Interatomic Interactions Research Articles

Simulation of ordering and diffusion in CrxMoNbTaVW alloys within the framework of the N-body approach when specifying interatomic interactions

Purpose. Development of interatomic potentials for atomistic simulation of alloys based on refractory metals of the V-Cr-Nb-Mo-Ta-W system and atomistic simulation using these ordering and diffusion potentials in CrxMoNbTaVW alloys. Methods. The development of the interatomic potentials of the V-Cr-Nb-Mo-Ta-W system was carried out within the framework of the 𝑁-body approach; To optimize the parameters of the potentials, the results of calculations within the framework of the electron density functional theory using the VASP software package were used as target values; the simulations of ordering and diffusion was carried out using methods of molecular dynamics and the developed We have previously used the combined method of molecular dynamics and the Monte Carlo method (MD+MK). Results. Within the framework of the 𝑁-body approach, potentials are constructed that complement the V-Nb-Mo-W potential system that we built earlier to the V-Cr-Nb-Mo-Ta-W system. The constructed potentials predict the characteristics of alloys in good agreement with experimental data, CALPHAD data and density functional theory data. Using these potentials by the MD+MC method, CrxMoNbTaVW alloys were modeled, where 𝑥 = 0, 0.5, 1, 2 and 3, in the temperature range from 500 ºC to 2300 ºC. The MD+MC calculations and CALPHAD data agreed in the temperature and concentration regions containing one phase of BCC. At a temperature of 1000ºC, MD + MC calculations show the presence of a single BCC phase, which contradicts CALPHAD data, but is consistent with experimental data. The simulation showed that the atomic structure of the CrMoNbTaVW model alloy is self-sufficient to realize the diffusion of components without artificial introduction of vacancies. The absolute values of the diffusion coefficients of the components and the values of the effective activation energy of diffusion in a solid solution of CrMoNbTaVW were calculated for the first time by the method of molecular dynamics. Analysis of the calculated diffusion characteristics indicates that a diffusion mechanism is implemented in the CrMoNbTaVW alloy, which includes coordinated movement of atoms of various grades. Conclusion. The development of methods for atomistic simulations of alloys based on refractory metals of the V-Cr-Nb-Mo-Ta-W system and the results of atomistic simulation of ordering and diffusion in CrxMoNbTaVW alloys have shown their importance for explaining and predicting heat resistance caused by diffusion processes in multicomponent alloys at high temperatures.

The role of interatomic interactions in the tribooxidation and wear of the multilayer Ti0.2Al0.55Cr0.2Si0.03Y0.02N/Ti0.25Al0.65Cr0.1N coating at severe cutting conditions

The role of interatomic interactions in the tribooxidation and wear of the multilayer Ti0.2Al0.55Cr0.2Si0.03Y0.02N/Ti0.25Al0.65Cr0.1N coating at severe cutting conditions

Exploring the influence of metal cations on individual hydrogen bonds in Watson-Crick guanine-cytosine DNA base pair: An interacting quantum atoms analysis.

This study delves into the nature of individual hydrogen bonds and the relationship between metal cations and hydrogen bonding in the Watson-Crick guanine-cytosine (GC) base pair and its alkali and alkaline earth cation-containing complexes (Mn+-GC). The findings reveal how metal cations affect the nature and strength of individual hydrogen bonds. The study employs interacting quantum atoms (IQA) analysis to comprehensively understand three individual hydrogen bonds within the GC base pair and its cationic derivatives. These analyses unveil the nature and strength of hydrogen bonds and serve as a valuable reference for exploring the impact of cations (and other factors) on each hydrogen bond. All the H D interactions (H is hydrogen and D is oxygen or nitrogen) in the GC base pair are primarily electrostatic in nature, with the charge transfer component playing a substantial role. Introducing a metal cation perturbs all H D interatomic interactions in the system, weakening the nearest hydrogen bond to the cation (indicated by a) and reinforcing the other (b and c) interactions. Notably, the interaction a, the strongest H D interaction in the GC base pair, becomes the weakest in the Mn+-GC complexes. A broader perspective on the stability of GC and Mn+-GC complexes is provided through interacting quantum fragments (IQF) analysis. This approach considers all pairwise interactions between fragments and intra-fragment components, offering a complete view of the factors that stabilize and destabilize GC and Mn+-GC complexes. The IQF analysis underscores the importance of electron sharing, with the dominant contribution arising from the inter-fragment exchange-correlation term, in shaping and sustaining GC and Mn+-GC complexes. From this point of view, alkaline and alkaline earth cations have distinct effects, with alkaline cations generally weakening inter-fragment interactions and alkaline earth cations strengthening them. In addition, IQA and IQF calculations demonstrate that the hydration of cations led to small changes in the hydrogen bonding network. Finally, the IQA interatomic energies associated with the hydrogen bonds and also inter-fragment interaction energies provide robust indicators for characterizing hydrogen bonds and complex stability, showing a strong correlation with total interaction energies.

