Atomic Configurations Research Articles

Size and shape dependence of hydrogen-induced phase transformation and sorption hysteresis in palladium nanoparticles

Abstract Phase transitions of metals in hydrogen environments are critically important for applications in energy storage, catalysis, and sensing. Nanostructured metallic particles can lead to faster charging and discharging kinetics, increased lifespan, and enhanced catalytic activities. However, establishing a direct causal link between nanoparticle structure and function remains challenging. In this work, we establish a computational framework to explore the atomic configuration of a metal-hydrogen (M-H) system when in equilibrium with a H environment. This approach combines Diffusive Molecular Dynamics with an iteration strategy, aiming to minimize the system's free energy and ensure uniform chemical potential across the system that matches that of the H environment. Applying this framework, we investigate H chemical potential-composition isotherms during the hydrogenation and dehydrogenation of palladium nanoparticles, ranging in size from $3.9$ nm to $15.6$ nm and featuring various shapes including cube, rhombic dodecahedron, octahedron, and sphere. Our findings reveal an abrupt phase transformation in all examined particles during both H loading and unloading processes, accompanied by a distinct hysteresis gap between absorption and desorption chemical potentials. Notably, as particle size increases, absorption chemical potential rises while desorption chemical potential declines, consequently widening the hysteresis gap across all shapes. Regarding shape effects, we observe that, at a given size, cubic particles exhibit the lowest absorption chemical potentials during H loading, whereas octahedral particles demonstrate the highest. Moreover, octahedral particles also exhibit the highest desorption chemical potentials during H unloading. These size and shape effects are elucidated by statistics of atomic volumetric strains resulting from specific facet orientations and inhomogeneous H distributions. Prior to phase transformation in absorption, a H-rich surface shell induces lattice expansion in the H-poor core, while before phase transformation in desorption, surface stress promotes lattice compression in the H-rich core. The magnitude of the volumetric strains correlates well with the size and shape dependence, underlining their pivotal role in the observed phenomena.

Influence of oxygen impurities in generating ferromagnetism in GaN doped with Mn, Fe, and Cr

We report the influence of oxygen impurities in generating ferromagnetism in GaN doped with Mn, Fe, and Cr through superexchange involving Mn–O–Mn, Fe–O–Fe, and Cr–N–Cr atomic configurations. Density Functional Theory (DFT) calculations demonstrated that these configurations originate within VGa-ON\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{\ ext{Ga}}-{O}_{\ ext{N}}$$\\end{document} complex defects by incorporating Mn2+, Fe2+, and Cr3+ ions into gallium vacancies (VGa\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{\ ext{Ga}}$$\\end{document}) sites promoted by the presence of oxygen as a substitutional impurity (ON\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${O}_{\ ext{N}}$$\\end{document}). These co-doped GaN microstructures were synthesized using the thermal evaporation method. Cathodoluminescence (CL) and photoluminescence (PL) measurements confirmed the presence of VGa-ON\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{\ ext{Ga}}-{O}_{\ ext{N}}$$\\end{document} complex defects in all GaN-grown samples. X-ray photoelectron spectroscopy (XPS) measurements confirmed the successful incorporation of Mn2+, Fe2+, and Cr3+ ions in GaN samples. SQUID measurements demonstrated room-temperature ferromagnetism with respective saturation magnetization (Ms) and coercive field (Hc) values of ± 1.5 × 10−5 emu and 4 mT for GaN:O,Mn, ± 4.4 × 10−5 emu and 2.6 mT for GaN:O,Fe, and ± 1.7 × 10−5 emu and 2.6 mT for GaN:O,Cr.

Molecular dynamics study of the scratching property of the tetrahedral amorphous carbon coating on the piston ring

In order to reduce friction and wear of the piston ring-cylinder liner system of the internal combustion engine, the tetrahedral amorphous carbon (ta-C) coating on the piston ring is considered. The scratching properties of the ta-C coating and diamond ball are studied by molecular dynamics simulation. The atomic configuration, surface morphology, RMS roughness, friction force, coefficient of friction, wear rate, and normal stress of the ta-C coating are analysed under different scratching depths, substrate temperatures, and scratching velocities. The interatomic interactions are described using the second nearest-neighbour modified embedded-atom method potential, as well as Tersoff potential and Lennard-Jones potential. The simulation results show that the ta-C coating exhibits excellent scratching properties. The scratching depth has a significant effect on the scratching property of the ta-C coating, while the substrate temperature and scratching velocity have a relatively small effect.

Cobalt Nitride-Implanted PtCo Intermetallic Nanocatalysts for Ultrahigh Fuel Cell Cathode Performance.

