检索结果-内蒙古大学图书馆

Machine learning-guided accelerated discovery of structure-property correlations in lean magnesium alloys for biomedical applications

引用

Journal of Magnesium and Alloys 2024年第6期12卷 2267-2283页

作者： Sreenivas Raguraman Maitreyee Sharma Priyadarshini Tram Nguyen Ryan McGovern Andrew Kim Adam J.Griebel Paulette Clancy Timothy P.Weihs Department of Materials Science and Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Hopkins Extreme Materials Institute Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Department of Chemical and Biomolecular Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Translational Tissue Engineering Center Johns Hopkins School of Medicine400 N BroadwayBaltimore21231MDU.S.A Department of Biomedical Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Research and Development Fort Wayne Metals Research ProductsLLC9609 Ardmore AveFort Wayne46809INU.S.A Department of Mechanical Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A

Magnesium alloys are emerging as promising alternatives to traditional orthopedic implant materials thanks to their biodegradability,biocompatibility,and impressive mechanical ***,their rapid in-vivo degradation presents challenges,notably in upholding mechanical integrity over *** study investigates the impact of high-temperature thermal processing on the mechanical and degradation attributes of a lean Mg-Zn-Ca-Mn alloy,*** rapid,cost-efficient characterization methods like X-ray diffraction and optical microscopy,we swiftly examine microstructural changes post-thermal *** Pearson correlation coefficient analysis,we unveil the relationship between microstructural properties and critical targets(properties):hardness and corrosion ***,leveraging the least absolute shrinkage and selection operator(LASSO),we pinpoint the dominant microstructural factors among closely correlated *** findings underscore the significant role of grain size refinement in strengthening and the predominance of the ternary Ca_(2)Mg_(6)Zn_(3)phase in corrosion *** suggests that achieving an optimal blend of strength and corrosion resistance is attainable through fine grains and reduced concentration of ternary *** thorough investigation furnishes valuable insights into the intricate interplay of processing,structure,and properties in magnesium alloys,thereby advancing the development of superior biodegradable implant materials.

关键词： Magnesium alloys Machine learning Corrosion Mechanical properties Rapid characterization

来源：评论

学校读者我要写书评

暂无评论

Gene expression modulation tools for bacterial synthetic biology

引用

Biotechnology for Sustainable Materials 2024年第1期1卷 1-10页

作者： Chang, Minjun Ahn, Se Jun Han, Taehee Yang, Dongsoo Synthetic Biology and Enzyme Engineering Laboratory Department of Chemical and Biological Engineering Korea University Seoul Republic of Korea Metabolic and Biomolecular Engineering National Research Laboratory and Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory Department of Chemical and Biomolecular Engineering (BK21 Four) Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea BioProcess Engineering Research Center KAIST Daejeon Republic of Korea

Synthetic biology has revolutionized the creation of microbial cell factories for the efficient production of value-added chemicals and materials from renewable resources. The rational design of these factories is based on the ability to precisely regulate the expression of multiple genes, enabling the programming of cells to exhibit desired behaviors. Tools for modulating gene expression facilitates the construction of intricate genetic circuits and complex metabolic pathways optimized for the efficient production of target chemicals and materials. In this review, we delve into recent synthetic biology tools and strategies that are used to efficiently control transcription, translation, as well as other gene expression-related processes. Representative examples emphasizing their practical applications are also illustrated. Additionally, we discuss future perspectives on the development and application of gene expression modulation tools, envisioning their pivotal role towards fostering a more sustainable bio-based economy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

