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This document discusses the importance of carbon reduction engineering in combating global climate change. It highlights the role of production and supply chain management in achieving carbon neutrality and reducing carbon emissions. The document presents 20 selected research papers that cover various aspects of production optimization in carbon reduction engineering, including carbon reduction in the production process, low-carbon and sustainable supply chains, assessment and optimization methodologies, and policy instruments. The papers provide insights into topics such as scheduling optimization, renewable energy production, carbon emission efficiency, sustainable consumption, government subsidizing arrangements, and the impact of policy instruments on carbon reduction. The document expresses gratitude to the authors and reviewers for their contributions and acknowledges the support of the International Journal of Production Research. [Extracted from the article]

This research examines the transformative potential of artificial intelligence (AI) in general and Generative AI (GAI) in particular in supply chain and operations management (SCOM). Through the lens of the resource-based view and based on key AI capabilities such as learning, perception, prediction, interaction, adaptation, and reasoning, we explore how AI and GAI can impact 13 distinct SCOM decision-making areas. These areas include but are not limited to demand forecasting, inventory management, supply chain design, and risk management. With its outcomes, this study provides a comprehensive understanding of AI and GAI's functionality and applications in the SCOM context, offering a practical framework for both practitioners and researchers. The proposed framework systematically identifies where and how AI and GAI can be applied in SCOM, focussing on decision-making enhancement, process optimisation, investment prioritisation, and skills development. Managers can use it as a guidance to evaluate their operational processes and identify areas where AI and GAI can deliver improved efficiency, accuracy, resilience, and overall effectiveness. The research underscores that AI and GAI, with their multifaceted capabilities and applications, open a revolutionary potential and substantial implications for future SCOM practices, innovations, and research. [ABSTRACT FROM AUTHOR]

This paper presents a novel solution approach for a variant of the job shop scheduling problem with machine unavailability due to both condition-based preventive maintenance and corrective maintenance following random breakdowns. We first provide an exact mathematical formulation of the problem under simplifying assumptions, namely that the number of breakdowns for each job position on each machine is known, the degradation rates are fixed, and the preventive and corrective maintenance durations are deterministic parameters. Moreover, to handle the more realistic case of stochastic machine degradation, random breakdowns, and uncertain maintenance durations, a simulation-optimisation algorithm is proposed. The real makespan function is first approximated using multiple surrogate measures, which are optimised through independent genetic algorithms. Then, the fittest solutions obtained from these surrogate measures are simulated, and the best among them is added to an elite list, which is included in the genetic algorithms' populations for the next iteration. Schedule robustness is ensured by using an objective function that consists of the weighted average of the expected makespan and its 90th percentile. Furthermore, to reduce the likelihood of falling into a local optimum, a stopping criterion based on simulated annealing is implemented. Numerical experimentation on extended benchmark instances confirmed the validity of the mathematical formulation and the favourable performance of the proposed simulation-optimisation algorithm in terms of computational time and solution quality. [ABSTRACT FROM AUTHOR]

Combined heat and power economic dispatch (CHPED) is one of the foremost subjects in the operation of power systems. In this article, a new variant of cuckoo search (CS) algorithm, elitist CS (yECS), is advanced to tackle CHPED. During the optimisation process of the original CS as well as lots of its variants, the guidance of search directions relies merely upon the best individual, causing the loss of other beneficial information and further influencing their performance potentials. Therefore, in yECS, an elitist mechanism is developed to fully utilise the beneficial information of other elite individuals. Specifically, three new iterative strategies are developed, one for the global search phase and the other two for the local search phase. Further, a coordinated mechanism is put forward to effectively integrate the local iterative strategies, thus helping yECS in maintaining an appropriate balance between exploitation and exploration. The superior performance of yECS is firstly substantiated via CEC 2017 test suite and two engineering design problems and then it is utilised to address CHPED problems. All optimal dispatch results acquired by yECS are feasible and in most cases display remarkable improvements over the results determined by other CS variants and some recently-published literature results. [ABSTRACT FROM AUTHOR]

In recent years, the industry has demanded high hardness, wear resistance, corrosion resistance, and other properties for critical components made of steel and its alloys. Enhancing the surface properties of a part by applying modification techniques to its surface is considered to be an economical and efficient method. Laser hardening, as a new surface modification technology, has received more and more attention due to its high hardening efficiency, fast cooling rate, and excellent surface properties. Laser hardening technology has good application prospects in surface modification, and significant progress has been made in the exploration of laser hardening strengthening mechanisms, optimization of process parameters, high-quality preparation of hardened layers, and theoretical simulation. However, some problems need to be addressed in the practical application of the technology. This paper reviews the research progress of the laser surface hardening process for steel and its alloys, including numerical investigation, process optimization, hardening performance analysis, and external field-assisted laser hardening technology. It also discusses the problems and challenges faced by the technology and gives an outlook on its development trend. [ABSTRACT FROM AUTHOR]

In aerospace, optical instrumentation, new energy, life science, and other fields, a large number of core components need ultra-precision polishing to obtain a high-quality inner surface, but polishing quality and efficiency are difficult due to mutual constraints. In order to polish the inner surface under both high quality and efficiency, a new soft abrasive rotary jet polishing (SARJP) method and system are proposed. Based on the polishing method and system proposed in this paper, an integrated multi-objective optimization algorithm model based on CatBoost and AGE-MOEA is proposed to realize the multi-objective prediction and process optimization of the roughness and material removal rate of the inner surface of a circular tube by SARJP. The lowest average absolute percentage error of surface roughness is 3.73%, and the largest average absolute percentage error is 6.49%, according to a comparison of the multi-objective optimization forecast findings with the experimental results. The minimum average absolute percentage error in the material removal rate is 3.72%, and the maximum average absolute percentage error is 8.28%. The initial surface Ra value of the inner surface of the circular tube is reduced by 94.99% from 211.16 to 10.57 nm, and the maximum material removal rate is increased by 15.83% from 5.234 to 6.218 mg/min, showing the effectiveness of the algorithm for prediction and optimization. [ABSTRACT FROM AUTHOR]

