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Akira TAKAHASHI
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Year
Representation of compounds for machine-learning prediction of physical properties
A Seko, H Hayashi, K Nakayama, A Takahashi, I Tanaka
Physical Review B 95 (14), 144110, 2017
2882017
Sparse representation for a potential energy surface
A Seko, A Takahashi, I Tanaka
Physical Review B 90 (2), 024101, 2014
1102014
First-principles interatomic potentials for ten elemental metals via compressed sensing
A Seko, A Takahashi, I Tanaka
Physical Review B 92 (5), 054113, 2015
902015
Conceptual and practical bases for the high accuracy of machine learning interatomic potentials: Application to elemental titanium
A Takahashi, A Seko, I Tanaka
Physical Review Materials 1 (6), 063801, 2017
662017
Electrically Benign Defect Behavior in Zinc Tin Nitride Revealed from First Principles
N Tsunoda, Y Kumagai, A Takahashi, F Oba
Physical Review Applied 10 (1), 011001, 2018
412018
Machine learning models for predicting the dielectric constants of oxides based on high-throughput first-principles calculations
A Takahashi, Y Kumagai, J Miyamoto, Y Mochizuki, F Oba
Physical Review Materials 4 (10), 103801, 2020
372020
Insights into oxygen vacancies from high-throughput first-principles calculations
Y Kumagai, N Tsunoda, A Takahashi, F Oba
Physical Review Materials 5 (12), 123803, 2021
362021
Theoretical exploration of mixed-anion antiperovskite semiconductors M 3 X N (M= Mg, Ca, Sr, Ba; X= P, As, Sb, Bi)
Y Mochizuki, HJ Sung, A Takahashi, Y Kumagai, F Oba
Physical Review Materials 4 (4), 044601, 2020
292020
Linearized machine-learning interatomic potentials for non-magnetic elemental metals: Limitation of pairwise descriptors and trend of predictive power
A Takahashi, A Seko, I Tanaka
The Journal of Chemical Physics 148 (23), 234106, 2018
232018
Point defects in -type transparent conductive (, Ga, In) from first principles
T Gake, Y Kumagai, A Takahashi, F Oba
Physical Review Materials 5 (10), 104602, 2021
82021
Origin of large magnetostriction in palladium cobalt and palladium nickel alloys: Strong pseudo-dipole interactions between palladium–cobalt and palladium–nickel atomic pairs
T Harumoto, J Shi, Y Nakamura, A Takahashi
Applied Physics Letters 118 (10), 102401, 2021
52021
Adaptive Sampling Methods via Machine Learning for Materials Screening
A Takahashi, Y Kumagai, H Aoki, R Tamura, F Oba
Science and Technology of Advanced Materials: Methods 2 (1), 55-66, 2022
42022
Oxygen vacancies in α-(Al x Ga1-x )2O3 alloys: A first-principles study
T Ishii, A Takahashi, T Nagafuji, F Oba
Applied Physics Express, 2023
12023
Fully autonomous materials screening methodology combining first-principles calculations, machine learning and high-performance computing system
A Takahashi, K Terayama, Y Kumagai, R Tamura, F Oba
Science and Technology of Advanced Materials: Methods, 2261834, 2023
2023
Dielectric ceramic composition and ceramic capacitor
T Murata, H AKAMATSU, F Oba, A Takahashi
US Patent App. 17/498,430, 2022
2022
Defect formation and carrier compensation in the layered oxychalcogenide La 2 CdO 2 Se 2: an insight from first principles
T Gake, Y Kumagai, A Takahashi, H Hiramatsu, F Oba
Journal of Materials Chemistry C, 2022
2022
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