物性 - Program search result - SCEJ 89th Annual Meeting (Sakai, 2024)

`SCEJ 89th Annual Meeting (Sakai, 2024)`

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Program search result : 物性 : 10 programs

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Title (J) field includes “物性”; 10 programs are found.
The search results are sorted by the start time.

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Day 1 11:00– 11:40	Z105	[The SCEJ Award] Prediction of fluid properties and phase equilibria at high pressures (Tohoku U.) (Reg)Inomata Hiroshi	The SCEJ Award	0-a	741
Day 2 13:00– 13:20	D213	[Invited lecture] Physical property prediction from small dataset using transfer learning (AIST) (Reg)Furuya T.	phase equilibria physical properties chemical engineering	X-53	207
Day 2 13:20– 13:40	D214	[Invited lecture] What are the companies looking for in terms of physical properties? (Kureha) (Reg)Otawara K.	physical property	X-53	318
Day 2 13:20– 15:20	PC273	Effect of raw material composition on texture of edible fiber containing plant-based protein (Kyoto U.) *(Stu)Kitawaki Takuto, (Reg)Nagamine Shinsuke, (Reg)Nakagawa Kyuya, (Reg)Kobayashi Takashi, Matsumiya Kentaro	meat substitute plant-based protein fiber wet spinning	12-k	600
Day 2 15:20– 15:40	D220	[Invited lecture] Physical property prediction from small dataset using transfer learning (Tokyo U. Sci.) *(Reg)Murakami Y., (Reg)Shono A.	Artificial intelligence Neural network Transfer learning	X-53	113
Day 2 15:40– 16:00	D221	[Invited lecture] Fragment-based Ab Initio Molecular Simulation for Predicting Physicochemical Properties of Functional Liquids (Chuo U./JST ACT-X) (Reg)Kuroki N.	Physicochemical Properties Molecular Simulation Functional Liquids	X-53	514
Day 2 16:40– 17:00	D224	[Invited lecture] High-throughput measurement of physical properties to accelerate the development of CO₂ absorbents (Nagoya U.) (Reg)Machida Hiroshi	CO2 capture Physical properties absorbent	X-53	175
Day 2 17:00– 17:20	D225	[Invited lecture] Physical Properties and CO₂ Absorption Characteristics of Blended Ionic Liquids for Low Partial Pressure CO₂ Capture (AIST) (Reg)Makino T.	Ionic liquid CO2 capture CO2 solubility	X-53	388
Day 3 11:00– 11:20	I307	Prediction of Physical Properties by Atomic Group Contribution Method with Deep Learning (TUS) (Reg)Ohe Shuzo	Prediction Physical properties Deep learning	1-a	702
Day 3 14:40– 15:00	E318	Effect of the properties of diffusion layer for direct formic acid fuel cell on formic acid and water transport (Kanazawa U.) *(Reg)Tsujiguchi Takuya, (Stu)Tsutsui Atsuki, (Reg)Osaka Yugo, (Reg)Kodama Akio, (JTEKT) Furuhashi Mototake	Direct formic acid fuel cell Porous electrode Liquid-gas transport	9-e	719

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SCEJ 89th Annual Meeting (Sakai, 2024)

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