separation performance compared with PEG-based membranes. As for PVA-based materials, membranes that showed high CO₂ separation performance under high-pressure conditions of 2.4 MPa (the supposed pressure in the IGCC process) were successfully prepared. In addition, the technology to prepare MGMs with a large membrane area was developed by a continuous membrane-forming method, and the membrane elements (diameter: 10–20 cm; length: 20–60 cm) were also fabricated. Pre-combustion CO₂ capture tests of the membrane elements were conducted using coal-derived gasification gas, and it was confirmed that the membrane elements were durable against the real gas, which contained components such as H₂S (on the order of 100 ppm) and CO (32.4%). Full article

Magnesium hydroxide is attracting growing interest as a versatile, halogen-free flame retardant, and this review surveys its production routes, structure–property relationships and use in polymer systems from commodity polyolefins to advanced bio-based materials. Industrial Mg(OH)₂ is still predominantly obtained from mining or hydration of MgO, but increasing attention is being devoted to recovery from seawater and saltwork brines, where precipitation from Mg²⁺-rich streams followed by controlled rehydration or direct precipitation yields fine, high-purity powders suitable for flame retardant use and simultaneously valorizes saline wastes. In parallel, hydrothermal synthesis has been extensively explored to tailor particle size and morphology by adjusting the precursor, solvent, temperature and time, enabling high-surface-area Mg(OH)₂ or MgO with narrow size distributions that are attractive for high-performance composites also evaluated via ball milling, crushing and refining. More recently, process intensification strategies such as microwaves and ultrasounds have been proposed to shorten reaction times, lower temperatures and better control nucleation and growth, opening paths toward energy efficient production of structured Mg(OH)₂ from both conventional and brine-derived precursors. The second part of the review analyzes how the intrinsic endothermic decomposition and basic character of Mg(OH)₂ can be utilized across a broad range of polymer matrices and how surface functionalization strategies extend its applicability. In addition to “as received” powders, stearic acid and other fatty acids, metal soaps and various organic coupling agents are widely used to render the surface more hydrophobic, enhance dispersion and interfacial adhesion, and in some cases introduce additional char-forming or barrier functionality. In terms of the application, the review methodically synthesizes and contrasts fire and mechanical data for Mg(OH)₂-containing polyolefins (HDPE, LLDPE, PP and EVA) utilized in cables and building products, expandable polymers and foams, biopolymers (PLA and PBS), and elastomers. The review places particular emphasis on the balance between loading level, processability, flame performance and mechanical integrity. This review aims to provide a comprehensive framework for designing next-generation Mg(OH)₂-based flame-retardant systems for both conventional and emerging polymer technologies. To this end, it integrates advances in sustainable feedstocks, controlled synthesis and surface engineering with the rapidly expanding application space. Full article

Driven by China’s “dual carbon” (carbon peak and carbon neutrality) goals and the national strategy of new-type urbanization, prefabricated construction has emerged as a pivotal pathway toward industrialized and sustainable development in the construction sector—leveraging its distinctive advantages in construction efficiency, cost optimization, environmental performance, and design adaptability. Nevertheless, the inherently sequential and interdependent nature of the full construction process—encompassing off-site component manufacturing, logistics transportation, and on-site assembly—introduces pronounced cross-stage risk transmission mechanisms, with prefabricated components serving as critical risk carriers. Such transmission dynamics significantly impede the scalable and safe deployment of prefabricated construction. To date, scholarly efforts on construction safety in prefabricated buildings have predominantly addressed isolated, stage-specific risks, falling short in quantitatively modeling the coupled propagation of risks across stages, accommodating epistemic uncertainties and latent (i.e., unknown or unobserved) risks, and informing targeted, evidence-based mitigation strategies. To bridge this gap, this study develops a rigorous quantitative framework for assessing cross-stage risk transmission in prefabricated construction safety. Specifically, it aims to (i) uncover the structural patterns and driving mechanisms underlying inter-stage risk propagation; (ii) reduce the likelihood of safety incidents throughout the construction life cycle; and (iii) deliver actionable theoretical insights and methodological guidance for practitioners and policymakers. Methodologically, we first conduct a systematic identification of safety-critical risk factors and establish a hierarchical risk indicator system comprising three first-level dimensions and twenty second-level indicators. Second, using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, causal relationships among risk factors are clarified, while incorporating the Leaky Noisy-or Gate (LNOG) extended model to account for unknown risks. Risk data are processed using triangular fuzzy functions, and a Bayesian network (BN) topology diagram is constructed via the GeNIe 5.0 platform, forming a DEMATEL-LNOG-BN-based model for assessing cross-phase risk transmission. Finally, applying the model to an actual project—”a prefabricated construction project in Shanghai”—the study conducts a cross-phase risk transmission analysis. Through forward probability inference, backward causality tracing, sensitivity analysis, and pathway decomposition, sensitivity comparisons are performed under different LNOG unknown risk parameters. Results are compared with those from the traditional DEMATEL-BN model to validate the stability and consistency of high-sensitivity risk factor identification, comprehensively verifying the applicability and predictive reliability of the proposed DEMATEL-LNOG-BN model. The study quantitatively reveals the progressive diffusion and amplification mechanisms of risks across the production–transportation–assembly process, providing scientific support and practical reference for precise safety risk prevention, critical node control, and the optimization of management systems in prefabricated construction sites. Full article

The submitted paper focuses on linking recycled material processing with digital technologies for monitoring and managing production processes in the context of Industry 4.0 principles. Despite the rapid development of additive manufacturing and Industry 4.0 technologies, limited attention has been devoted to the integration of sustainable recycled materials with real-time digital monitoring and structured manufacturing data management. Existing studies often address either recycled materials or digital process monitoring separately, while their combined implementation in additive manufacturing environments remains insufficiently explored. The introductory part highlights polyvinyl butyral (PVB) recovered from post-consumer laminated glass and its potential application in additive manufacturing. The theoretical section provides an overview of current knowledge in the fields of additive manufacturing, circular economy, production, and digitization, forming a foundation for the practical part of the research. The practical section focuses on the design and implementation of a data collection system for additive manufacturing processes, enabling the real-time digital monitoring and evaluation of selected technological parameters. Previous research conducted by the authors addressed the preparation of recycled PVB filament; however, commercially available PVB filament was used in the present experimental study due to the limited laboratory-scale production capacity of recycled filament. Full article

Long-acting injectables (LAIs) are widely used for chronic conditions such as schizophrenia, opioid use disorder, and HIV. Their prolonged efficacy improves adherence and reduces dosing frequency. Among these systems, poly(lactide-co-glycolide) (PLGA)-based formulations are commonly used to deliver drugs ranging from small molecules to peptides and proteins. In vitro release (IVR) tests play a critical role in evaluating drug product performance for both immediate- and prolonged-release dosage forms. However, there is a lack of standardized compendial IVR methods for the assessment of LAIs. This lack impedes the development of new drug products in this area and also complicates their regulatory approval process. Considering the complexity of drug release mechanisms and the diversity of various formulation design approaches, it is not possible to devise a universal IVR method that is applicable to all LAI products. The in vitro release test applied for quality control should be simple, robust, reproducible, and discriminatory. On the other hand, more complex biorelevant media and methods are often used during development to better reflect physiological conditions. This article provides a comprehensive review of compendial and non-compendial methods used for in vitro release testing of PLGA-based LAIs (microspheres and in situ forming implants), with the goal of aiding the development and standardization of future methodologies. Full article