引用

Joule 2024年第7期8卷 1958-1981页

作者： Maradesa, Adeleke Py, Baptiste Huang, Jake Lu, Yang Iurilli, Pietro Mrozinski, Aleksander Law, Ho Mei Wang, Yuhao Wang, Zilong Li, Jingwei Xu, Shengjun Meyer, Quentin Liu, Jiapeng Brivio, Claudio Gavrilyuk, Alexander Kobayashi, Kiyoshi Bertei, Antonio Williams, Nicholas J. Zhao, Chuan Danzer, Michael Zic, Mark Wu, Phillip Yrjänä, Ville Pereverzyev, Sergei Chen, Yuhui Weber, André Kalinin, Sergei V. Schmidt, Jan Philipp Tsur, Yoed Boukamp, Bernard A. Zhang, Qiang Gaberšček, Miran O'Hayre, Ryan Ciucci, Francesco Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong Metallurgical and Materials Engineering Colorado School of Mines Golden80401 United States Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical Engineering Tsinghua University Beijing China Green Energy Storage Trento38123 Italy Department of Manufacturing and Production Engineering Faculty of Mechanical Engineering and Ship Technology Institute of Machine and Materials Technology Gdańsk University of Technology Gdańsk Poland Electrode Design for Electrochemical Energy Systems University of Bayreuth Bayreuth Germany School of Chemistry University of New South Wales Sydney Australia School of Advanced Energy Sun Yat-Sen University Shenzhen China Sustainable Energy Center CSEM Neuchâtel2002 Switzerland Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Centre for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Department of Civil and Industrial Engineering University of Pisa Pisa Italy Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Department of Chemical Engineering Massachusetts Institute of Technology Cambridge02139 United States Electrical Energy Systems University of Bayreuth Bayreuth Germany Ruder Boskovic Institute Zagreb Croatia Department of Materials and Minerals Resources Engineering National Taipei University Taipei Taiwan Finland Johann Radon Institute for Computational and Applied Mathematics Linz Austria School of Science and Engineering Nanjing Tech. University Nanjing China Karlsruhe Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Physical Science Division Pacific Northwest National Laboratory RichlandWA99354 United States Systems Engineering for Electrical Energy Storage University of B

Electrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric models, such as the distribution of relaxation times (DRT, also known as the distribution function of relaxation times, DFRT), have emerged as promising tools for EIS analysis. For example, the DRT can be used to generate equivalent circuit models, initialize regression parameters, provide a time-domain representation of EIS spectra, and identify electrochemical processes. However, mastering the DRT method poses challenges as it requires mathematical and programming proficiency, which may extend beyond experimentalists’ usual expertise. Post-inversion analysis of DRT data can be difficult, especially in accurately identifying electrochemical processes, leading to results that may not always meet expectations. This article examines non-parametric EIS analysis methods, outlining their strengths and limitations from theoretical, computational, and end-user perspectives, and provides guidelines for their future development. Moreover, insights from survey data emphasize the need to develop a large impedance database, akin to an impedance genome. In turn, software development should target one-click, fully automated DRT analysis for multidimensional EIS spectra interpretation, software validation, and reliability. Particularly, creating a collaborative ecosystem hinged on free software could promote innovation and catalyze the adoption of the DRT method throughout all fields that use impedance data. © 2024 Elsevier Inc.

关键词： Electrochemical impedance spectroscopy

来源：评论

学校读者我要写书评

暂无评论

Novel entrance and exit designs towards fully developed dual Vortexes in cyclone separators

引用

Advanced Powder Technology 2025年第7期36卷

作者： Wang, C.M. Wang, T.F. Fukui, K. Fukasawa, T. Hsu, W.Y. Huang, A.N. Kuo, H.P. Department of Chemical Engineering National Taiwan University Taipei106319 Taiwan Chemical Engineering Program of Advanced Science and Engineering Hiroshima University 739-8527 Japan Center for Sustainability and Energy Technologies Chang Gung University Taoyuan33302 Taiwan Department of Chemical Engineering National Taiwan University of Science and Technology Taipei106335 Taiwan

