Frontiers of Chemical Science and Engineering最新文献

{"title":"Challenges and AI-powered strategies for multi-scale superquadric DEM-CFD modeling of non-spherical particles","authors":"Jianjian Dai,&nbsp;Zihao Ma,&nbsp;Xi Gao","doi":"10.1007/s11705-026-2705-z","DOIUrl":"10.1007/s11705-026-2705-z","url":null,"abstract":"<div><p>Multi-scale superquadric discrete element method-computational fluid dynamics (DEM-CFD) coupling provides a powerful tool to resolve cross-scale behaviors inside fluidized bed reactors, yet several critical obstacles restrict its industrial application, including anisotropic contact hydrodynamics, incomplete heat transfer frameworks, immature non-spherical reaction models, and high computational cost for large-scale particle systems. This view systematically dissects the above bottlenecks, summarizes unresolved research gaps, and proposes targeted remedies: reduced-space Newton iteration for contact singularity, generalized shape-factor Nusselt correlations, superquadric coordinate-based shrinking core reaction models, and the synergy of coarse-grained particle models with graphics processing unit acceleration. Furthermore, this work elaborates on the transformative potential of artificial intelligence: deep learning can construct universal drag/heat transfer correlations from direct numerical simulation data, generate interpretable chemical reaction kinetics, and accelerate stiff solvers to cut simulation overhead. This view delivers clear development roadmaps for the next-generation multi-scale SuperDEM-CFD platform, supporting predictive design and real-time digital twin construction of gas-solid reactors.</p></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 12","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148878106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic and environmental comparison of mainstream and potential alternative routes: a study on one-step and two-step processes for methacrylonitrile production via isobutene ammoxidation","authors":"Mengzhen Zhu,&nbsp;Xinrui Song,&nbsp;Zhibo Zhang,&nbsp;Jiarong Lu,&nbsp;Xiaolin Zhu,&nbsp;Xin Zhou,&nbsp;Xiang Feng,&nbsp;Hao Yan,&nbsp;Guozhen Qi","doi":"10.1007/s11705-026-2701-3","DOIUrl":"10.1007/s11705-026-2701-3","url":null,"abstract":"<div><p>Methacrylonitrile is an indispensable chemical intermediate in aerospace and wind energy material manufacturing. Currently, the one-step isobutene ammoxidation process is the industrial mainstream for its production, but its drawbacks of high reaction temperature, many byproducts and high purification energy consumption have prompted researchers to explore alternatives. Although the two-step ammoxidation process has theoretical advantages, it is still in the experimental stage, with its economic and environmental benefits not systematically evaluated. Under unified conditions (99.5% product purity, 1 t·h⁻¹ isobutene feed), this study compared the two processes via technoconomic analysis and life cycle assessment. Results show the two-step process has a higher yield (82.4% <i>vs.</i> 77.3%), while the one-step process is superior in unit cost (1.90 <i>vs.</i> 2.23 USD·kg_MAN⁻¹) and life cycle carbon emissions (7.42 <i>vs.</i> <span>(9.10 text{t}_{text{CO}_2text{-eq}} cdot text{t}_{text{MAN}} ^{-1})</span>). Sensitivity analysis indicates yield is key to the two-step process’s competitiveness: each 1% increase reduces cost by 0.07 USD·kg_MAN⁻¹ and emissions by <span>(0.37 text{t}_{text{CO}_2text{-eq}} cdot text{t}_{text{MAN}} ^{-1})</span>, and 86.9% yield makes it comparable to the one-step process. Thus, improving yield to over 86.9% via catalyst modification is critical for its industrialization, providing quantitative targets for optimization and a scientific basis for process selection and sustainability assessment.\u0000</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 11","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combined effects of Si-OH content and pore size of SiO2 carriers on Ni3P/SiO2 catalysts for selective dimethyl oxalate hydrogenation to methyl glycolate","authors":"Yuhui Wang,&nbsp;Xiaobo Feng,&nbsp;Yaqin Wu,&nbsp;Chenyan Fu,&nbsp;Yuxin Duan,&nbsp;Zhiyang Ren,&nbsp;Tianlong Liu,&nbsp;Jingpei Cao","doi":"10.1007/s11705-026-2699-6","DOIUrl":"10.1007/s11705-026-2699-6","url":null,"abstract":"<div><p>The selective hydrogenation of dimethyl oxalate (DMO) to methyl glycolate (MG) is critical for biodegradable polyglycolic acid production, but MG is prone to overhydrogenation to ethylene glycol. Ni₃P/SiO₂ catalysts show promise in selective hydrogenation due to their unique electronic structure and thermal stability. The conventional strategies to enhance the performance of these catalysts rely on maximizing the carrier specific surface area to expose more active sites. In this study, we synthesized three spherical SiO₂ carriers with similar particle diameters but different internal structures to load Ni₃P. Unexpectedly, among the three catalysts, the