Soil electrokinetics (SEK) research has been widely used in various fields such as soil remediation, dewatering, land restoration, geophysics, sedimentation, pollution prevention, consolidation, and seed germination. According to our most recent published research on SEK process design modifications during the last 30 years (1993–2022), more than 150 designs have been introduced to assure SEK's maximum performance. Incorporating lateral electrodes/anodes was not documented in the existing literature, which motivated us to investigate the output of this design. In this study, we aimed to enhance the performance of the perforated cathode pipe soil electrokinetic remediation (SEKR) system (PCPSS) for removing inorganic pollutants by installing lateral anodes (LA-PCPSS) using two approaches. In the first approach, the LA-PCPSS was connected to different sources of applied voltages (DSAV) from different power supplies, while in the second approach, the entire operation system was connected to the same source of applied voltage (SSAV). We used the Taguchi approach (L9OA) to determine the optimal levels of applied voltages for the DSAV system. The results indicated that the DSAV-(LA-PCPSS) could be optimized at an applied voltage of 1 V cm−1 for the surface and the first and second lateral anodes. The indigenous Sr (elements found in the tested soil without artificial pollution) in kaolinite showed the best response among other elements (Ni and other indigenous elements) when optimizing the DSAV-(LA-PCPSS) using the Taguchi approach. Installing lateral anodes (position B) supplied to low applied voltage (0.5 V cm−1) improved the electroosmosis (EO) rate/dewatering. Reverse migration of ions was observed during the remediation of real contaminated soil using the SSAV-(LA-PCPSS). The DSAV-(LA-PCPSS) is considered an appropriate design for the SEKR of inorganic pollutants, and increases the EO flow/dewatering. Additionally, the increased energy consumption employing the DSAV-(LA-PCPSS) was extremely minimal compared to the traditional PCPSS, which is an economic advantage for SEKR research. The DSAV-(LA-PCPSS) is still under optimization/intensification process, and subsequent processes will be examined to achieve high efficiency. [ABSTRACT FROM AUTHOR]

AbstractTo investigate the process parameters of refillable friction stir spot welding for AA6061-T6 aluminum alloy with a 3 mm plate thickness, and to extend the applicability of this technology, experiments were conducted using custom-made tools under varying rotational and penetration speeds. This study aimed to produce well-formed welds and analyze the metallurgical structure, tensile shear strength, and microhardness of the welded joints. The experiments were performed at rotational speeds of 1000, 1200, 1400, and 1600 rpm and penetration speeds of 20, 30, 40, and 50 mm/min. These conditions were found to facilitate effective refillable friction stir spot welding. The results indicated that at lower rotational speeds, the joints failed at the interface, while at higher speeds, failure occurred through the plug. Optimal tensile shear strength was achieved at a rotational speed of 1400 rpm and a penetration speed of 30 mm/min, with a peak force of 9.27 kN and a joint surface fracture mode. Microstructural examination revealed a significant refinement of grains in the weld zone compared to the base metal. Microhardness measurements showed a concentric ring pattern on the upper surface with higher hardness at the center, decreasing toward the edges. The cross-sectional hardness demonstrated a vertical gradient, being higher at the top and decreasing toward the bottom. Notably, the welded area exhibited signs of annealing with a reduced hardness compared to the base metal, where the maximum value was recorded as HV79. [ABSTRACT FROM AUTHOR]

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The synthesis of 5‐(halomethyl)furfurals (XMFs, X=F, Cl, Br, I), including 5‐(chloromethyl)furfural (CMF), 5‐(bromomethyl)furfural (BMF), 5‐(iodomethyl)furfural (IMF), and 5‐(fluoromethyl)furfural (FMF), from biomass represents a pivotal advancement in renewable chemistry and engineering. Harnessing waste biomass as a raw material offers a sustainable alternative to fossil‐based resources, mitigating environmental degradation and addressing pressing energy needs. CMF and BMF, characterized by their enhanced stability over the hydroxyl analog, 5‐(hydroxymethyl)furfural (HMF), exhibit promise as renewable building blocks for scale‐up and commercialization. The surge in research interest, particularly from 2010 to 2024, reflects a growing recognition of XMFs′ potential as novel platform chemicals. This review highlights the evolution of XMF synthesis methods, focusing on their transformation from saccharides and lignocellulosic biomass. Mechanistic insights and experimental setups are scrutinized for industrial feasibility and scalability, shedding light on technical challenges and avenues for further research. The analysis underscores the burgeoning significance of XMFs in the transition towards sustainable chemical production, emphasizing the importance of process optimization and mechanistic understanding for commercial deployment. [ABSTRACT FROM AUTHOR]