Thermal decomposition mechanism of HMX/HTPB hybrid explosives studied by reactive molecular dynamics.

The thermal decomposition process of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine/hydroxyl-terminated polybutadiene (HMX/HTPB) hybrid explosives and pure HMX explosives at different temperatures (2000 ~ 3500 K) was investigated using the reactive molecular dynamics method. This study aimed to analyze the effect of binders on the thermal decomposition of HMX at the atomic scale and reveal the thermal decomposition mechanism of HMX/HTPB. The results showed that the thermal decomposition process of the HMX molecule in the HMX/HTPB hybrid system involves a continuous denitration followed by the disintegration of the main ring. The HTPB chain will experience dehydrogenation, dehydroxylation, and chain fragmentation. Including HTPB in the hybrid system significantly increased the presence of H and OH radicals. These radicals then interacted with HMX and its decomposition products and produced more of the final products H2O and H2 in the HMX/HTPB hybrid system compared to pure HMX. Additionally, it was observed that the HTPB chain fragments attached to the HMX decomposition products prevented the formation of N2 and CO2. Furthermore, the activation energies (Ea) of the initial and intermediate decomposition stages of the HMX/HTPB hybrid system were 98.45 kJmol-1 and 90.69 kJmol-1, respectively. The results showed that the activation energies of the HMX/HTPB hybrid system are lower than the pure HMX system in these two stages. Consequently, HTPB will enhance HMX's thermal decomposition and decreased the system's insensitivity to heat stimuli. The molecular dynamics simulation of the HMX/HTPB hybrid system was performed using the ReaxFF module in the LAMMPS software, and the ReaxFF/lg force field was used to describe the interatomic interactions as well as the chemical reactions.

An Exploration of the Phonon Frequency Spectrum and Born–von Karman Periodic Boundary Conditions in 1D and 2D Lattice Systems Using a Computational Approach

Periodic boundary conditions (PBCs) are a pivotal concept in the treatment of ideal lattices of infinite extent as a finite lattice. Most undergraduate texts that delve into the analytical treatment of lattice dynamics solve the problem in the reciprocal space with an implicit assumption of PBCs. While the traditional approach centered in the reciprocal or [Formula: see text]-space is elegant for simple one-dimensional lattice structures, the method becomes mathematically cumbersome for more complex lattices with real-world applications, such as a honeycomb lattice involving a [Formula: see text] secular determinant. In this work, we have explored the solution of lattice dynamics in direct space numerically, by constructing unit cells through an explicit implementation of Born–von Karman PBCs and solving the lattice dynamical equations in the displacement–time domain using the fourth-order Runge–Kutta algorithm. The Fast Fourier Transform technique is then used to obtain the phonon frequency spectrum corresponding to the computed instantaneous displacements. The fidelity of the model is validated by the agreement of the computational results obtained for the phonon spectrum at high symmetry points in the Brillouin zone with the analytical values for the given problem. Initially, the dynamics and the phonon spectrum are explored for monatomic and diatomic linear lattices which serve to act as introductory cases for the approach before investigating the 2D monatomic square and honeycomb lattices using the nearest and next-nearest neighbor approximations. A short-range force constant model employing the central forces and angular forces is used for the monatomic square lattice to account for the interatomic interactions. Our computational approach is expected to be physically more intuitive for a student for visualizing the periodicity of a given lattice and understanding its related dynamics. The approach demonstrates the usage of Born–von Karman PBCs in constructing a unit cell that effectively captures the dynamics of a lattice system, complementing the traditional secular determinant formalism. The work also illustrates an instance of how the computer programming can be used as a tool to empower the students to explore abstract concepts in physics. A honing of programming and computational skills of students enables them to interact with dynamic models in physics and gain deeper insight into the real-world applications of physics principles. Target group of this work is the students and educators at undergraduate level who seek a thorough and didactic comprehension of lattice dynamics.