highest-surface-area Ni₃P/SiO₂-II catalyst exhibited the best Ni₃P dispersion yet the poorest DMO conversion (only 55.4%), as its micro-mesoporous structure compromised the formation of phase-pure Ni₃P and limited the effective utilization of active sites. The lowest-surface-area Ni₃P/SiO₂-III, which lacks sufficient Si-OH anchoring, suffered from severe Ni₃P agglomeration but still achieved 75.4% DMO conversion owing to its mesoporous structure. In contrast, Ni₃P/SiO₂-I, despite its low surface area, achieved excellent performance with 92.2% DMO conversion and 94.8% MG selectivity at 220 °C, benefiting from abundant Si-OH groups and large mesopores. Systematic characterization revealed that the density of surface Si-OH groups and the pore size were the two carrier properties responsible for the observed differences in catalytic activity. Further analysis showed that abundant Si-OH groups suppressed Ni₃P agglomeration via chemical anchoring, while large mesopores enabled sufficient Ni-P precursor contact to ensure pure Ni₃P formation and also enhance DMO accessibility and timely MG diffusion. This combination promoted activity and maintained high MG selectivity by minimizing overhydrogenation. Thus, besides specific surface area, abundant Si-OH groups combined with large mesopores are key factors for Ni₃P catalytic performance in DMO hydrogenation.\u0000</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 11","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electromagnetic induction heating for endothermic reactions in energy chemical engineering: a review on susceptor design and reaction coupling","authors":"Yuxin Yan,&nbsp;Xuhui Zhang,&nbsp;Zhenyu Liu,&nbsp;Lei Shi,&nbsp;Qingya Liu","doi":"10.1007/s11705-026-2702-2","DOIUrl":"10.1007/s11705-026-2702-2","url":null,"abstract":"<div><p>The majority of energy chemical processes require heat supply to sustain reactions. The conventional heat supply relies mainly on fossil fuel combustion, plagued by high energy consumption and intensive carbon emissions. Advanced heating technologies are urgently demanded for low-carbon transition. Electromagnetic induction heating (EIH), featuring non-contact heating, ultra-fast temperature ramp rate, and high energy efficiency, has emerged as a promising technical pathway for the low-carbon transformation of energy chemical engineering. This paper reviews the research progress of EIH utilization in energy chemical processes, focusing on performance regulation strategies and typical reaction applications of three susceptor categories: carbon-based, macroscopic metal, and magnetic nanoparticle susceptors. Carbon-based susceptors enable reactant-heat source integration for high-temperature carbon-involved endothermic reactions such as calcium carbide synthesis; macroscopic metal susceptors combine excellent machinability with heat-catalysis synergy and support tunable temperature gradients for staged conversion; magnetic nanoparticle susceptors feature high specific heating power and excel in microscale local hot spot intensification for medium-low temperature catalysis. Overall, EIH achieves deep heat-reaction coupling and serves as an effective electrification solution for strongly endothermic processes, with excellent adaptability to intermittent green electricity. Future key research directions include long-life susceptor optimization, multiphysics coupling simulation, and standardized techno-economic evaluation for industrial scale-up.\u0000</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 11","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the critical role of initial isomerization in n-hexane catalytic cracking over HZSM-5 with molecular kinetic model","authors":"Rui Li,&nbsp;Yuming Li,&nbsp;Ruipu Wang,&nbsp;Siying An,&nbsp;Yan Zhang,&nbsp;Qingxin Yang,&nbsp;Zhengyu Chen,&nbsp;Kebin Chi,&nbsp;Dejun Shi,&nbsp;Zhongdong Zhang,&nbsp;Caizhong Hu,&nbsp;Linzhou Zhang,&nbsp;Guiyuan Jiang","doi":"10.1007/s11705-026-2700-4","DOIUrl":"10.1007/s11705-026-2700-4","url":null,"abstract":"<div><p>Although HZSM-5 zeolite is widely used in catalytic cracking reactions, most relevant studies have not thoroughly examined the initial reaction behavior of <i>n</i>-hexane catalytic cracking, leading to an insufficient understanding of molecular-scale reaction mechanisms. Herein, we conducted precise catalyst tests to establish a molecular-scale reaction kinetic model for <i>n</i>-hexane catalytic cracking. The results showed that isohexane is an important primary product of the reaction. Two reaction networks, with and without <i>n</i>-hexane isomerization to isohexane, were compared, revealing that isohexane directly influences ethylene and propylene formation pathways and indirectly affects substances like isobutane. Results from the kinetic model showed that consideration of the pathway of <i>n</i>-hexane isomerization to isohexane helps reduce model errors. The detailed investigation indicated that the pathway of <i>n</i>-hexane isomerization exerts opposite effects on the formation of ethylene and propylene, and the model conclusions were confirmed by co-feeding experiments, which demonstrated that adding isohexane boosts ethylene selectivity and suppresses propylene formation. The present study deepens the understanding of the <i>n</i>-hexane cracking mechanism and provides a basis for the directional regulation of reaction pathways and the optimization of industrial process conditions.