Related papers: Complex $\mathrm{Ga}_{2}\mathrm{O}_{3}$ Polymorphs…
Gallium oxide (Ga2O3) is a wide-bandgap semiconductor with promising applications in high-power and high-frequency electronics. However, its complex polymorphic nature poses substantial challenges for fundamental studies, particularly in…
Ga$_2$O$_3$ and its polymorphs are attracting increasing attention. The rich structural space of polymorphic oxide systems such as Ga$_2$O$_3$ offers potential for electronic structure engineering, which is of particular interest for a…
We introduce machine-learned potentials for Ag-Pd to describe the energy of alloy configurations over a wide range of compositions. We compare two different approaches. Moment tensor potentials (MTP) are polynomial-like functions of…
Recently reported remarkably high radiation tolerance of $\gamma$/$\beta$-Ga$_2$O$_3$ double-polymorphic structure brings this ultrawide bandgap semiconductor to the frontiers of power electronics applications that are able to operate in…
Gallium oxide is a novel advanced material gaining increasing attention for its unique combination of functional properties. It forms in several phases or polymorphs - {\alpha}, {\beta}, {\gamma}, and {\kappa} - having variable properties…
Developing data-driven machine-learning interatomic potentials for materials containing many elements becomes increasingly challenging due to the vast configuration space that must be sampled by the training data. We study the learning…
The Gaussian approximation potential (GAP) is an accurate machine-learning interatomic potential that was recently extended to include the description of radiation effects. In this study, we seek to validate a faster version of GAP, known…
Ga2O3 is a wide-band-gap semiconductor of great interest for applications in electronics and optoelectronics. Two-dimensional (2D) Ga2O3 synthesized from top-down or bottom-up processes can reveal brand new heterogeneous structures and…
We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorphous elemental carbon. Based on a machine-learning representation of the density-functional theory (DFT) potential-energy surface, such…
Machine learning (ML) has become widely used in the development of interatomic potentials for molecular dynamics simulations. However, most ML potentials are still much slower than classical interatomic potentials and are usually trained…
The search for new wide band gap materials is intensifying to satisfy the need for more advanced and energy efficient power electronic devices. Ga$_2$O$_3$ has emerged as an alternative to SiC and GaN, sparking a renewed interest in its…
We explore different ways to simplify the evaluation of the smooth overlap of atomic positions (SOAP) many-body atomic descriptor [Bart\'{o}k et al., Phys. Rev. B 87, 184115 (2013)]. Our aim is to improve the computational efficiency of…
We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed using the Gaussian approximation potential (GAP) methodology. The potential, named GAP-20, describes the properties of the bulk crystalline…
We present a swift walk-through of our recent work that uses machine learning to fit interatomic potentials based on quantum mechanical data. We describe our Gaussian Approximation Potentials (GAP) framework, discussing a variety of…
Van der Waals In$_2$Se$_3$ has garnered significant attention due to its unique properties and wide applications associated with its rich polymorphs and polymorphic phase transitions. Despite extensive studies, the vast complex polymorphic…
Split Ga vacancies are the dominant native acceptor in $\beta$-$Ga_2O_3$; however, their role in $\alpha$ and $\kappa$ phases has been largely overlooked or assumed to be unfavorable. A detailed understanding of these defects is critical…
Its piezo- and potentially ferroelectric properties make the metastable kappa polymorph of Ga$_2$O$_3$ an interesting material for multiple applications, while In-incorporation into any polymorphs of Ga$_2$O$_3$ allows to lower their…
We introduce a new class of machine learning interatomic potentials - fast General Two- and Three-body Potential (GTTP), which is as fast as conventional empirical potentials and require computational time that remains constant with…
The pressure-induced polymorphism of binary octect compounds has long been considered a settled problem although the possible atomic disordering of some phases remains a puzzling observation. Taking GaP as a case study, we conclude, through…
The ultrawide-bandgap semiconductor $\beta$-Ga2O3 holds exceptional promise for next-generation power electronics and deep-ultraviolet optoelectronics, yet its widespread application is hindered by the lack of cost-effective, high-quality…