Oral Session

[A5-O101] Oral 101

2023年12月11日(月) 13:30 〜 16:00 Session 2 (Room C-2)

Chair: Hiori Kino (NIMS), Milica Todorović (University of Turku), Tetsuya Fukushima (AIST)

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13:30 〜 13:50

[A5-O101-01 (Symposium Invited)] Universal neural network potential applicable to arbitrary combination of 72 elements

*So Takamoto¹ (1. Preferred Networks, Inc. (Japan))

13:50 〜 14:10

[A5-O101-02 (Symposium Invited)] On-the-fly machine learning potential and applications to energy materials

*Ryoji Asahi¹ (1. Nagoya Univ. (Japan))

14:10 〜 14:30

[A5-O101-03 (Symposium Invited)] Ab Initio Thermodynamic Sampling of Millions of Configurations in Many-Component Oxides Accelerated by Machine Learning

*Shusuke Kasamatsu¹, Tatsumi Aoyama², Yuichi Motoyama², Kazuyoshi Yoshimi², Akihide Kuwabara³, Takafumi Ogawa³, Junji Hyodo⁴, Yoshihiro Yamazaki⁴ (1. Yamagata Univ. (Japan), 2. Univ. of Tokyo (Japan), 3. Japan Fine Ceramics Center (Japan), 4. Kyushu Univ. (Japan))

14:30 〜 14:45

[A5-O101-04] A Neural Network Simulation Method to Investigate Ion Behavior under External Electric Fields: Applications to Crystalline and Amorphous Li₃PO₄

*Koji Shimizu¹, Ryuji Otsuka¹, Satoshi Watanabe¹ (1. UTokyo (Japan))

14:45 〜 15:00

[A5-O101-05] Stability and Equilibrium Structures of Unknown Ternary Metal Oxides Explored Using Machine-Learned Potentials

*Seungwoo Hwang¹, Jisu Jung¹, Changho Hong¹, Wonseok Jeong¹, Sungwoo Kang¹, Seungwu Han¹ (1. Seuol National Univ (Korea))

15:00 〜 15:15

[A5-O101-06] Constructing Reactive Neural Network Potentials for Simulating TiN Atomic Layer Deposition

*Hyungmin An¹, Jisu Jung¹, Jisu Kim¹, Jaesun Kim¹, Seungwu Han¹ (1. Seoul National Univ. (Korea))

Break （15:15 〜 15:25）

15:25 〜 15:45

[A5-O101-07 (Symposium Invited)] Process informatics of experimental functional polymer research accelerated by deep learning

*Kan Hatakeyama¹ (1. Tokyo Inst. Tech. (Japan))

15:45 〜 16:00

[A5-O101-08] Using The Question Answering Method To Extract Information From Materials Science Literature

*Matilda Sipilä¹, Farrokh Mehryary¹, Jouni Luoma¹, Filip Ginter¹, Sampo Pyysalo¹, Milica Todorovic¹ (1. Univ. of Turku (Finland))

Poster Session

[A5-P501] Poster 501

2023年12月15日(金) 10:00 〜 12:00 Poster (Annex)

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[A5-P501-01] Analysis of trade-off relations between magnetization, Curie temperature and price in ThMn₁₂-type Magnet compounds and multi-objective Bayesian optimization for obtaining Pareto Front

*Taro Fukazawa¹, Takashi Miyake¹ (1. National Institute of Advanced Industrial Science and Technology (Japan))

[A5-P501-02] Theory towards Predicting the Lifetime of Electrocatalysis

*Hideshi Ooka¹, Marie E Wintzer¹, Hirokazu Komatsu², Kiyohiro Adachi¹, Ailong Li¹, Shuang Kong¹, Daisuke Hashizume¹, Atsushi Mochizuki³, Ryuhei Nakamura^1,4 (1. RIKEN (Japan), 2. Toyota Natl. College of Tech. (Japan), 3. Kyoto Univ. (Japan), 4. Tokyo Inst. Tech. (Japan))

[A5-P501-03] Global Optimization of Atomic Arrangement in Multicomponent Alloys Accelerated by Universal Neural Network Potential

*Tien Quang Nguyen¹, Michihisa Koyama¹ (1. Shinshu Univ. (Japan))