ABSTRACT Star anise has been used for a long time in improving human health and curing diseases, owing to its unlimited components with complex chemical structures and a wide range of bioactivities. This study is aimed to investigate the influence of extraction methods (steam distillation, ethanol Soxhlet extraction, supercritical carbon dioxide extraction, subcritical n‐butane extraction) on the yield, aroma properties, chemical composition, and bioactivity of star anise essential oils. Electronic nose detection revealed the essential oils from subcritical extraction exhibited the most intense aroma, while the essential oils from ethanol Soxhlet extraction had a more complex aroma profile. Fourier‐transform infrared analysis showed the presence of benzene rings, carbonyl groups, C=C, and aromatic ether bonds in the essential oils extracted through different methods. The major components were heterocyclic olefins, heterocyclic oxygenates, and aromatic oxygenates, as well as certain amounts of flavonoids and polyphenols. Correlation analysis revealed the relative contents of volatile trans‐anethole, wormwood, d‐limonene, cineole, and trans‐α‐citronelene were strongly associated with the antibacterial activity of the essential oils. Similarly, the contents of volatile components (d‐limonene, cineole) and non‐volatile components (total flavonoids and total polyphenols) were strongly correlated with the DPPH scavenging activity of the essential oils. These results confirm the effectiveness of the ethanol Soxhlet extraction method in retaining the bioactivity of the essential oils. Finally, with a Box–Behnken central composite design of response surface and single‐factor experiments, the optimal extraction conditions for the ethanol Soxhlet method were determined: ultrasonic frequency of 80 kHz, crushing particle size of 60 meshes, liquid–material ratio of 8:1 (mL:g), and ultrasonic time of 35 min. Under these conditions, the essential oil yield was 25.51% ± 0.21%. Overall, these findings highlight the significance of extraction methods in obtaining high‐quality star anise essential oils with desirable aroma properties and potent bioactivities. [ABSTRACT FROM AUTHOR]

lysine is an essential amino acid with significant importance, widely used in the food, feed, and pharmaceutical industries. To meet the increasing demand, microbial fermentation has emerged as an effective and sustainable method for L-lysine production. Escherichia coli has become one of the primary microorganisms for industrial L-lysine production due to its rapid growth, ease of genetic manipulation, and high production efficiency. This paper reviews the recent advances in E. coli strain engineering and fermentation process optimization for L-lysine production. Additionally, it discusses potential technological breakthroughs and challenges in E. coli-based L-lysine production, offering directions for future research to support industrial-scale production. [ABSTRACT FROM AUTHOR]

We demonstrate the application of free-to-use and easy-to-implement Bayesian optimization (BO) software to streamline atomic layer deposition (ALD) process optimization. By employing machine learning-based Bayesian optimization algorithms, we enhanced the silicon surface passivation quality of titanium dioxide layers deposited using titanium tetraisopropoxide (TTIP). Unlike classical designs of experimental methods, such as Box–Behnken or Plackett–Burman designs, which require a predefined set of experiments and can become resource intensive, BO offers several advantages. It dynamically updates the search strategy based on previous outcomes, allowing for efficient exploration of parameter spaces with fewer experimental runs. This adaptive approach is particularly advantageous in small-scale experiments or laboratories where time, resources, and materials are limited. In a single-objective optimization experiment, we identified constrained search spaces that limited further optimization, underscoring the importance of properly defined parameter bounds prior to the optimization process. Our findings highlight that Bayesian optimization can not only reduce time and resource costs associated with ALD process optimization but also support faster discovery of more optimal ALD process parameters, even with minimal prior knowledge of the deposition process or precursor chemistry. [ABSTRACT FROM AUTHOR]

The topological characteristics of the down-skin surfaces for as-built components by laser powder bed fusion (LPBF) are particularly representative, while the study on the improvement of the surface quality of these surfaces remains largely unexplored. Herein, the laser polishing of LPBF-built components with different inclination angles was systematically investigated with an emphasis on the down-skin surfaces. Our result shows that the topography of the top surface is independent of the inclination angle, and the surface topography of the down-skin surface is dominated by additional angle-dependent surface characteristics. It also indicates that the surface roughness can be reduced sharply when increasing the laser power from 40 W to 60 W, and the reduction slows down when further increasing the laser power while decreasing the scanning speed leads to a progressive improvement of the surface morphology. Moreover, a second-order regression model was established to evaluate the influence of the initial surface morphology and polishing parameters on the polished surface roughness and to achieve surface roughness optimization. Therefore, our established methodology can be readily applied to surface morphology manipulation and process optimization for laser polishing of widely used metals and alloys fabricated by the additive manufacturing process. [ABSTRACT FROM AUTHOR]

Lutein is a macular biopigment that can protect the retina from oxidative stress induced by chronic exposure to light and oxidants. The peel of gac fruit (Momordica cochinchinensis) contains high levels of lutein, but the extraction optimisation parameters are complex, requiring saponification, and the effects on ocular bioactivity are not well understood. This study is aimed at optimising parameters for lutein extraction validated using HPLC from gac peel to determine their protective effects on oxidatively stressed retinal cells. The factors investigated for optimisation were KOH concentration, time, and temperature using (1) single factor, (2) multiple factor response surface methodology, and (3) predictive modelling. The optimum conditions for lutein extraction using single factors were 9% KOH for 3 h at 60°C, multiple factors were 9% KOH for 3 h at 45°C, and predictive modelling was 18% KOH for 1.9 h at 39.9°C, with the maximum extraction of lutein at 12.37, 15.64, and 17.4 mg/g DW, respectively. The extracted lutein purity and chemical composition were compared using HPLC and FTIR and indicated high purity and similarities in all extracts including the commercially purified lutein. Lutein extracted exhibited benefits on oxidatively stressed retinal pigment epithelium (RPE) cells that reversed damage to baseline unstressed levels exceeding 80% viability, similar to purified lutein standards. The feasibility of gac lutein and extraction optimisation were discussed for commercial translational opportunities as a medicinal bioproduct with a focus on eye benefits. [ABSTRACT FROM AUTHOR]