Correct Nucleotide Selection Is Confined at the Binding Site of Polymerase Enzymes.

DNA polymerases (Pols) add incoming nucleotides (deoxyribonucleoside triphosphate (dNTPs)) to growing DNA strands, a crucial step for DNA synthesis. The insertion of correct (vs incorrect) nucleotides relates to Pols' fidelity, which defines Pols' ability to faithfully replicate DNA strands in a template-dependent manner. We and others have demonstrated that reactant alignment and correct base pairing at the Pols catalytic site are crucial structural features to fidelity. Here, we first used equilibrium molecular simulations to demonstrate that the local dynamics at the protein-DNA interface in the proximity of the catalytic site is different when correct vs incorrect dNTPs are bound to polymerase β (Pol β). Formation and dynamic stability of specific interatomic interactions around the incoming nucleotide influence the overall binding site architecture. This explains why certain Pols' mutants can affect the local catalytic environment and influence the selection of correct vs incorrect nucleotides. In particular, this is here demonstrated by analyzing the interaction network formed by the residue R283, whose mutant R283A has an experimentally measured lower capacity of differentiating correct (G:dCTP) vs incorrect (G:dATP) base pairing in Pol β. We also used alchemical free-energy calculations to quantify the G:dCTP →G:dATP transformation in Pol β wild-type and mutant R283A. These results correlate well with the experimental trend, thus corroborating our mechanistic insights. Sequence and structural comparisons with other Pols from the same family suggest that these findings may also be valid in similar enzymes.

Mode analysis of spin field of thermal atomic ensembles

The spin dynamics in a thermal atomic vapor cell have been investigated thoroughly over the past decades and have proven to be successful in quantum metrology and memory owing to their long coherent time and manipulation convenience. The existing mean field analysis of spin dynamics among the whole cell is sometimes inaccurate due to the non-uniformity of the ensemble and spatial coupling of multi-physical fields interacting with the ensembles. Here we perform mode analysis onto the quasi-continuous spin field including atomic thermal motion to derive Bloch mode equations and obtain corresponding analytical solutions in diffusion regime. We demonstrate that the widely used mean field dynamics of thermal gas is a particular case in our solution, corresponding to the uniform spatial mode. This mode analysis approach offers a precise method for analyzing the dynamics of the spin ensemble in greater detail from a field perspective, enabling the effective determination of spatially non-uniform multi-physical fields coupling with the spin ensembles, which cannot be accurately analyzed by the mean field method. Furthermore, this work paves the way to address quantum noises and relaxation mechanisms associated with non-uniform fields and inter-atomic interactions, which limit further improvement of ultra-sensitive spin-based sensors.

Navigating the 18-n+m Isomers of PdSn2: Chemical Pressure Relief through Isolobal Bonds and Main Group Clustering.

