Events

Considering the global spread of new coronavirus infectious diseases, we have decided to cancel the VAMAS Workshop on "Data Driven Materials Science and Metrology".

 Date: 30 September 2020

Chairs: Dr. Daisuke Fujita (NIMS, Japan), Dr. Toshiyuki Fujimoto (AIST, Japan) 

Registration fee: Free (Except mixer fee. It must be paid in Japanese yen at the registration desk.)
All participants are required to register. Pre-registration is required for reception and banquet.

External Registration link will be opened soon. 

Background

Data-driven materials science is an emerging field of study that applies the principles of informatics to materials science to accelerate the selection, development, and discovery of materials. In a recent data-intensive metrological system, novel tools of informatics that can be applied to giga-sized measurement data are increasingly required. Accordingly, the fusion of metrology and informatics, that is, “measurement informatics” is emerging as a new paradigm. Thus, data-driven materials science and metrology will open a very wide spectrum of new applications in different technical areas. Real applications of the data-driven materials science and metrology in engineering and industry require the development of universal data format, the comprehensive platforms of materials properties and metrological data, the online access of multidimensional data, the novel tools to extract embedded information. This workshop will present the state-of-the-art achievements of current projects on data-driven materials science and metrology and will discuss the role of standardization and pre-standardization activities.

Topics

• Data platform for comprehensive materials properties and metrological data
• Modeling and code validation on test data sets for artificial intelligence (AI) and machine learning
• AI-based smart laboratory: autonomous experiment algorithm and protocol for materials processing and analysis
• Data infrastructure and workflow: metadata capture, tracking and collating multimodal data
• Standardizing data and/or information formats for multi-modal materials data