Stable and active oxygen reduction electrocatalysts are essential for practical fuel cells. Herein, we report a novel class of highly ordered platinum-cobalt (Pt-Co) alloys embedded with cobalt nitride. The intermetallic core-shell catalyst demonstrates an initial mass activity of 0.88 A mgPt-1 at 0.9 V with 71% retention after 30,000 potential cycles of an aggressive square-wave accelerated durability test and loses only 9% of its electrochemical surface area, far exceeding the US Department of Energy 2025 targets, with unprecedented stability and only a minimal voltage loss under practical fuel cell operating conditions. We discover that regulating the atomic ordering in the core results in an optimal lattice configuration that accelerates the oxygen reduction kinetics. The presence of cobalt nitride decorated within PtCo superlattices guarantees a larger barrier to Co dissolution, leading to the excellent endurance of the electrocatalysts. This work brings up a transformative structural engineering strategy for rationally designing high-performing Pt-based catalysts with a unique atomic configuration for broad practical uses in energy conversion technology.

Transforming Nanocrystals into Superhard Boron Carbide Nanostructures.

Boron carbide (B4+δC) possesses a large potential as a structural material owing to its lightness, refractory character, and outstanding mechanical properties. However, its large-scale industrialization is set back by its tendency to amorphize when subjected to an external stress. In the present work, we design a path toward nanostructured boron carbide with greatly enhanced hardness and resistance to amorphization. The reaction pathway consists of triggering an isomorphic transformation of covalent nanocrystals of Na1-xB5-xC1+x (x = 0.18) produced in molten salts. The resulting 10 nm B4.1C nanocrystals exhibit a 4-fold decrease of size compared to previous works. Solid-state 11B and 13C NMR coupled to density functional theory (DFT) reveal that the boron carbide nanocrystals are made of a complex mixture of atomic configurations, which are located at the covalent structural chains between B11C icosahedral building units. These nanocrystals are combined with a spark plasma-sintering-derived method operated at high pressure. This yields full densification while maintaining the particle size. The nanoscaled grains and high density of grain boundaries provide the resulting nanostructured bodies with significantly enhanced hardness and resistance to amorphization, thus delivering a superhard material.

The Emerging Strategy of Symmetry Breaking for Enhancing Energy Conversion and Storage Performance.

Symmetry breaking has emerged as a novel strategy to enhance energy conversion and storage performance, which refers to changes in the atomic configurations within a material reducing its internal symmetry. According to the location of the symmetry breaking, it can be classified into spontaneous symmetry breaking within the material, local symmetry breaking on the surface of the material, and symmetry breaking caused by external fields outside the material. However, there are currently few summaries in this field, so it is necessary to summarize how symmetry breaking improves energy conversion and storage performance. In this review, the fundamentals of symmetry breaking are first introduced, which allows for a deeper understanding of its meaning. Then the applications of symmetry breaking in energy conversion and storage are systematically summarized, providing various mechanisms in energy conversion and storage, as well as how to improve energy conversion performance and storage efficiency. Last but not least, the current applications of symmetry breaking are summarized and provide an outlook on its future development. It is hoped that this review can provide new insights into the applications of symmetry breaking and promote its further development.

Bandgap Characteristics of Boron-Containing Nitrides—Ab Initio Study for Optoelectronic Applications

Hexagonal boron nitride (h-BN) is recognized as a 2D wide bandgap material with unique properties, such as effective photoluminescence and diverse lattice parameters. Nitride alloys containing h-BN have the potential to revolutionize the electronics and optoelectronics industries. The energy band structures of three boron-containing nitride alloys—BxAl1−xN, BxGa1−xN, and BxIn1−xN—were calculated using standard density functional theory (DFT) with the hybrid Heyd–Scuseria–Ernzerhof (HSE) function to correct lattice parameters and energy gaps. The results for both wurtzite and hexagonal structures reveal several notable characteristics, including a wide range of bandgap values, the presence of both direct and indirect bandgaps, and phase mixing between wurtzite and hexagonal structures. The hexagonal phase in these alloys is observed at very low and very high boron concentrations (x), as well as in specific atomic configurations across the entire composition range. However, cohesive energy calculations show that the hexagonal phase is more stable than the wurtzite phase only when x > 0.5, regardless of atomic arrangement. These findings provide practical guidance for optimizing the epitaxial growth of boron-containing nitride thin films, which could drive future advancements in electronics and optoelectronics applications.

