Poster presentation

[2a08-0900] Poster sess. B

Fri. Oct 28, 2022 9:00 AM - 3:00 PM Poster sess. room-B (P09-P15) (12H Conf. room)

+Add all to schedule

[P09] Mechanistic study of Ni₂P catalyzed dehydrogenative coupling of methane

Rattanawalee Rattanawan¹, Min Gao¹, Shoji Iguchi², Ichiro Yamanaka², ○Jun-ya Hasegawa¹ (1. Hokkaido University, 2. Tokyo Institute of Technology)

[P10] Machine Learning-Aided Catalyst Modification in Oxidative Coupling of Methane by Addition of Promoter Element

○Shun Nishimura¹, Junya Ohyama², Xinyue Li¹, Itsuki Miyazato³, Toshiaki Taniike¹, Keisuke Takahashi³ (1. JAIST, 2. Kumamoto University, 3. Hokkaido University)

[P11] Development of low-temperature methanol synthesis process from CO₂

○Ayaka Miura¹, Kenji Nakao¹, Noriyuki Yamane¹, Fei Chen², Noritatsu Tsubaki² (1. Nippon Steel Corp., 2. University of Toyama)

[P12] Gas-phase hydrogenation of CO₂ over supported iron-based catalysts.

○Misuzu Komuro¹, Miru Hirahara¹, Hitoshi Ogihara¹, Hideki Kurokawa¹ (1. Saitama University)

[P13] Mechanism of foaming phenomena during pre-heating in the liquid phase synthesis of bio-jet fuel form triglycerides

○Shimada Hikaru¹, Kenji Asami¹, Haruki Tani², Yayoi Murakami³, Kaoru Fujimoto³ (1. Asami Laboratory, The University of Kitakyushu, 2. Environment Energy Co., Ltd., 3. HiBD Research Institute, Inc.)

[P14] Optimization of reaction conditions with machine learning in woody biomass solvolysis using vegetable oil solvent

○Emi Fukutani¹, Mitsumasa Osada¹, Hiroshi Fukunaga¹, Nobuhide Takahashi¹, Iori Shimada¹ (1. Shinshu University)

[P15] Efficient prediction of jet fraction yield and optimal condition using machine learning in catalytic cracking of vegetable oils

○Yuzuki Katayama¹, Iori Shimada¹ (1. Shinshu University)

Session information

[2a08-0900] Poster sess. B

[P09] Mechanistic study of Ni₂P catalyzed dehydrogenative coupling of methane

[P10] Machine Learning-Aided Catalyst Modification in Oxidative Coupling of Methane by Addition of Promoter Element

[P11] Development of low-temperature methanol synthesis process from CO₂

[P12] Gas-phase hydrogenation of CO₂ over supported iron-based catalysts.

[P13] Mechanism of foaming phenomena during pre-heating in the liquid phase synthesis of bio-jet fuel form triglycerides

[P14] Optimization of reaction conditions with machine learning in woody biomass solvolysis using vegetable oil solvent

[P15] Efficient prediction of jet fraction yield and optimal condition using machine learning in catalytic cracking of vegetable oils

Authentication

Session information

[2a08-0900] Poster sess. B

[P09] Mechanistic study of Ni2P catalyzed dehydrogenative coupling of methane

[P10] Machine Learning-Aided Catalyst Modification in Oxidative Coupling of Methane by Addition of Promoter Element

[P11] Development of low-temperature methanol synthesis process from CO2

[P12] Gas-phase hydrogenation of CO2 over supported iron-based catalysts.

[P13] Mechanism of foaming phenomena during pre-heating in the liquid phase synthesis of bio-jet fuel form triglycerides

[P14] Optimization of reaction conditions with machine learning in woody biomass solvolysis using vegetable oil solvent

[P15] Efficient prediction of jet fraction yield and optimal condition using machine learning in catalytic cracking of vegetable oils

Authentication

[P09] Mechanistic study of Ni₂P catalyzed dehydrogenative coupling of methane

[P11] Development of low-temperature methanol synthesis process from CO₂

[P12] Gas-phase hydrogenation of CO₂ over supported iron-based catalysts.