This study aimed to optimize the osmotic dehydration process of strawberry slices by examining the effects of glycerol concentration, immersion time, and temperature on water loss and solid gain. Additionally, the study explored the use of chokeberry infusion to enhance the total phenolic content of the strawberries, thereby increasing their nutritional value. Using the Box–Behnken design and response surface methodology, the study identified optimal conditions to maximize water loss and solid gain. The findings revealed that high glycerol concentration (60% w/w) and temperature (50 °C), combined with optimal immersion times, significantly influenced water loss and solid gain. Experimental validations confirmed the model's predictions, showing high prediction accuracy (87.37% to 87.69%) for water loss determination but moderate prediction accuracy (42.80% to 64.72%) for solid gain. The immersion of strawberry slices in a hypertonic osmotic chokeberry infusion for 170–220 min maximized the migration of natural antioxidants. Moreover, the osmotic dehydration process effectively reduced water activity and moisture content, enhancing the strawberries' shelf stability. Furthermore, the addition of calcium chloride (CaCl2) helped maintain the strawberries' firmness and color during dehydration. Overall, the optimized osmotic dehydration process preserved the structural integrity and improved the nutritional profile and preservation quality of the strawberries, suitable for preparation of various fruit-based products. [ABSTRACT FROM AUTHOR]

Several lignin isolation and thermochemical pretreatment methods are practiced industrially to replace the usage of fossil fuels. In the present study, corncob residue after furfural extraction was sourced from a local industry for the recovery of lignin. Alkali and organosolv treatment methods are the two processes tried and the effect of temperature, concentration, and reaction time on the yield is recorded. Process optimization has been carried out using response surface methodology (RSM) and the optimized process conditions were derived. A quadratic model was developed based on the experimental data obtained. The obtained lignin is characterized by Fourier-transform infrared red (FTIR) spectroscopy and themogravimetric analysis (TGA) and found to have properties matching closely with authentic lignin. Furthermore, it was observed that the purity of lignin obtained from both these processes was >93% and a yield of greater than 95%. The focus of the present work was also to minimize the usage of water and reuse the water through NaCl precipitation process. A process flow diagram for the optimized conditions and process is developed and techno-economic analysis (TEA) is carried out. The annual revenue generated and the annual profits are listed to arrive at the payout period of 0.96 year for alkali process in comparison to that of organosolv process. [ABSTRACT FROM AUTHOR]

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Continuous flow synthesis is pivotal in dye production to address batch‐to‐batch variations. However, synthesizing water‐insoluble dyes in an aqueous system poses a challenge that can lead to clogging. This study successfully achieved the safe and efficient synthesis of azo dyes by selecting and optimizing flow reactor modules for different reaction types in the two‐step reaction and implementing cascade cooperation. Integrating continuous flow microreactor with continuous stirred tank reactor (CSTR) enabled the continuous flow synthesis of Sudan Yellow 3G without introducing water‐soluble functional groups or using organic solvents to enhance solubility. Optimizing conditions (acidity/alkalinity, temperature, residence time) within the initial modular continuous flow reactor resulted in a remarkable 99.5% isolated yield, 98.6 % purity, and a production rate of 2.90 g h−1. Scaling‐up based on different reactor module characteristics further increased the production rate to 74.4 g h−1 while maintaining high yield and purity. The construction of this small 3D‐printing modular cascaded reactor and process scaling‐up provide technical support for continuous flow synthesis of water‐insoluble dyes, particularly high‐market‐share azo dyes. Moreover, this versatile methodology proves applicable to continuous flow processes involving various homogeneous and heterogeneous reaction cascades. [ABSTRACT FROM AUTHOR]

Introduction: Treatment with chimeric antigen receptor T (CAR-T) cells involves a large number of interdisciplinary stakeholders and is associated with complex processes ranging from patient-specific production to follow-up care. Due to the complexity, maximum process optimization is required in order to avoid efficiency losses. This study aimed at systematically determining the preconditions for a frictionless flow of the CAR-T process by surveying the stakeholders involved. Methods: A Group Concept Mapping (GCM) analysis, a mixed-methods participatory research, was conducted. CAR-T experts from different professional backgrounds went through three steps: 1) Brainstorming relevant aspects (statements) for a frictionless process, 2) Sorting the collected statements based on their similarity, and 3) Rating the importance and feasibility of each statement. A cluster map reflecting the overarching topics was derived, and mean ratings per statement and cluster were calculated. Results: Overall, 20 CAR-T experts participated. A total of 80 statements were collected, resulting in a map of the following 10 clusters (mean importance/feasibility): Information for patients and physicians (4.16/3.77), Supportive network (4.03/3.53), Eligibility of patients (4.41/3.63), Evidence, transparency and communication (4.01/3.33), Paperwork (4.1/2.52), Interface with pharmaceutical manufacturer (4.03/2.85), Reimbursement (4.29/2.31), Quality Management (4.17/3.18), Infrastructure of CAR-T clinics (4.1/2.93), and Patientoriented processes (4.46/3.32). Discussion: The 80 statements underlined the complex and manifold nature of the CAR-T treatment process. Our results reflect the first step in overcoming hurdles: identifying potential hurdles and required preconditions. Decisionmakers and stakeholders can use the results to derive strategies and measures to further promote a frictionless process. [ABSTRACT FROM AUTHOR]