[A5-P501-04] Kinetic Monte Carlo Simulation using Machine-Learned Potentials for Assessing Durability of Platinum-Based Alloy Nanoparticle Catalysts for Fuel Cells

*Deokgi Hong¹, Jisu Jung¹, Seungwu Han¹ (1. Seoul National Univ. (Korea))

[A5-P501-05] Atmospheric Corrosion Prediction of Carbon Steel Based on Improved Double Hidden Layer Neural Network

*Peng Shi¹, Huike Zhang¹, Liwu Jiang¹ (1. University of Science and Technology Beijing (China))

[A5-P501-06] A Neural Network Interatomic Potential for α-Iron and Carbon Binary System

*Fan-Shun Meng¹, Shigenobu Ogata¹ (1. Osaka Univ. (Japan))

[A5-P501-07] Molecular Dynamics Study on HF Etching of amorphous Si₃N₄ with Neural Network Potential

*Changho Hong¹, Sangmin Oh¹, Seungwu Han¹ (1. Seoul National Univ. (Korea))

[A5-P501-08] Atomistic study of TaN_x-Cu Interfaces using Neural Network Interatomic Potentials

*JeongMin Choi¹, Jaehoon Kim¹, Seungwu Han¹ (1. Seoul National Univ. (Korea))

[A5-P501-09] New Paradigms in Machine Learning for Materials Design: ML Forcefields, De Novo Design, and LLMs

*Anand Chandrasekaran¹, Garvit Agarwal¹, H. Shaun Kwak², Tsuguo Morisato³, Mathew D. Halls⁴, Karl Leswing¹ (1. Schrödinger Inc., New York, New York, 10036 (United States of America), 2. Schrödinger Inc., Portland, Oregon, 97204 (United States of America), 3. Schrödinger K.K., Chiyoda-ku, Tokyo 100-0005 (Japan), 4. Schrödinger Inc., San Diego, California, 92121 (United States of America))

[A5-P501-10] Machine Learning Molecular Dynamics Simulation of CO-driven Formation of Cu Clusters on Cu(111) Surface

*Harry Handoko Halim¹, Ryo Ueda¹, Yoshitada Morikawa¹ (1. Osaka University (Japan))

[A5-P501-11] Prediction of density of states for multinary nanoalloys

*Yusuke Nanba¹, Michihisa Koyama¹ (1. Shinshu Univ. (Japan))

[A5-P501-12] Application of LSTM machine learning to battery emulators

*Kanato Oka¹, Naoto Tanibata¹, Hayami Takeda¹, Masanobu Nakayama¹ (1. Nagoya Institute of Technology (Japan))

[A5-P501-13] Crystal Structure Prediction for Li-Mg-P₂O₇ Using First-principles Calculations

*Takuma Otani¹, Takumi Sato¹, Shogo Nakamori¹, Futoshi Utsuno², Tsuyoshi Honma¹, Tomoki Yamashita¹ (1. Nagaoka Univ. Tech. (Japan), 2. Idemitsu Kosan Co.,Ltd. (Japan))

[A5-P501-14] Topological Data Analysis for Feature Extraction of Phase-separated Structures in Proton Exchange Membranes

*Yukito Higashi¹, Tsuyohiko Fujigaya^1,2,3, Koichiro Kato^1,2 (1. Department of Applied Chemistry, Graduated School of Engineering, Kyushu Univ. (Japan), 2. Center of Molecular systems, Kyushu Univ. (Japan), 3. Int'l Inst. for Carbon-Neutral Energy Res., Kyushu Univ. (Japan))

[A5-P501-15] Ab-initio Electrical Conductivity Calculations of Ag-Pd Alloy based on Wannier-CPA Method

*Shota Namerikawa¹, Takashi Koretsune¹ (1. Department of Physics, Tohoku University (Japan))

[A5-P501-16] QSGW calculations for thousands of materials to predict accurate band gaps

*Shota Takano¹, Katsuhiro Suzuki¹, Kazunori Sato^1,2,3, Takao Kotani^2,4 (1. Osaka Univ. (Japan), 2. CSRN, Osaka Univ. (Japan), 3. OTRI, Osaka Univ. (Japan), 4. Tottori Univ. (Japan))

