Atomic Interactions Research Articles

Revealing the correlation between asymmetric structure and low thermal conductivity in Janus-graphene via machine learning force constant potential

Understanding the fundamental link between structure and functionalization is crucial for designing and optimizing functional materials, since different structural configurations could trigger materials to demonstrate diverse physical and chemical properties. However, the correlation between crystal structure and thermal conductivity (κ) remains unclear. In this study, taking two-dimensional (2D) carbon allotropes Janus-graphene and graphene as study cases, we utilize phonon Boltzmann transport equation combined with machine learning potential to thoroughly investigate the complex folding structure of pure sp2 hybridized Janus-graphene from the perspective of crystal structure, phonon modal resolved thermal transport, and atomic interactions, with the goal of identifying the underlying relationship between 2D geometry and κ. The results reveal that the folded structure in Janus-graphene causes strong symmetry breaking, significantly reduces phonon group velocities, increases phonon–phonon scattering, and ultimately leads to low κ. These findings enhance our understanding of how atomic structure folding affects thermal transport and the relationship between structure and functionalization.

Atomic Hydrogen Interaction with Transition Metal Surfaces: A High-Throughput Computational Study

Atomic Hydrogen Interaction with Transition Metal Surfaces: A High-Throughput Computational Study

Theoretical Study of Position-Dependent Mass Particle in Cosmic String Space-Time and External Magnetic Field

In this work, we discuss the case of a non-relativistic quantum particle in the cosmic string space-time under the influence of the presence of external magnetic and exponential potential. It’s shown with the help of the Laplace transform method the second-order differential equation of the Schrodinger equation is solvable where it is reduced to a first-order differential equation. We obtain the eigenfunction and the non-relativistic energy spectrum. In addition, these results may be useful in the future study of thermodynamic, optic, and magnetic properties of the atomic interaction of a system particle. Keywords: Schrodinger equation; Laplace transform method; Position dependent mass; External magnetic field; Cosmic string

A Dynamical Density Field That Shows the Localizability of Electrons: The Exchange-Correlation Ehrenfest Force.

A gradual but steady tide in theoretical chemistry is favoring the exploration of atomic and molecular interactions through the dynamical forces perceived and exerted by the particles of a system. By integrating the quantum mechanical force operator over all the spin and all but one of the spatial coordinates of the electrons, the Ehrenfest force density field reveals these forces directly and is separable into a classical term, related to the electric field, and a quantum mechanical correction, which we introduce and analyze for various atoms and molecules in this work. This exchange-correlation Ehrenfest force density field, Fxc(r), excludes the dominant nuclear components that shape the full Ehrenfest field, revealing information about electron sharing, pairing, and delocalization. In a manner similar, though not equal, to the electron localization function, Fxc(r) unveils covalent and core basins. Its divergence, ∇·Fxc(r), indicates the presence of electron shells in atoms and recovers the positions of lone pairs and the shell structure of ionic, polar, and covalent interactions in molecules. It also exhibits a semiquantitative match with the Laplacian of the electron density that we also explore. In alignment with the established role of exchange-correlation as nature's glue, we demonstrate that a significant number of fundamental concepts in chemical bonding can be derived from the Fxc(r) dynamical field.

Molecular dynamics study on the enhancement of high‐temperature friction and mechanical properties of perfluoroelastomers by carbon nanomaterials

AbstractThe mechanical and frictional properties of pure perfluoroelastomer, graphene (GN)/perfluoroelastomer, and carbon nanotube (CNT)/perfluoroelastomer composite systems were investigated using molecular dynamics simulations. The influence of carbon nanomaterials on the glass transition temperature, mechanical properties, and frictional behavior of perfluoroelastomers at various temperatures was evaluated. The simulation results demonstrated that the addition of GN and CNTs increased the glass transition temperature of perfluoroelastomers to varying extents. CNTs enhanced the mechanical properties of perfluoroelastomers more effectively than GN, whereas GN provided superior improvement in frictional properties compared to CNTs. Analysis of stress–strain distribution, atomic motion trajectory, interaction energy, mass density, and temperature distribution, bond orientation parameters, radial distribution function (RDF), mean square displacement (MSD), and diffusion coefficients revealed the mechanisms and differences by which GN and CNTs enhance the mechanical and frictional properties of perfluoroelastomers.Highlights Carbon nanomaterials enhance perfluoroelastomer's high‐temperature performance. CNTs provide higher mechanical strength but lower wear resistance. GN nanosheets outperform CNTs in reducing friction and wear. Molecular dynamics simulations reveal distinct enhancement mechanisms.