This study explores the application of a hybrid algorithm based on Differential Evolution (DE) and Support Vector Machine (SVM) in the mineral processing of elutriation machine. To address the problems of low quality and efficiency in metal beneficiation during elutriation, the DE-SVM algorithm was proposed, and a corresponding beneficiation quality prediction model was constructed. Experimental results showed that the average prediction accuracy and precision of the DE-SVM algorithm were 93. 7 % and 95. 6 %, respectively. The predicted concentrate recovery rate and the absolute error of predicted concentrate grade using the model were 98. 4 % and 0. 309 %, respectively. Compared with other algorithms and models, the DE-SVM algorithm and its associated elutriation machine beneficiation quality prediction model demonstrated significant advantages, providing an effective method to improve the quality and efficiency of precious metal beneficiation. [ABSTRACT FROM AUTHOR]

A natural extract, i.e., urushiol, was employed to effectively cross-link and modify commercial wet-cured polyurethane acrylic resin. Comprehensive characterization of the paint film was performed using techniques such as FTIR, SEM, and TGA. The results indicated that the incorporation of urushiol significantly increased the cross-linking density of the resin, which in turn enhanced the film-forming properties, mechanical strength, and thermal stability of the paint film. Additionally, the study discovered that under isothermal conditions, the dynamic moduli (G′ and G″) of the paint film are related to the gel point frequency by a power law, aligning with the predictions of percolation theory. The application of the autocatalytic model has provided a novel approach to studying non-isothermal kinetic reactions, offering valuable insights for process optimization and further development of urushiol-based polyurethane. [ABSTRACT FROM AUTHOR]

As a novel coating spray technique, the aerosol deposition method is applied for the fabrication of dense, nanostructured ceramic coatings at room temperature via an impact consolidation mechanism. It is widely recognized that the successful deposition of coatings is strongly dependent on processing parameters during the deposition process. In this study, a brush‐type aerosol generator was employed to enhance the continuity and stability of the aerosol supply. The uniformity of powder consumption at different packing densities was evaluated; an optimal loading density of 33% was identified for the alumina powders used in this study. Both simulation and experimental studies were performed to investigate the influence of gas flow rate and standoff distance (SoD) on coating fabrication and properties. The predicted particle impact velocity increased with increasing gas flow intensity and SoD, resulting in enhanced mechanical properties of the coatings, including adhesive strength and hardness. The maximum compressive residual stress value of 389 MPa was determined for an alumina coating fabricated at a gas flow rate of 20 L/min. [ABSTRACT FROM AUTHOR]

The article focuses on the review of HPGR operation mainly from a technological point of view. A critical review of recent achievements in HPGR technology was carried out, and major research areas and interests were distinguished and characterized. The economic potentials of HPGR presses were analyzed from the scope of the energy consumption. The HPGR researches were grouped into the following subjects: construction and design of HPGR machines, HPGR feed characterizations, the process course and assessment of comminution operations in HPGR devices, modeling and optimization of HPGR operation, HPGR-based technological circuits, and impact of HPGR operation on effectiveness of beneficiation processes. Apart from that, quantitative and qualitative analyses of the publications registered in the Web of Science database were performed. The evaluation has been performed according to the most frequently published institutions, countries, and journals. The analysis of merit content was performed through a critical review of research areas and investigative topics characterized by keywords. [ABSTRACT FROM AUTHOR]

This review article explores the azeotropic mixtures and investigates the application of Pressure Swing Distillation (PSD) as an effective separation method. Azeotropic mixtures have compositions that result in vapor and liquid phases with the same composition, making them challenging to separate using simple distillation. The content offers a structured approach to design, optimize, and execute separation processes, emphasizing the importance of heat integration, process optimization, control strategies, economic considerations, and environmental impacts within the context of PSD. Furthermore, these findings provide valuable insights for practitioners in the selection of appropriate heat-integration, optimization methods, and balancing the trade-off between economy and controllability when selecting an appropriate separation technique by balancing the economic benefits and controllable performance of different methods. PSD is reviewed detailing thermodynamic equilibrium, selection of pressure and column sequence, heat integration, optimization techniques, control strategy, and economics. The recent progresses of PSD are evaluated to determine how different heat integration techniques are useful in achieving cost and energy savings. The review provides valuable guidance to researchers and engineers navigating the complexities of azeotropic mixture separation, with a specific focus on PSD practical applications. [ABSTRACT FROM AUTHOR]

Direct capture of CO 2 from ambient air is technically feasible today, with commercial units already in operation. A demonstrated technology for achieving direct air capture (DAC) is chemical separation of CO 2 in a steam-assisted temperature-vacuum swing adsorption (S-TVSA) process. However, the potential to develop scalable solutions remains high, requiring a detailed understanding of the impact of both process design and operation on the performance of the DAC unit. Here, we address this knowledge gap by presenting a state-of-the-art process simulation tool for the purification of CO 2 from ambient air by a 5-step S-TVSA process. By considering the benchmark adsorbent APDES-NFC, we conduct multi-objective productivity/energy usage optimization of the DAC unit, subject to the requirement of producing a high purity CO 2 product ( ≥ 95 %). For the base case scenario, we find a maximum productivity of Pr max = 6.20 kg/m 3 /day and a minimum specific equivalent work of W EQ , min = 1.66 MJ/kg. While in reasonable agreement with published data, our results indicate that the description of both competitive adsorption and adsorption kinetics are key factors in introducing uncertainty in process model predictions. We also demonstrate that the application of formal optimization techniques, rather than design heuristics, is central to reliably assess the process performance limits. We identity that system designs employing moderate CO 2 sorption kinetics and contactors with low length-to-radius ratios yield the best performance in terms of system productivity. Finally, we find that moderate-high ambient relative humidities (50–75%) offer significantly favourable performance, and that a wide range of feed temperatures (5–30 ∘ C) can be accommodated via process optimization without a significant impact on performance. [ABSTRACT FROM AUTHOR]