[A5-P501-17] High-performance quadratic spectral neighbor analysis potential for Al-H binary system to investigate hydrogen embrittlement

*Yuxi Liu¹, Koji Shimizu¹, Satoshi Watanabe¹ (1. UTokyo (Japan))

[A5-P501-18] Efficient stacking pattern search for van der Waals hetero structures via Bayesian optimization

*Beomgyu Choi¹, Tsuyohiko Fujigaya^1,2,3, Koichiro Kato^1,3 (1. Graduate School of Eng., Kyushu Univ. (Japan), 2. Int'l. Inst. for Carbon-Neutral Energy Res., Kyushu Univ. (Japan), 3. Center of Molcule Systems, Kyushu Univ. (Japan))

[A5-P501-19] Graph Neural Network Molecular Dynamics Study of Thermal Degradation of Clean and Oxygen-terminated Diamond (111) and (100) Surfaces

*John Isaac Guinto Enriquez¹, Harry Handoko Halim¹, Takahiro Yamasaki², Masato Michiuchi², Kouji Inagaki¹, Masaaki Geshi³, Ikutaro Hamada¹, Yoshitada Morikawa^1,4 (1. Graduate School of Engineering, Osaka Univ. (Japan), 2. Advanced Materials Laboratory, Sumitomo Electric Industries Ltd. (Japan), 3. R^3 Institute for Newly-Emerging Science Design, Osaka Univ. (Japan), 4. Research Center for Precision Engineering, Graduate School of Engineering, Osaka Univ. (Japan))

[A5-P501-20] Material design and condition optimization for generating higher force of photomechanical crystals by machine learning

*Kazuki Ishizaki¹, Toru Asahi¹, Takuya Taniguchi¹ (1. Waseda Univ. (Japan))

[A5-P501-21] Developing Machine Learning Lattice Optimization Methods Based On Crystal Graph Convolutional Neural Network

*Sang woo Park¹, Jong-Goo Park¹, Ki-Ha Hong¹ (1. Hanbat national Univ. (Korea))

[A5-P501-22] Efficient Exploration of Organic Anode Active Materials for Lithium-ion Battery with Advances in Capacity Prediction Models

*Haruka Tobita¹, Yuki Namiuchi², Hiroaki Imai¹, Koki Obinata³, Masato Okada³, Yasuhiko Igarashi², Yuya Oaki¹ (1. Keio Univ. (Japan), 2. Univ. of Tsukuba (Japan), 3. Univ. of Tokyo (Japan))

[A5-P501-23] Effect of Data Size on Extraction of Descriptors using Sparse Modeling for Small Data: Three Predictors for Controlled Synthesis of Exfoliated Nanosheets

*Yuka Kitamura¹, Yasuhiko Igarashi², Hiroaki Imai¹, Yuya Oaki¹ (1. Keio Univ. (Japan), 2. Univ. of Tsukuba (Japan))

[A5-P501-24] Organization of computational and experimental metadata using function decomposition trees

*Hiori Kino¹ (1. NIMS (Japan))

[A5-P501-25] Developing Smart Floor Sensor using Monitoring Automation Mapping Algorithm for Healthcare Application

*Hyunsoo Kim¹, Soojin Ryu¹, Ji Soo Son¹, Hae Inn Lee¹, Seong Jin Jang¹ (1. Korea Inst. of Indus. Tech. (Korea))

[A5-P501-26] Interface tool from Wannier90 to RESPACK: wan2respack

Kensuke Kurita², Takahiro Misawa¹, Kazuyoshi Yoshimi¹, *Kota Ido¹, Takashi Koretsune² (1. ISSP, Univ. of Tokyo (Japan), 2. Dept. of Phys., Tohoku Univ. (Japan))

[A5-P501-27] A spectral preprocessing method using piecewise regression

*Shinjiro Yagyu¹, Takahiro Nagata¹ (1. NIMS (Japan))

[A5-P501-28] Machine Learning and Computational Modeling for Predicting the Deformation of Natural Fiber-Reinforced Polymer Composites in Bulletproof Material Prototyping