Interaction of complex particles: A framework for the rapid and accurate approximation of pair potentials using neural networks

Motivated by the limitations of conventional coarse-grained molecular dynamics for simulation of large systems of nanoparticles and the challenges in efficiently representing general pair potentials for rigid bodies, we present a method for approximating general rigid body pair potentials based on a specialized type of deep neural network that maintains essential properties, such as conservation of energy and invariance to the chosen origins of the particles. The network uses a specialized geometric abstraction layer to convert the relative coordinates of the rigid bodies to input more suitable to a conventional artificial neural network, which is trained together with the specialized layer. This results in geometric representations of the particles optimized for the specific potential. The network can be trained directly on scalar values to fit a model without explicit gradient and then used to efficiently evaluate the force and torque on the particles resulting from the potential. The concept is demonstrated with an atomistic interaction model for carbon nanotubes and the resulting model is compared with a common type of coarse-grained model optimized for the same potential, with even very small networks comparing favourably and larger networks achieving up to two orders of magnitude lower cost. The sensitivity to noise in the training data is investigated and the model is found to strongly reject noise up to 12.5% given a dataset of 107 samples. The performance of a proof-of-concept implementation is demonstrated on a variety of hardware, showing the models viability for large-scale simulations. Furthermore, generalization to soft bodies and potentials for polydisperse systems are discussed. Published by the American Physical Society 2024

Interactions involved in the adsorption of ethylene glycol and 2-hydroxyethoxide on the Au(111) surface: a Density Functional Theory study.

The monolayers of ethylene glycol and 2-hydroxyethoxide on gold surfaces have been used in hybrid materials as biosensors. In this article, the adsorption of ethylene glycol and 2-hydroxyethoxide on the Au(111) surface was analyzed. For the first system, ethylene glycol on Au(111), there are Au O and Au H interactions. To the best of our knowledge, the Au H interaction has been overlooked until now. However, in this work, there is strong evidence that this interaction is important to stabilize the system. For the second system, the atomic interactions mentioned previously are also predicted, although there is an additional interaction between 2-hydroxyethoxide molecules. Such an interaction induces the link -O-H-O-, with high values of the electron density at the critical points of the corresponding bond path of the O-H interaction. These links suggest the forming of ethylene glycol chains. The calculations were performed using two exchange-correlation functionals: BEEF-vdW and C09 -vdW; both functionals incorporate dispersion effects within the Kohn-Sham approach in Density Functional Theory as implemented in GPAW code and ASE computational packages. The contacts between the molecules considered in this article and the Au(111) surface were analyzed through the Quantum Theory of Atoms in Molecules implemented in GPUAM code.

Molecular Dynamics Simulation of High-Energy Beam Irradiation of SiO2 Single Crystal with Three Different Morphologies: No Free Surface, with a Free Surface, and Thin Films

Abstract High-energy beam irradiation of SiO2 crystal with the α-quartz structure was simulated by the molecular dynamics method. Three types of specimen structures were examined: a single crystal without a free surface, a single crystal with a free surface, and a thin film. After structural relaxation at room temperature, a cylindrical region with diameter of 3.0 nm was set at the center of the specimen and high-thermal energy of Seff = 0.1 – 2.5 keV/nm was added to that region, where Seff is the effective stopping power. Atomic motions were calculated by the molecular dynamics method using the large-scale atomic/molecular massively parallel simulator). Vashishta potential was used for the atomic interaction. The single crystal structure of α-quartz without the free surface was stable up to 1.0 keV/nm and it gradually became amorphous with increasing thermal energy. In contrast, the single crystal structure with the free surface was stable up to 0.5 keV/nm and was amorphous at higher thermal energy. In particular, the atomic structures for the thermal impact Seff ≥ 2.0 keV/nm had a facet-like structure at the impacted surface, which corresponds to actual experimental results. Nano-hole formation was observed in the irradiation process of the film structure.

