Hall E - Hall and day program - SCEJ 55th Autumn Meeting (Sapporo, 2024)

`SCEJ 55th Autumn Meeting (Sapporo, 2024)`

Last modified: 2024-09-09 18:25:12

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Hall and day program : Hall E

The preprints are now open. These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants and invited persons are required.

Hall E(Block B1 1F B11)

Hall E, Day 1 | Hall E, Day 2 | Hall E, Day 3
SY-80 | ST-22

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Hall E(Block B1 1F B11), Day 1(Sep. 11)
SY-80 [Symposium of Division of Materials and Interfaces] Recent Technology of Industrial Crystallization
(9:00–10:00) (Chair: Mikami Takashi)
9:00– 9:20	E101	Fundamental study on air-Zn battery under high-pressure (U. Hyogo) *(Reg)Maeda Kouji, (Stu·PCEF)Maihara Tomoki, Tamura Erika, (Reg)Iimura Kenji, (Reg)Arafune Koji, (Reg)Itoh Kazuhiro, (Reg)Yamamoto Takuji, (Reg)Taguchi Shogo	Air-Zn battery High-pressure Crystallization	SY-80	132
9:20– 9:40	E102	Investigation of controlling the properties of particles considering the interaction with solvents. (TUAT) *(Reg)Amari Shuntaro, (Reg)Takiyama Hiroshi	Crystallization Solvation Properties of crystalline particles	SY-80	699
9:40– 10:00	E103	Effect of impurities on batch cooling crystallization of nickel sulfate (Iwate U.) *(Reg)Doki Norihito, Maruyama Keita, (Reg)Yokota Masaaki, (Satake MultiMix) (Reg)Nemoto Takahiro, (Cor)Tateshita Ryota, (Reg)Kato Yoshikazu	Batch cooling crystallization Nickel sulfate Impurities	SY-80	329
(10:00–11:00) (Chair: Misumi Ryuta)
10:00– 10:20	E104	Antisolvent crystallization of glycine by a baffle replaceable continuous tubular oscillatory crystallizer (Osaka Metro. U.) *(Stu)Imai Ayumu, (Reg)Igarashi Koichi	crystallization COBC Glycine	SY-80	705
10:20– 10:40	E105	Elucidating the enrichment process of enantiomeric excess in deracemization by crystallization. (Osaka U.) *(Stu)Naito R., (Reg)Oketani R., Hisaki I.	deracemization crystallization chiral enrichment	SY-80	135
10:40– 11:00	E106	[Featured presentation] Effects of aeration on external shape of crystalline particles in reactive crystallization with modulation operation (TUAT) *(Stu)Abe Sayaka, (Reg)Amari Shuntaro, (Reg)Takiyama Hiroshi	Crystallization Aeration External shape	SY-80	520
(11:00–12:00) (Chair: Funakoshi Kunio)
11:00– 11:20	E107	Interaction between lysozyme and membrane properties in membrane crystallization (Waseda U.) *(Stu)Ogawa Yuji, (Reg)Kohori Fukashi	membrane lysozyme hydrophilicproperty	SY-80	855
11:20– 11:40	E108	separation of aluminum nitrate from simulated nuclear fuel waste by batch cooling crystallization method (Niigata U.) *(Stu)Yamaoka Seiya, Kawai Ryo, (Reg)Mikami Takashi	cool crystallization nuclear fuel waste decontamination factor	SY-80	523
11:40– 12:00	E109	Co-precipitation of Ni/Mn carbonate and evaluation of crystal morphology behavior and fillability . (Niigata U.) *(Stu)Furukawa Yuuhi, Sone Kenta, (Reg)Mikami Takashi	co-precipitation tap density morphology	SY-80	524
(13:00–14:00) (Chair: Maeda Kouji)
