"Keisuke Kameda,Sergei Manzhos,Manabu Ihara","炭素と二酸化炭素の酸化還元反応を利用した大容蓄電技術「カーボン空気二次電池システム」",,"月刊 電設技術 -特集 二次電池の現状と用途およびライフサイクル- 4月号",,,,,2024,Apr.
"Keisuke Kameda,Kei Nakagawa,Yasutomo Koga,Kexin Chen,Reimi Takagi,Taishiro Wakamiya,Narumi Okazaki,Hyojae Lee,Natsuki Otoshi,Sergei Manzhos,Manabu Ihara","電極反応モデルに基づく水素発電におけるBaZr0.9Y0.1O3-δ添加Ni/YSZ燃料極の反応種被覆率の推定","化学工学会 第89年会 (堺)",,,,,,2024,Mar.
"Natsuki Otoshi,Hyojae Lee,Keisuke Kameda,Sergei Manzhos,Manabu Ihara","リアルタイム雲画像データに基づく日射成分を用いた影を含む太陽電池発電量予測モデル","化学工学会 第89年会 (堺)",,,,,,2024,Mar.
"Takuma Okamoto,Anastassia Sorkin,Keisuke Kameda,Wang Hao,Sergei Manzhos,Manabu Ihara","Rutile型酸化チタンの自然発生的粒界形成の検討","第71回応用物理学会春季学術講演会",,,,,,2024,Mar.
"Ruicheng Li,Keisuke Maeda,Man-Fai Ng,Keisuke Kameda,Sergei Manzhos,Manabu Ihara","Exploring Electronic Properties of Carbon Nanoflake-Based Materials for Charge Transport Layers in Perovskite Solar Cells: Insight from Solid-state Modelling","第71回応用物理学会春季学術講演会",,,,,,2024,Mar.
"Sergei Manzhos","Insightful machine learning beyond traditional neural networks and kernel regression",,,,,,,2024,Mar.
"Sergei Manzhos","Beyond silicon solar cells",,,,,,,2024,Mar.
"Hirokatsu Yoshioka,Sayaka Shirakura,Keisuke Kameda,Sergei Manzhos,Manabu Ihara","熱・電力需要の変動が建物規模分散型水素蓄エネルギーシステムの経済性に与える影響","化学工学会 第89年会 (堺)",,,,,,2024,Mar.
"Kexin Chen,Aulia Sukma Hutama,Keisuke Kameda,Sergei Manzhos,Manabu Ihara","Modulation of Molecular Adsorption Properties of Zirconia Nanoparticles: A Density Functional Tight Binding Theory Study",,,,,,,2024,Mar.
"Keisuke Kameda,Taishiro Wakamiya,Kexin Chen,Sergei Manzhos,Manabu Ihara","炭素析出制御可能なカーボン空気二次電池システムの電極開発","化学工学会 第89年会 (堺)",,,,,,2024,Mar.
"Chen Kexin,Kameda Keisuke,Koga Yasutomo,Manzhos Sergei,Ihara Manabu","Modelling of CO/CO2 Electrode Reactions in Carbon/Air Secondary Battery System","化学工学会第89年会 (堺)",,,,,,2024,Mar.
"MANZHOS SERGEI","Machine learning beyond off-the-shelf methods",,,,,,,2024,Feb.
"Sergei Manzhos","Beyond neural networks and kernel regression: hybrid methods for machine learning from sparse data in high-dimensional spaces",,,,,,,2024,Feb.
"Sergei Manzhos","Machine learning for advancing large scale ab initio materials modeling",,,,,,,2024,Feb.
"S. Manzhos, M,Ihara","Machine learning in computational chemistry beyond off-the-shelf methods: how to cut the cost, handle overfitting, and obtain elements of insights","International Workshop on Massively Parallel Programming for Quantum Chemistry and Physics (MPQCP 2024)",,,,,,2024,Jan.
"S. Manzhos,M. Ihara","Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimension",,"The Journal of Chemical Physics",,"Volume 160","Issue 2",,2024,Jan.
"Methawee Nukunudompanich,H. Yoon,Lee Hyojae,Keisuke Kameda,Manabu Ihara,Sergei Manzhos","Machine learning of properties of lead-free perovskites with a neural network with additive kernel regression-based neuron activation functions",,"MRS Advances",,,,,2024,Jan.
"Takuma Okamoto,A. Sorkin,Keisuke Kameda,Manabu Ihara,H. Wang,Sergei Manzhos","Natural-like generation of grain boundary models and the combined effects of microstructural elements and lithiation on the plastic behavior of TiO2: a computational study",,"Computational Materials Science",,,,,2024,