Chinese Journal of Chemical Engineering最新文献

{"title":"Genome-scale metabolic reconstruction of Botrytis cinerea for enhanced abscisic acid biosynthesis","authors":"Dechun Kong,&nbsp;Lingru Wang,&nbsp;Mengyao Cheng,&nbsp;Qian Wang,&nbsp;Tianjun Gan,&nbsp;Yunge Tong,&nbsp;Tianqiong Shi,&nbsp;Chao Ye","doi":"10.1016/j.cjche.2026.05.012","DOIUrl":"10.1016/j.cjche.2026.05.012","url":null,"abstract":"<div><div>Abscisic acid (ABA), as one of the five major natural plant growth regulators, plays an important role in agricultural production. <em>Botrytis cinerea</em> is a natural strain for ABA production. However, the insufficient understanding of its metabolic network makes it difficult to further increase the yield, which limits its application in the fermentation industry. In this research, a genome-scale metabolic network model (GSMM, iDK916) of <em>B</em>. <em>cinerea</em> was constructed, which includes 916 genes, 2318 reactions and 1770 metabolites. Firstly, the model's accuracy was validated by analyzing its growth on 35 carbon sources and 25 nitrogen sources, along with the identification of 79 essential genes consistent with those in the DEG database. Subsequently, dynamic flux balance analysis (dynamic FBA) revealed that the carbon source plays a more critical role in ABA yield: when fructose was used as the sole carbon source, the simulated ABA yield reached 0.95 mmol·gDW⁻¹·h⁻¹, while the yield obtained from wet lab experiments was 0.41 g·L⁻¹. Finally, using flux scanning based on enforced objective flux (FSEOF), 64 upregulated genes were identified. To validate the predictions, <em>BCIN_12g04570</em> (Phosphomevalonate kinase, EC: 2.7.4.2) was selected for targeted overexpression in the strain, ultimately increasing ABA production to 1.35 g·L⁻¹, representing a 49.8% improvement compared to the original strain. This provides a reliable reference for subsequent research aimed at enhancing ABA production.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 308-317"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148778196","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":"Molecular reconstruction of vacuum residue based on high-resolution mass spectrometric characterization","authors":"Xiangyu Zhao,&nbsp;Dong Guan,&nbsp;Yuanfeng Wang,&nbsp;Zhengyu Chen,&nbsp;Quan Shi,&nbsp;Chunming Xu,&nbsp;Linzhou Zhang","doi":"10.1016/j.cjche.2026.05.007","DOIUrl":"10.1016/j.cjche.2026.05.007","url":null,"abstract":"<div><div>Accurately obtaining the molecular composition of vacuum residue (VR) is of great significance for feedstock screening, process development, and operational optimization. However, due to the complex molecular composition of VR, traditional molecular reconstruction models based on bulk properties struggle to accurately capture the characteristics of the molecular distribution. To address this, this study proposed a precise molecular reconstruction method for VR based on high-resolution mass spectrometry (HRMS) data. Using molecular-level characterization data obtained from HRMS as a reference, a method for the compositional similarity between the calculated and experimental molecular distribution was introduced. The compositional similarity was incorporated into the global optimization algorithm that simultaneously matched both bulk properties and molecular composition, effectively constraining the distribution of both hydrocarbon and heteroatom-containing species. The method was applied to five inferior VRs from different sources. The results demonstrate that the developed model can accurately calculate the VR bulk properties. Moreover, the predicted molecular distribution agreed well with experimental measurements, and the content of over 20000 molecules in VR was quantitatively predicted. This approach reduced the multi-solution problem inherent in the traditional molecular reconstruction method, providing a precise foundational model for molecular-level process optimization and regulation.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 109-119"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148646541","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":"Lewis acid sites stabilized Pt-Sn clusters for propane dehydrogenation","authors":"Ke Li,&nbsp;Xinyue Zhu,&nbsp;Lijuan Su,&nbsp;Haibo Zhu","doi":"10.1016/j.cjche.2026.07.010","DOIUrl":"10.1016/j.cjche.2026.07.010","url":null,"abstract":"<div><div>Pt-based particles supported on alumina are the industrial catalysts for propane dehydrogenation processes. However, the high-temperature reaction conditions promote metal sintering and coke deposition, leading to catalyst deactivation, which constitutes a major technical challenge for this process. In this study, the interplay among the acidity and texture of alumina support, metal–support interaction, and catalyst durability/regenerability was explored. A series of alumina materials with varied acidity and textural properties were prepared