13:00– 13:20	E113	Analysis of diffusion behavior between liquid-liquid phases in the water/ethanol/butylparaben system (Doshisha U.) *(Stu)Matsushima Naoya, (Stu)Tsugawa Yuhei, (Reg)Yoshida Mikio, (Reg)Shirakawa Yoshiyuki	Oiling-out LLPS Crystallization	SY-80	707
13:20– 13:40	E114	Population balance model simulation of temporal change of supersaturation and particle size distribution in seeding batch cooling crystallization (Yokohama Nat. U.) *(Stu·PCEF)Yoshimura R., (Reg)Misumi R.	mixing crystallization population balance	SY-80	185
13:40– 14:00	E115	[The Outstanding Paper Award] Effect of Additive Anion on Promoting Nucleation of Latent Heat Storage Material Na₂HPO₄・12H₂O (Waseda U.) *(Reg)Watanabe Yasuyuki, (Reg)Hirasawa Izumi	Crystallization Nucleating Agent Latent Heat Storage	SY-80	143
(14:00–15:00) (Chair: Kohori Fukashi)
14:00– 14:20	E116	Crystallization operation recipe design for improvement of crystalline particle properties by solution mixing (TUAT) *(Reg)Takiyama Hiroshi, Ohyama Mitsuki, (Reg)Amari Shuntaro	Crystallization operation recipe	SY-80	511
14:20– 14:40	E117	Analysis of particle growth behavior in coprecipitation of nickel, manganese, and cobalt-containing hydroxides (Sumitomo Metal Mining) *(Cor)Koshika Yuki, (Cor)Hirata Yuki, (Cor)Ito Hiroaki, (Cor)Furuichi Yuki, (TUAT) (Reg)Amari Shuntaro, (Reg)Takiyama Hiroshi	Coprecipitation particle growth aggregation	SY-80	60
14:40– 15:00	E118	Purification Phenomena of Organic Agglomerates under Various Heating Conditions (NIT Suzuka) *(Reg)Funakoshi K., Kimura K., Maezawa K.	Agglomerates Purification Organic compounds	SY-80	607
Hall E(Block B1 1F B11), Day 2(Sep. 12)
ST-22 [Trans-Division Symposium] Frontiers of Data-driven Research and Development
(13:00–14:20) (Chair: Kim Sanghong)
13:00– 13:20	E213	Calculating Potential of Solar Cell on Building Façades for Japan's Energy System Optimization in 2050 (Tokyo Tech) *(Stu)Wang Shuai, (Stu)Oya Masashi, (Stu)Otoshi Natsuki, (Reg)Hamasaki Hiroshi, (Reg)Kameda Keisuke, (Reg)Manzhos Sergei, (Reg)Ihara Manabu	Solar cell facade installation Energy system optimization	ST-22	580
13:20– 13:40	E214	Prediction model for real-time power generation of solar cells with shadow simulation based on module structure and irradiance fraction (Tokyo Tech) *(Stu)Otoshi Natsuki, Kasai Yuya, (Reg)Kameda Keisuke, (Reg)Manzhos Sergei, (Reg)Ihara Manabu	Solar cell Energy system Prediction model	ST-22	865
13:40– 14:00	E215	Analysis of anion selectivity in Mg-based Layered Double Hydroxide using a Universal Neural Network Potential (Shinshu U. RISM) *(Reg)Aspera Susan Menez, Chen Yingjie, Nguyen Tien Quang, (Reg)Koyama Michihisa	machine learning layered double hydroxide (LDH) anion selectivity	ST-22	732
14:00– 14:20	E216	Molecular design using deep learning and vecror annealing (NEC) (Reg)Ishida Masahiko	Deep learning Quantum anealing Generative model	ST-22	1099
(14:40–16:00) (Chair: Sugawara Yuuki)
14:40– 15:00	E218	[The Outstanding Paper Award] Optimization of metal nanoparticle synthesis conditions using automated flow system and machine learning (AIST) *(Reg)Ono Takumi, (Reg)Takebayashi Yoshihiro, (ADMAT) Kashiwagi Tsuneo, (AIST) (Reg)Sue Kiwamu	Nanoparticle Microreactor Machine Learning	ST-22	448