Stairmand-type cyclones are commonly used in industry to separate particles from gas streams by inertia, driven by the dual-vortex flow patterns. Here, new designs are proposed to eliminate the local non-ideal vortex patterns in a conventional Stairmand cyclone by inserting a flow divider at the entrance and adjusting the elbow exit orientation. A two-way coupled CFD–DPM approach is employed to analyze the performance of the modified cyclones. Simulation results show that the cyclone with the elbow exit oriented orthogonal to the entrance direction demonstrates better performance in terms of the cut size and sharpness. The installation of the flow divider reduces the vortex eccentricity by approximately 50%. The flow divider increases the gas velocity near the outer wall, allowing the quasi-free vortex in the cyclone's outer region to become nearly fully developed at the entrance section through the reduction of the local secondary recirculation flows. The optimum flow divider outer wall thickness correlates to the wall shear stress distribution. With the optimum 2 mm outer wall thickness flow divider installed, the separation efficiency for 2 μm particles increases from 56.74% to 77.4%, and the cut size decreases from 1.87 μm to 1.23 μm. © 2025 The Society of Powder Technology Japan

关键词： Shear stress

来源：评论

学校读者我要写书评

暂无评论

Correction: Materials laboratories of the future for alloys, amorphous, and composite materials (MRS Bulletin, (2025), 50, 2, (190-207), 10.1557/s43577-024-00846-y)

引用

MRS Bulletin 2025年 1-2页

作者： Banerjee, Sarbajit Meng, Y. Shirley Minor, Andrew M. Zhang, Minghao Zaluzec, Nestor J. Chan, Maria K.Y. Seidler, Gerald McComb, David W. Agar, Joshua Mukherjee, Partha P. Melot, Brent Chapman, Karena Guiton, Beth S. Klie, Robert F. McCue, Ian D. Voyles, Paul M. Robertson, Ian Li, Ling Chi, Miaofang Destino, Joel F. Devaraj, Arun Marquis, Emmanuelle A. Segre, Carlo U. Liu, Huinan H. Yang, Judith C. Momeni, Kasra Misra, Amit Abdolrahim, Niaz Medvedeva, Julia E. Cai, Wenjun Sehirlioglu, Alp Dizbay-Onat, Melike Mehta, Apurva Graham-Brady, Lori Maruyama, Benji Rajan, Krishna Warner, Jamie H. Taheri, Mitra L. Kalinin, Sergei V. Reeja-Jayan, B. Schwarz, Udo D. Simon, Sindee L. Brown, Craig M. Department of Chemistry and Department of Materials Science & Engineering Texas A & M University College Station United States Pritzker School of Molecular Engineering The University of Chicago Chicago United States Department of Materials Science & Engineering University of California Berkeley Berkeley United States National Center for Electron Microscopy Molecular Foundry Lawrence Berkeley National Laboratory Berkeley United States Center for Nanoscale Materials Argonne National Laboratory Lemont United States Department of Physics University of Washington Seattle United States Department of Materials Science & Engineering The Ohio State University Columbus United States Department of Mechanical Engineering and Mechanics Drexel University Philadelphia United States School of Mechanical Engineering Purdue University West Lafayette United States Department of Chemistry University of Southern California Los Angeles United States Department of Chemistry Stony Brook University The State University of New York Stony Brook United States Department of Chemistry University of Kentucky Lexington United States Department of Physics University of Illinois at Chicago Chicago United States Department of Materials Science & Engineering Northwestern University Evanston Bangladesh Department of Materials Science & Engineering University of Wisconsin–Madison Madison United States Department of Materials Science and Engineering University of Pennsylvania Philadelphia United States Department of Mechanical Engineering and Materials Science Duke University Durham United States Department of Chemistry Creighton University Omaha United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory Richland United States Department of Materials Science & Engineering University of Michigan–Ann Arbor Ann Arbor United States Department of Physics Illinois Institute of Technology Chicago United States Department of Bioengineering and the Mater

This article was updated to correct Minghao Zhang’s affiliation from "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA" to "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA;Argonne National Laboratory, Lemont, USA." Argonne National Laboratory was left off the original publication. © The Author(s) 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Modulating Oxygen Affinity to Enhance Liquid Products for the Electrochemical Reduction of Carbon Monoxide