Copper diffusion hindrance in Ti-TM (TM = W, Ru) alloys: A first-principles insight

This study utilizes DFT calculations to assess the effectiveness of Ti-TM (TM = W, Ru) alloys in obstructing copper diffusion, a pivotal factor for semiconductor device reliability. The calculated diffusion barriers for Cu in TiRu and Ti4W12 alloys are found to be 0.48 eV and 0.34 eV, respectively, significantly surpassing the 0.25 eV barrier for Cu diffusion in Si. This comparative analysis highlights the enhanced diffusion resistance of these alloys, with TiRu displaying a barrier nearly twice that of Si. An in-depth examination of the electronic structure and microstructural attributes of the alloys indicates that atomic interactions at the Cu/Ti-TM interface play a crucial role in hindering Cu diffusion. The local density of states, charge density differences, and electron localization functions were scrutinized to clarify the nature of these interactions. The research uncovers that the combined action of Ru, W, Cu, and Ti atoms leads to a synergistic strengthening of the diffusion barrier, implying a robust interatomic repulsion that restricts Cu migration. The findings contribute to a deeper fundamental understanding of Cu diffusion mechanisms in Ti-TM alloys and offer a scientific basis for the judicious selection of materials for diffusion barrier layers. The study supports the further exploration and potential application of TiRu and Ti4W12 alloys in the semiconductor industry.

Crystal Chemistry at Interfaces Between Liquid Al and Polar SiC{0001} Substrates

Silicon carbide (SiC) has been widely added into light metals, e.g., Al, to enhance their mechanical performance and corrosion resistance. SiC particle-reinforced metal matrix composites (SiC-MMCs) exhibit low weight/volume ratios, high strength/hardness, high corrosion resistance, and thermal stability. They have potential applications in aerospace, automobiles, and other specialized equipment. The macro-mechanical properties of Al/SiC composites depend on the local structures and chemical interactions at the Al/SiC interfaces at the atomic level. Moreover, the added SiC particles may act as potential nucleation sites during solidification. We investigate local atomic ordering and chemical interactions at the interfaces between liquid Al (Al(l) in short) and polar SiC substrates using ab initio molecular dynamics (AIMD) methods. The simulations reveal a rich variety of interfacial interactions. Charge transfer occurs from Al(l) to C-terminating atoms (Δq = 0.3e/Al on average), while chemical bonding between interfacial Si and Al(l) atoms is more covalent with a minor charge transfer of Δq = 0.04e/Al. The prenucleation at both interfaces is moderate with three to four recognizable layers. The information obtained here helps increase understanding of the interfacial interactions at Al/SiC at the atomic level and the related macro-mechanical properties, which is helpful in designing novel SiC-MMC materials with desirable properties and optimizing related manufacturing and machining processes.

Hydrogen adsorption on zinc-terminated ZnO(0001) surface at varying coverages and its effects on electronic and optical properties: a DFT+U study

Abstract Spin-polarized density functional theory implementing Hubbard corrections (DFT + U) were utilized to study H adsorption of different coverages on Zn-terminated ZnO(0001) surface. Changes in electronic and optical properties were observed upon H adsorption of varying coverages, namely with 0.25 monolayer (ML), 0.50 ML, 1 ML, and 2 ML coverage. In terms of surface structure, H atoms were found to adsorb on top of Zn forming Zn–H bond lengths ranging from 1.54–1.73 Å for certain coverages. On the other hand, O–H bond length values are 2.41 Å and 2.37 Å for 0.50 ML and 2 ML coverage respectively. Additionally, for 0.50 ML, the most stable configuration is when one H atom adsorbs on top of Zn and the other near the hollow site. At low coverage (0.25 ML and 0.50 ML), H prefers to interact with topmost layer Zn atoms resulting to shifts in the electronic bands relative to the pristine surface’s. In addition, at high coverage (1 ML and 2 ML), shifting of bands are observed and are mainly guided by Zn–H atom interaction for 1 ML and weak H–O atom interaction for 2 ML. The observed decrease in band gap as the coverage was increased from 1 ML to 2 ML is supported by the red shift in the absorption plot. However, for low H coverage adsorption, the optical plots deviate due to emergence of flat bands. Changes in electronic properties such as shifts in conduction band minimum and decrease in measured band gap occur as guided by the interaction of adsorbed H atoms with the surface atoms and are supported with obtained optical plots. These findings present the tunability of Zn-terminated ZnO(0001) polar surface properties depending on H coverage.

