Atomic Clusters Research Articles

Incorporation of atomic Fe-oxide triggers a quantum leap in the CO2 methanation performance of Ni-hydroxide

The heterogeneous catalytic conversion of carbon dioxide (CO2) to methane (CH4) via CO2 methanation offers a promising avenue for establishing the closed carbon loop. Nevertheless, the lack of effective catalysts limits its industrial applications. Considering this, we developed a novel heterogeneous catalyst comprising oxygen vacancies enriched atomic Fe-oxide clusters confined in the TiO2-supported Ni-hydroxide (denoted as NiFe-TiO2) via wet chemical reduction method. This material delivers an unprecedently high CH4 productivity of ∼24,358 mmol g-1h−1 in CO2 methanation at 300 °C, surpassing the Ni-TiO2 (12,481 mmol g-1h−1) by ∼ 95 %. On top of that, the high structural reliability of the Fe-oxide atomic clusters endows the NiFe-TiO2 catalyst with outstanding durability, where it achieves an optimum CH4 productivity of ∼ 36,399 mmol g-1h−1 after 116 cycles (155 h) with CH4 selectivity of 90.5 % and retains the pristine performance up to 220 cycles (330 h) in the stability test. With evidence from in-situ X-ray absorption and ambient pressure X-ray photoelectron spectroscopy studies, the performance descriptors and reaction pathways were unveiled, where the oxygen vacancies in the atomic Fe-oxide clusters and the adjacent Ni-hydroxide domains synergistically boost the CO2 activation and the H2 dissociation, respectively. Such a potential synergy enables the simultaneous operation of all intermediate steps for enhanced CO2 methanation kinetics on the NiFe-TiO2 surface. Most importantly, these findings not only unravel the merits of oxygen vacancies in transition metals for CO2 methanation but mark a step ahead for the rational design of heterogeneous catalysts in various catalytic applications.

Effects of nanocrystals on hydrogen permeation and diffusion in amorphous electroless Ni-P coatings

Amorphous electroless-plated Ni-P coatings readily form nanocrystalline at relatively low temperatures. The current efforts to investigate the impact of proportion of nanocrystals on hydrogen permeation remain relatively limited, particularly when seeking to determine the impact of surface and internal nanocrystals on hydrogen permeation. The present work addresses this issue by conducting detailed analyses for amorphous electroless-plated Ni-P coatings and heat-treated coatings with a greater nanocrystalline concentration. The results show that the plated state samples exhibit excellent hydrogen permeation barrier properties.In addition, the heat-treated coatings exhibit a greater surface free energy and lower corrosion resistance due primarily to the higher density of phase boundaries arising from the increased crystallinity. The hydrogen diffusion coefficient of the heat-treated coating remains relatively stable (between 1.148×10−11 to 1.517×10−11 cm2/s) with increasing hydrogen charging current from 1 to 10 mA/cm², while the hydrogen diffusion coefficient of the as-plated amorphous coating increases from 3.406×10−12 to 7.996×10−12 cm2/s with increasing hydrogen charging current. The diffusion of hydrogen in the amorphous coating is primarily governed by low activation energy positions (i.e., 23.16 kJ/mol) associated with gaps between short-range-ordered atomic clusters in the material. A few high-energy positions (i.e., 45.58 kJ/mol) may be related to reversible hydrogen traps. The increasing crystalline content arising under heat treatment drastically reduces the prominence of low activation energy positions.

Quantum liquid in lower dimensions: From the perspective of surface tension

We analyze the surface tension in ultra-cold atomic gases in a quasi one-dimensional and one-dimensional geometry. In recent years, experimental observations have confirmed the “clustering of atoms” to form droplets in ultra-cold atomic gases and the emergence of this new phase is attributed to the beyond mean-field interaction. However, two decades earlier, liquid formation was predicted due to the competition of two-body and three-body interactions. Here, we review both propositions and comment on the role of beyond mean-field and three-body interaction in liquid formation by calculating the surface tension.