The 18-n electron-counting rule provides structural guidelines for electronically feasible transition metal (T)-main group (E) phases, contributing toward the goal of material design. However, the availability of numerous potential structure types at any electron count creates a challenge for the prediction of the preferred structures of specific compounds, as is illustrated by the concept of 18-n+m isomerism. In this Article, we explore the driving forces stabilizing one 18-n+m isomer over another with an analysis of the structure of PdSn2, a layered intergrowth of the fluorite and CuAl2 structure types. The DFT-reversed approximation Molecular Orbital (DFT-raMO) method reveals that PdSn2 and its hypothetical parent structures all adhere to bonding schemes approximating the electronic configurations expected from the 18-n rule, with various degrees of isolobal Pd-Pd bonding and Sn clustering. However, partial electron transfer between the Pd 5p orbitals to the Sn 5s orbitals contributes to the absence of convincing electronic pseudogaps near their Fermi energies. As such, there is no clear electronically driven preference among the structure types. This situation allows for atomic packing effects to prevail: DFT-Chemical Pressure (DFT-CP) analysis illustrates that in the fluorite-type parent structure, positive Pd-Sn CPs lead to overcompression of the Pd atoms and a stretching of the relatively open Sn sublattice. In contrast, in the CuAl2-type parent structure, Sn atoms cluster into tetrahedra, opening space for an expanded Pd environment and the formation of Pd-Pd interactions. However, the tetrahedral packing of the Sn atoms here leads to frustration between negative and positive Sn-Sn CPs. Through the development of the angular CP correlation function (CPcor+) as a tool to quantify frustration among interatomic interactions, we demonstrate how the observed PdSn2 structure balances these effects by tuning the degree of Sn-Sn clustering and expansion of the Pd environment. These observations point to generalizations for most 18-n+m isomers, where increased main group ligand clustering (+m) and isolobal bonds (+n) can accommodate compositions with different T and E atomic sizes.

Derivation of Morse potential

The Morse potential is widely used in chemistry, physics, and material science to describe interatomic interactions. We show that the Morse potential can be derived from a simple screened charge model accounting for the shielding of the nuclear charge by electron density. In this model, the parameter governing the width of the potential is related to the average shielding strength and the exponents of the atomic orbitals used in electronic structure calculations. The parameter representing the bond dissociation energy of a diatomic molecule is derived by combining the quantum mechanical covalent and classical electrostatic interactions. Moreover, the revealed connection between the parameters of the Morse potential and Pauling’s bond order and electronegativity provides insight into the relation between the classical and quantum mechanical descriptions of chemical bonds. This derivation of the Morse potential from the atomic quantities is expected to contribute to the development of the new basis sets incorporating Slater-type orbitals for electronic structure calculations and the transferable reactive force fields for molecular dynamics simulations. Furthermore, this interpretation of the Morse potential helps to understand the relationships between widely used chemical concepts, including effective atomic charge, bond dissociation energy, electronegativity, and bond order.

Epidemiological trends, antifungal drug susceptibility and SQLE point mutations in etiologic species of human dermatophytosis in Al-Diwaneyah, Iraq

Dermatophytes show a wide geographic distribution and are the main causative agents of skin fungal infections in many regions of the world. Recently, their resistance to antifungal drugs has led to an obstacle to effective treatment. To address the lack of dermatophytosis data in Iraq, this study was designed to investigate the distribution and prevalence of dermatophytes in the human population and single point mutations in squalene epoxidase gene (SQLE) of terbinafine resistant isolates. The identification of 102 dermatophytes isolated from clinical human dermatophytosis was performed through morphological and microscopic characteristics followed by molecular analysis based on ITS and TEF-1α sequencing. Phylogeny was achieved through RAxML analysis. CLSI M38-A2 protocol was used to assess antifungal susceptibility of the isolates to four major antifungal drugs. Additionally, the presence of point mutations in SQLE gene, which are responsible for terbinafine resistance was investigated. Tinea corporis was the most prevalent clinical manifestation accounting for 37.24% of examined cases of dermatophytosis. Based on ITS, T. indotineae (50.98%), T. mentagrophytes (19.61%), and M. canis (29.41%) was identified as an etiologic species. T. indotineae and T. mentagrophytes strains were identified as T. interdigitale based on TEF-1α. Terbinafine showed the highest efficacy among the tested antifungal drugs. T. indotineae and T. mentagrophytes showed the highest resistance to antifungal drugs with MICs of 2–4 and 4 μg/mL, while M. canis was the most susceptible species. Three of T. indotineae isolates showed mutations in SQLE gene Phe397Leu substitution. A non-previously described point mutation, Phe311Leu was identified in T. indotineae and mutations Lys276Asn, Phe397Leu and Leu419Phe were diagnosed in T. mentagrophytes XVII. The results of mutation analysis showed that Phe397Leu was a destabilizing mutation; protein stability has decreased with variations in pH, and point mutations affected the interatomic interaction, resulting in bond disruption. These results could help to control the progression of disease effectively and make decisions regarding the selection of appropriate drugs for dermatophyte infections.