Behaviour of 1-butyl-3-methylimidazolium chloride, 1-butyl-3-methylimdazolium thiocyanate and 1-butyl-1-methypyrrolidium chloride in dimethyl sulfoxide: Experimental, NCI and QTAIM analysis

The aim of this study is to examine the cation and anion influence on intermolecular interactions of mixtures comprising ionic liquids (ILs): 1-butyl-3-methylimidazolium chloride [Bmim][Cl], 1-butyl-3-methylimdazolium thiocyanate [Bmim][SCN] and 1-butyl-1-methylpyrrolidium chloride [Bmpym][Cl] with dimethyl sulfoxide (DMSO) at various temperatures. To understand the influence of cation and anion as well as temperature on interactions between the mixtures, thermodynamics parameters: apparent molar properties were calculated from the measured density (ρ) and sound velocity (u) data and fitted to the Redlich-Mayer type equation in order to obtained limiting apparent molar properties of the studied mixtures. A detailed non-covalent interaction (NCI) and quantum theory of atoms in molecules (QTAIM) analysis was done using density functional theory calculations. These calculations provided information on the electrostatic interactions between the anion, cation, and solvent. The experimental and computational results show that there is hydrogen bonding and strong ionic interactions in the studied systems.

Unveiling the structural mechanisms behind high affinity and selectivity in phosphorylated epitope-specific rabbit antibodies.

Protein phosphorylation is a crucial process in various cellular functions, and its irregularities have been implicated in several diseases, including cancer. Antibodies are commonly employed to detect protein phosphorylation in research. However, unlike the extensive studies on recognition mechanisms of the phosphate group by proteins such as kinases and phosphatases, only a few studies have explored antibody mechanisms. In this study, we produced and characterized two rabbit monoclonal antibodies that recognize a mono-phosphorylated Akt peptide. Through crystallography, thermodynamic mutational analyses, and molecular dynamics simulations, we investigated the unique recognition mechanism that enables higher binding affinity and selectivity of the antibodies compared to other generic proteins with lower binding affinity to phosphorylated epitopes. Our results demonstrate that molecular dynamics simulations provide novel insights into the dynamic aspects of molecular recognition of post-translational modifications by proteins beyond static crystal structures, highlighting how specific atomic level interactions drive the exceptional affinity and selectivity of antibodies.

Study on the Mechanical Properties of beta Silicon Nitride Based on Neural Network Potential

Silicon nitride is widely utilized in the manufacture of cutting tools, bearings, and engine components, making accurate predictions of its mechanical and thermal behaviors crucial for engineering design. This study significantly advances the modeling of complex atomic interactions by employing machine learning, specifically Neural Network Potential (NNP), to enhance precision over traditional empirical potentials. Through NNP, predictions of stress-strain curves, thermal conductivity, and grain boundary behavior are achieved. The results demonstrate that NNP not only reduces computational time but also enhances the accuracy of material property predictions. This work provides the mechanical and thermal performance of Si3N4 and opens new avenues for further applications of machine learning in advanced ceramic materials.

Atomic Printing Strategy Achieves Precise Anchoring of Dual-Copper Atoms on C2N Structure for Efficient CO2 Reduction to Ethylene.

Isolated metal sites catalysts (IMSCs) play crucial role in electrochemical CO2 reduction, with potential industrial applications. However, tunable synthesis strategies for IMSCs are limited. Herein, we present an atomic printing strategy that draws inspiration from the ancient Chinese "movable-type printing technology". Selecting customizable combinations of metal atoms as metal precursors from an extensive binuclear metal library. A series of dual-atom catalysts were prepared by utilizing the edge nitrogen atoms in the C2N cavity as anchoring "pincers" to capture metal atoms. To prove utility, the dual atom catalyst Cu2-C2N is investigated as electrocatalytic CO2RR catalyst. The synergistic interaction of dual Cu atoms promotes C-C coupling and guarantees FEC2+ (90.8 %) and FEC2H4. (71.7 %) at -1.10 V vs RHE. DFT calculations revealed the Cu2 site would be subtly flipped during CO2RR for enhancing *CO adsorption and dimerization. We validate that atomic printing strategies are applicable to wide range of metal combinations, representing a significant advancement in the development of IMSCs.

