ST-24 - Session programs - SCEJ 57th Autumn Meeting (Higashihiroshima, 2026)

`SCEJ 57th Autumn Meeting (Higashihiroshima, 2026)`

Last modified: 2026-07-16 06:38:20

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Session programs : ST-24

The chairs are under negotiation.
Yellow-backs on Technical sessions denote the Hybrid sessions.
(All other sessions are on-site only sessions).

ST-24 [Trans-Division Symposium]
Symposium on Digital Fluid Phase Process: Rapid Measurement and Modeling of Fluid Phase Property toward Process Design Using Information Technology

Organizers:

Shimoyama Yusuke (Science Tokyo), Suzuki Shogo (Albion), Osada Mitsumasa (Shinshu Univ.), Ono Takumi (AIST), Kuroki Nahoko (Ochanomizu Univ.), Murakami Yuya (Shizuoka Univ.)

Fluid phase properties and solvent characteristics are crucial insights not only in the development of chemical and materials processes but also in the design of final products. In recent diverse product development landscape, accelerating process development through the use of information technology is essential. This symposium will focus on accelerating the process from raw material and solvent molecule exploration and selection to process development. We will share information and discuss the modeling of fluid phase properties and solvent characteristics using information technologies such as machine learning and image analysis, as well as the rapid measurement of data necessary for information technology and the construction of soft sensors. Outstanding student presentations will be awarded a student award.

Hall D, Day 1

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Hall D(K1F K103), Day 1(Sep. 14)
(9:00–10:10)
9:00– 9:10		Digital Fluid Phase Process symposium (Science Tokyo) (Reg)Shimoyama Yusuke
9:10– 9:30	D102	[Invited lecture] Acceleration of Process Development with an In House CFD Platform (Sumitomo Chemical) *(Cor)Muramatsu Hiroki, (Cor)Yaegashi Yuta, (Cor)Shimada Naoki	simulation computational fluid dynamics (CFD) adaptive mesh refinement (AMR)	ST-24	272
9:30– 9:50	D103	[Invited lecture] Rapid Prediction of Flow Characteristics for Liquid-Liquid Slug Flow Process Design (Keio U.) (Reg)Fujioka Satoko	liquid-liquid slug flow flow pattern mixing	ST-24	928
9:50– 10:10	D104	[Invited lecture] Scale-Up Study of a Slurry Bubble Column Reactor for CO2 Reduction (Idemitsu Kosan) *(Cor)Ide Tomoyuki, (Cor)Matsumura Takamichi, (Cor)Nakamura Atsushi, (Cor)Sakakura Kei	carbon neutrality slurry bubble column computational fluid dynamics (CFD)	ST-24	386
(10:10–11:10)
10:10– 10:30	D105	Machine-Learning-Based Rapid Characterization of Emulsion Properties (U. Hyogo) *(Stu)Hashimoto Sayu, (Reg)Itoh Kazuhiro, (Int)Jain Mehak, Morimoto Masakazu	Emulsion Machine learning Random forest algorism	ST-24	126
10:30– 10:50	D106	Thermophysical Properties and Finite Expansion Mechanism in CO₂-Expanded Ionic Liquid via Molecular Dynamics Simulation (Shizuoka U.) *(Stu)Wang Lida, (Reg)Onodera Norihiro, (Reg)Kong Chang Yi	molecular dynamics simulation CO2-expanded ionic liquid interfacial behavior	ST-24	767
10:50– 11:10	D107	Rheology-Informed Generative AI for In Silico Optimization of Morphology Fidelity in Extrusion-Based 3D Bioprinting (U. Osaka) *(Stu)Zhang Colin, (Reg)Elvitigala Kelum, (Reg)Sakai Shinji	3D bioprinting Generative AI Closed-loop optimization	ST-24	154
(11:10–12:10)
11:10– 11:30	D108	Prediction of Sugar Reactions in High-Temperature and High-pressure Water by Natural Language Processing (Shinshu U.) *(Stu)Koike Ayami, (Reg)Osada Mitsumasa	Natural language processing Sugars Reaction product prediction	ST-24	759
11:30– 11:50	D109	In-situ droplet evaluation of supercritical CO2 emulsions in a microfluidic process (Science Tokyo) *(Stu)Puprompan Purin, (Reg)Orita Yasuhiko, (Reg)Shimoyama Yusuke	dynamic light scattering emulsion supercritical fluid	ST-24	257
11:50– 12:10	D110	Extension of Dushman Reaction Kinetics to a Wide Range of Conditions Using an AI-Based Rate Law (Shizuoka U.) *(Stu)Sasaki Yu, (Reg)Murakami Yuya	Dushman reaction Extrapolation Machine learning	ST-24	704
(13:00–14:20)
13:00– 13:20	D113	[Invited lecture] New business making examples with AI (Baycurrent) Furuta Satoshi	AI expertise business	ST-24	234
13:20– 13:40	D114	[Invited lecture] Data-Driven Design of Nanocarbon Dispersions Using Machine Learning and Automated Experimentation (AIST) Jintoku Hirokuni	machine learning dispersion nanocarbon	ST-24	148
13:40– 14:00	D115	[Invited lecture] Data-Driven Multi-Scale Simulation for Integrated Reaction-Transport Modeling and Process Design (Mitsubishi Chemical) *(Reg)Kato Yuki, (Cor)Yamashita Hiroki, (Cor)Mikami Masayoshi, (Reg)Ninomiya Wataru, (Kyushu U.) (Reg)Inoue Gen		ST-24	978
14:00– 14:20	D116	[Invited lecture] Application of Semi-Empirical Model and Computational Fluid Dynamics to a Semi-Batch Reaction with Liquid-Liquid Phase Separation (Daiichi Sankyo) *(Reg)Yasuda Tomoki, (Cor)Shiraishi Shohei, (Cor)Oka Sunao, (Reg)Ishikawa Hideaki	liquid-liquid phase separation semi-batch reaction computational fluid dynamics	ST-24	269
14:20– 14:40		Awards ceremony

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SCEJ 57th Autumn Meeting (Higashihiroshima, 2026)

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SCEJ 57th Autumn Meeting (Higashihiroshima, 2026)

Session programs : ST-24

ST-24 [Trans-Division Symposium] Symposium on Digital Fluid Phase Process: Rapid Measurement and Modeling of Fluid Phase Property toward Process Design Using Information Technology

`SCEJ 57th Autumn Meeting (Higashihiroshima, 2026)`

ST-24 [Trans-Division Symposium]
Symposium on Digital Fluid Phase Process: Rapid Measurement and Modeling of Fluid Phase Property toward Process Design Using Information Technology