Jian Hui , Yang Ren,Hong Wang
School of Materials Science and Engineering, Zhangjiang Institute for Advanced Study, Zhiyuan
Innovative Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
Department of Physics, City University of Hong Kong, Kowloon, Hong Kong, China
EXTENDED ABSTRACT: The AI for Science research model, which features "data-driven +AI", represents the development strategy of material genome engineering, and has become a revolutionary tool to promote advanced "smart" manufacturing. In particular, the source of data is at the very core of the paradigm change in materials genome research. The construction of high-throughput experimental platforms is essential for the generation of experimental data in the datadriven paradigm. In recent years, the on-fly autonomous closed-loop intelligent material screening with "high-throughput experimental data + AI" as the core elements is a novel high-throughput experimental research approach. It integrates highthroughput experimental technology and active learning data analysis methods. This research method intelligently optimizes the experimental scheme, thus dramatically accelerating the screening process of new materials. This paper introduces the construction and typical cases of the on-the-fly autonomous closed-loop high-throughput comprehensive research platform, which integrates high-throughput preparation of combinatorial multilayer thin film, multi-parameter high-throughput isocharacterization, and automatic and intelligent data mining, at the Materials Genomics Research Center of Shanghai Jiao Tong University. The future development and cross-cooperation models in the field of materials genomics are also prospected.
Keywords: High-throughput synthesis; Multiple parameter high-throughput coupled-site characterization; Combinatorial multilayer thin film; on-the-fly research approach.
Dr. Jian Hui is an assistant research fellow at the School of Materials Science and Engineering, Zhangjiang Institute for Advanced Study of Shanghai Jiao Tong University. She graduated from the School of Materials Science and Engineering of Shanghai Jiao Tong University in 2020 with a Ph.D. She attended the University of Illinois at Urbana-Champaign for a visiting fellowship from 2019 to 2021. Since 2016, she has focused on the construction of high-throughput comprehensive experimental platforms and related technology research and development. As a key member, she has participated in several national key projects of material genetic engineering and guided multiple "Zhiyuan Scholar" projects at Shanghai Jiaotong University. She led the establishment of a data-driven platform at Shanghai Jiao Tong University that integrates high-throughput preparation, high-throughput characterization, automated data analysis, and machine learning data mining. She utilized the data-driven model to systematically study the phase transition and diffusion mechanism of the combinatorial thin film with a superlattice-like structure, which has filled the absence of systematic experimental data in this field. At the same time, she investigated the interaction of thin film with synchrotron X-rays using a time-resolved in situ synchrotron high throughput characterization technique combined with an Ag-Cu combination material chip. For the first time, the room temperature nitrogen fixation reaction was achieved and the irradiation damage mechanism was quantitatively and systematically excavated, which provided the experimental and theoretical basis for avoiding synchrotron radiation damage. During her visit to the U.S., she utilized the ultrafast nano-DSC technique to study the fast reversible phase transformation and failure mechanism of phase change material thin films, which overturned the previous conclusions of the past 10 years and published the cover article. She has published more than 10 SCI papers in the field of high throughput experiments in reputable journals such as Small, ACS Applied Materials & Interfaces, Materials& Design, etc., and applied for/authorized 3 invention patents.