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SCEJ 53rd Autumn Meeting (Nagano, 2022)

Last modified: 2022-12-14 13:12:56

Hall and day program : Hall PA, Day 3 : PA303

The preprints can be viewed by clicking the Paper IDs.
Yellow-back sessions on Technical sessions will be On-site/online Hybrid sessions, others are Online sessions.
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Hall P(), Day 3(Sep. 16)

Poster: odd 9:00-10:30 even 10:30-12:00, Award Ceremony: 13:00-13:40 Poster venue

ST-23

TimePaper
ID
Title / AuthorsKeywordsTopic codeAck.
number
ST-23 [Trans-Division Symposium]
New Developments of Fuel Cells, Batteries and Energy Conversion Devices (Poster)
(9:00–12:00)
9:0010:30PA301Development of Fibrous Connected Metal Nanoparticle Catalysts for Polymer Electrolyte Fuel Cells
(Tokyo Tech) *(Stu)Akimoto Minori, (Reg)Kuroki Hidenori, (Reg)Yamaguchi Takeo
Nanonetwork
Nanofiber
Fuel cell
ST-23406
10:3012:00PA302Core-shell type connected Pt-based catalysts with advanced oxygen-reduction performances
(Tokyo Tech) *(Stu)Chitra Sudheer Aparna, (Reg)Gopinathan M Anilkumar, (Reg)Kuroki Hidenori, (Reg)Yamaguchi Takeo
Polymer electrolyte fuel cell
Oxygen reduction reaction
Carbon-free electrocatalyst
ST-23609
9:0010:30PA303Effect of Carbon Addition to Oxide Electrodes for Polymer Electrolyte Fuel Cell
(Shinshu U.) *(Stu)Yamamoto Kanta, (Reg)Shimada Iori, (Reg)Osada Mitsumasa, (Reg)Takahashi Nobuhide, (Reg)Fukunaga Hiroshi
polymer electrolyte fuel cell
conductive carbon additive
oxide catalyst
ST-23777
10:3012:00PA304Voltage loss breakdown of carbon-free ionomer-free Pt electrode for polymer electrolyte fuel cell
(Shinshu U.) *(Stu)Sonobe Saaya, (Reg)Shimada Iori, (Reg)Osada Mitsumasa, (Reg)Takahashi Nobuhide, (Reg)Fukunaga Hiroshi
polymer electrolyte fuel cell
overpotential analysis
Pt black
ST-23792
9:0010:30PA305Prediction of agglomeration behavior in fuel cell catalyst ink by simulation
(Kyushu U.) *(Stu)Saito Y., So M., (Reg)Inoue G.
fuel cell
simulation
particle agglomeration
ST-2399
10:3012:00PA306Preparation of graphene oxide electrolyte membrane and its fuel cell performance
(Gunma U.) *(Stu)Iwasaki Haruka, (Reg)Ishitobi Hirokazu, (Reg)Nakagawa Nobuyoshi
Graphene oxide
Fuel cell
Electrolyte membrane
ST-23295
9:0010:30PA307Pore controlling for the anode catalyst layer in direct formic acid fuel cells
(Kanazawa U.) *(Stu)Iwatani Shokei, (JTEKT) (Cor)Furuhashi Mototake, (Kanazawa U.) (Reg)Osaka Yugo, (Reg)Kodama Akio, (Reg)Tsujiguchi Takuya
Direct formic acid fuel cell
pore-forming agent
concentration overvoltage
ST-23564
10:3012:00PA308Effects of the Molybdenum Addition to the anode catalyst of direct formic acid fuel cell on the formic acid oxidation activity and stability
(Kanazawa U.) *(Stu)Mino Marino, Abd Lah Halim Fahimah, (Reg)Osaka Yugo, (Reg)Kodama Akio, (Reg)Tsujiguchi Takuya
Pd-based catalyst
Formic acid oxidation
Direct formic acid fuel cell
ST-23647
9:0010:30PA309Preparation of Ni nanoparticle-deposited carbon nanotube sheets for thermoelectric materials
(NIT Gunma) *(Stu)Kotajima Masaru, Tomaru Taisei, (Chiba Inst. Tech.) (Reg)Kudo Shoji, (NIT Gunma) Ota Michiya
thermoelectric materials
carbon nanotubes
Nickel-nanoparticles
ST-23711
10:3012:00PA310Application of Neural Network Model for Valence Bond Method Calculation for Proton Conductor
(Tokyo Tech) *(Stu)Ariga Takaaki, (Stu)Kameda Keisuke, Ito Kazuma, (Reg)Manzhos Sergei, (Reg)Ihara Manabu
solid oxide fuel cell
valence bond method
machine learning
ST-23228
9:0010:30PA311Optimal design of building-scale distributed hydrogen energy storage systems for realizing low-carbonization and high economic efficiency
(Tokyo Tech) *(Stu)Shirakura Sayaka, (Stu)Okubo Tatsuya, (Toshiba) Matsuoka Kei, (Toshiba ESS) (Reg)Matsunaga Kentaro, (Cor)Sato Junichi, (Tokyo Tech) (Reg)Manzhos Sergei, (Reg)Ihara Manabu
hydrogen
microgrid
optimization
ST-23243