Atomic scale in-situ observation of gas-solid interaction regulating the pre-nucleation process of Pd atomic clusters

Advancements in nanotechnology have propelled the understanding of atomic-scale nucleation processes, essential for the evolution of atomic manufacturing. The process of amorphous precursors nucleation showcases a complex transition influenced by various factors. Utilizing aberration-corrected ETEM and theoretical calculation, we explore the nucleation of amorphous Pd atomic clusters. This study examines the nucleation dynamics and gas-solid interaction regulating of Pd clusters on ultrathin carbon films, prepared via electron beam evaporation. HRTEM observation and FFT analysis reveal that, in the early stage of nucleation, Pd cluster growth predominantly follows an Ostwald ripening-like mechanism. Atoms from smaller clusters migrate and attach to larger ones, facilitating their progression to critical nucleation size. Environmental conditions significantly influence this process; hydrogen atmospheres lower the surface energy of Pd clusters, reducing the critical nucleation size, while argon atmospheres impede growth of Pd clusters by occupying migration sites on the carbon surface. These insights into atomic cluster behavior and environmental interactions are crucial for understanding the early stages of nucleation from amorphous to crystalline and can help opens new avenues for the controlled fabrication of materials with optimized functionalities.

Electron work function guided tailoring of (W4-x, Mx)C4 /doped Ni matrix interfacial bonding: Insights from first-principles calculations

Heavy tungsten carbide (WC) may cause inhomogeneous distributions in WC-metal matrix composite hardfacing overlays, thus negatively affecting its performance as reinforcement. WC can be lightened by partially substituting W with lighter metals, e.g., Mo and Cr, while maintaining its strength. However, the bonding between modified WC and matrix metals such as nickel (a typical metal-matrix for overlays) is uncertain. This article reports a study on the interfacial bonding between (W4-x, Mx)C4 (M=Mo or Cr) and Ni matrix via first-principle calculations. Different atomic interactions i.e., metal-metal and metal-carbon interactions, at the interface were studied to understand the interfacial bonding through analyses of electron work function (EWF), electron localization function, electronic density of states, bond order, and net charge. It was demonstrated that the lighter (W4-x, Mx)C4 carbides exhibit strong bonding with Ni, comparable to or even stronger than that of WC/Ni interface, and the interfacial bonding includes covalent, ionic and metallic bond components. It is demonstrated that the interfacial bonding can be tuned by doping elements in the Ni matrix with different EWFs, e.g., Mn, Cu, Au, Pt, and Se. Efforts have been made to verify a hypothesis that EWF is an indicator, which can be used to guide selecting effective dopants for tailoring the interfacial bond strength.

Engineering Rydberg-pair interactions in divalent atoms with hyperfine-split ionization thresholds

Quantum information processing with neutral atoms relies on Rydberg excitation for entanglement generation. While the use of heavy divalent or open-shell elements, such as strontium or ytterbium, has benefits due to their optically active core and a variety of possible qubit encodings, their Rydberg structure is generally complex. For some isotopes in particular, hyperfine interactions are relevant even for highly excited electronic states. We employ multichannel quantum defect theory to infer the Rydberg structure of isotopes with nonzero nuclear spin and perform nonperturbative Rydberg-pair interaction calculations. We find that due to the high level density and sensitivities to external fields, experimental parameters must be precisely controlled. Specifically in Sr87, we study an intrinsic Förster resonance, unique to divalent atoms with hyperfine-split thresholds, which simultaneously provides line stability with respect to external field fluctuations and enhanced long-range interactions. Additionally, we provide parameters for pair states that can be effectively described by single-channel Rydberg series. The explored pair states provide exciting opportunities for applications in the blockade regime, as well as for more exotic long-range interactions such as largely flat, distance-independent potentials. Published by the American Physical Society 2024

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

Investigation of self-diffusion and specific heat capacity of eutectic al-si systems using molecular dynamics simulations with ADP

Aluminum-silicon (Al-Si) alloys are of significant interest in various engineering applications due to their favorable mechanical properties and low density. Understanding the thermodynamic and transport properties of these alloys is essential for optimizing their performance in practical applications. In this study, an angular dependent potential (ADP) for Al-Si systems is employed to describe the atomic interactions and dynamics of an Al-Si alloy system. A set of molecular dynamics (MD) simulations are performed to explore the diffusion behavior of the Al-Si alloy at different temperatures, with a specific focus on the eutectic composition of the Al-Si system. The mean squared displacement (MSD) method is applied to calculate its diffusion coefficients, enabling a detailed analysis of the system’s atomic mobility and transport characteristics. Furthermore, the specific heat capacity of the Al-Si system is determined through energy fluctuation analysis, providing insights into the system’s thermodynamic behavior. The obtained diffusion coefficients play a vital role in predicting the kinetics of the eutectic solidification of Al-Si alloys, while the specific heat capacity will facilitate the understanding of the thermal behavior and the energy changes associated with the eutectic reaction in such alloys.