Oral Session

[A1-O3] Slot 03

Tue. Dec 14, 2021 9:00 AM - 11:00 AM Room J (G302)

Chair: Ryo Tamura (National Institute for Materials Science), Yuhki Tsukada (Nagoya University)

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9:00 AM - 9:20 AM

[A1-O3-01 (Symposium Invited)] XERUS: Towards an open-source python wrapper for quick identification of XRD phases and refinement automation.

*Pedro Baptista de Castro^1,2, Kensei Terashima¹, Hiroyuki Takeya¹, Yoshihiko Takano^1,2 (1. National Inst. for Materials Science (Japan), 2. Univ. of Tsukuba (Japan))

9:20 AM - 9:40 AM

[A1-O3-02] Automatic extraction of materials and properties from superconductors scientific literature

*Luca Foppiano¹, Pedro Baptista de Castro¹, Kensei Terashima¹, Yoshihiko Takano¹, Ishii Masashi¹ (1. National Inst. for Materials Science (Japan))

9:40 AM - 10:00 AM

[A1-O3-03 (Symposium Invited)] Machine-learning-aided exploration of magnetocaloric materials

*Kensei Terashima¹, Pedro Baptista de Castro^1,2, Takafumi D Yamamoto¹, Zhufeng Hou³, Hiroyuki Takeya¹, Yoshihiko Takano^1,2 (1. National Inst. for Materials Science (Japan), 2. Univ. of Tsukuba (Japan), 3. Chinese Academy of Sci. (Japan))

10:00 AM - 10:20 AM

[A1-O3-04] Construction of material dictionary database for extracting the extensive amount of training data for Materials informatics

*Akira Suzuki¹, Masashi Ishii¹ (1. National Institute for Materials Science (Japan))

Cancelled

10:20 AM - 10:40 AM

[A1-O3-05] Autonomous and multi-objective Bayesian-optimal generation of novel small molecules and polymers with targeted properties

*Guillaume Lambard¹ (1. National Institute for Materials Science (Japan))

10:40 AM - 11:00 AM

[A1-O3-06] Structure-property Relationship of Porous Polymers Investigated by Materials Informatics

*Sadaki Samitsu¹ (1. National Inst. for Materials Sci. (Japan))

Oral Session

[A1-O4] Slot 04

Tue. Dec 14, 2021 1:30 PM - 3:30 PM Room A (G401)

Chair: Yukari Katsura (National Institute for Materials Science), Tomofumi Tada (Kyushu University)

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Introductory Talk of This Session （1:30 PM - 1:40 PM）

1:40 PM - 2:00 PM

[A1-O4-01(Symposium Invited)] Large-diameter SiC crystal grown by solution growth using surrogate model

*Toru UJIHARA¹ (1. Nagoya Univ. (Japan))

2:00 PM - 2:20 PM

[A1-O4-02(Symposium Invited)] Data-driven experiment-based parameter exploration in production processes – Toward Process Informatics accelerating Materials Informatics

*Keisuke . Nagato¹ (1. Univ. Tokyo (Japan))

2:20 PM - 2:40 PM

[A1-O4-03(Symposium Invited)] Autonomous inorganic thin-film synthesis by combining artificial intelligence and robotics

*Ryota Shimizu¹ (1. Tokyo Institute of Technology (Japan))

2:40 PM - 3:00 PM

[A1-O4-04(Symposium Invited)] Catalyst design from scratch based on high-throughput experimentation and data science

*Toshiaki Taniike¹ (1. Japan Advanced Institute of Science and Technology (Japan))

3:00 PM - 3:20 PM

[A1-O4-05 (Symposium Invited)] AI-Accelerated Materials Structure-Property-Synthesizability Prediction

*Yousung Jung¹ (1. KAIST (Korea))

Oral Session

[A1-O5] Slot 05

Tue. Dec 14, 2021 3:55 PM - 6:00 PM Room A (G401)

Chair: Masayuki Karasuyama (Nagoya Institute of Technology), Yasunobu Ando (AIST)

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4:00 PM - 4:20 PM

[A1-O5-01 (Symposium Invited)] Starrydata: A Curation-Based Database of Published Plot Data in Materials Science