</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 11","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Active learning-assisted optimization and investigation of gas diffusion layer physical properties in anion exchange membrane water electrolyzers","authors":"Junliang Xiao,&nbsp;Shengwei Yuan,&nbsp;Lin Guo,&nbsp;Haoyang Tang,&nbsp;Haiyang Zhao,&nbsp;Liang Wang,&nbsp;Fan Fan,&nbsp;Yang Zhou,&nbsp;Quan Xu","doi":"10.1007/s11705-026-2693-z","DOIUrl":"10.1007/s11705-026-2693-z","url":null,"abstract":"<div><p>To address the challenge of synergistic optimization of the multi-physical property parameters for the gas diffusion layer—a core component of anion exchange membrane water electrolyzers (AEMWEs)—this study establishes an integrated analytical framework combining multi-physics mechanism simulation and active learning-based intelligent optimization. Based on a three-dimensional steady-state multi-physics coupling numerical model of AEMWEs, the regulatory mechanisms of permeability, electrical conductivity, and porosity in the mass transport and heat transfer processes were elucidated. On this basis, a multi-model weighted ensemble active learning surrogate model was constructed to optimize the ele0ctrochemical performance of the electrolyzer. The model achieved a root mean square error (RMSE) of 16.5539 and a mean absolute error (MAE) of 12.9643 during the training process. On the test set, the model achieved a coefficient of determination (<i>R</i>²) of 0.9994, an RMSE of 5.0240, and an MAE of 4.0694. The optimal parameter combination for electrochemical performance identified by the proposed framework (a permeability of 1.18 × 10⁻¹⁰ m², an electrical conductivity of 2208.86 S·m⁻¹, and a porosity of 0.605) effectively suppresses local heat accumulation and eliminates mass transport bottlenecks. Detailed post-optimization analyses further demonstrated that the optimal parameter combination achieved a favorable balance between the optimal electrochemical response and acceptable multi-physics field distribution uniformity.\u0000</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 10","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-guided discovery of γ-Al2O3 as defect-rich structural ensemble governs single-atom Pt catalysis","authors":"Ka Lok Cliff Choong,&nbsp;Ran Luo,&nbsp;Zhi-Jian Zhao,&nbsp;Jinlong Gong","doi":"10.1007/s11705-026-2690-2","DOIUrl":"10.1007/s11705-026-2690-2","url":null,"abstract":"<div><p><i>γ</i>-Al₂O₃ is one of the most widely used catalyst supports in heterogeneous catalysis, yet its catalytic role remains unclear due to intrinsic structural disorder and complex surface species. This paper describes the development of a high-accuracy Al–O–H machine learning interatomic potential combined with global optimization to explore the structural landscape of <i>γ</i>-Al₂O₃ and its influence on propane dehydrogenation over single-atom Pt catalysts. Two energetically favorable structures, <i>γ</i>-no aluminum vacancy (NAV) and <i>γ</i>-aluminum vacancy (AV), are identified with energies lower than the conventional model by up to 34.44 meV·(f.u.)⁻¹. These optimized structures expose abundant penta-coordinated Al³⁺ sites on the (100) surface, serving as preferred anchoring sites for Pt atoms. Simulated X-ray diffraction patterns indicate that <i>γ</i>-AV shows better qualitative agreement with experimental data. Surface phase diagrams further reveal that defect-rich surfaces are thermodynamically stabilized under realistic reaction conditions. Catalytic calculations demonstrate that <i>γ</i>-NAV and <i>γ</i>-AV significantly reduce propane dehydrogenation activation barriers through enhanced metal-support interactions associated with penta-coordinated Al³⁺ sites and defect-modulated local environments. These results suggest that <i>γ</i>-Al₂O₃ is better described as an ensemble of defect-rich surface configurations rather than a single crystal structure. These findings establish a direct relationship between atomic structure, defect chemistry, and catalytic performance in <i>γ</i>-Al₂O₃.