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Developing an atmospheric aging evaluation model of acrylic coatings:A semi-supervised machine learning algorithm
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作者 Yiran Li zhongheng fu +5 位作者 Xiangyang Yu Zhihui Jin Haiyan Gong Lingwei Ma Xiaogang Li Dawei Zhang 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2024年第7期1617-1627,共11页
To study the atmospheric aging of acrylic coatings,a two-year aging exposure experiment was conducted in 13 representative climatic environments in China.An atmospheric aging evaluation model of acrylic coatings was d... To study the atmospheric aging of acrylic coatings,a two-year aging exposure experiment was conducted in 13 representative climatic environments in China.An atmospheric aging evaluation model of acrylic coatings was developed based on aging data including11 environmental factors from 567 cities.A hybrid method of random forest and Spearman correlation analysis was used to reduce the redundancy and multicollinearity of the data set by dimensionality reduction.A semi-supervised collaborative trained regression model was developed with the environmental factors as input and the low-frequency impedance modulus values of the electrochemical impedance spectra of acrylic coatings in 3.5wt%NaCl solution as output.The model improves accuracy compared to supervised learning algorithms model(support vector machines model).The model provides a new method for the rapid evaluation of the aging performance of acrylic coatings,and may also serve as a reference to evaluate the aging performance of other organic coatings. 展开更多
关键词 acrylic coatings coatings aging atmospheric environment machine learning
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Universal machine learning potential accelerates atomistic modeling of materials
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作者 zhongheng fu Dawei Zhang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2023年第8期1-2,I0002,共3页
With the rapid development of computer techniques,atomistic modeling is playing an increasingly important role in understanding the structure-activity relationship of materials.Molecular dynamics (MD) is a computation... With the rapid development of computer techniques,atomistic modeling is playing an increasingly important role in understanding the structure-activity relationship of materials.Molecular dynamics (MD) is a computational simulation approach to predicting the structural evolution of an atomic system over time,widely used to understand physical and chemical phenomena including phase transition,diffusion,crystallization,and reaction [1]. 展开更多
关键词 MACHINELEARNING Atomisticmodeling Neural networkpotential Solid-statematerials
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电催化还原氮制氨的最新进展
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作者 海广通 富忠恒 +1 位作者 刘欣 黄秀兵 《Chinese Journal of Catalysis》 SCIE CAS 2024年第5期107-127,共21页
氮还原反应在生态系统、农业系统和工业氮循环中发挥着至关重要的作用.然而,由于氮气在水中的溶解度低,N≡N三键结构稳定,且存在与析氢反应的激烈竞争,因此目前电化学氮还原反应面临着产率缓慢、法拉第效率低等挑战.尽管研究者们通过不... 氮还原反应在生态系统、农业系统和工业氮循环中发挥着至关重要的作用.然而,由于氮气在水中的溶解度低,N≡N三键结构稳定,且存在与析氢反应的激烈竞争,因此目前电化学氮还原反应面临着产率缓慢、法拉第效率低等挑战.尽管研究者们通过不懈的努力已经在该领域取得了显著的进展,但距离其实际应用仍有较大差距.因此,如何通过多方面的调控手段,尽早实现人工固氮的工业化生产,成为当前该领域亟待解决的关键问题.本文系统梳理了电催化还原氮制氨的最新进展.首先,对NRR的机理进行了全面介绍.详细介绍了五种备受关注的氮还原机理:解离机理、结合机理、交替机理、酶促机理以及最新发现的马尔斯-范克雷维伦机理.通过对比电催化氮还原与哈珀法催化氮还原的反应机理,阐明了电催化氮还原的优势.然后,总结了该领域最新的研究进展.详细介绍了高性能氮还原催化剂的最新设计开发成果,基于近五年的相关报道,重点介绍了Mo基催化剂、Cu基催化剂、Ru基催化剂、Bi基催化剂和Fe基催化剂的研究进展.此外,对其他过渡金属基催化剂和非金属催化剂也进行了评述和展望,并对不同催化剂的优缺点进行了系统的比较.随后,对新型氮还原反应装置的研究进展进行了综述.讨论了新型反应器对缓解氮分子低溶解度这一问题的关键作用,强调了研发新型氮还原反应装置对提升电催化氮还原性能的重要性.在NRR反应路径的调控和优化方面,本文总结了最新的研究成果,特别是Li介导的氮还原反应的重要意义,证实了反应路径的调控优化是提升氮还原性能的有效手段.更为重要的是,从目前最新的研究成果出发,提出了氮还原性能的提升需要多方面的协同调控,单一的优化手段难以突破现有的瓶颈,这为后续的研究提供了重要参考.在展望部分,强调了氮还原领域目前面临的挑战并讨论了未来的研究方向.综上,本文系统地总结了近年来的研究进展,包括高性能催化剂、新型反应设备以及氮还原反应路径的调控和优化.提升氮还原反应的整体性能需要多方面的协调调控,仅关注催化剂很难取得重大突破.本文旨在为氮还原催化剂和反应器的设计以及反应路径的调控优化提供参考. 展开更多
关键词 氮还原反应 电催化 催化剂 反应设备 反应途径
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