*Yukari Katsura^1,2,3, Masaya Kumagai^4,5,3, Tomoya Mato¹, Yuki Ando¹, Atsumi Tanaka², Yoshihiro Sakamoto³, Erina Fujita², Kaoru Kimura², Koji Tsuda^2,3,1 (1. National Inst. for Materials Science (Japan), 2. Univ. of Tokyo (Japan), 3. RIKEN (Japan), 4. SAKURA Internet Inc. (Japan), 5. Kyoto Univ. (Japan))

4:20 PM - 4:40 PM

[A1-O5-02] Quantitative Prediction of Fracture Toughness (K1c) of Polymer via Fractography using Deep Neural Networks

*Yoh-ichi Mototake¹, Kaita Ito², Masahiko Demura² (1. The institute of statistical mathematics (Japan), 2. National Institute for Materials Science (Japan))

4:40 PM - 5:00 PM

[A1-O5-03] MaterialBERT for Natural Language Processing of Materials Science Texts

*Michiko Yoshitake¹, Fumitaka Sato^1,2, Hiroyuki Kawano^1,2, Hiroshi Teraoka^1,2 (1. National Institute for Material Science (Japan), 2. RidgeLinez (Japan))

5:00 PM - 5:20 PM

[A1-O5-04(Symposium Invited)] Materials and Process Informatics in Organic Synthesis and Catalyst

*Akira Yada¹ (1. National Institute of Advanced Industrial Science and Technology (AIST) (Japan))

5:20 PM - 5:40 PM

[A1-O5-05] New Materials Search Maps Generated by Machine Learning

*Yuki Inada¹, Yukari Katsura^2,1, Haruhiko Morito³, Masaya Kumagai⁴, Kaoru Kimura¹ (1. Univ. of Tokyo (Japan), 2. National Inst. for Materials Sci. (Japan), 3. Tohoku Univ. (Japan), 4. Kyoto Univ. (Japan))

5:40 PM - 5:50 PM

[A1-O5-06 (Symposium Invited)] Launching STAM Methods: imaginative new publication platform for highlighting data-driven methods to accelerate research on innovative materials

*Masanobu Naito¹ (1. National Institute for Materials Science (NIMS) (Japan))

Oral Session

[A1-O7] Slot 07

Wed. Dec 15, 2021 2:30 PM - 6:00 PM Room R (G319)

Chair: Hieu-Chi Dam (Japan Advanced Institute of Science and Technology), Junjie Wang (Northwestern Polytechnical University), Junya Inoue (The University of Tokyo)

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2:30 PM - 3:00 PM

[A1-O7-01(Symposium Keynote)] Automatic design of functional molecules: black-box optimization and curiosity-based sampling

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

3:00 PM - 3:20 PM

[A1-O7-02(Symposium Invited)] Machine learning algorithms for data-driven materials science

*Masayuki Karasuyama¹ (1. Nagoya Institute of Technology (Japan))

3:20 PM - 3:40 PM

[A1-O7-03(Symposium Invited)] Large scale atomistic simulations driven by neural-network potential molecular dynamics and kinetic Monte Carlo with external fields

*Tomofumi Tada^1,2 (1. Kyushu Univ. (Japan), 2. Tokyo Tech. (Japan))

3:40 PM - 4:00 PM

[A1-O7-04(Symposium Invited)] Integrating Computational Model with Microstructure Data

*Yuhki Tsukada¹, Toshiyuki Koyama¹ (1. Nagoya Univ. (Japan))

4:00 PM - 4:20 PM

[A1-O7-05(Symposium Invited)] Developments of materials informatics methods to design and to understand materials

*Ryo Tamura^1,2 (1. National Institute for Materials Science (Japan), 2. Univ. Tokyo (Japan))

4:20 PM - 4:40 PM

[A1-O7-06(Symposium Invited)] Learning similarities between materials from data

*Hieu-Chi DAM¹ (1. Japan Advanced Institute of Science and Technology (Japan))

4:40 PM - 5:00 PM

[A1-O7-07 (Symposium Invited)] Inverse problems in designing structural materials

*Junya INOUE¹ (1. Univ. Tokyo (Japan))

5:00 PM - 5:20 PM

[A1-O7-08(Symposium Invited)] Discovery of hexagonal MAB phases by high-throughput calculations

*Junjie Wang¹, Nanxi Miao¹, Artem R. Oganov², Hideo Hosono³ (1. Northwestern Polytechnical University (China), 2. Skolkovo Institute of Science and Technology (Russia), 3. Tokyo Institute of Technology (Japan))

5:20 PM - 5:40 PM

[A1-O7-09(Symposium Invited)] Organic Materials Repurposing: Theoretical Prediction of New Applications for Existing Compounds.