</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 10","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State of health estimation of lithium batteries based on a transformer with physical constraints and multidimensional feature fusion","authors":"Hao Guo,&nbsp;Jinye Lu,&nbsp;Kun Wang,&nbsp;Puming Yu,&nbsp;Huajun Dong,&nbsp;Kai Wang","doi":"10.1007/s11705-026-2689-8","DOIUrl":"10.1007/s11705-026-2689-8","url":null,"abstract":"<div><p>To address the key bottlenecks in the state of health prediction of lithium-ion batteries under random variable load conditions, such as poor physical consistency, insufficient feature representation, and non-physical fluctuations in the prediction curves, this paper proposes a high-precision state of health prediction model that combines physical information constraints and multi-dimensional features, aiming to enhance the safety and long-term reliability of the battery management system. A neural network-transformer framework based on physical information was constructed, converting the consistency laws of irreversible battery aging into regularization loss terms in the training process to ensure physical rationality. Multidimensional coupled features including voltage, current, and cycle count were extracted to characterize the aging characteristics of the battery, and Bayesian optimization was applied to adaptively adjust key hyperparameters. Experimental results show that this model outperforms the comparison models in terms of MAE, RMSE, and R² metrics, effectively suppressing non-physical fluctuations, balancing high prediction accuracy and physical rationality, and providing technical support for the full life cycle health management and safe operation of lithium-ion batteries.</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 10","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A coordinate-aware Mamba2 framework for remaining useful life prediction of lithium-ion battery","authors":"Longqing He,&nbsp;Ming Zhang,&nbsp;Sujuan Huang,&nbsp;Zongyang Jing,&nbsp;Wenqing Wei,&nbsp;Kai Wang","doi":"10.1007/s11705-026-2687-x","DOIUrl":"10.1007/s11705-026-2687-x","url":null,"abstract":"<div><p>To address the limitations of existing methods in capturing long-term temporal dependencies, local capacity regeneration, and nonlinear degradation characteristics in lithium-ion battery remaining useful life prediction, this paper proposes a coordinate-aware Mamba2 framework based on state-space modeling. Mamba2 is adopted as the backbone to model long-range degradation evolution, while a coordinate feature attention network is introduced in the feature extraction stage to enhance the selection and representation of key degradation in00formation. Additionally, a swiGLU-gated residual network is constructed for feature transformation and prediction, improving the modeling of complex dynamic relationships and endpoint stability. Through the collaborative design of these modules, the proposed framework effectively captures both global degradation trends and local fluctuation patterns. Experiments were conducted on the National Aeronautics and Space Administration, Tongji University, and Xi’an Jiaotong University datasets under single-variable input, multivariable input, and cross-dataset generalization settings. The mean absolute error values are lower than 0.0098, 0.0016, and 0.0083, while the root mean square error values are lower than 0.0172, 0.0024, and 0.0111, respectively. Results demonstrate that coordinate-aware Mamba2 achieves superior accuracy, lower computational cost, faster training and inference, and stronger robustness to different prediction starting points.\u0000</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 9","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in enzyme engineering for santalene and santalol biosynthesis","authors":"Bo-Long Chen,&nbsp;Ming-Dong Yao,&nbsp;Guang-Rong Zhao,&nbsp;Jian Zha,&nbsp;Ying-Jin Yuan","doi":"10.1007/s11705-026-2686-y","DOIUrl":"10.1007/s11705-026-2686-y","url":null,"abstract":"<div><p>Santalene and santalol, the primary active components of sandalwood essential oils, possess excellent pharmacological properties, including neurosedative, antibacterial, and anti-inflammatory activities. Owing to the limited supply of sandalwood, heterologous biosynthesis of santalene and santalol has garnered extensive attention. With the rapid advancements in synthetic biology, microbial cell factories have emerged as promising and sustainable methods for production of santalene and santalol. This review summarizes the advances in mining, functional expression, structural characterization, and catalytic mechanisms of two key enzymes in the pathway for production of santalene and santalol: santalene synthase and oxygenase. We have also elucidated metabolic engineering strategies across diverse microbial and plant chassis species, including <i>Escherichia coli</i>, <i>Saccharomyces cerevisiae</i>, and tobacco. Furthermore, we have critically analyzed the current bottlenecks that limit the industrial application of santalene and santalol biosynthesis and identified future directions that may address these problems.</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":571,"journal":{"name":"Frontiers of Chemical Science and Engineering","volume":"20 9","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148465125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}