引用

SmartMat 2025年第2期6卷 214-223页

作者： Jiayi Chen Juan Manuel Arce-Ramos Ioannis Katsounaros Emiel de Smit Saifudin MAbubakar Yanwei Lum Jia Zhang Lei Wang State Key Laboratory of Photocatalysis on Energy and Environment College of ChemistryFuzhou UniversityFuzhouChina Department of Chemical and Biomolecular Engineering National University of SingaporeSingaporeSingapore Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)SingaporeSingapore ExxonMobil Chemical Europe LLC MachelenBelgium ExxonMobil Asia Pacific Pte.Ltd SingaporeSingapore Centre for Hydrogen Innovations National University of SingaporeSingaporeSingapore

Electrocatalytic CO reduction(COR)offers a promising alternative approach for synthesizing valuable chemicals,potentially at a lower carbon intensity as compared to conventional chemical ***-based catalysts have shown encouraging selectivity and activity toward multi-carbon(C^(2+))products,albeit typically in the form of a *** COR selectivity toward specific types of C2+products,such as liquid products with high energy density,remains a *** this study,we developed a Cu/Zn bimetallic catalyst composite and demonstrated enhanced selectivity toward liquid products as compared to reference CuO and Cu-based catalysts,approaching 60%at a high current density of 300 mA/cm^(2).Our investigation highlights that the introduction of Zn promoted the emergence of a Cu/Zn heterojunction interface during *** functional theory simulations were used to rationalize the observed differences in selectivity,revealing that interface plays a crucial role in diminishing the oxygen adsorption at the Cu-sites and modifying the adsorption energy of COR reaction intermediates,consequently leading to enhanced selectivity toward liquid products.

关键词： C_(2)liquid production CO_(2)/CO reduction copper/zinc electrocatalysts oxygen affinity

来源：评论

学校读者我要写书评

暂无评论

Spatially Resolved Spectroscopy for Electron Beam Patterned Metal-Organic-Based Materials 42

Spatially Resolved Spectroscopy for Electron Beam Patterned ...

引用

Advances in Patterning Materials and Processes XLII

作者： Kraetz, Andrea Miao, Yurun Waltz, Kayley E. Prerna, Prerna Ahmad, Mueed Boscoboinik, J. Anibal Siepman, J. Ilja Tenney, Samuel Tsapatsis, Michael Department of Chemical and Biomolecular Engineering Institute for NanoBioTechnology Johns Hopkins University BaltimoreMD21218 United States Department of Chemical Engineering and Materials Science University of Minnesota MinneapolisMN55455 United States Center for Functional Nanomaterials Brookhaven National Laboratory UptonNY11973 United States Department of Materials Science and Chemical Engineering Stony Brook University Stony BrookNY11790 United States Department of Chemistry Chemical Theory Center University of Minnesota MinneapolisMN55455 United States Applied Physics Laboratory Johns Hopkins University LaurelMD20723 United States

ISBN: (纸本)9781510686427

Spatially resolved spectroscopy was used to determine spectroscopic signatures of electron beam induced changes in a metal-organic framework called Zeolitic Imidazolate Framework (ZIF)-L. Investigation of the structural changes caused by e-beam treatment were then used to develop a process for pattern development. ZIF-L exhibits dual-tone behavior depending on the choice of solvent, producing both negative and positive tone patterns. © 2025 SPIE.