Step‐Directed Epitaxy of Unidirectional Hexagonal Boron Nitride on Vicinal Ge(110)

Insulating hexagonal boron nitride (hBN) films with precisely controlled thickness are ideal dielectric components to modulate various interfaces in electronic devices. To achieve this, high‐quality hBN with controlled atomic configurations must be able to form pristine interfaces with various materials in devices. However, previously reported large‐scale hBN films with uniform thickness either are polycrystalline or are not suitable for atomically clean assembly via mechanical exfoliation, limiting their applications in device technology. Herein, the large‐scale growth of monolayer (ML) single crystalline hBN films on Ge(110) substrates by using chemical vapor deposition is reported. Vicinal Ge(110) substrates are used for the step‐directed epitaxial growth of hBN, where Ge atomic steps act as the hBN nucleation sites, guiding the unidirectional alignments of multiple hBN domains. Density functional theory calculations reveal that the optimum hydrogen passivations on both hBN edges and Ge surfaces enable the epitaxial coupling between hBN and the Ge step edges and the single crystallinity of the final hBN films. Using epitaxially grown ML hBN films, a few hBN films with controlled stacking orders and pristine interfaces through a layer‐by‐layer assembly process are fabricated. These films function as high‐quality dielectrics to enhance carrier transport in graphene and MoS2 channels.

A Radial Distribution Function Based Recognition Algorithm of Point Defects in Large-Scale β-Ga2O3 Systems.

The atomic configurations and concentrations of intrinsic defects profoundly influence the electrical and optical properties of the semiconductor materials. This influence is particularly significant in the case of β-Ga2O3, which is a highly promising ultrawide bandgap semiconductor characterized by highly complex intrinsic defect configurations. Despite its importance, there is a notable absence of an accurate method to recognize these defects in large-scale atomistic computational modeling. We design an effective algorithm for the explicit identification of various intrinsic point defects in the β-Ga2O3 lattice, which constitutes the integration of the particle swarm optimization (PSO) and K-means clustering (K-MC) methods. Our algorithm attains the recognition accuracy exceeding 95%. Finally, the algorithm is applied to dynamic simulations, where the feasibility of dynamic real-time detection is explored.

Neural-network approach to running high-precision atomic computations

Modern applications of atomic physics, including the determination of frequency standards and the analysis of astrophysical spectra, require prediction of atomic properties with exquisite accuracy. For complex atomic systems, high-precision calculations are a major challenge due to the exponential scaling of the involved electronic configuration sets. This exacerbates the problem of required computational resources for these computations and makes indispensable the development of approaches to select the most important configurations out of otherwise intractably huge sets. We have developed a neural-network (NN) tool for running high-precision atomic configuration interaction (CI) computations with iterative selection of the most important configurations. Integrated with the established atomic codes, our approach results in computations with significantly reduced computational requirements in comparison with those without NN support. We showcase a number of NN-supported computations for the energy levels of Fe16+ and Ni12+ and demonstrate that our approach can be reliably used and automated for solving specific computational problems for a wide variety of systems. Published by the American Physical Society 2024

Machine learning force field for thermal oxidation of silicon.

Looking back at seven decades of highly extensive application in the semiconductor industry, silicon and its native oxide SiO2 are still at the heart of several technological developments. Recently, the fabrication of ultra-thin oxide layers has become essential for keeping up with trends in the down-scaling of nanoelectronic devices and for the realization of novel device technologies. With this comes a need for better understanding of the atomic configuration at the Si/SiO2 interface. Classical force fields offer flexible application and relatively low computational costs, however, suffer from limited accuracy. Ab initio methods give much better results but are extremely costly. Machine learning force fields (MLFF) offer the possibility to combine the benefits of both worlds. We train a MLFF for the simulation of the dry thermal oxidation process of a Si substrate. The training data are generated by density functional theory calculations. The obtained structures are in line with abinitio simulations and with experimental observations. Compared to a classical force field, the most recent reactive force field, the resulting configurations are vastly improved. Our potential is publicly available in an open-access repository.

Structural entropy of glass-forming liquid

Drawing on Shannon entropy, we developed a parameter called “structural entropy,” which is derived uniquely from atomic configurations and serves to measure the evolution of disorder during the glass transition. We applied this parameter to the glass transition in the CuZrAl system. A comparison with configurational entropy suggests that both may fundamentally encapsulate the same physical concept: the system’s level of disorder. This new structural entropy parameter bridges the gap between the macroscopic properties and the microscopic structure of glass, offering insights into the mechanisms underlying the glass transition.

Engineering the Atomic Configurations of Surface-Active Sites for Retuning the Photoreduction CO2 Selectivity

Engineering the Atomic Configurations of Surface-Active Sites for Retuning the Photoreduction CO₂ Selectivity

Insights of the Multimode Orientation-Dependent Initial Oxidation of Aluminum by First-Principles Theory Calculations.