Large shaft grinding processes are required to generate multiple quality indices with good consistency, such as profile dimension accuracy, surface roughness, and optical glossiness. Generating profiles for large shafts in the grinding process requires the grinding wheels to move transversely under the desired path, which includes rough grinding, semi-finish grinding, finish grinding, and spark-out grinding stages, and each grinding stage needs to go through multiple passes under different process parameters. Therefore, the design and selection of process parameters for each grinding stage is always challenging to meet both quality and efficiency requirements. In this study, a multi-objective optimization method for transverse profile grinding processes of large shafts is developed. In the proposed method, multiple grinding quality indices and grinding efficiency are taken as optimization objectives, and grinding surface quality, grinding depth, and grinder machining performance are taken as constraints. By utilizing the dynamic factor improvement strategy and the adaptive grid density improvement strategy, an improved particle swarm algorithm is developed to optimize the grinding process parameters. The grinding dimensional error compensation method and the surface quality consistency control method are integrated into the improved particle swarm algorithm to realize the accurate prediction of grinding dimensional accuracy and surface quality. Based on the proposed method, the optimized grinding process can be obtained, and the effectiveness of the method is verified by grinding experiments. [ABSTRACT FROM AUTHOR]

Recently application of 3D bioprinting to bioengineering has gained interest for the availability of advanced biomaterials with promising properties for regenerative medicine and drug delivery. In particular, extrusion-based bioprinting has the possibility to use a wide range of hydrogels of natural and synthetic origin. One of the most critical weaknesses of bioprinting is the poor post-printing shape fidelity of 3D scaffold possibly due to the porous-viscoelastic nature and swelling behavior of extruded polymers through the printing head. In this work, a quantitative index, termed shape fidelity index, is proposed to evaluate the discrepancy between ideal and real printed scaffolds. Scaffolds were printed with natural polysaccharides, such as alginate and cellulose (Xplore®), and synthetic polymers, such as polyethylene glycol (START®). Four process parameters on 2 levels were selected for the study according to a DOE analysis: inlet pressure, printing speed, temperature and type of biomaterial. 16 experiments were performed with an extrusion-based bioprinter to produce 3D porous scaffolds, the shape and surface areas of which were characterized with optical microscopy and image analysis. Shape fidelity indices were characterized to guide the optimization of the bioprinting process. The proposed approach permits also to determine the process parameter influencing the most the printing outcome and to rank the parameter importance for optimizing the shape fidelity of the bioprinted manufacts with soft biomaterials. [ABSTRACT FROM AUTHOR]

The fabrication of three-dimensional (3D) bioprinted free-standing, low viscous, cell-laden hydrogels with good resolution, low cytotoxicity, and mechanical properties, comparable to native soft tissues, is a current challenge in tissue engineering. Recently, a new syringe extrusion approach, called Freeform Reversible Embedding of Suspended Hydrogels (FRESH), has been introduced to enhance 3D-bioprinting of soft hydrogels. Printing is conducted with the material embedded in a thermo-reversible gelatin bath, which acts as supporting material and can also initiate in-situ crosslinking when proper crosslinker agents are added. This work is the first to develop a 3D FRESH printable, low-cost, polymeric hydrogel composed of sodium alginate (SA), carboxymethylcellulose (CMC), and gelatin. A factorial design is investigated to identify best printing parameters. Printability Pr and CAD fidelity indexes are defined as responses of interest against scaffold resolution and shape fidelity. Results show a free-standing scaffold with a printability index, Pr ~ 1, a compression Young's Modulus of about 4 kPa, and a cellular ATP content of stromal cells up to 50% compared to a 2D cell culture after 14 days. These promising results demonstrate the potential of such hydrogel to print soft constructs, applicable for neural or skin tissue engineering applications. [ABSTRACT FROM AUTHOR]

Nickel contamination in water is a critical issue due to its toxicity and persistence. This study presents a novel magnetic resin, developed by modifying Lewatit® MonoPlus TP 207 with magnetite nanoparticles, to enhance adsorption capacity and facilitate efficient separation. A Definitive Screening Design (DSD) was employed to identify and optimize key parameters affecting nickel adsorption, including pH, resin dosage, initial nickel concentration, and the presence of competing ions (calcium and magnesium). The DSD analysis revealed that pH and magnesium concentration were the most significant factors influencing nickel removal. Optimal conditions were determined as pH 7, 270 min contact time, resin dosage of 0.5 mL/L, initial nickel concentration of 110 µg/L, calcium concentration of 275 mg/L, and magnesium concentration of 52.5 mg/L, achieving a maximum removal efficiency of 99.21%. The magnetic resin exhibited enhanced adsorption capacity and faster kinetics compared to the unmodified resin, leading to more efficient nickel removal. Moreover, its magnetic properties facilitated rapid separation from treated water, offering practical advantages for real-world applications. This study demonstrates the effective use of DSD in optimizing adsorption parameters and underscores the potential of magnetic resin as a sustainable and efficient adsorbent for water treatment. [ABSTRACT FROM AUTHOR]