Regulation of electrons between Ru and VN for high performance HER of low-level Ru doping in vanadium-nitrogen doped carbon catalysts

Transition metal nitrides (TMNs) have garnered significant attention for their catalytic activity similar to noble metals, attributed to their distinctive electronic structures. However, the sluggish reaction kinetics have hindered the progress in TMN development. In this study, an alloying approach was employed to create Ru@VN/C catalysts by uniformly dispersing low levels of ruthenium (Ru) in vanadium-nitrogen doped carbon (VN/C) on carbon spheres. Through alloying, the electronic structures of ruthenium and vanadium atoms were further adjusted, leading to exceptional catalytic activity resulting from unique electron transfer between the atoms. The Ru@VN/C catalyst demonstrated a low overpotential of 5 mV and a Tafel slope of 27 mV·dec−1 at 10 mA·cm−2 in alkaline seawater solution, as well as superior performance in alkaline and simulated seawater solutions. The interatomic synergistic interactions, driven by charge redistribution as confirmed by density functional theory calculations and experimental data, play a crucial role in expanding the applications of TMNs in green hydrogen production.

Characterization of Bisphosphonate Hydrate Crystals by Phosphorus K-Edge X-Ray Absorption Near-Edge Structure Spectroscopy.

X-ray absorption near-edge structure (XANES) spectroscopy is a new method for the characterization of active pharmaceutical ingredients. XANES spectra show unique features depending on the electronic states of the X-ray absorbing elements and provide information about the chemical environment that affects the electronic states. In this study, six bisphosphonate hydrate crystals were used to investigate, for the first time, how the phosphorus K-edge XANES spectra are affected by the interatomic interactions and charged states of phosphonate moieties. Phosphorus K-edge XANES spectra showed several differences among the bisphosphonates. In particular, the chlorine atoms covalently bonded near the phosphonate and the number of electric charges of the phosphonate moieties seemed to have large effects on peak shape in XANES spectra. Unique shapes of the XANES spectra demonstrated that differences in interactions at the oxygen atoms of the phosphonate moieties could change the shapes of the XANES spectrum peaks to the extent that each material was distinguished based on the spectra. Since slight differences in interatomic interactions and charged states lead to variations in the spectra, XANES spectroscopy could be widely applied as the fingerprint method to evaluate active pharmaceutical ingredients.

Bifunctional Pt dual atoms for overall water splitting

While dual-atom catalysts benefiting from synergetic interatomic interactions have inspired the development of emerging catalysts, the role of atomic interactions on the catalytic selectivity and activity has yet to be clearly discovered. Herein, two-types of Pt dual-atom active sites, Pt dimers (2Pt) with an interatomic distance of 2.6 Å and Pt pairs (Pt2) at a distance of 0.9 Å, are fabricated by anchoring onto cationic vacancy-rich nickel-based hydroxide (Pt@NiFeCo-E). It reveals that 2Pt sites are favorable for hydrogen evolution reaction (HER) while Pt2 sites are active towards oxygen evolution reaction (OER). The coexistence of two types of Pt dual atoms endows the bifunctional activity, which reached an overpotential of 14 mV@10 mA cm−2 for HER, an overpotential of 234 mV@100 mA cm−2 for OER, and an effective overall water splitting reaction (OWS) in alkaline at an overpotential of 1.42 V to reach 10 mA cm−2 and at 100 mA cm−2 for 50 h. This work not only clarifies a new mechanism in manipulating the selectivity of dual-atom catalysts via controlling the interatomic distance, but also paves a pathway for designing novel high-efficient bifunctional catalysts.

