Identifying Unknown Crystal Structures Prior to Experiments — Designing and Applying Crystal Structure Prediction with Matlantis CSP —

Event Overview

While crystal structure prediction (CSP) is an important approach for identifying unknown stable crystals and evaluating phase stability, it can be difficult to know when and how to utilize it in actual research. This webinar will explore Matlantis CSP, a new feature in Matlantis, to explain how crystal structure prediction can support decision-making in the early research phase when the crystal structure is still unknown. It will also provide specific guidance on how to select the appropriate search method (global search or permutation search) based on research objectives, how to design search conditions, and how to post-analyze the search results and apply them to experiments and subsequent processes. Using actual use cases, the lecturer, who is involved in the development and research of Matlantis CSP, will introduce how to utilize crystal structure searching as a "process that supports research decisions" rather than a "computational task." This content is aimed at Matlantis users who want to clarify the role of CSP in crystal structure searching research, from those who are just starting to use Matlantis CSP to those who are already using it and want to deepen their understanding.

【Speakers】

Preferred Networks, Inc.　

Kohei Shinohara

He graduated from the Department of Engineering Physics, Faculty of Engineering, Kyoto University in 2018, earning a Bachelor of Engineering.
In 2020, he graduated from the Graduate School of Engineering, Kyoto University, majoring in Materials Engineering, and obtained a Master's degree in Engineering.
He will complete his studies in the department in 2023 and obtain a PhD in Engineering.
Since 2023, he has been working as a researcher at Preferred Networks, Inc.
His specialties are computational science-based crystal structure search, computational crystallography, and scientific software development.

【Webinar Details】

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