关键词： Electron spectroscopy

来源：评论

学校读者我要写书评

暂无评论

Novel amino-beta cyclodextrin-based organic solvent nanofiltration membranes with fast and stable solvent transport

引用

Journal of Membrane science 2024年 689卷

作者： Abdi, Zelalem Gudeta Chen, Jyh-Chien Chung, Tai-Shung Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Materials Science and Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Chemical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Chemical & Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 117585 Singapore

To expand industrial utilizations, membranes with fast transport of organic solvents and precision molecular separation, along with strong chemical stability, have great potential for minimizing energy consumption in separation processes. In this study, novel amino-cyclodextrin organic solvent nanofiltration (OSN) membranes containing P84 polymer were successfully fabricated using amino-cyclodextrin and amino-5-guanidinopentanoic acid (DL-A) as monomers through a two-step green modification process. The resulting membranes exhibit high stability in harsh organic solvents, such as dimethylsulfoxide (DMSO) and N-methyl-2-pyrrolidone (NMP), with a weight loss of less than 5 % after 30 days of immersion. These membranes also demonstrate rapid solvent transport for both polar solvents, such as methanol (86.56 L m−2 h−1 bar−1), and nonpolar solvents, such as n-hexane (48.97 L m−2 h−1 bar−1), along with high dye rejections. Additionally, the membranes possess rigid nanopores structures and consistent rejections across different pressures and solute concentrations. Most importantly, the newly synthesized amino-cyclodextrin OSN membranes are capable of separating molecules based on their 3D structures, particularly those with relatively similar molecular weights. Comparing to those reported cyclodextrin-based membranes, the newly developed amino-cyclodextrin OSN membranes show significant improvements in permeance for both polar and nonpolar organic solvents, while maintaining comparable dye rejection capabilities. The combination of fast solvent transport, excellent chemical stability, and shape selectivity makes these membranes highly promising for high-performance molecular separation in various industrial applications. © 2023 Elsevier B.V.

关键词： Organic solvents

来源：评论

学校读者我要写书评

暂无评论

Catalytic conversion of lignocellulosic biomass into chemicals and fuels

引用

Green Energy & Environment 2023年第1期8卷 10-114页

作者： Weiping Deng Yunchao Feng Jie Fu Haiwei Guo Yong Guo Buxing Han Zhicheng Jiang Lingzhao Kong Changzhi Li Haichao Liu Phuc T.T.Nguyen Puning Ren Feng Wang Shuai Wang Yanqin Wang Ye Wang Sie Shing Wong Kai Yan Ning Yan Xiaofei Yang Yuanbao Zhang Zhanrong Zhang Xianhai Zeng Hui Zhou State Key Laboratory for Physical Chemistry of Solid Surfaces Collaborative Innovation Center of Chemistry for Energy MaterialsNational Engineering Laboratory for Green Chemical Productions of Alcohols-Ethers-Estersand College of Chemistry and Chemical EngineeringXiamen UniversityXiamen361005China Fujian Engineering and Research Center of Clean and High-valued Technologies for Biomass Xiamen Key Laboratory of High-valued Utilization of BiomassCollege of EnergyXiamen University361102China Key Laboratory of Biomass Chemical Engineering of Ministry of Education College of Chemical and Biological EngineeringZhejiang UniversityHangzhou310027China Institute of Zhejiang University-Quzhou 78 Jiuhua Boulevard NorthQuzhou324000China School of Energy and Environmental Engineering Hebei University of TechnologyTianjin300401China Shanghai Key Laboratory of Functional Materials Chemistry Research Institute of Industrial CatalysisSchool of Chemistry and Molecular EngineeringEast China University of Science and TechnologyShanghai200237China Beijing National Laboratory for Molecular Sciences CAS Key Laboratory of Colloid and Interface and ThermodynamicsCAS Research/Education Center for Excellence in Molecular SciencesInstitute of ChemistryChinese Academy of SciencesBeijing100190China Department of Biomass Science and Engineering Sichuan UniversityChengdu610065China CAS Key Laboratory of Low-carbon Conversion Science and Engineering Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai201210China University of Chinese Academy of Sciences Beijing100049China CAS Key Laboratory of Science and Technology on Applied Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian116023China Beijing National Laboratory for Molecular Sciences College of Chemistry and Molecular EngineeringPeking UniversityBeijing100871China Department of Chemical and Biomolecular Engineering National University of Singapore4 Engineering Drive 4Singapore117585Singapore Sta