by controlling aluminum alkoxide hydrolysis and calcination conditions, producing alumina materials with high Lewis acid site density and porosity. Comprehensive characterizations and propane dehydrogenation tests were performed to investigate how the Lewis acidity and textural properties of the alumina supports influence the deactivation and regeneration behavior of the supported PtSn catalysts. The high density of strong Lewis acid sites effectively anchors metal clusters <em>via</em> strong metal–support interactions, thereby inhibiting sintering and enhancing long-term regenerability. After four reaction-regeneration cycles under simulated industrial conditions, the PtSn/Al-600 catalyst achieved a regeneration rate of 90%. Meanwhile, the ultrahigh surface area and porosity endow the catalyst with high coke accommodation capacity, delaying deactivation by coking.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 299-307"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148778195","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":"Electrocatalytic nitrate reduction to ammonia at industrial current densities via interfacial tandem catalysis on Ag/Co3O4","authors":"Jiqiu Zhang,&nbsp;Wei Liu,&nbsp;Wenkai Teng,&nbsp;He Li,&nbsp;Honghui Ou,&nbsp;Guidong Yang","doi":"10.1016/j.cjche.2026.05.001","DOIUrl":"10.1016/j.cjche.2026.05.001","url":null,"abstract":"<div><div>Electrocatalytic conversion of nitrate (NO₃⁻) to ammonia (NH₃) offers an beneficial route for green NH₃ synthesis, yet challenges such as complex reaction pathways and uncoordinated adsorption and conversion of reactive species hinder the enhancement of reaction kinetics. In this study, a high-aspect-ratio Ag/Co₃O₄ nanowire array catalyst was successfully fabricated on cobalt foam <em>via</em> an <em>in-situ</em> growth combined with an interfacial engineering strategy, constructing a tandem catalytic system with synergistic Ag and Co active sites. The results demonstrate that Ag loading promotes interface electron transfer and increases proportion of Co³⁺, which can promote yield improvement. Electrochemical tests show that in an H-cell, Ag/Co₃O₄ achieves a Faradaic efficiency (FE) of 91.4% and NH₃ rate of 70.2 mg·h⁻¹·cm⁻² at −0.4 V <em>vs</em>. RHE. In a membrane electrode assembly (MEA) system, Ag/Co₃O₄ exhibits a high FE of 94.2% at large-scale applicable current density of 800 mA·cm⁻² and maintains over 90% FE even at 1000 mA·cm⁻², along with excellent stability. This work elucidates the core mechanism involving tandem catalysis and the synergistic enhancement <em>via</em> interfacial electron transfer regulating Co³⁺ active center, providing a novel strategy for designing high-performance and robust catalysts for the electrochemical nitrate reduction reaction (NO₃RR) and advancing this technology toward industrial application.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 66-75"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148646491","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":"Understanding the role of surface Zn species in CO2 hydrogenation to methanol over Cu/ZnO/Al2O3","authors":"Yurou Bai,&nbsp;Ge Li,&nbsp;Heng Zhang,&nbsp;Xuan Wu,&nbsp;Shixiong Tang,&nbsp;Sandeep Dhital,&nbsp;Maoshuai Li,&nbsp;Xiaoyu Han,&nbsp;Yue Wang,&nbsp;Shouying Huang,&nbsp;Jing Lv,&nbsp;Xinbin Ma","doi":"10.1016/j.cjche.2026.04.007","DOIUrl":"10.1016/j.cjche.2026.04.007","url":null,"abstract":"<div><div>The structural characteristics of surface Zn species are of significance to regulate the activity and selectivity of Cu-based catalysts for CO₂ hydrogenation to methanol. A series of Cu/ZnO/Al₂O₃ catalysts derived from layered double hydroxides (LDH) precursors was systematically optimized and subjected to calcination and reduction at various temperatures to tune the surface Zn species with controlled characteristics of Cu species, including Cu sizes and Cu⁺/Cu⁰ ratios. Structural characterization reveals that formation of a well-defined Cu–ZnO interface with variable surface Zn species (Zn²⁺ and Zn^<em>δ</em>+), and maintained Cu nanoparticle sizes and Cu⁺/Cu⁰ ratios within similar degrees. A strong positive correlation is established between the fraction of surface Zn^<em>δ</em>+ species and methanol productivity, highlighting the critical role of ZnO_<em>x</em> species in Cu–ZnO interface during CO₂ hydrogenation. The optimized catalyst achieved a methanol space-time yield of 610.6 mg·g⁻¹·h⁻¹ at 250 °C and 3.0 MPa, exceeding most reported Cu-based catalysts under comparable conditions. This work provides mechanistic insights into interfacial structure–activity relationships and offers practical guidelines for the rational design of high-performance Cu/ZnO/Al₂O₃ catalysts for CO₂ hydrogenation to methanol.