*Isaiah Nikolo Gonzales¹, John Henry Galino¹, Eduardo Magdaluyo, Jr.², Paul Rossener Regonia¹ (1. Univ. of the Philippines Diliman, Dept. of Computer Science (Philippines), 2. Univ. of the Philippines Diliman, Dept. of Mining, Metallurgical, and Materials Engineering (Philippines))

[A5-P501-29] Bayesian Spectroscopy for X-ray Absorption and X-ray Magnetic Circular Dichroism Spectra Measured on a Nickel Thin Film

*Taiga Yamasaki^1,2, Iwamitsu Kazunori¹, Hiroyuki Kumazoe³, Masahiro Sawada⁴, Masahiro Hara¹, Ichiro Akai¹ (1. Kumamoto Univ. (Japan), 2. Res. Fellow of Japan Society for the Promotion of Sci. (Japan), 3. Hitotsubashi Univ. (Japan), 4. Hiroshima Univ. (Japan))

[A5-P501-30] Deep learning model for data compression of Wannier functions

*Tatsuki Oikawa¹, Kota Ido², Takahiro Misawa², Takashi Koretsune¹, Kazuyoshi Yoshimi² (1. Dept. of Phys., Tohoku Univ. (Japan), 2. ISSP, Univ. of Tokyo (Japan))

[A5-P501-31] Automatic Magnetic Data Extraction from Tables in Scientific Documents to Create a Magnet Database

*Hiroyuki Oka¹, Masashi Ishii¹ (1. National Institute for Materials Science (Japan))

[A5-P501-32] SpM: Sparse Modeling Method/Tool for Analytical Continuation of Imaginary-time Green's Function

*Yuichi Motoyama¹, Hiroshi Shinaoka², Junya Otsuki³, Kazuyoshi Yoshimi¹ (1. The Inst. for Solid State Physics, The Univ. of Tokyo (Japan), 2. Saitama Univ. (Japan), 3. Okayama Univ. (Japan))

[A5-P501-33] A Framework to Investigate Motion Behaviors of Particles in Heterogeneous Media

*Anh Duc Dao¹, Chi Hieu Dam¹ (1. Japan Advanced Institute of Science and Technology (Japan))

[A5-P501-34] Identification of Structural Information from X-ray CT Images Based on Topological Data Analysis

*Xichan Gao¹, Kazuto Akagi¹, Daiki Kido^2,3, Masao Kimura^2,3 (1. Advanced Institute for Materials Research (AIMR), Tohoku Univ. (Japan), 2. High Energy Accelerator Research Organization (KEK) (Japan), 3. SOKENDAI (The Graduate Univ. for Advanced Studies) (Japan))

[A5-P501-35] Combining MLFF with DFT: Examples of MXenes and TMDs

*ADISAK BOONCHUN¹ (1. Kasetsart University (Thailand))

[A5-P501-36] Deep learning for phase retrieval from virtual experiments in coherent X-ray diffraction imaging

*Sinh Tien Vu¹, Dam Hieu Chi¹ (1. Japan Advanced Institute of Science and Technology (Japan))

[A5-P501-37] An evidence-based framework to measure similarity between materials with considering uncertainty for discovering novel materials

*Minh Quyet Ha¹, Hieu-Chi Dam¹, Duong-Nguyen Nguyen¹ (1. Japan Advanced Institute of Science and Technology (Japan))

[A5-P501-38] Machine learning-aided Genetic Algorithm in investigating structure-stability relationship of SmFe₁₂ based structures

*Duong-Nguyen Nguyen¹, Hiori Kino², Takahashi Miyake³, Hieu-Chi Dam¹ (1. Japan Advanced Institute of Science and Technology (Japan), 2. National Institute for Materials Science (Japan), 3. National Institute of Advanced Industrial Science and Technology (Japan))

[A5-P501-39] Material ontology-based data linkage in “Data Creation and Utilization-Type Material Research and Development Project (DxMT)”: Approach from Magnetic Materials Research

*Masashi Ishii¹, Taisuke Sasaki¹, Yukiko Takahashi¹, Keitaro Sodeyama¹, Tadakatsu Ohkubo¹ (1. NIMS (Japan))

[A5-P501-40] Quantitative expression of electrode potential by machine learning analysis and liquid Madelung potential

*Norio Takenaka¹, Seongjae Ko¹, Atsushi Kitada¹, Masanobu Nakayama², Atsuo Yamada¹ (1. The Univ. of Tokyo (Japan), 2. Nagoya Inst. of Tech. (Japan))

[A5-P501-41] Mathematical Framework for Efficient Prediction of Local Strain Field in Binary Composites Using Low Rank Approximation.

