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SCEJ 54th Autumn Meeting (Fukuoka, 2023)

Last modified: 2023-12-10 19:09:26

Hall and day program : Hall H

The preprints(abstracts) are now open (Aug. 28). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants and invited persons are required.

Hall H(835)

Hall H, Day 1 | Hall H, Day 2 | Hall H, Day 3
ST-21 | SY-82

TimePaper
ID
Title / AuthorsKeywordsTopic codeAck.
number
Hall H(835), Day 1(Sep. 11)
ST-21 [Trans-Division Symposium]
Frontiers of Data-driven Research and Development
(9:00–10:40) (Chair: Shimada Iori)
9:009:20H101Development of machine learning model for CO2 absorption performance of blended amine solutions
(AIST) *(Reg)Fujii Tatsuya, (Reg)Kohno Yuki, (Reg)Makino Takashi, (Tokyo Tech) Sako Masami, Ishihama Keisuke, Yasuo Nobuaki, Kawauchi Susumu
CO2 absorption
machine learning
amine
ST-21445
9:209:40H102Predicting Physical Properties of Structurally Unknown Polymers Using Spectroscopy Data
(Resonac) (Cor)Nagai Yuuki
Machine Learning
Predict
Descriptor
ST-21353
9:4010:00H103(withdrawn)