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 130-143"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148646489","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":"DFT study on mechanism for size-dependence of Pt catalysts for propane dehydrogenation","authors":"Dingding Jin,&nbsp;Ping Liu,&nbsp;Haoxiang Xu,&nbsp;Jiqin Zhu,&nbsp;Daojian Cheng","doi":"10.1016/j.cjche.2026.03.019","DOIUrl":"10.1016/j.cjche.2026.03.019","url":null,"abstract":"<div><div>Pt-based catalysts for propane dehydrogenation (PDH) are known to exhibit size-dependent activity, selectivity and stability, but the nature of the active Pt species responsible for size-dependent behavior remains unknown. In this paper, by employing density functional theory, microkinetic modeling as well as kinetic Monte Carlo simulations, we investigate PDH over (i) single Pt atom supported on the Al₂O₃(1 1 0), (ii) cluster of 13 Pt atoms adsorbed on Al₂O₃(1 1 0) and (iii) Pt(1 1 1) crystal surface. With decreasing size of Pt species, PDH activity increase, while both propene selectivity and stability against coking precursors exhibit an inverted volcano trend, which indicate the superiority of Pt single-atom catalyst and align closely with relevant experiment. Electronic structure analysis revealed that Pt species transfer electrons to the alumina, resulting in Pt positively charged. The valence electrons of Pt exhibit an inverted volcano relationship with adsorption energies of C₃H₇—H (activity index), while a volcano relationship with energy difference between propylene desorption and deep dehydrogenation (selectivity and stability index). The size reduction affects the number of electrons transferring, and the loss of relative moderate electrons of supported Pt single-atom, compared with Pt nanocluster and Pt large particle, leads to enhanced PDH activity, selectivity and stability against carbon deposition.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 97-108"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148646490","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":"Accurate prediction of drug thermodynamic behaviors in polymeric solutions by combining machine learning with molecular interaction mechanisms","authors":"Mengfei Guo,&nbsp;Yewei Ding,&nbsp;Haomin Wu,&nbsp;Bin Liu,&nbsp;Kai Ge,&nbsp;Yuanhui Ji","doi":"10.1016/j.cjche.2026.06.003","DOIUrl":"10.1016/j.cjche.2026.06.003","url":null,"abstract":"<div><div>In oral drug delivery systems, drug solubility is a critical determinant of <em>in vivo</em> absorption and clinical efficacy. However, the increasing number of poorly soluble drug candidates emerging from modern drug discovery has posed significant challenges for formulation development. Although amorphous solid dispersions have been widely employed to enhance drug solubility, selecting optimal polymer carriers still largely relies on empirical screening because reliable drug-polymer solubility data remain relatively limited. To address this challenge, a drug-polymer solubility dataset containing 9701 data points was first constructed by systematically collecting experimental data and thermodynamically consistent data augmentation based on solid-liquid phase equilibrium theory. On this basis, molecular descriptors and thermodynamic parameters derived from the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) were used as two categories of input features for systematic modeling and comparison using six machine learning algorithms, thereby establishing a solubility prediction framework. The results show that the gradient-boosting regression model constructed using PC-SAFT thermodynamic parameters achieved the best predictive performance. Moreover, the model exhibited strong prediction capability for the solubility of gemfibrozil and bifendate, which were experimentally verified using the static equilibrium method. Furthermore, a knowledge distillation strategy was employed to transfer knowledge from the best-performing Thermo-GBR model to a distilled model, KD-Thermo-GBR. This approach optimized the model structure, reduced systematic bias, and improved physical consistency, without compromising predictive accuracy (<em>R</em>² = 0.9583). Overall, this study not only establishes a relatively comprehensive dataset on drug-polymer solubility but also proposes a machine learning prediction framework that incorporates the thermodynamic mechanism of PC-SAFT, providing a reliable and efficient tool for the rational design of polymer-based solubilization systems in drug development.