This study investigated the influence of printing parameters and strategies on the morphological characteristics of austenitic stainless steel beads deposited on carbon steel substrates, using plasma directed energy deposition (DED). The experimental setup varied the welding current, wire feed speed, and torch travel speed, and we analyzed three printing strategies: simple-linear, overlapping, and oscillating. Moreover, advanced 3D scanning and computational analysis were used to assess the key morphological features, including bead width and height. The results showed that the computational model developed by using parabolic assumptions accurately predicted the geometric outcomes of the overlapping beads. The oscillating printing strategy was the one that showed improved morphological uniformity and bead substrate wettability, so these features were used for multi-layer component manufacturing. The use of equivalent wavelength–amplitude values resulted in maximum combinations of bead height and width. Moreover, cost-effective carbon steel substrates were feasibly used in microstructural and elemental analyses, with the latter ones confirming the alignment of the bead composition with the wire-fed material. Overall, this study provides practical insights for optimizing plasma DED processes, thus enhancing the efficiency and quality of metal component manufacturing. [ABSTRACT FROM AUTHOR]

Laser wire-feed metal additive manufacturing (LWAM) is an innovative technology that shows many advantages compared with traditional manufacturing approaches. Despite these advantages, its industrial adoption is limited by complex parameter management and inconsistent process quality. To address these issues and improve geometric accuracy, this study explores how process parameters influence bead geometry. We conducted a parameter study varying laser power, wire feed rate, traverse speed, and welding angle. Using a full factorial design with a central composite design methodology, we assessed bead height and width. This allowed us to develop a model to estimate ideal process parameters. The findings offer a detailed analysis of parameter interactions and their effects on bead geometry, aiming to enhance geometric accuracy and process stability in LWAM. Moreover, we have evaluated the proposed process parameters from our developed model, which showed a significant enhancement to the overall quality. This was validated via printing a single layer and multi-layer structures. The quality of the final predicted sample using the proposed method was improved by 40% compared to the best sample produced for the Design of Experiment trials. [ABSTRACT FROM AUTHOR]

Copyright of Chemical Engineering (China) / Huaxue Gongcheng is the property of Hualu Engineering Science & Technology Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

From 2011 to 2023, a total of 20 ecological operation experiments of artificial flood peak were conducted in the Lower Jinsha River-Three Gorges cascade reservoirs, focusing on the fish spawning, and a lot of experience was accumulated while achieving good experiments results. In order to systematically figure out the effectiveness and experience of the ecological operation experiments of artificial flood peak over the years, this paper takes the Lower Jinsha River-Three Gorges cascade reservoirs as an example. First, the principles, key points, monitoring and evaluation methods of the ecological operation experiments of artificial flood peak were introduced. Second, the development of operation experiments over the years was reviewed. Finally, the operation experience was summarized and the future optimal direction was proposed. The results showed that the ecological operation experiments of artificial flood peak in the Lower Jinsha River-Three Gorges cascade reservoirs effectively promoted the spawning of fishes spawning drifting eggs in the Yangtze River. The effect of promoting the natural spawning of the representative fishes spawning drifting eggs--the four major Chinese carps under the dam is the most significant in the Three Gorges Reservoir. By 2023, the total spawning scale of the four major Chinese carps in the middle reaches of the Yangtze River reached 38.25 billion. Under the joint promotion of multi-year ecological operation practice and 10-year fishing ban plan, the fish resources of the four major Chinese carps is close to the level of the 1980s. However, under the influence of climate change, fish spawning and developmental characteristics change, spawning ground change and other factors, the ecological operation experiments of artificial flood peak need to carry out targeted optimization and adjustment in the aspects of operation process optimization, operation effect evaluation, and operation effect improvement. The results can provide a reference for the ecological operation of artificial flood peak for fish spawning in similar basins under changing environment. [ABSTRACT FROM AUTHOR]

Mercury (Hg) is a hazardous heavy metal, non-biodegradable and toxic, posing a serious threat to aquatic life and human health. Therefore, the removal of Hg ions from contaminated water using effective and eco-friendly adsorbents is necessary. In the present study, three magnetic chitosan-based organic–inorganic nanocomposites, such as CS-MnFe2O4, CS-MnFe2O4-CoS, and CS-MnFe2O4-CoS-MWCNTs, were designed and constructed to investigate their capacity for adsorbing Hg ions from aqueous solutions. The physicochemical properties of prepared composites were characterized by various analyses. The BET analyses indicated their high surface area and porous structure, and the N2 adsorption–desorption showed that the modification of CS in three stages by MnFe2O4 and crosslinking reaction, CoS preparation, and MWCNT incorporation resulted in increased N2 adsorption. The XRD confirms the synthesis of MnFe2O4 and CoS in the CS matrix and also the distinct peaks of MWCNTs. The CS-MnFe2O4-CoS-MWCNTs showed acceptable thermal stability with 45% char yields and superparamagnetic properties with magnetic saturation (Ms) of 16 emu g−1. The interactive impacts of independent variables (pH, contact time, and adsorbent dosage) on the removal percentage of Hg(II) onto three prepared adsorbents, as well as the process optimization, were assessed by the Box-Behnken design. The optimum conditions were identified, and the data from the analysis of variance showed that the three independent factors (pH, contact time, and adsorbent dosage) significantly influenced the adsorption of Hg(II). The adsorption isotherm and thermodynamics analysis investigation showed that at low concentrations of Hg(II), the adsorption process was both endothermic and spontaneous for the studied adsorbents. [ABSTRACT FROM AUTHOR]