Single‐Atom Long‐Range Interaction: Basic Principles and Applications

AbstractSingle‐atom catalysis involves loading the active metal onto the carrier's surface as a single‐atom. This atom is primarily bonded to the carrier surface through hetero‐atom bonding. It is important to note that the coordination environment of the metal atoms may not be the same when each dispersed active metal atom has an identical coordination environment on the carrier's surface. The utilization of single‐atom catalysts (SACs) doesn't strictly imply that a solitary metal atom with zero valency functions as the active core. Singular atoms can also engage in distant interactions with other atoms or clusters of atoms on the substrate, like electron transfer, and frequently demonstrate specific charges. The main reason for the high activity of the catalyst is the remote (i.e., long‐range) interaction of the active atom with the surrounding coordination atoms. For this reason, the study of the mechanism of long‐range interactions between multiple single‐atom sites and between single‐atom sites and atomic cluster sites has become an important and urgent task in the design and regulation of single‐atom catalyst performance.

Catalytic Dehydrogenation on Ultradisperse Sn-Promoted Ir Catalysts Supported on MgAl2O4 Prepared by Different Techniques

Ir and IrSn catalysts with different Sn contents (0.5, 0.7 and 0.9 wt%) were prepared using MgAl2O4 supports synthesized using two different techniques (the citrate–nitrate combustion and coprecipitation methods). Both supports, with a spinel structure, presented low acidity and good textural properties. However, the support prepared by coprecipitation had higher specific surface area and pore volume than the one prepared by combustion, which would favor the dispersion of the metals to be deposited. Likewise, during the preparation of the catalytic materials, a very good interaction was achieved between the metals and both supports, which was confirmed by the presence of sub-nanometer atomic clusters in the mono- and bimetallic catalysts. Regarding the catalytic properties, while the monometallic Ir/MgAl2O4 samples lead to a very low conversion of n-butane and a selectivity towards hydrogenolysis products, the addition of Sn to Ir increases the conversion, decreases hydrogenolysis and therefore sharply increases the selectivity towards the different butenes. Catalysts with higher Sn loadings present better catalytic behavior. One of the roles of the Sn promoter would be to geometrically modify the Ir clusters, drastically decreasing the hydrogenolytic activity. This effect, added to the strong electronic modification of the Ir sites by the action of Sn, with probable Ir-Sn alloy formation, is responsible for the high catalytic performance of these bimetallic catalysts.

Graph Atomic Cluster Expansion for Semilocal Interactions beyond Equivariant Message Passing

The atomic cluster expansion provides local, complete basis functions that enable efficient parametrization of many-atom interactions. We extend the atomic cluster expansion to incorporate graph basis functions. This naturally leads to representations that enable the efficient description of semilocal interactions in physically and chemically transparent form. Simplification of the graph expansion by tensor decomposition results in an iterative procedure that comprises current message-passing machine learning interatomic potentials. We demonstrate the accuracy and efficiency of the graph atomic cluster expansion for a number of small molecules, clusters, and a general-purpose model for carbon. We further show that the graph atomic cluster expansion scales linearly with the number of neighbors and layer depth of the graph basis functions. Published by the American Physical Society 2024

Low temperature phase transition mechanism of amorphous Al-oxalate to nano α-alumina

α-Alumina (α-Al2O3), widely used as a raw material or production in advanced manufacturing industry, has attracted much attention in terms of its preparation temperature. A simple dissolution-evaporation-precipitation process was employed to obtain the amorphous Al-oxalate (AAO) precursor, serving as the starting material for the low temperature preparation of nano α-Al2O3. The crystalline structure and thermal behavior of the AAO were compared with commercially available aluminum hydroxide (Al(OH)3) powder using the X-ray powder diffraction (XRD) instrument, the thermal gravity analysis and differential scanning calorimetry (TG-DSC). The phase transition mechanism of AAO was investigated by the fourier transform infrared spectroscopy (FTIR), transmission electron microscope (TEM), scanning electron microscope (SEM), and 27Al magic angle spinning nuclear magnetic resonance (27Al-MAS-NMR). The DSC results indicated that AAO underwent a phase transformation at 982 °C. The α-alumina diffraction peaks appeared in AAO at 1000 °C, while α-Al2O3 phase was observed for Al(OH)3 at 1200 °C. Furthermore, an absorption peak at 452 cm−1, corresponding to Al–O bond in α-alumina was detected at 1000 °C. The proposed low-temperature preparation mechanism of α-alumina from AAO is as follows: four coordination Al-oxalate species entities coexist within the AAO sample; with increasing temperature, organic acid functional groups oxidize and volatilize, resulting in the formation of tetra-coordinate [AlO4], penta-coordinate [AlO5], and hexa-coordinate [AlO6] atomic groups; these atomic clusters further polymerize to form a structurally dense α-alumina crystal at the nano-scale (∼50 nm) at around 1000 °C. The experimental findings present a novel approach and method for the low-temperature preparation of nano-sized alumina powder. Additionally, a feasible theoretical reference for the low-temperature phase transition mechanism of amorphous Al-oxalate was provided.