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 219-233"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148740636","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":"Research progress of domain-specific large language models for chemical materials","authors":"Weijian Chen,&nbsp;Lanyu Li,&nbsp;Haoxiang Xu,&nbsp;Daojian Cheng","doi":"10.1016/j.cjche.2026.05.013","DOIUrl":"10.1016/j.cjche.2026.05.013","url":null,"abstract":"<div><div>Chemical materials research is transitioning from experience-driven paradigms to data- and artificial intelligence–driven approaches. While large language models (LLMs) have shown strong capabilities in scientific text understanding and knowledge integration, LLMs remain constrained in chemical and materials science by limited domain knowledge, missing physical constraints, and hallucination risks. Domain-specific LLMs have therefore emerged as a key enabler for translating AI for Science into practical materials research. This review provides a concise overview of the construction of chemical materials–oriented LLMs, including prompt engineering, retrieval-augmented generation, knowledge-graph–assisted retrieval, domain fine-tuning, agent-based architectures, and continual pretraining. We further summarize recent advances in their applications, spanning scientific question answering and research assistance, synthesis design and property prediction, LLMs-enabled computational simulation workflows, and self-driving laboratory systems. Finally, we discuss critical challenges such as data scarcity and standardization, interpretability limitations, and safety and deployment costs, and outline future directions with an emphasis on multimodal intelligence. This review aims to offer a structured reference for the development and application of domain-specific LLMs in chemical materials research.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 144-165"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148646542","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":"Complexation induced highly loaded mixed-matrix membranes for organic azeotropic separation","authors":"Zhuo Yang,&nbsp;Lianhao Li,&nbsp;Yaxin Zhang,&nbsp;Haonan Yang,&nbsp;Haoyu Nie,&nbsp;Guozhen Liu,&nbsp;Gongping Liu,&nbsp;Wanqin Jin","doi":"10.1016/j.cjche.2026.05.020","DOIUrl":"10.1016/j.cjche.2026.05.020","url":null,"abstract":"<div><div>Mixed matrix membranes (MMMs), consisting of inorganic fillers in a polymer matrix, have shown great potential for molecular separation. Prussian blue analogues (PBAs) nanomaterials featuring regular and straight nanochannels are promising nanoporous fillers. However, fabricating defect-free PBA MMMs is challenging, particularly at a high loading. Herein, we proposed a complexation-assisted strategy to construct a highly loaded Cu–Fe PBA MMM for the pervaporation separation of a methanol (MeOH)/dimethyl carbonate (DMC) azeotropic mixture. The membrane casting solution was synthesized by pre-dispersing a complexing agent, sodium citrate (SC), and CuCl₂ in a polymer solution, followed by <em>in situ</em> coordination with potassium hexacyanoferrate (III) (K₃[Fe(CN)₆]) to form PBA nanocrystals in the polymer matrix. SC formed a complex with CuCl₂, preventing Cu²⁺ from crosslinking the polymer and reducing the coordination rate by slowing the release of Cu²⁺, thereby achieving the uniform growth and dispersion of PBA nanocrystals in the MMM. The introduced PBA provided interconnected transport nanochannels and enhanced the membrane's affinity for MeOH over DMC. The PBA MMM with 60% (mass) loading exhibited a total flux of 2910 g·m⁻²·h⁻¹ and a separation factor of 337, outperforming state-of-the-art membranes for MeOH/DMC separation, showing great potential for organic solvents separation and purification.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 267-278"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148742876","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":"Room-temperature quasi-solid lithium metal batteries enabled by IL@HKUST-1 gel polymer electrolyte","authors":"Yuxin Zhu,&nbsp;Jiaxing Li,&nbsp;Lielin Xiang,&nbsp;Liang He,&nbsp;Chao Su,&nbsp;Zhong Li,&nbsp;Mohamed Mamlouk,&nbsp;Mindrov K. Anatolyevich,&nbsp;Tao Wei","doi":"10.1016/j.cjche.2026.04.015","DOIUrl":"10.1016/j.cjche.2026.04.015","url":null,"abstract":"<div><div>Based on the confinement of the ionic liquid (IL) within the HKUST-1 metal–organic framework (MOF), this work successfully developed a novel gel polymer electrolyte (HKU-5), for room-temperature (RT) quasi-solid lithium metal batteries. X-ray diffraction, scanning electron microscopy, N₂ adsorption-desorption isotherm analysis and different electrochemical characterizations were carried out. In Li|Li symmetric cells, HKU-5 enables stable lithium plating/stripping for over 800 h (0.1 mA·cm⁻²) and effectively suppresses lithium dendrite growth. When assembled Li|LiFePO₄ full cells using HKU-5 as the separator, it exhibits excellent cycling stability and interfacial compatibility, retaining a discharge specific capacity of 151.2 mA·h·g⁻¹ for 100 cycles at 0.5 C and RT. This study presents a promising IL@MOF-based strategy for developing next-generation electrolytes toward practical lithium metal batteries.</div></div>","PeriodicalId":9966,"journal":{"name":"Chinese Journal of Chemical Engineering","volume":"96 ","pages":"Pages 234-242"},"PeriodicalIF":3.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148740635","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}