*PRABHAT KARMAKAR¹, SAYAN GUPTA^1,2, ILAKSH ADLAKHA¹ (1. Department of Applied Mechanics, Indian Inst of Tech. Madras (India), 2. Complex Systems and Dynamics Group, Indian Inst of Tech. Madras (India))

[A5-P501-42] Advancement of software usability toward materials design on large-scale computers

*Tatsumi Aoyama¹, Yuichi Motoyama¹, Kazuyoshi Yoshimi¹, Naoki Kawashima¹ (1. Inst. for Solid State Physics, Univ. of Tokyo (Japan))

Oral Session

[A5-O502] Oral 502

2023年12月15日(金) 14:00 〜 16:00 Session 5 (Room E)

Chair: Hiori Kino (NIMS), Milica Todorović (University of Turku), Toyohiro Chikyo (NIMS), Tetsuya Fukushima (AIST)

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14:00 〜 14:40

[A5-O502-01 (Symposium Keynote)] Disordered enthalpy-entropy descriptor for high-entropy ceramics discovery

*Stefano Curtarolo¹ (1. Duke University (United States of America))

14:40 〜 15:00

[A5-O502-02 (Symposium Invited)] Active materials exploration and characterization with Bayesian optimization

*Patrick Rinke¹ (1. Aalto University (Finland))

Break （15:00 〜 15:15）

15:15 〜 15:35

[A5-O502-03 (Symposium Invited)] Inverse design of functional magnetic materials

*Hongbin Zhang¹ (1. Technical University of Darmstadt (Germany))

15:35 〜 15:50

[A5-O502-04] Machine learning models for the dielectric tensor and energetics of colossal permittivity oxides

*Alex Kutana¹, Yuho Shimano¹, Ryoji Asahi¹ (1. Nagoya University (Japan))

Oral Session

[A5-O503] Oral 503

2023年12月15日(金) 16:30 〜 18:30 Session 5 (Room E)

Chair: Hiori Kino (NIMS), Milica Todorović (University of Turku), Toyohiro Chikyo (NIMS), Tetsuya Fukushima (AIST)

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16:30 〜 16:50

[A5-O503-01 (Symposium Invited)] Data-driven Materials Discovery

*Jacqueline M Cole^1,2 (1. University of Cambridge (UK), 2. ISIS Neutron and Muon Source (UK))

16:50 〜 17:05

[A5-O503-02] Hybrid system for complex data extraction from scientific literature in Magnetic Materials using Large Language Models

*Luca Foppiano^1,2, Masashi Ishii¹ (1. National Inst. for Materials Science (Japan), 2. Univ. of Tsukuba (Japan))

17:05 〜 17:25

[A5-O503-03 (Symposium Invited)] Development of a scheme for the computational simulation of materials science toward the effective data generation and use

*Kazuyoshi Yoshimi¹ (1. Institute for Solid State Physics, Univ. of Tokyo (Japan))

Break （17:25 〜 17:40）

17:40 〜 17:55

[A5-O503-04] System Development for Correlation Analysis with Measurement Meta-data and Spectral Structures in XPS data

*Ryo Murakami¹, Kenji Nagata¹, Hayaru Shouno², Hiroshi Shinotsuka¹, Hideki Yoshikawa¹ (1. NIMS (Japan), 2. The University of Electro-Communications (Japan))

17:55 〜 18:10

[A5-O503-05] Gate modulation spectrum analyses in an organic field-effect transistor of pentacene using Bayesian spectroscopy

*Kazunori Iwamitsu¹, Hiroyuki Kumazoe², Katsuichi Kanemoto³, Ichiro Akai¹ (1. Kumamoto Univ. (Japan), 2. Hitotsubashi Univ. (Japan), 3. Osaka Metropolitan Univ. (Japan))