Activation and reaction mechanism of nano‐aluminized explosives under shock wave

AbstractTo investigate the effect of aluminum (Al) nanoparticles on the energy release mechanism of high explosives, a comprehensive analysis was conducted on the mechanical response and chemical reaction mechanism of pure 1,3,5‐Trinitro‐1,3,5‐triazinane (RDX) and nano‐aluminized RDX across varying particle velocities using molecular dynamics simulation. The simulation results show that the velocity of the shock wave which is formed in the explosive increases as the velocity of the particle increases. Notably, detonation was absent when the particle velocity was below 3 km/s, but prominently observed beyond this threshold, accompanied by a diminishing delay in reaction time for aluminum particles as particle velocity increased. After detonation, a localized pressure reduction behind aluminum particles was observed, elucidating the diminished detonation efficacy of aluminized explosives. Furthermore, the introduction of aluminum particles led to a deceleration in the RDX reaction rate, with the emergence of aluminum atomic clusters highlighting previously overlooked gas‐phase reactions that necessitate inclusion in detonation modeling for aluminized explosives.

Silver Single Atoms Combined with Clusters on Carbon Nanotubes Mediates Exclusive Electrochemical CO2‐to‐CO Conversion

AbstractThe electrochemical reduction of CO2 (eCO2RR) that exclusively produces one product at industrial current density is crucial for the substantial storage of renewable energy. Modulating the electronic structure of atomically dispersed catalysts can effectively regulate the adsorption of rate‐determining‐step intermediates to achieve the desired products. Here, the study constructs a hybrid catalyst consisting of single Ag atoms and Ag atomic clusters supported on nitrogen‐doped multi‐walled carbon nanotubes that can effectively regulate the important intermediate structure of *COOH. The X‐ray photoelectron and X‐ray absorption near‐edge spectroscopies demonstrate that turning Ag single atoms into Ag clusters can weaken the electron transfer between Ag–N and present a relatively rich electron state. Thus, the rate‐determining step of *COOH massive formation is significantly accelerated, as proven by in situ synchrotron infrared spectroscopy and density functional theory calculations. Using this strategy, a CO Faradaic efficiency outperforming 99% from −0.3 to −0.8 V (vs reversible hydrogen electrode) with current densities above 200 mA cm−2 and a half‐cell energetic efficiency of 86% is achieved. This work highlights a promising approach to advancing synergistic catalysts for achieving more controllable and efficient eCO2RR.

Orbital Hybridization Induced Dipole Polarization and Room Temperature Magnetism of Atomic Co‐N4‐C toward Electromagnetic Energy Attenuation

AbstractManipulating the electronic structure and geometric coordination environment of single metal atoms has been considered as promising approach for enhancing dipole polarization and enriching electromagnetic attenuation mechanisms. However, achieving precise control of the dielectric polarization response at atomic scale remains a huge challenge. Herein, a metal‐acetate coordination complexes‐assisted strategy is proposed to prepare spatially isolated cobalt (Co) atoms embedded in accordion‐like nitrogen‐doped carbon (NC) matrix. The interactions between metal atoms and NC matrix are carefully tailored through the successive evolution of dispersion states of Co species, ranging from individual atoms to atomic clusters to nanoparticles. Density functional theory reveals that the orbital hybridization between the d electrons of embedded Co atoms and p electrons of coordinated N atoms induces the electron redistribution at N sites, enabling enhanced electric dipole polarization and robust room temperature magnetism (a saturation magnetization of 0.108 emu g−1 at 300 K). Consequently, Co‐SAs@NC exhibits optimal electromagnetic wave absorption properties with a minimum reflection loss of ‐54.4 dB and an effective absorption bandwidth of 8.4 GHz. This work demonstrates an efficient strategy for modulating electromagnetic response at atomic level and provides a novel insight into the d/p electrons orbital hybridization between single metal atoms and NC species.