A fundamental understanding of the oxidation mechanisms of aluminum (Al) alloys is of great importance for its applications in corrosion, catalysis, sensors, etc. In this work, we systematically investigated the first-stage oxidation behaviors of three low-index Al facets with O coverage up to two monolayers (ML) by using density-functional theory (DFT). The large negative adsorption energies indicated favorable oxidation on all three facets. However, distinctive structural and electronic changes induced by the adsorption of oxygen have led to different oxidation modes. More specifically, the oxidation process proceeded by "intercalating" into the subsurface region along the (111) plane out of the (110) facet with spontaneous O ingress into (110) far below one ML, as revealed by the electron density distribution, whereas the oxide ad-layer grew in a "layer-by-layer" mode on Al(111) and (001) facets. Moreover, various Al-O complexes with different atomic coordination numbers (CN), configurations, and sizes may be indicators of the tendency of an Al surface to be oxidized. Besides, the oxide phases formed on (111)/(001) and (110) assembled the Al-O bond distribution within α-Al2O3 and γ-Al2O3, respectively.

Adsorption Property and Morphology Evolution of C Deposited on HCP Co Nanoparticles.

Despite extensive studies of deposited carbon in Fischer-Tropsch synthesis (FTS), an atomic-level comprehension of the effect of carbon on the morphology of cobalt-based FTS catalysts remains elusive. The adsorption configurations of carbon atoms on different crystal facets of hexagonal close-packed (hcp) Co nanoparticles were studied using density functional theory (DFT) calculations to explore the interaction mechanism between C and Co surfaces. The weaker adsorption strength of C atoms on Co(0001), Co(10-10), and Co(11-20) surfaces accounted for lower diffusion energy, leading to the facile formation of C dimers. Electronic property analysis shows that more electrons are transferred from Co surfaces to C atoms on corrugated facets than on flat facets. The deposition of carbon atoms on Co nanoparticles affects surface energy by forming strong Co-C bonds, which causes the system to reach a more energetically favorable morphology with an increased proportion of exposed Co(10-12) and Co(11-20) areas as the carbon content increases slightly. This transformation in morphology implies that C deposition plays a crucial role in determining the facet proportion and stability of exposed Co surfaces, contributing to the optimization of cobalt-based catalysts with improved performance.

Analysis of mapping atomic models to coarse-grained resolution.

Low-resolution coarse-grained (CG) models provide significant computational and conceptual advantages for simulating soft materials. However, the properties of CG models depend quite sensitively upon the mapping, M, that maps each atomic configuration, r, to a CG configuration, R. In particular, M determines how the configurational information of the atomic model is partitioned between the mapped ensemble of CG configurations and the lost ensemble of atomic configurations that map to each R. In this work, we investigate how the mapping partitions the atomic configuration space into CG and intra-site components. We demonstrate that the corresponding coordinate transformation introduces a nontrivial Jacobian factor. This Jacobian factor defines a labeling entropy that corresponds to the uncertainty in the atoms that are associated with each CG site. Consequently, the labeling entropy effectively transfers configurational information from the lost ensemble into the mapped ensemble. Moreover, our analysis highlights the possibility of resonant mappings that separate the atomic potential into CG and intra-site contributions. We numerically illustrate these considerations with a Gaussian network model for the equilibrium fluctuations of actin. We demonstrate that the spectral quality, Q, provides a simple metric for identifying high quality representations for actin. Conversely, we find that neither maximizing nor minimizing the information content of the mapped ensemble results in high quality representations. However, if one accounts for the labeling uncertainty, Q(M) correlates quite well with the adjusted configurational information loss, Îmap(M), that results from the mapping.

Optical and electronic properties of RENiO3 doped with alkali earth metals (Be, Mg, Ca, Sr and Ba): Combining first principles calculations and machine learning

The perovskite rare earth nickelate (RENiO3) has attracted significant attention owing to its peculiar physical properties and promising potential for diverse applications. It is reported that introducing H or Li might change the electronic and optical properties of RENiO3. However, little is known about multi-electrons doping in RENiO3. In this study, the bandgaps, optical and electronic properties were investigated in RENiO3 with alkaline earth metal (AEM) elements (Be, Mg, Ca, Sr and Ba) doping. For the atomic configurations of doped RENiO3, the interstitial sites of RENiO3 are more likely to be occupied by Be, Mg and Ca atoms, whereas Sr and Ba atoms tend to replace RE atoms in RENiO3. The band gap of RENiO3 decreases after AEM doping. Moreover, the machine learning results found that the formation energy of the AEM, the relative atomic mass of the AEM, and the doping position significantly influence the band gap. Furthermore, the infrared light blocking capability, the visible light transmission, and the electronic conductivity are enhanced in AEM doped RENiO3. This study may contribute to the experimental modulation of the optical and electronic properties of RENiO3 through AEM doping.

