Machine learning for materials chemistry
Machine learning has huge potential as a tool to investigate new materials and new applications of existing materials, as well as to streamline and focus future experimentation through rapid screening. This Collection Explores the use of machine learning in all aspects of materials chemistry, from discovering and designing new materials to modelling and optimising their performance, defining structure-property relationships and identifying new applications.
Editors
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Ting Liao
Queensland University of Technology, Australia
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Taylor Sparks
University of Utah, USA
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Hao Yu
Southern University of Science and Technology, China
Ting Liao is an Associate Professor at the School of Mechanical Medical & Process Engineering from Queensland University of Technology, Australia. As a computational chemistry academic, Prof Liao is interested in the unique properties of low dimensional materials which cannot be obtained from the corresponding bulk forms. She has been focusing on computational design of low dimensional materials in diverse energy application, including catalysis and energy storage. Prof Liao has been an Editorial Board Member for Scientific Reports since 2015.
Taylor Sparks is an Associate Professor and Associate Chair of the Materials Science and Engineering Department at the University of Utah, USA. His current research centers on using materials informatics for the discovery, synthesis, characterization, and properties of new materials for energy applications. He also hosts a podcast entitled “Materialism” where he discusses the past, present, and future of Materials Science. Prof Sparks has been an Editorial Board Member for Scientific Reports since 2019.
Hao Yu is a tenured Professor and Associate Dean at the School of Microelectronics from the Southern University of Science and Technology in Shenzhen, China. He obtained his M.S and PhD degrees at UCLA, USA. His main research interest lies in emerging technologies for machine learning. Prof Yu has been an Editorial Board Member for Scientific Reports since 2016.
