6 papers
Band Structure Modulation of ZrO2 Nanoparticles for Control of CO Adsorption Properties: A Combined Density Functional Theory - Density Functional Tight Binding Study
Kexin Chen, William Dawson, Aulia Sukma Hutama +4
We present a combined density functional theory (DFT) and density functional tight binding (DFTB) study of zirconia (ZrO2) nanoparticles of experimentally relevant sizes of several…
Neural networks for neurocomputing circuits: a computational study of tolerance to noise and activation function non-uniformity when machine learning materials properties
Ye min Thant, Methawee Nukunudompanich, Chu-Chen Chueh +2
Dedicated analog neurocomputing circuits are promising for high-throughput, low power consumption applications of machine learning (ML) and for applications where implementing a di…
Gaussian Process Regression -- Neural Network Hybrid with Optimized Redundant Coordinates
Sergei Manzhos, Manabu Ihara
Recently, a Gaussian Process Regression - neural network (GPRNN) hybrid machine learning method was proposed, which is based on additive-kernel GPR in redundant coordinates constru…
Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory
Sergei Manzhos, Johann Luder, Pavlo Golub +1
Machine learning (ML) of kinetic energy functionals (KEF) for orbital-free density functional theory (OF-DFT) holds the promise of addressing an important bottleneck in large-scale…
A machine-learned kinetic energy model for light weight metals and compounds of group III-V elements
Johann Lüder, Manabu Ihara, Sergei Manzhos
We present a machine-learned (ML) model of kinetic energy for orbital-free density functional theory (OF-DFT) suitable for bulk light weight metals and compounds made of group III-…
Machine learning the screening factor in the soft bond valence approach for rapid crystal structure estimation
Keisuke Kameda, Takaaki Ariga, Kazuma Ito +2
Development of new functional ceramics is important for several applications, including electrochemical batteries and fuel cells. Computational prescreening and selection of such m…