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Investigating Li$^+$ transport within the amorphous lithium phosphorous oxynitride (LiPON) framework, especially across a Li||LiPON interface, has proven challenging due to its amorphous nature and varying stoichiometry, necessitating large…
Once trained, machine-learned interatomic potentials (MLIPs) provide a fast and accurate way to study catalytic reaction pathways, but their performance strongly depends on the training set. Here, we compare nine MLIPs trained with…
Powder neutron diffraction experiments have been employed to establish the effects of site-selective magnetic dilution in the Sm2MnMnMn4-x Tix O12 A-site columnar ordered quadruple perovskite manganites (x = 1, x = 2 and x = 3). We show…
Molecular dynamics (MD) employing machine-learned interatomic potentials (MLIPs) serve as an efficient, urgently needed complement to ab initio molecular dynamics (aiMD). By training these potentials on data generated from ab initio…
The synthesis of metal-organic frameworks (MOFs) in a monolithic morphology is a promising way to achieve the transition of this class of materials from academia to industrial applications. The sol-gel process has been widely employed to…
Polynomial machine learning potentials (MLPs) based on polynomial rotational invariants have been systematically developed for various systems and applied to efficiently predict crystal structures. In this study, we propose a robust…
The electronic structure of SrBi2Ta2O9 is investigated from first-principles, within the local density approximation, using the full-potential linearized augmented plane wave (LAPW) method. The results show that, besides the large…
We report neutron inelastic scattering on single crystal 0.68Pb(Mg1/3Nb2/3O3)-0.32PbTiO3 (PMN-0.32PT), a relaxor ferroelectric material that lies within the compositional range of the morphotropic phase boundary (MPB). Data were obtained…
Na-ion batteries (NIBs) are increasingly looked at as a viable alternative to Li-ion batteries due to the abundance, low cost, and thermal stability of Na-based systems. To improve the practical utilization of NIBs in applications, it is…
We have performed molecular dynamics simulations using a shell model potential developed by fitting first principles results to describe the behavior of the relaxor-ferroelectric (1-x)PbMg1/3Nb2/3O3-xPbTiO3 (PMN-xPT) as function of…
Atomistic modeling is a widely employed theoretical method of computational materials science. It has found particular utility in the study of magnetic materials. Initially, magnetic empirical interatomic potentials or spin-polarized…
Machine-learning interatomic potentials (MLIPs) have become a mainstay in computationally-guided materials science, surpassing traditional force fields due to their flexible functional form and superior accuracy in reproducing physical…
Fracture toughness ($K_\mathrm{Ic}$) and fracture strength ($\sigma_\mathrm{f}$) are key criteria in the selection and design of reliable ceramics. However, their experimental characterization remains challenging -- especially for ceramic…
Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are…
Structures of metal nanoparticles (NPs) significantly influence their catalytic reactivities. Recent in situ experimental observations of dramatic structural changes in NPs have underscored the need to establish a dynamic structure-property…
Prevailing machine-learned interatomic potential (MLIP) uncertainty-quantification methods rely on ensembles of independently trained backbones. These methods scale unfavorably with foundation-scale MLIPs, and their member-disagreement…
Machine learning interatomic potentials (MLIPs) offer first-principles accuracy with reduced computational cost, but their transferability across different thermodynamic states remains questionable, particularly for fluid systems where…
Machine-learning interatomic potentials (MLIPs) have greatly extended the reach of atomic-scale simulations, offering the accuracy of first-principles calculations at a fraction of the cost. Leveraging large quantum mechanical databases and…
Ferroelectric domain structure evolution induced by an external electric field was investigated by means of nematic liquid crystal (NLC) method in two strontium-barium niobate single crystals of nominal composition:…
Using inelastic neutron scattering we measured the microscopic magnetic coupling associated with the ferromagnetic (FM) clusters of the ``colossal magnetoresistance'' (CMR) compound Pr$_{0.70}$Ca$_{0.30}$MnO$_3$. When the insulating to…