Crystal structures and electronic and magnetic properties of Janus bilayer Cl[formula omitted]Cr[formula omitted]I[formula omitted]

Two-dimensional (2D) magnetic material CrI3 has aroused extensive attention, because it could provide a new platform for investigating the relations between crystal structures and electronic and magnetic properties. Here, we study crystal structures and electronic and magnetic properties of three configurations (Cl-Cl I-I and Cl-I) of Janus bilayer Cl3Cr2I3 with two stacking orders (AB and AA1/3) by using the first principles approach incorporating the spin–orbit coupling (SOC) effect and the dipole correction. It is found that the spin polarization and the SOC effect can expand the lattice constant and the interlayer distance (ID) of the three configurations. Especially, the ID of the I-I configuration is 1 Å larger than that of the Cl-Cl configuration. The total energy calculation results show that the atomic configuration, the SOC effect and the stacking order play an important role in determining the magnetic ground states of the Janus layers. Our results indicate the atomic configurations of the Janus bilayers are not conducive to the increase of critical temperature. Interestingly, the Cl-I configuration has a vertical dipole moment, and its AFM state has large spin splitting. It is revealed that the non-periodic structure, the symmetry breaking of the average potential and the weak interlayer interaction lead to the vertical dipole moment and the abnormal AFM state that is not the most stable state.

Large coercivity and enhanced magnetization in La-substituted Sm6Mn23 alloys

The magnetic properties of Sm6Mn23-based alloys are still not fully understood for their high complexity in magnetic and crystallographic structures. This work presents studies of the structure and magnetic properties of Sm6Mn23 and Sm5LaMn23 alloys. The results show that both the binary and La-substituted ternary alloys crystallize in a cubic Th6Mn23 type structure (Fm-3m) with trace amount of Mn impurities. The lattice parameter of Sm5LaMn23 is slightly larger than that of Sm6Mn23. The Curie temperature of Sm5LaMn23 is ∼403 K, which is lower than that of Sm6Mn23. A field-dependent magnetic transition was observed in Sm5LaMn23, which shows a decreasing temperature at which Sm5LaMn23 exhibiting maximal magnetization with increasing field, indicating a suppression of the antiferromagnetic coupling of the rare earth and Mn moments under applied field. Large coercivities up to 0.74 T and 1.2 T are observed in Sm5LaMn23 bulk alloys and powders, respectively. The saturate magnetization, the remanent magnetization, and the coercivity of Sm5LaMn23 at 5 K are much higher than that of Sm6Mn23. The ball-milled Sm5LaMn23 powders exhibit significantly enhanced coercivity and magnetization. The refinement of the grain size during ball-milling results in the enhanced coercivity. The magnetic purification of the powders and possible local ferromagnetic configuration of the surface Mn atoms may result in the enhanced magnetization.

The tensile behaviour of non-equi-atomic configurations of multiple elemental alloys: molecular dynamics based study

This article aims to study the effect of lattice distortion on the mechanical behavior of equi-atomic and non-equi-atomic configurations of high entropy alloys. Molecular dynamics-based simulations were performed with an embedded atomic method force field. Random alloy configuration of multiple elemental alloys (MEAs) was developed along with average atom (A-atom) configurations by modifying the embedded atom potential. The non-equi-atomic configuration of MEAs was generated by varying the contribution of Cr, Co, Fe, Cu, Ni, and Cr in pairs and all together. It was predicted from the simulations that the deformation governing mechanism, as well as the tensile strength of high entropy alloys, can be tailored by switching from equi-atomic to non-equi-atomic configurations of high entropy alloys. Increasing the composition of Cr, Fe, and Ni helps enhance the tensile strength and Young's modulus of the high entropy alloy, which is even higher than equi-atomic configurations. Partial Shockley dislocations, in conjunction with the phase change from fcc to hcp, primarily govern the deformation in the non-equi-atomic composition of MEAs. The tensile behaviour of MEAs was directly associated with the distortion present in the lattice, which was quantified with the help of the radial distribution function. It was revealed from the simulations that lattice distortion present in the random alloy configuration helps in improving the ductility of material by early onset of dislocation emission. A higher value of lattice distortion also increases the gap between the peak stress values in A-atom and random alloy configurations. The article will help develop high-entropy alloys for broader space, nuclear, defense, and energy generation applications.