18:10 〜 18:25

[A5-O503-06] Mesoscopic spatial variation of electronic states extracted from two-dimensional X-ray absorption spectra representing ion transport in a model electrode of a lithium-ion battery

*Ichiro Akai¹, Kazunori Iwamitsu¹, Yuta Kimura², Koji Amezawa², Masaichiro Mizumaki¹, Toshihiro Okajima³, Toru Aonishi⁴ (1. Kumamoto Univ. (Japan), 2. Tohoku Univ. (Japan), 3. Aichi SR (Japan), 4. Tokyo Inst. Tech. (Japan))

Oral Session

[A5-O601] Oral 601

2023年12月16日(土) 09:00 〜 12:00 Session 5 (Room E)

Chair: Hiori Kino (NIMS), Milica Todorović (University of Turku), Toyohiro Chikyo (NIMS), Tetsuya Fukushima (AIST)

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09:00 〜 09:40

[A5-O601-01 (Symposium Keynote)] Multimodal Deep Learning for Composite Materials

*Shun Muroga¹ (1. National Institute of Advanced Industrial Science and Technology (Japan))

09:40 〜 09:55

[A5-O601-02] Multi-fidelity Bayesian optimization structure search

*Milica Todorović¹, Ulpu Remes², Jukka Corander^3,2,4, Patrick Rinke⁵ (1. Univ. of Turku (Finland), 2. Univ. of Helsinki (Finland), 3. Univ. of Oslo (Norway), 4. Wellcome Sanger Inst. (UK), 5. Aalto Univ. (Finland))

Break （09:55 〜 10:10）

10:10 〜 10:30

[A5-O601-03 (Symposium Invited)] Applications of Bayesian Sampling Techniques in Materials Science

*Koji Hukushima¹ (1. University of Tokyo (Japan))

10:30 〜 10:50

[A5-O601-04 (Symposium Invited)] Entropic Sampling and Its Use in Materials Informatics

*Koji Tsuda¹ (1. Univ. Tokyo (Japan))

10:50 〜 11:10

[A5-O601-05 (Symposium Invited)] Developing quantum-classical hybrid algorithms beyond variational algorithms for practical first-principles calculations using quantum computers

*Wataru Mizukami¹ (1. Osaka Univ. (Japan))

11:10 〜 11:30

[A5-O601-06 (Symposium Invited)] Materials design by black-box optimization with Ising machine

*Ryo Tamura^1,2,3, Koji Tsuda^2,1,3 (1. NIMS (Japan), 2. Univ. Tokyo (Japan), 3. RIKEN (Japan))

11:40 〜 12:00

[A5-O601-07 (Symposium Invited)] Advancements in Informatics for Materials Design: Non-Machine Learning Techniques for the Next Generation

*Lauren Takahashi¹ (1. Hokkaido University (Japan))

Oral Session

[A5-O602] Oral 602

2023年12月16日(土) 13:00 〜 16:00 Session 5 (Room E)

Chair: Hiori Kino (NIMS), Milica Todorović (University of Turku), Toyohiro Chikyo (NIMS), Tetsuya Fukushima (AIST)

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13:00 〜 13:40

[A5-O602-01 (Symposium Keynote)] Towards Intuitively Interpretable AI in Materials Discovery: A Data-Driven Framework Emphasizing Material Similarity

*Hieu-Chi Dam¹, Minh-Quyet Ha¹, Duong-Nguyen Nguyen¹, Van-Nam Huynh¹, Hiori Kino² (1. Japan Advanced Institute of Science and Technology (Japan), 2. National Institute for Materials Science (Japan))

13:40 〜 14:00

[A5-O602-02 (Symposium Invited)] Creating Materials Map: Materials Representation with Deep Neural Networks

*Yuta Suzuki¹ (1. TOYOTA Motor Corp. (Japan))

14:00 〜 14:20

[A5-O602-03 (Symposium Invited)] Non-iterative crystal structure prediction

*Ryo Yoshida¹, Chang Liu¹, Hiromasa Tamaki², Tomoyasu Yokoyama², Kensuke Wakasugi², Satoshi Yotsuhashi², Minoru Kusaba¹ (1. Inst.of Stat. Math. (Japan), 2. Panasonic Holdings Corp. (Japan))