Manabu Ihara

Tokyo Institute of Technology — Japan

Materials Science · Physical Sciences

26h-index2.7kcitations433works4.72yr avg
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Research Topics

Advancements in Solid Oxide Fuel Cells(61), Fuel Cells and Related Materials(57), Asymmetric Synthesis and Catalysis(51), Electrocatalysts for Energy Conversion(38), Synthetic Organic Chemistry Methods(34)

Publications433 total

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox
Advanced Intelligent Discovery·2026Open Access
Neural networks for neurocomputing circuits: A computational study of tolerance to noise and activation function non-uniformity when machine learning materials properties
Artificial Intelligence Chemistry·2025Open Access
Effects of nonlinearity and inter-feature coupling in machine learning studies of Nb alloys with center-environment features
Journal of Materials Informatics·2025· 6 citedOpen Access
A novel encoding method for high-dimensional categorical data for electricity demand forecasting in distributed energy systems
Applied Energy·2025· 2 cited
Corrigendum to “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” [Comput. Mater. Sci. 239 (2024) 112989]
Computational Materials Science·2025· 1 cited
Effects of nonlinearity and inter-feature coupling in machine learning of substitution energy of Nb alloys with center-environment features
2025Open Access
Kernel regression methods for prediction of materials properties: Recent developments
Chemical Physics Reviews·2025· 10 citedOpen Access
Exploring the electronic properties of carbon nanoflake-based charge transport materials for perovskite solar cells: a computational study
Physical Chemistry Chemical Physics·2025· 1 cited
Significantly Improved Stability of Carbon/Air Secondary Battery System By Separating Carbon Deposition Area
ECS Meeting Abstracts·2024
Concept and Advantages of Carbon/Air Secondary Battery System as a Fixed Compact Power Storage with Large Capacity
ECS Meeting Abstracts·2024
The Analysis of Electron Densities: From Basics to Emergent Applications
Chemical Reviews·2024· 35 cited
A machine-learned kinetic energy model for light weight metals and compounds of group III-V elements
Electronic Structure·2024· 6 citedOpen Access
Computational Investigation of the Potential and Limitations of Machine Learning with Neural Network Circuits Based on Synaptic Transistors
The Journal of Physical Chemistry Letters·2024· 6 citedOpen Access
Machine learning the screening factor in the soft bond valence approach for rapid crystal structure estimation
arXiv (Cornell University)·2024Open Access
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· 3 cited
Machine learning of properties of lead-free perovskites with a neural network with additive kernel regression-based neuron activation functions
MRS Advances·2024· 8 cited
Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimension
The Journal of Chemical Physics·2024· 15 citedOpen Access
Comparison of Different Types of Machine Learning Methods for Short-Term Prediction of Electricity Demand in a Small-Scale Distributed Energy System from High Dimensional Data
SSRN Electronic Journal·2024Open Access
A Novel Encoding Method for High-Dimensional Categorical Data for Electricity Demand Forecasting in Distributed Energy Systems
SSRN Electronic Journal·2024Open Access
A Novel Encoding Method for High-Dimensional Categorical Data for Electricity Demand Forecasting in Distributed Energy Systems
SSRN Electronic Journal·2024Open Access
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Frequent Co-authors

Sergei Manzhos(10), Hiroshi Komiyama(6), Takahiro Igarashi(4), Tsuneo Kusunoki(4), K. Ohno(4), Kei Hasegawa(4), Hiroyuki Shimada(4), Akifusa Hagiwara(4), Kôichi Yamada(3), J. Krogh-Moe(3), Shinichi Hasegawa(3), Teruyuki Shimizu(3), Yasunori Kikuchi(3), Yongcheng Jin(3), Tetsuhiko Isobe(2), Mamoru Senna(2), Chiaki Yokoyama(2), H. Maeno(2), K. Miyamoto(2), Xinyu Li(2)