100364
10:0010:20H104[Featured presentation] Multimodal Deep Learning for Predictions of Various Properties of Composite Materials
(AIST) *(Reg·PCEF)Muroga Shun, Miki Yasuaki, Hata Kenji
multimodal deep learning
materials informatics
generative deep learning
ST-21602
10:2010:40H105Construction of MI platform for functional materials
(Resonac) (Cor)Sekiguchi Kazuhide
Materials informatics
DX
ST-21450
(10:40–11:20) (Chair: Kaneko Shogo)
10:4011:20H106[Invited lecture] Material exploration and process optimization by digital technology
(NAIST) Fujii Mikiya
Materials Informatics
Process Informatics
Quantum Chemistry
ST-21784
(11:20–12:00) (Chair: Mukaida Shiho)
11:2012:00H108[Invited lecture] Data-driven Approaches for Functional Materials Development in SEKISUI CHEMICAL.
(Sekisui Chemical) (Cor)Masuyama Yoshikazu
Data-Driven Development
Functional Materials
Materials Informatics
ST-21976
(13:00–13:40) (Chair: Mukaida Shiho)
13:0013:40H113[Invited lecture] Remote Operation Support and Automatic Plant Operation Technology In Waste-to-Energy Plants
(JFE Eng.) (Cor)Kojima Hiroshi
Remote operation
Automatic operation
AI and Data analysis
ST-21979
(13:40–15:20) (Chair: Toya Yoshihiro)
13:4014:20H115[Invited lecture] Prediction and control of bacterial evolution through high-throughput automated experiments using robots
(RIKEN) *Shibai Atsushi, Furusawa Chikara
Laboratory automation
Laboratory evolution
Escherichia coli
ST-21805
14:2014:40H117Deep learning model for predicting all protein-protein interactions from sequence data
(Kyutech) *(Reg)Kurata Hiroyuki, Tsukiyama Sho
Cross attention
deep learning
prediction
ST-2133
14:4015:00Break
15:0015:20H119Development of mechanistic cell cultivation models in monoclonal antibody production using data-driven insights
(UTokyo) *(Stu)Okamura K., (Int)Badr S., (Stu)Ichida Y., (Reg·SPCE)Yamada A., (Reg)Sugiyama H.
Biopharmaceuticals
Lactate consumption
Glutamine
ST-21728
(15:20–17:00) (Chair: Muroga Shun)
15:2015:40H120Development of microbial production process by model based metabolic design and directed evolution
(Osaka U.) *(Reg)Shimizu Hiroshi, (Reg)Toya Yoshihiro, (RIKEN) Furusawa Chikara, Shibai Atsushi, (AIST) Horinouchi Takaaki, (Chuo U.) Suzuki Hiroaki, (Osaka U.) Tokuyama Kento, (Reg)Niide Teppei
Model based metabolic pathway design
Directed evolution
Metabolic engineering
ST-21225
15:4016:00H121Machine learning guided enzyme’s molecular recognition specificity conversion
(Osaka U.) *(Reg)Niide Teppei, Sugiki Sou, Mori Seiya, (Reg)Toya Yoshihiro, (Reg)Shimizu Hiroshi
enzyme design
machine learning
ST-21235
16:0016:20H122High accuracy prediction of edible oil oxidation stability by multivariate analysis incorporating chemiluminescence information
(Tohoku U.) *(Stu·PCEF)Yoshida Yuta, (Reg)Hiromori Kousuke, (Reg)Shibasaki-Kitakawa Naomi, (Reg)Takahashi Atsushi
multivariate analysis
oxidative stability
edible oil
ST-21686
16:2016:40H123Application of reaction mechanism search method using chemical reaction neural network to glycerol oxidation reaction
(Shinshu U.) *(Stu)Shionoya Tomoki, (Reg)Shimada Iori
physics informed neural network
kinetics model
data-driven
ST-21480
16:4017:00H124Applicational study of symbolic regression to exploring new materials and constructing kinetics models
(Waseda U.) *(Stu)Isoda T., Takahashi S., (WISE/Mitsubishi Chemical Group) Nakano M., (WISE) Nakajima Y., (Waseda U./WISE) Seino J.
Machine learning
Materials Informatics
Reaction Kinetics
ST-21948
Hall H(835), Day 2(Sep. 12)
(9:00–10:20) (Chair: Kaneko Shogo)
9:009:20H201Elucidation of appropriate data acquisition conditions for API concentration prediction by NIR
(Kyoto U.) *(Stu)Fukuoka Norihiko, (Powrex/TUAT) (Reg)Oishi Takuya, (Powrex) (Reg)Nagato Takuya, (TUAT) (Reg·APCE)Kim Sanghong, (Kyoto U.) (Reg)Sotowa Ken-Ichiro
NIR Spectrum
diffuse reflectance measurement
API concentration prediction
ST-21741
9:209:40H202Development of a soft sensor and a controller system of hydrogen concentration in the exhaust gas in fuel cell systems
(TUAT) *(Stu)Izawa Taisei, (Reg·APCE)Kim Sanghong, (Reg)Matsumoto Miyuki, (Kyoto U.) (Reg)Hasegawa Shigeki, (Reg)Kawase Motoaki
PEFC
Hydrogen control
soft sensor
ST-21203
9:4010:00H203Novel encoding method for high dimensional power consumption data in distributed energy system for short-term electricity demand forecasting
(TokyoTech) *(Stu)Lee Hyojae, (Stu)Tsuda Shunsaku, (Stu)Iijima Taiki, (Reg)Kameda Keisuke, (Reg)Manzhos Sergei, (Reg)Ihara Manabu
