89 citations · 135 across the 12 of their papers we have counts for
13 papers
Impact of interstitial carbon on local lattice distortions in CoCrFeMnNi high-entropy alloys
Alevtina Smekhova, Alexei Kuzmin, G. Mohan Muralikrishna +5
Here, we explore component-dependent local lattice distortions in polycrystalline, equiatomic, face-centered cubic CrMnFeCoNi high-entropy alloys and their modifications induced by…
An Ontology for Machine Learning Interatomic Potentials
Daniel Hernández, Jong Hyun Jung, Yuji Ikeda +11
Machine learning interatomic potentials (MLIPs) approximate quantum-mechanical energies and forces---conventionally computed by density functional theory (DFT) or wave-function met…
Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature
Shivam Dangwal, Pranav Kumar, Yuji Ikeda +2
High-entropy alloys (HEAs) have received considerable attention for hydrogen storage because of their compositional flexibility; however, designing HEAs with optimal thermodynamics…
Hydrogen uptake and hydride formation in AlCoCrFeNi high-entropy alloys: First-principles, universal-potential, and experimental study
Fritz Körmann, Yuji Ikeda, Konstantin Glazyrin +9
Hydrogen uptake in complex multicomponent alloys, including high-entropy alloys (HEAs), governs both hydrogen storage capacity and resistance to hydrogen-induced degradation. We co…
Finely Tunable Thermal Expansion of NiTi by Stress-Induced Martensitic Transformation and Thermomechanical Training
Won Seok Choi, Won-Seok Ko, Yejun Park +6
Tailoring the thermal expansion of martensitic materials by crystallographic texture and anisotropic variation of lattice parameters is a promising route to a flexible design of th…
Hydrogen diffusion in TiCrH Laves phases: A combined ab initio and machine-learning-potential study
Pranav Kumar, Fritz Körmann, Kaveh Edalati +2
The kinetics of hydrogen diffusion in C15 cubic and C14 hexagonal TiCrH (0 < <= 4) Laves-phase hydrogen storage alloys is investigated with density functional theory (D…
Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling
Yongliang Ou, Lena Scholz, Sanath Keshav +7
Improving solid electrolytes is critical for high-performance all-solid-state batteries, yet the microstructural features that enable fast ion transport remain poorly understood. H…
Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions
Yuji Ikeda, Axel Forslund, Pranav Kumar +4
Machine-learning interatomic potentials (MLIPs) enable large-scale atomistic simulations at moderate computational cost while retaining ab initio accuracy. MLIPs trained on coupled…
Free-energy perturbation in the exchange-correlation space accelerated by machine learning: Application to silica polymorphs
Axel Forslund, Jong Hyun Jung, Yuji Ikeda +1
We propose a free-energy-perturbation approach accelerated by machine-learning potentials to efficiently compute transition temperatures and entropies for all rungs of Jacob's ladd…
Machine Learning Potentials for Hydrogen Absorption in TiCr Laves Phases
Pranav Kumar, Fritz Körmann, Blazej Grabowski +1
The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCrH Laves phases is investigated for with density functional theory (DFT) and machine l…
Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte LiPSCl using machine-learning interatomic potentials
Yongliang Ou, Yuji Ikeda, Lena Scholz +3
LiPSCl is a promising candidate for the solid electrolyte in all-solid-state Li-ion batteries. In applications, this material is in a polycrystalline state with grain bound…
Mechanism of anatase-to-columbite TiO2 phase transformation via sheared phases: first-principles calculations and high-pressure torsion experiments
Jacqueline Hidalgo-Jimenez, Taner Akbay, Yuji Ikeda +2
High-pressure torsion (HPT) can facilitate phase transformations in titanium dioxide (TiO2) and stabilize its high-pressure columbite phase, as an active photocatalyst, by shear st…
Machine learning to explore high-entropy alloys with desired enthalpy for room-temperature hydrogen storage: Prediction of density functional theory and experimental data
Shivam Dangwal, Yuji Ikeda, Blazej Grabowski +1
Safe and high-density storage of hydrogen, for a clean-fuel economy, can be realized by hydride-forming materials, but these materials should be able to store hydrogen at room temp…