Interfacial Optimization for AlN/Diamond Heterostructures via Machine Learning Potential Molecular Dynamics Investigation of the Mechanical Properties.

AlN/diamond heterostructures hold tremendous promise for the development of next-generation high-power electronic devices due to their ultrawide band gaps and other exceptional properties. However, the poor adhesion at the AlN/diamond interface is a significant challenge that will lead to film delamination and device performance degradation. In this study, the uniaxial tensile failure of the AlN/diamond heterogeneous interfaces was investigated by molecular dynamics simulations based on a neuroevolutionary machine learning potential (NEP) model. The interatomic interactions can be successfully described by trained NEP, the reliability of which has been demonstrated by the prediction of the cleavage planes of AlN and diamond. It can be revealed that the annealing treatment can reduce the total potential energy by enhancing the binding of the C and N atoms at interfaces. The strain engineering of AlN also has an important impact on the mechanical properties of the interface. Furthermore, the influence of the surface roughness and interfacial nanostructures on the AlN/diamond heterostructures has been considered. It can be indicated that the combination of surface roughness reduction, AlN strain engineering, and annealing treatment can effectively result in superior and more stable interfacial mechanical properties, which can provide a promising solution to the optimization of mechanical properties, of ultrawide band gap semiconductor heterostructures.

Interatomic Interaction Models for Magnetic Materials: Recent Advances

Abstract Atomistic modeling is a widely employed theoretical method of computational materials science. It has found particular utility in the study of magnetic materials. Initially, magnetic empirical interatomic potentials or spin-polarized density functional theory (DFT) served as the primary models for describing interatomic interactions in atomistic simulations of magnetic systems. Furthermore, in recent years, a new class of interatomic potentials known as magnetic machine-learning interatomic potentials (magnetic MLIPs) has emerged. These MLIPs combine the computational efficiency, in terms of CPU time, of empirical potentials with the accuracy of DFT calculations. In this review, our focus lies on providing a comprehensive summary of the interatomic interaction models developed specifically for investigating magnetic materials. We also delve into the various problem classes to which these models can be applied. Finally, we offer insights into the future prospects of interatomic interaction model development for the exploration of magnetic materials.

Elementary processes in dilatational plasticity of glasses

Materials typically fail under complex stress states, essentially involving dilatational (volumetric) components that eventually lead to material decohesion/separation. It is therefore important to understand dilatational irreversible deformation—i.e., dilatational plasticity—en route to failure. In the context of glasses, much focus has been given to shear (volume-preserving) plasticity, both in terms of the stress states considered and the corresponding material response. Here, using a recently developed methodology and extensive computer simulations, we shed basic light on the elementary processes mediating dilatational plasticity in glasses. We show that plastic instabilities, corresponding to singularities of the glass Hessian, generically feature both dilatational and shear irreversible strain components. The relative magnitude and statistics of the strain components depend both on the symmetry of the driving stress (e.g., shear versus hydrostatic tension) and on the cohesive (attractive) part of the interatomic interaction. We further show that the tensorial shear component of the plastic strain is generally nonplanar and also extract the characteristic volume of plastic instabilities. Elucidating the fundamental properties of the elementary micromechanical building blocks of plasticity in glasses sets the stage for addressing larger-scale, collective phenomena in dilatational plasticity such as topological changes in the form of cavitation and ductile-to-brittle transitions. As a first step in this direction, we show that the elastic moduli markedly soften during dilatational plastic deformation approaching cavitation. Published by the American Physical Society 2024

Deformation state of a graphene sheet within the framework of the continuum moment-membrane theory of elasticity

