Publications

The field of machine learning-based interatomic potentials (ML-IAPs) has seen increasing development in recent years. In this work, we compare three widely used ML-IAPs–the moment tensor potential (MTP), the spectral neighbor analysis potential (SNAP), and the tabulated Gaussian approximation potential (tabGAP)with a conventional non-ML-IAP, the embedded atom method (EAM) potential. We evaluated these potentials on the basis of their accuracy and efficiency in determining basic structural parameters and Peierls stress under equivalent conditions. Three tungsten (W)-based alloys (Mo-W, Nb-W, and Ta-W) are considered, and their lattice parameter, formation energy, elastic tensor, and Peierls stress of edge dislocation are calculated. Compared with DFT results, MTP demonstrates the highest accuracy in predicting the lattice parameter and the best computational efficiency among the three ML-IAPs, while tabGAP accurately predicts two independent elastic constants, C₁₁ and C₁₂. Despite being the slowest, SNAP shows the highest accuracy in predicting the third independent elastic constant C₄₄ and its Peierls stress value is comparable to that based on MTP.

This review aims to give a collective analysis of ionic transport mechanisms through the solid electrolyte interphase (SEI) in lithium-ion batteries. In electrochemical cells, the SEI is the least understood and most important complex thin layer that forms on electrodes when they come in contact with electrolytes. Though the SEI is the key factor in any electrochemical cell, the complete picture of the SEI is still fuzzy because of its diverse and dynamic nature. To address the complexity of this interphase, the fabric of this review is arranged in such a way that each component of the SEI is separately analyzed by means of its chemical structure and the possible diffusion mechanism. Since most of the studies about ionic transport through the SEI are based on first-principles studies, a section of this review is devoted to discussing the theoretical concepts of ionic transport. Further, this review has audited other possible means of ionic transport occurring through grain boundaries including open channels. A brief overview of the electronic conductivity of SEI components is also included herewith.

Density functional theory (DFT) calculations are performed to study the effects of ferromagnetism on basic structural parameters including lattice parameters and elastic constants in 45 body-centered cubic (BCC) Fe-based random binary alloys. Each binary consists of Fe and one of the five pure BCC metals, including Mo, Nb, Ta, V, and W. To provide references, six pure metals are also studied. It is found that (i) the effects of ferromagnetism are more pronounced for elastic constants than for lattice parameter, (ii) the effects of ferromagnetism increase with the Fe concentration in the binary, (iii) when ferromagnetism is neglected in DFT calculations, pure Fe is elastically unstable, while most Fe-based alloys are stable, and (iv) relatively good estimates of the structural parameters of alloys can be provided via the simple rule of mixtures only when the ferromagnetism is included.