Intrinsic point defects in buckled and puckered arsenene: a first-principles study.

Using first-principles calculations, we study the structural, energetic, and electronic properties of various point defects in arsenene. Stone-Wales defects are found to be thermodynamically favorable and are predicted to be stable at room temperature. Defects are found to significantly influence the electronic properties in buckled phase. In particular, single vacancies generate gap states whereas strain induced states close to the valence and conduction band edges are observed for Stone-Wales and di-vacancy defects. The computed band structures of di-vacancy defects in puckered phase are less disturbed compared to the corresponding band structures in the buckled one. The influence of a hydrogen-rich atmosphere on the electronic properties of defective arsenene is also investigated. Hydrogen termination of mono/di-vacancies is an exothermic process which removes all defect induced gap states.

Harnessing machine learning for efficient large-scale interatomic potential for sildenafil and pharmaceuticals containing H, C, N, O, and S.

In this study a cutting-edge approach to producing accurate and computationally efficient interatomic potentials using machine learning algorithms is presented. Specifically, the study focuses on the application of Allegro, a novel machine learning algorithm, running on high-performance GPUs for training potentials. The choice of training parameters plays a pivotal role in the quality of the potential functions. To enable this methodology, the "Solvated Protein Fragments" dataset, containing nearly 2.7 million Density Functional Theory (DFT) calculations for many-body intermolecular interactions involving protein fragments and water molecules, encompassing H, C, N, O, and S elements, is considered as the training dataset. The project optimizes computational efficiency by reducing the initial dataset size according to the intended application. To assess the efficacy of the approach, the sildenafil citrate, iso-sildenafil, aspirin, ibuprofen, mebendazole and urea, representing all five relevant elements, serve as the test bed. The results of the Allegro-trained potentials demonstrate outstanding performance, benefiting from the combination of an appropriate training dataset and parameter selection. This notably enhanced computational efficiency when compared to the computationally intensive DFT method aided by GPU acceleration. Validation of the produced interatomic potentials is achieved through Allegro's own evaluation mechanism, yielding exceptional accuracy. Further verification is carried out through LAMMPS molecular dynamics simulations. Structural optimization by energy minimization and NPT Molecular Dynamics simulations are performed for each potential, assessing relaxation processes and energy reduction. Additional structures, including urea, ammonia, uracil, oxalic acid, and acetic acid, are tested, highlighting the potential's versatility in describing systems containing the aforementioned elements. Visualization of the results confirms the scientific accuracy of each structure's relaxation. The findings of this study demonstrate strong scaling and the potential for applications in pharmaceutical research, allowing the exploration of larger molecular structures not previously amenable to computational analysis at this level of accuracy The success of the machine learning approach underscores its potential to revolutionize computational solid-state physics.

Nanostructure and strain in InGaN/GaN superlattices grown in GaN nanowires.

The structural properties and the strain state of InGaN/GaN superlattices embedded in GaN nanowires were analyzed as a function of superlattice growth temperature, using complementary transmission electron microscopy techniques supplemented by optical analysis using photoluminescence and spatially resolved microphotoluminescence spectroscopy. A truncated pyramidal shape was observed for the 4 nm thick InGaN inclusions, where their (0001¯) central facet was delimited by six-fold {101¯l} facets towards the m-plane sidewalls of the nanowires. The defect content of the nanowires comprised multiple basal stacking faults localized at the GaN base/superlattice interface, causing the formation of zinc-blende cubic regions, and often single stacking faults at the GaN/InGaN bilayer interfaces. No misfit dislocations or cracks were detected in the heterostructure, implying a fully strained configuration. Geometrical phase analysis showed a rather uniform radial distribution of elastic strain in the (0001¯) facet of the InGaN inclusions. Depending on the superlattice growth temperature, the elastic strain energy is partitioned among the successive InGaN/GaN layers in the case of low-temperature growth, while at higher superlattice growth temperature the in-plane tensile misfit strain of the GaN barriers is accommodated through restrained diffusion of indium from the preceding InGaN layers. The corresponding In contents of the central facet were estimated at 0.42 and 0.25, respectively. However, in the latter case, successful reproduction of the experimental electron microscopy images by image simulations was only feasible, allowing for a much higher occupancy of indium adatoms at lattice sites of the semipolar facets, compared to the invariable 25% assigned to the polar facet. Thus, a high complexity in indium incorporation and strain allocation between the different crystallographic facets of the InGaN inclusions is anticipated and supported by the results of photoluminescence and spatially resolved microphotoluminescence spectroscopy.

Atomic-resolution imaging of surface and core melting in individual size-selected Au nanoclusters on carbon.

Although the changes in melting behaviour on the nanoscale have long attracted the interest of researchers, the mechanism by which nanoparticles melt remains an open problem. We report the direct observation, at atomic resolution, of surface melting in individual size-selected Au clusters (2-5 nm diameter) supported on carbon films, using an in situ heating stage in the aberration corrected scanning transmission electron microscope. At elevated temperatures the Au nanoparticles are found to form a solid core-liquid shell structure. The cluster surface melting temperatures, show evidence of size-dependent melting point suppression. The cluster core melting temperatures are significantly greater than predicted by existing models of free clusters. To explore the effect of the interaction between the clusters and the carbon substrate, we employ a very large-scale ab initio simulation approach to investigate the influence of the support. Theoretical results for surface and core melting points are in good agreement with experiment.

Energetic, structural and electronic properties of metal vacancies in strained AlN/GaN interfaces.

AlN/GaN heterostructures have been studied using density-functional pseudopotential calculations yielding the formation energies of metal vacancies under the influence of local interfacial strains, the associated charge distribution and the energies of vacancy-induced electronic states. Interfaces are built normal to the polar <0 0 0 1> direction of the wurtzite structure by joining two single crystals of AlN and GaN that are a few atomic layers thick; thus, periodic boundary conditions generate two distinct heterophase interfaces. We show that the formation energy of vacancies is a function of their distance from the interfaces: the vacancy-interface interaction is found repulsive or attractive, depending on the type of the interface. When the interaction is attractive, the vacancy formation energy decreases with increasing the associated electric charge, and hence the equilibrium vacancy concentration at the interface is greater. This finding can reveal the well-known morphological differences existing between the two types of investigated interfaces. Moreover, we found that the electric charge is strongly localized around the Ga vacancy, while in the case of Al vacancies is almost uniformly distributed throughout the AlN/GaN heterostructure. Crucially, for the applications of heterostructures, metal vacancies introduce deep states in the calculated bandgap at energy levels from 0.5 to 1 eV above the valence band maximum (VBM). It is, therefore, predicted that vacancies could initiate 'green luminescence' i.e. light emission in the energy range of 2.5 eV stemming from electronic transitions between these extra levels, and the conduction band, or energy levels, due to shallow donors.

Atomic scale morphology, growth behaviour and electronic properties of semipolar {101[overline]3} GaN surfaces.

First-principles calculations relating to the atomic structure and electronic properties of {101[overline]3} GaN surfaces reveal significant differentiations between the two polarity orientations. The (101[overline]3) surface exhibits a remarkable morphological stability, stabilizing a metallic structure (Ga adlayer) over the entire range of the Ga chemical potential. In contrast, the semiconducting, cleaved surface is favoured on (101[overline]3[overline]) under extremely and moderately N-rich conditions, a Ga bilayer is stabilized under corresponding Ga-rich conditions and various transitions between metallic reconstructions take place in intermediate growth stoichiometries. Efficient growth schemes for smooth, two-dimensional GaN layers and the isolation of {101[overline]3} material from parasitic orientations are identified.