In the search of alternative resources to make commodity chemicals and transportation fuels for a low carbon future,lignocellulosic biomass with over 180-billion-ton annual production rate has been identified as a promising *** review focuses on the state-of-the-art catalytic transformation of lignocellulosic biomass into value-added chemicals and *** a brief introduction on the structure,major resources and pretreatment methods of lignocellulosic biomass,the catalytic conversion of three main components,i.e.,cellulose,hemicellulose and lignin,into various compounds are comprehensively *** in separate steps or in one-pot,cellulose and hemicellulose are hydrolyzed into sugars and upgraded into oxygen-containing chemicals such as 5-HMF,furfural,polyols,and organic acids,or even nitrogen-containing chemicals such as amino *** the other hand,lignin is first depolymerized into phenols,catechols,guaiacols,aldehydes and ketones,and then further transformed into hydrocarbon fuels,bioplastic precursors and bioactive *** review then introduces the transformations of whole biomass via catalytic gasification,catalytic pyrolysis,as well as emerging ***,opportunities,challenges and prospective of woody biomass valorization are highlighted.

关键词： Lignocelullose Biomass Catalytic conversion Biofuels Renewable chemicals

来源：评论

学校读者我要写书评

暂无评论

AI for organic and polymer synthesis

引用

science China Chemistry 2024年第8期67卷 2461-2496页

作者： Xin Hong Qi Yang Kuangbiao Liao Jianfeng Pei Mao Chen Fanyang Mo Hua Lu Wen-Bin Zhang Haisen Zhou Jiaxiao Chen Lebin Su Shuo-Qing Zhang Siyuan Liu Xu Huang Yi-Zhou Sun Yuxiang Wang Zexi Zhang Zhunzhun Yu Sanzhong Luo Xue-Feng Fu Shu-Li You Center of Chemistry for Frontier Technologies Department of ChemistryZhejiang UniversityHangzhou 310027China Center of Basic Molecular Science Department of ChemistryTsinghua UniversityBeijing 100084China Guangzhou National Laboratory Guangzhou 510005China Center for Quantitative Biology Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular ScienceFudan UniversityShanghai 200433China School of Materials Science and Engineering Peking UniversityBeijing 100871China Beijing National Laboratory for Molecular Sciences Center for Soft Matter Science and EngineeringKey Laboratory of Polymer Chemistry and Physics of Ministry of EducationCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China AI for Science(AI4S)-Preferred Program Shenzhen Graduate SchoolPeking UniversityShenzhen 518055China State Key Laboratory of Chemical Biology Shanghai Institute of Organic ChemistryUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200032China Department of Chemical Sciences National Natural Science Foundation of ChinaBeijing 100085China State Key Laboratory of Organometallic Chemistry Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai 200032China

Recent years have witnessed the transformative impact from the integration of artificial intelligence with organic and polymer synthesis. This synergy offers innovative and intelligent solutions to a range of classic problems in synthetic chemistry. These exciting advancements include the prediction of molecular property, multi-step retrosynthetic pathway planning, elucidation of the structure-performance relationship of single-step transformation, establishment of the quantitative linkage between polymer structures and their functions, design and optimization of polymerization process, prediction of the structure and sequence of biological macromolecules, as well as automated and intelligent synthesis platforms. Chemists can now explore synthetic chemistry with unprecedented precision and efficiency, creating novel reactions, catalysts, and polymer materials under the datadriven paradigm. Despite these thrilling developments, the field of artificial intelligence(AI) synthetic chemistry is still in its infancy, facing challenges and limitations in terms of data openness, model interpretability, as well as software and hardware support. This review aims to provide an overview of the current progress, key challenges, and future development suggestions in the interdisciplinary field between AI and synthetic chemistry. It is hoped that this overview will offer readers a comprehensive understanding of this emerging field, inspiring and promoting further scientific research and development.

关键词： organic synthesis polymer synthesis machine learning prediction chemical database automated synthesis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：