The paper proposes an approach to finding the stress-strain state (SSS) of structures containing graphene, a novel nanomaterial that has currently found а wide range of practical applications in nanoelectromechanical systems. Graphene is a 2D basic building block for other carbon structures such as membranes, sheets, nanotubes, etc. To describe the SSS of a graphene sheet, the phenomenological continuum moment-membrane theory of plates is used, from which, due to the fact that graphene is an ultrathin material, the concept of thickness is excluded. The physical elasticity relationships of a graphene sheet are expressed through its rigidity characteristics, determined using the harmonic potential of interatomic interactions in carbon. A differential formulation and the corresponding variational formulation are given for the problem of static deformation and determination of the natural frequencies and modes of vibration of a graphene sheet. The variational formulation is based on the Lagrange principle and is implemented numerically using the finite element method. Finite element relations are constructed taking into account moment effects of the behavior of a graphene sheet. For approximation, a 4-node rectangular finite element is used. Numerical solutions to several problems of static deformation of a graphene sheet under conditions of a plane stress state and transverse bending are presented, and the analysis of its natural vibrations is also performed. Good convergence of numerical simulation results in all considered problems is demonstrated. The obtained numerical solutions are essential in designing and calculating resonators in which ultrathin nanostructures are used. The establishment of the fact that a graphene sheet has a high intrinsic frequency falling in the GHz region (for example, quartz resonators are characterized by megahertz frequencies) opens up new prospects for using graphene itself as an ultrasensitive nanomechanical resonator for detecting small masses and ultrasmall displacements.

Strategies for Achieving Ultra-Long ORR Durability-Rh Activates Interatomic Interactions in Alloys.

The stability of platinum-based alloy catalysts is crucial for the future development of proton exchange membrane fuel cells, considering the potential dissolution of transition metals under complex operating conditions. Here, we report on a Rh-doped Pt3Co alloy that exhibits strong interatomic interactions, thereby enhancing the durability of fuel cells. The Rh-Pt3Co/C catalyst demonstrates exceptional catalytic activity for oxygen reduction reactions (ORR) (1.31 A mgPt -1 at 0.9 V vs. the reversible hydrogen electrode (RHE) and maintaining 92 % of its mass activity after 170,000 potential cycles). Long-term testing has shown direct inhibition of Co dissolution in Rh-Pt3Co/C. Furthermore, tests on proton exchange membrane fuel cells (PEMFC) have shown excellent performance and long-term durability with low Pt loading. After 50,000 cycles, there was no voltage loss at 0.8 A cm-2 for Rh-Pt3Co/C, while Pt3Co/C experienced a loss of 200 mV. Theoretical calculations suggest that introducing transition metal atoms through doping creates a stronger compressive strain, which in turn leads to increased catalytic activity. Additionally, Rh doping increases the energy barrier for Co diffusion in the bulk phase, while also raising the vacancy formation energy of the surface Pt. This ensures the long-term stability of the alloy over the course of the cycle.

Strategies for Achieving Ultra‐Long ORR Durability—Rh Activates Interatomic Interactions in Alloys

AbstractThe stability of platinum‐based alloy catalysts is crucial for the future development of proton exchange membrane fuel cells, considering the potential dissolution of transition metals under complex operating conditions. Here, we report on a Rh‐doped Pt3Co alloy that exhibits strong interatomic interactions, thereby enhancing the durability of fuel cells. The Rh−Pt3Co/C catalyst demonstrates exceptional catalytic activity for oxygen reduction reactions (ORR) (1.31 A mgPt−1 at 0.9 V vs. the reversible hydrogen electrode (RHE) and maintaining 92 % of its mass activity after 170,000 potential cycles). Long‐term testing has shown direct inhibition of Co dissolution in Rh−Pt3Co/C. Furthermore, tests on proton exchange membrane fuel cells (PEMFC) have shown excellent performance and long‐term durability with low Pt loading. After 50,000 cycles, there was no voltage loss at 0.8 A cm−2 for Rh−Pt3Co/C, while Pt3Co/C experienced a loss of 200 mV. Theoretical calculations suggest that introducing transition metal atoms through doping creates a stronger compressive strain, which in turn leads to increased catalytic activity. Additionally, Rh doping increases the energy barrier for Co diffusion in the bulk phase, while also raising the vacancy formation energy of the surface Pt. This ensures the long‐term stability of the alloy over the course of the cycle.

Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set

This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupied d states near the Fermi level, we determine that the large, sharp d density of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.