10:3012:00PA312Analysis of high-dimensional energy data and application of regression models toward generalized electricity demand forecasting
(Tokyo Tech) *(Stu)Tsuda Shunsaku, (Stu)Okubo Tatsuya, (Stu)Lee Hyojae, (Stu)Iijima Taiki, (Stu)Otoshi Natsuki, (Reg)Manzhos Sergei, (Reg)Ihara Manabu
energy system
machine learning
data science
ST-23265
9:0010:30PA313Study and analysis of clustering methods for high-dimensional "Energy Data" for building power forecasting models
(Tokyo Tech) *(Stu)Iijima Taiki, (Stu)Lee Hyojae, (Stu)Tsuda Shunsaku, (Reg)Manzhos Sergei, (Reg)Ihara Manabu
energy system
machine learning
data science
ST-23544
10:3012:00PA314Rational design for reduction potential of photosensitizer based on materials informatics
(Osaka U.) *(Reg)Kitagawa Yasutaka, Tokuyama Kazuaki, Amamizu Naoka, Kishi Ryohei
Quantum Chemistry
Photosensitizer
Materials Informatics
ST-23291
9:0010:30PA315The relation between bubble generation behavior and hydrogen evolution performance at the cathode in alkaline water electrolysis
(Yokohama Nat. U.) *(Stu·PCEF)Kitajima Daisuke, (Reg)Misumi Ryuta, Mitsusima Sigenori
Alkaline Water Electrolysis
impedance measurement
hydrogen
ST-23410
10:3012:00PA316System evaluation of electrochemically promoted ammonia synthesis using proton-conducting ceramic electrolysis cells
(U. Tokyo) *(Stu)Okazaki Moe, (Tokyo Tech) (Reg)Otomo Junichiro
ammonia electrosynthesis
electrochemical promotion
system evaluation
ST-23445
9:0010:30PA317Electrochemical promotion in carbon dioxide reduction reaction using proton-conducting ceramic electrolysis cells
(Tokyo Tech) *(Stu)Huang Rui, (Reg)Otomo Junichiro
CO2 utilization
electrochemical reduction
proton conductor
ST-23742
10:3012:00PA318Reaction Field Design for Improving Ethylene Selectivity in Carbon Dioxide Electroreduction
(Tokyo Tech) *(Stu)Shibata Takahito, (Reg)Tamaki Takanori, (Reg)Yamaguchi Takeo
CO2 reduction
Anion-conductive polymer
Copper electrode
ST-23246
9:0010:30PA319Anode reaction selectivity control on seawater electrolysis using thin flow channel electrolysis cell.
(Yamaguchi U.) *(Stu)Masada Issei, Gondo Mamoru, (Reg)Endo Nobutaka
Seawater electrolysis
Chlorine
Oxygen selectivity
ST-23802
10:3012:00PA320Prediction of an in-Plane Anomalous Current Using Numerical Simulation and Machine Learning
(Kyushu U.) *(Stu)Mori Y., (Stu)Komori C., (Reg)Inoue G.
Modeling
Machine learning
Current distribution
ST-23100
9:0010:30PA321Continuous sulfur/conductive-additive compositing process for all-solid-state lithium-sulfur batteries
(Osaka Metro. U.) *(Stu·PCEF)Iwao Motoshi, Miyamoto Hiromi, (Reg)Nakamura Hideya, (Reg)Hayakawa Eiji, (Reg)Ohsaki Shuji, (Reg)Watano Satoru
lithium sulfur battery
solid-state battery
continuous process
ST-23167
10:3012:00PA322Mathematical Modeling on Recycling of Cathode Active Materials from NCM Lithium-Ion Batteries
(U. Tokyo) *(Stu)Li Peidan, (Reg)Heiho Aya, Dou Yi, (Reg)Kanematsu Yuichiro, (Reg·APCE)Kikuchi Yasunori
Lithium-ion Battery
Recycle
optimization
ST-23522
9:0010:30PA323Mass Transport Analysis of the Electrodes of Redox Flow Battery
(Gunma U.) *(Stu)Ide Tomoki, (Reg)Ishitobi Hirokazu, Shiraishi Soshi, (AION) Tsukada Hidehiko, (Toyo Eng.) (Reg)Nakao Takato, (Gunma U.) (Reg)Nakagawa Nobuyoshi
Redox flow battery
Limiting current
Transport of active materials
ST-23268
10:3012:00PA324Effect of carbon particle concentration on the charge/discharge performance of a flow capacitor
(Gunma U.) *(Stu)Makino Naoki, (Reg)Ishitobi Hirokazu, (formerly Nihon U.) Teramoto Kazunori, (Gunma U.) (Reg)Nakagawa Nobuyoshi
flow capacitor
pressure drop
carbon slurry
ST-23348
9:0010:30PA325Synthesis of porous reduced graphene oxide as an electrode material for supercapacitor
(Shizuoka U.) *(Stu)Yao F., Khainunni S., (Reg)Kong C. Y.
supercapacitor
prGO
specific capacitance
ST-23372

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SCEJ 53rd Autumn Meeting (Nagano, 2022)


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