15:00– 15:20	E219	Statistical consideration for investigating a direct correlation between solvent effect and hydrogenation of nitrobenzene using flow-tubular reactor (AIST) *(Reg)Wahyudianto Benny, (Reg)Yamaki Takehiro, (Reg)Hara Nobuo, (Reg)Takebayashi Yoshihiro, (Reg)Kataoka Sho	statistical analysis hydrogenation flow reactor	ST-22	121
15:20– 15:40	E220	Development of a product composition prediction model for catalytic cracking reactions and its application to the prediction of reactions with unknown feedstocks (Shinshu U.) *(Reg)Shimada Iori, Kodama Yuhei, Yasuike Shun	physics-informed machine learning catalytic cracking reaction prediction	ST-22	1128
15:40– 16:00	E221	Automated reaction process analysis using data-driven approaches (U. Tokyo/Auxilart) *(Reg)Kim Junu, (Riken) Sakata Itsushi, (Independent Researcher) Yamatsuta Eitaro, (U. Tokyo) (Reg)Sugiyama Hirokazu	Dynamic mode decomposition Chemical reaction Machine learning	ST-22	969
Hall E(Block B1 1F B11), Day 3(Sep. 13)
(9:00–10:20) (Chair: Shimada Iori)
9:00– 9:20	E301	Development of a transfer learning method using O-PLS (Kyoto U.) *(Stu)Fukuoka Norihiko, (Reg)Sotowa Ken-Ichiro, (TUAT) (Reg·APCE)Kim Sanghong	O-PLS transfer learning calibration transfer	ST-22	311
9:20– 9:40	E302	Application of Transfer Learning Using Generative Adversarial Networks to Virtual Sensing (Kyoto U.) Kasuga Yasuko, Yoshida Ryoya, (Reg)Kato Shota, *(Reg)Kano Manabu	transfer learning soft-sensor Generative Adversarial Networks	ST-22	66
9:40– 10:00	E303	Control of foam on white water and improvement of operational efficiency by modeling a soft sensor (RENGO) *(Reg)Okura Y., Inui T., Okahara K.	soft sensor machine learning factory automation	ST-22	95
10:00– 10:20	E304	¹³C-MFA software with a support function for high accuracy flux estimations by proposing additional experiments (Osaka U.) *(Reg)Imada Tatsumi, (Reg)Shimizu Hiroshi, (Reg)Toya Yoshihiro	13C-metabolic flux analysis flux analysis software	ST-22	615
(10:40–12:00) (Chair: Muroga Shun)
10:40– 11:20	E306	[Invited lecture] Autonomous Materials Search (NIMS) Iwasaki Yuma	Machine learning Autonomous Active learning	ST-22	145
11:20– 12:00	E308	[Invited lecture] Representation and Generation of Crystal Structures with Deep Learning (Toyota Motor) Suzuki Yuta	Materials informatics Deep learning Crystal structure	ST-22	894
(13:00–13:40) (Chair: Mukaida Shiho)
13:00– 13:40	E313	[Invited lecture] Introduction to Case Studies on the Development and Utilization of Informatics Technologies (Mitsubishi Chemical) (Cor)Sugisawa Hiroki	Informatics Industry R&D acceleration	ST-22	144
(13:40–14:20) (Chair: Yoshida Hideaki)
13:40– 14:20	E315	[Invited lecture] Digital infrastructure to reduce time to market / R&D to production (Microsoft Japan) Yasunami Yutaka	digital AI data integration	ST-22	616
(14:20–15:00) (Chair: Toya Yoshihiro)
14:20– 15:00	E317	[Invited lecture] Understanding the diversity of metabolisms with the advances of computational metabolomics (TUAT) Tsugawa Hiroshi	metabolomics mass spectrometry informatics	ST-22	142

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SCEJ 55th Autumn Meeting (Sapporo, 2024)

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