Recently, pectin, a versatile polysaccharide with different industrial applications, has gained significant attention as an eco-friendly and functional ingredient. This study investigates pumpkin peels (Cucurbita maxima L., Mantua variety) as a novel source of pectin, using a microwave-assisted extraction method with citric acid-acidified water as solvent. The extraction conditions were optimized using a Design of Experiments approach, considering the solvent-to-solid ratio (SSR), pH, temperature, and extraction time. The optimized conditions (94.8 °C, 5 min, pH 1.5, and 46 mL/g SSR) resulted in a pectin yield of 18.05%. A comprehensive characterization of the extracted pectin was performed, including FT-IR spectroscopy, DSC, TGA, rheological properties, and techno-functional assessments such as water holding capacity and fat binding capacity. The results indicated a high degree of esterification (56.19 ± 0.87%), classifying the pumpkin peels (PP) extract as a high methoxyl pectin. PP pectin demonstrated potential as a stabilizer and emulsifying agent, although its high methoxyl content limits its use as a carrier for targeted bioactive delivery. The findings support the viability of using agricultural by-products to obtain valuable polysaccharides, contributing to waste valorization and sustainable industrial practices. [ABSTRACT FROM AUTHOR]

The level of consumption of summer tea is a problem in the development of China's tea industry. Current strategies to enhance the quality of summer and autumn teas primarily target the cultivation environment, with less emphasis on processing improvements. This study aimed to optimize the fermentation parameters to impact the quality of summer and autumn teas. We screened four strains of lactic acid bacteria (LAB) suitable for tea fermentation and determined their optimal mix. This optimized blend was applied to ferment summer and autumn teas. Through single-factor experiments, we evaluated the impact of various processing parameters, including the fixation method, rolling degree, inoculation amount, glucose concentration, fermentation temperature, and fermentation duration, on LAB growth and tea quality. The optimal processing conditions were established as microwave fixation, heavy rolling, an inoculation rate of 1.8% LAB, glucose addition at 8.8%, and fermentation at 36.5 °C for five days. Analysis revealed that the fermentation process significantly reduced the levels of polyphenols and ester-type catechins, which are associated with astringency and bitterness while enhancing the content of gamma-aminobutyric acid (GABA). Specifically, after five days, polyphenol content decreased by 26.89%, and GABA levels increased from 0.051 mg/g to 0.126 mg/g. The predominant aroma compounds in the fermented tea were alcohols with floral and fruity scents, constituting 54.63% of the total aroma profile. This research presents a methodical approach to reduce the astringency and bitterness of summer and autumn teas while concurrently increasing GABA levels. [ABSTRACT FROM AUTHOR]

Copyright of China Condiment is the property of China Condiment and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Condiment is the property of China Condiment and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aerosol jet printing is a promising technology for printing functional materials on a variety of substrates with high precision and resolution. This technology has the potential to revolutionize the manufacturing industry by providing a low‐cost, high‐resolution printing technique that can be used to produce additively printed electronics, sensors, and energy devices. However, the optimization of this process has traditionally relied on time‐consuming trial‐and‐error methods, hampering its efficiency and scalability. Machine learning (ML) models have the potential to overcome these challenges and improve the quality, speed, and efficiency of the printing process. In this paper, we propose an approach that leverages ML algorithms to streamline and enhance the aerosol jet printing optimization process. Our methodology involves data collection through systematic experimentation with various parameter settings. This data set serves as the foundation for training different ML model capable of predicting printed line characteristics and optimal printing process parameter. We validate our approach by performing experiments on different inks, and we compare the results of our ML‐based optimization approach to those obtained using traditional trial‐and‐error methods. The results demonstrate that our approach offers significantly higher accuracy and efficiency. To enhance our approach's accessibility and ease of use, we incorporate AutoML techniques which automates the process of selecting the most suitable ML algorithms and hyperparameters, reducing the burden of manual configuration. Furthermore, we introduce a user‐friendly web‐based interface that facilitates the entire ML pipeline, from data preprocessing to prediction and batch processing. This interface empowers users to efficiently manage and manipulate their data, select appropriate ML algorithms, and execute predictions, ultimately improving accuracy and model performance. [ABSTRACT FROM AUTHOR]

In this study, on the basis of single factor experiments, the effects of raw material mass concentration, ethanol volume fraction, ultrasonic power, extraction temperature, and extraction time on the lipase inhibition activity of mulberry leaves extract were investigated in combination with response surface methodology to optimize the ultrasonic-assisted extraction process of the lipase-inhibiting components of mulberry leaves. Meanwhile, the active ingredients of mulberry leaves extract were analyzed by UPLC-Q-TOF HRMS. The results showed that the optimal 21extraction process parameters for the lipase-inhibiting components of mulberry leaves were as follows: The mass concentration of raw material was 0.05 g/mL, volume fraction of ethanol was 70%, ultrasonic power was 195 W, extraction temperature was 31 °C and the extraction time was 40 min. Under these conditions, the lipase inhibition rate of mulberry leaves extract was 39.68%. A total of 1067 compounds were identified. Flavonoids and phenolic acids accounted for the highest proportion, containing 203 and 201 compounds, respectively. These compounds might be the material basis for the lipase inhibiting activity of mulberry leaves extract. In this study, the ultrasonic-assisted extraction process of mulberry leaves was optimized to improve the extraction efficiency of the lipase-inhibiting active components, and the main active ingredients were analyzed. The results may provide a reference for the functional application of mulberry leaves in improving lipid metabolism and the development of health food. [ABSTRACT FROM AUTHOR]

Copyright of Packaging & Food Machinery is the property of Packaging & Food Machinery Magazine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)