*Daniele Padula¹, Tahereh Nematiaram², Omer Hasan Omar², Ke Zhao⁴, Alessandro Landi³, Zhi-Wen Zhao⁵, Alessandro Troisi² (1. University of Siena (Italy), 2. University of Liverpool (UK), 3. University of Salerno (Italy), 4. Shandong Normal University (China), 5. Northeast Normal University (China))

5:40 PM - 6:00 PM

[A1-O7-10(Symposium Invited)] Data-driven Acceleration of Materials Simulation and Analysis

*Ando Yasunobu¹ (1. AIST (Japan))

Sessions

A. New Materials Methodology for Next-Generation » [A-1] STAM Methods: Leading-Edge Methods for New Materials

[A1-O3] Slot 03

[A1-O3-01 (Symposium Invited)] XERUS: Towards an open-source python wrapper for quick identification of XRD phases and refinement automation.

[A1-O3-02] Automatic extraction of materials and properties from superconductors scientific literature

[A1-O3-03 (Symposium Invited)] Machine-learning-aided exploration of magnetocaloric materials

[A1-O3-04] Construction of material dictionary database for extracting the extensive amount of training data for Materials informatics

[A1-O3-05] Autonomous and multi-objective Bayesian-optimal generation of novel small molecules and polymers with targeted properties

[A1-O3-06] Structure-property Relationship of Porous Polymers Investigated by Materials Informatics

[A1-O4] Slot 04

[A1-O4-01(Symposium Invited)] Large-diameter SiC crystal grown by solution growth using surrogate model

[A1-O4-02(Symposium Invited)] Data-driven experiment-based parameter exploration in production processes – Toward Process Informatics accelerating Materials Informatics

[A1-O4-03(Symposium Invited)] Autonomous inorganic thin-film synthesis by combining artificial intelligence and robotics

[A1-O4-04(Symposium Invited)] Catalyst design from scratch based on high-throughput experimentation and data science

[A1-O4-05 (Symposium Invited)] AI-Accelerated Materials Structure-Property-Synthesizability Prediction

[A1-O5] Slot 05

[A1-O5-01 (Symposium Invited)] Starrydata: A Curation-Based Database of Published Plot Data in Materials Science

[A1-O5-02] Quantitative Prediction of Fracture Toughness (K1c) of Polymer via Fractography using Deep Neural Networks

[A1-O5-03] MaterialBERT for Natural Language Processing of Materials Science Texts

[A1-O5-04(Symposium Invited)] Materials and Process Informatics in Organic Synthesis and Catalyst

[A1-O5-05] New Materials Search Maps Generated by Machine Learning

[A1-O5-06 (Symposium Invited)] Launching STAM Methods: imaginative new publication platform for highlighting data-driven methods to accelerate research on innovative materials

[A1-O7] Slot 07

[A1-O7-01(Symposium Keynote)] Automatic design of functional molecules: black-box optimization and curiosity-based sampling

[A1-O7-02(Symposium Invited)] Machine learning algorithms for data-driven materials science

[A1-O7-03(Symposium Invited)] Large scale atomistic simulations driven by neural-network potential molecular dynamics and kinetic Monte Carlo with external fields

[A1-O7-04(Symposium Invited)] Integrating Computational Model with Microstructure Data

[A1-O7-05(Symposium Invited)] Developments of materials informatics methods to design and to understand materials

[A1-O7-06(Symposium Invited)] Learning similarities between materials from data

[A1-O7-07 (Symposium Invited)] Inverse problems in designing structural materials

[A1-O7-08(Symposium Invited)] Discovery of hexagonal MAB phases by high-throughput calculations

[A1-O7-09(Symposium Invited)] Organic Materials Repurposing: Theoretical Prediction of New Applications for Existing Compounds.

[A1-O7-10(Symposium Invited)] Data-driven Acceleration of Materials Simulation and Analysis

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