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SCEJ 87th Annual Meeting (Kobe, 2022)

Last modified: 2022-03-04 12:00:00

Hall and day program : Hall B, Day 2

Program of CS-2 is updated.
The preprints are now open (Mar. 2nd). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants in Period I/II and invited persons are required. (The participants registered in Period III will get the ID/PW on Mar. 15th.)
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Hall B(2F C201), Day 2(Mar. 17)

CS-1

TimePaper
ID		Title / AuthorsKeywordsTopic codeAck.
number
CS-1 Frontiers of Data-driven Research and Development
(10:40–12:00) (Chair: Toya Yoshihiro)
10:40– 11:20B204[Invited lecture] Development of smart cells using Bio Digital Transformation
(Kobe U.) (Reg)Hasunuma Tomohisa
Metabolic engineering
Enzyme engineering
Automation
CS-1716
11:20– 12:00B208[Invited lecture] Digitalization of Organic Synthesis
(Kyoto U.) Matsubara Seijiro

CS-1724
(13:00–14:20) (Chair: Ono Tsutomu)
13:00– 13:40B213[Invited lecture] Sumitomo Chemical's Materials Informatics Initiatives
(Sumitomo Chemical) *(Reg)Kaneko Shogo, (Cor)Nishino Shinya
materials Informatics
data driven R&D strategy
education and training
CS-1714
13:40– 14:20B215[Invited lecture] How to drive R&D with limited data?
(Kyoto U.) (Reg)Kano Manabu
data-driven approach
domain knowledge
modeling
CS-1715
14:20– 14:40Break
(14:40–15:20) (Chair: Kim Sanghong)
14:40– 15:00B218Use of machine learning and feature engineering for product composition prediction in heavy oil catalytic cracking reactions
(Shinshu U.) *(Reg)Shimada Iori, (Reg)Osada Mitsumasa, (Reg)Fukunaga Hiroshi, (Reg)Koyama Michihisa
machine learning
feature engineering
catalytic cracking
CS-1484
15:00– 15:20B219Prediction of organic compound solubility for subcritical water by machine learning
(Shinshu U.) *(Reg)Osada Mitsumasa, Minesugi Yuuka, (Stu)Tamura Kotaro, (Reg)Shimada Iori
machine learning
subcritical water
solubility
CS-1577
(15:20–16:00) (Chair: Shimada Iori)
15:20– 15:40B220Inverse estimation of physical properties using physics informed neural networks in TSSG method for SiC crystal growth
(Osaka U.) *(Stu)Takehara Yuto, (Reg)Okano Yasunori
Numerical simulation
Top-Seeded Solution Growth
Physics Informed Neural Networks
CS-1312
15:40– 16:00B221Computer Automated Material Design by Universal Neural Network Potential
(Shinshu U.) *(Reg)Valadez Huerta Gerardo, Tamura Ayako, Nanba Yusuke, Hisama Kaoru, (Reg)Koyama Michihisa
Universal Neural Network Potential
Computational Material Design
Automation
CS-1640
(16:00–16:40) (Chair: Koyama Michihisa)
16:00– 16:40Panel discussion

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SCEJ 87th Annual Meeting (Kobe, 2022)

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