Preferred Computational Chemistry
Technical Sales & Customer Success Department,
Senior Manager

Mr. Akihiro Nagoya

2005 Osaka university, Master of Engineering
2007 TOYOTA CENTRAL R&D LABS., INC.
2022 ENEOS Corporation
2023 Preferred Computational Chemistry, Inc. (PFCC)

Matlantis is a AI-based universal atomic-level simulator that has been trained on extensive computational dataset. Since its domestic launch as a cloud service in 2021, Matlantis has steadily increased its user base, and it has embarked on international expansion in 2023. By using Matlantis, atomic-level simulations are significantly acceleratesd. Simulations that previously took several months are completed in a few hours. These advances have enabled the industrial application of computational chemistry, addressing challenges previously considered difficult with conventional simulation methods.
While Matlantis has successfully applied to various materials, we receive needs from our customers that are not applicable to Matlantis. In this presentation, I will provide an overview of Matlantis, showcase recent computational case studies, and then discuss the challenges faced and future prospects for expanding the service.

Tohoku University
Advanced Institute for Materials Research (WPI-AIMR)
Research professor/ Emeritus professor

Prof. Tadafumi Adschiri

Graduated from the Faculty of Engineering, University of Tokyo in 1981, and completed the doctoral course there in 1986. In 1987, he became a teaching / research associate at University of Tokyo. In 1989, he arrived at Tohoku University. He has been a professor since 2002. He developed a new academic field as a pioneer of various "supercritical reactions" using supercritical water. He has published more than 320 papers, 13,015 citations, and an h-index of 67 (Web of Science, Dec.1st, 2023). For his research excellence, he has received numerous awards, including The Chemical Society of Japan (CSJ) Award for 2020, The Society of Chemical Engineers, Japan (SCEJ) Award for 2012, the Minister of Education, Culture, Sports, Science and Technology (METI) Commendation for 2010, and the Minister of Education, Culture, Sports, Science and Technology (METI) Award twice, as well. He received the Medal with Purple Ribbon at the spring conferment of decorations in 2019.

MI is a structure-property/function relationship, and is an effective method for exploring structures of materials to achieve desired physical properties and functions. On the other hand, for the commercialization of the new materials or devices, it’s crucial to establish the process to achieve optimization of new materials, structured materials, and devices, that is, the process-structure relationship. In the future of materials informatics, it’ll be vital to predict optimal structures and further integrate them with processes to create process-structure-function relationships, eventually for predict material and process design. However, for that purpose, elucidating the principles/mechanism is critical. Here, we’ll focus on nanoparticle dispersion systems (nanofluids, nanocomposites), and consider the process-structure relationship by focusing on the prediction of dispersion and aggregation, the associated viscosity, and the structure formation associated with coating and drying.