electricity demand prediction
distributed energy system
big data
ST-21550
10:0010:20H204Calculation of Tokyo's Photovoltaic Potential and Study of the Effects of Reducing Daily Power Fluctuations from Facade Installations
(Tokyo Tech) *(Stu)Wang Shuai, (Stu)Oya Masashi, (Reg)Kameda Keisuke, (Reg)Manzhos Sergei, (Reg)Ihara Manabu
Facade installation
Photovoltaic power potential
Power fluctuation
ST-21646
(10:20–12:00) (Chair: Kim Sanghong)
10:2010:40H205Gaussian Process Regression Approaches for Process Optimization: A Case Study of Interface State Density Prediction between Insulator and Semiconductor
(NAIST) *(Stu)Matsunaga K., (AIST) Uenuma M., (NAIST) Sato A., Uraoka Y., Miyao T.
Gaussian process regression
length-scale
Metal-oxide-semiconductor
ST-21204
10:4011:00H206Design of integrated upstream and downstream monoclonal antibody production processes using surrogate models
(U. Tokyo) *(Stu)Shigeyama Akinori, (Reg)Hayashi Yusuke, (Int)Badr Sara, (Reg)Sugiyama Hirokazu
Surrogate model
Machine learning
Bayesian optimization
ST-21816
11:0011:20H207Utilization of Bayesian optimization in the process development of drug substance
(Astellas Pharma) *(Reg)Morishita Toshiharu, Sumii Yuta, Hanada Shogo, Shimizu Takashi
DX
Bayesian optimization
Simulation
ST-21167
11:2011:40H208Batch Bayesian optimization method for goal-oriented multi-objective functional materials design
(Resonac) (Cor)Hanaoka Kyohei
Bayesian Optimization
ST-21385
11:4012:00H209Bayesian Optimization Framework for Polymer Composites Design Using High Dimensional Past Materials Data
(Resonac) *(Cor)Arai Ryosuke, (Cor)Sekiguchi Kazuhide, (Cor)Hanaoka Kyohei
Bayesian optimization
DX
Materials informatics
ST-21187
SY-82 [Symposium of Division of Materials and Interfaces]
Coating Technology and Surface Processing
(13:20–14:40) (Chair: Komoda Yoshiyuki, Yoshihara Hirokazu)
13:2014:00H214[Invited lecture] Structure and Elastic Properties of Microparticle in Suspensions by Ultrasonic Scattering Methods
(Kyoto Inst. Tech.) Norisue Tomohisa
ultrasound
microparticle
elasticity
SY-827
14:0014:20H216Viscoelastic analysis of structural change in slurry during mixing
(PIA) *(Reg)Tatsumi R., (Reg)Koike O., (Reg)Yamaguchi Y., (UTokyo) (Reg)Tsuji Y.
rheology
numerical simulation
shear thickening
SY-821017
14:2014:40H217Coating flow simulation using particle method
(Murozono Kaken) (Reg)Murozono Koji
Coating flow
numerical simulation
particle method
SY-82983
14:4015:00Break
(15:00–16:00) (Chair: Inasawa Susumu, Shibata Yusuke)
15:0015:20H219Effects of rheological properties on flow behavior in the die lip of a slit die coater
(Kobe U.) *(Stu)Kohno A., (Reg)Komoda Y., (Reg)Ohmura N.
die coater
coating film shape
coating bead
SY-82818
15:2015:40H220Evaluation of the interfacial affinity between organic-modified nanoparticles and organic solvents
(Tohoku U.) *(Reg)Kubo Masaki, (Stu)Konishi Toru, (Stu·PCEF)Saito Takamasa
nanoparticles
organic solvent
interfacial affinity
SY-82776
15:4016:00H221Airflow Analysis of a Coating Room Using Full Cloud CAE
(Kozo Keikaku Eng.) *(Cor)Watanabe Kaoru, (Cor)Yamanaka Yuma, (Cor)Fujimura Kento, (AndanTEC) (Reg)Hamamoto Nobuo
CAE
FVM
Coating
SY-821052
Hall H(835), Day 3(Sep. 13)
(9:40–11:20) (Chair: Tatsumi Rei, Katayama Ryo)
9:4010:20H303[Invited lecture] Operando observation technique based on combined OCT-TG for monitoring internal structure of drying ceramic coating film
(Yokohama Nat. U.) *Tatami Junichi, Kuroda Hiromasa, Iijima Motoyuki
OCT
drying
Operando observation
SY-821047
10:2010:40H305Simulation of crosslinked network structure formation and prediction of physical properties of bifunctional monomers using a lattice model
(Kanazawa U.) Nishimura Yuki, *(Reg)Taki Kentaro
lattice model
cross-link
photopolymerization
SY-82159
10:4011:00H306Compression and liquid-solid transition of particulate films induced by water evaporation
(TUAT BASE) *(Stu·PCEF)Tanaka Masahiko, (Reg)Inasawa Susumu
water evaporation
compression
liquid-solid transition
SY-82184
11:0011:20H307Dry process to create solid electrolyte composite flexible film
(AndanTEC) *(Reg)Hamamoto Nobuo, (NEION) Yamada Takeshi
all solid-state battery
solid electrolyte
Flexible film
SY-821055

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SCEJ 54th Autumn Meeting (Fukuoka, 2023)


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