Progress in the Construction of On-the-ffy High-throughput Experimental“Data Factory”

EXTENDED ABSTRACT: The “Data+Knowledge” dual-driven new paradigm of materials R&D is an innovative support for the Intelligent and high-quality development of materials industry. In particular, data is a core component of the new materials R&D infrastructure, and standardised ‘data factories’ adapted with artificial intelligence to integrate common disruptive technologies in the ffeld of genetic engineering of materials are irreplaceable infrastructures that drive paradigm change. The on-the-ffy autonomous closed-loop pattern based on ‘standardised material big data + artiffcial intelligence’ is an innovative example of a paradigm transformation. It releases the full potential of data through a strong combination of standardised data and AI technology, and leads the international leadership. The team has developed an on-the-ffy autonomous closed-loop intelligent ‘data factory’ prototype at Shanghai Jiao Tong University, relying on the genetically engineered materials common subversive technologies and synchrotron radiation. This report presents the progress of the ‘On-the-Fly High-Throughput Experimental “Data Factory” and the typical application cases in material discovery and development.

Keywords: Materials Data Standards; "Data Factory"; MGE common subversive technologies; on-the-ffy research approach.

Brief Introduction of Speaker
Jian, Hui

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. 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 has published more than 20 SCI papers in the ffeld of high throughput experiments in reputable journals such as Small, Engineering, Materials& Design, etc., and applied for/authorized several patents.