Assessing the global natural orbital functional approximation on model systems with strong correlation.

In the past decade, natural orbital functional (NOF) approximations have emerged as prominent tools for characterizing electron correlation. Despite their effectiveness, these approaches, which rely on natural orbitals and their associated occupation numbers, often require hybridization with other methods to fully account for all correlation effects. Recently, a global NOF (GNOF) has been proposed [Piris, Phys. Rev. Lett. 127, 233001 (2021)] to comprehensively address both dynamic and static correlations. This study evaluates the performance of GNOF on strongly correlated model systems, including comparisons with highly accurate Full Configuration Interaction calculations for hydrogen atom clusters in one, two, and three dimensions. Additionally, the investigation extends to a BeH2 reaction, involving the insertion of a beryllium atom into a hydrogen molecule along a C2v pathway. According to the results obtained using GNOF, consistent behavior is observed across various correlation regions, encompassing a range of occupations and orbital schemes. Furthermore, distinctive features are identified when varying the dimensionality of the system.

AIGO-DTI: Predicting Drug-Target Interactions Based on Improved Drug Properties Combined with Adaptive Iterative Algorithms.

Artificial intelligence-based methods for predicting drug-target interactions (DTIs) aim to explore reliable drug candidate targets rapidly and cost-effectively to accelerate the drug development process. However, current methods are often limited by the topological regularities of drug molecules, making them difficult to generalize to a broader chemical space. Additionally, the use of similarity to measure DTI network links often introduces noise, leading to false DTI relationships and affecting the prediction accuracy. To address these issues, this study proposes an Adaptive Iterative Graph Optimization (AIGO)-DTI prediction framework. This framework integrates atomic cluster information and enhances molecular features through the design of functional group prompts and graph encoders, optimizing the construction of DTI association networks. Furthermore, the optimization of graph structure is transformed into a node similarity learning problem, utilizing multihead similarity metric functions to iteratively update the network structure to improve the quality of DTI information. Experimental results demonstrate the outstanding performance of AIGO-DTI on multiple public data sets and label reversal data sets. Case studies, molecular docking, and existing research validate its effectiveness and reliability. Overall, the method proposed in this study can construct comprehensive and reliable DTI association network information, providing new graphing and optimization strategies for DTI prediction, which contribute to efficient drug development and reduce target discovery costs.

Approaching 1 GPa Ultra‐High Tensile Strength in a Nanostructured Al–Zn–Mg–Cu–Zr–Sc Alloy Prepared by Severe Plastic Deformation

Alloy composition and heat treatment processes have limited possibility to enhance ultra‐high strength of aluminum alloys, which restricts their widespread application in lightweight equipment. Consequently, high‐density dislocations and grain refinement are suggested to strengthen ultra‐high strength aluminum alloys. Herein, a novel nanostructured Al–Zn–Mg–Cu–Zr–Sc (AZMCZS) alloy with homogeneous microstructure is prepared through the synergistic processing of hot extrusion and high‐pressure torsion. Additionally, the microstructures and strengthening mechanisms of the nanostructured Al alloy are analyzed. It is observed that the ultimate tensile strength of the nanostructured Al alloy reaches nearly 1 GPa, and the elongation of the alloy is 1.9%. The nanostructured Al alloy mainly consists of nanoscale grains (≈117.7 nm), high‐density dislocations (2.4 × 1015 m−2), nano‐sized precipitates (the size of 20–51 nm), and solute atom clusters (≈3 nm). The multiple strengthening mechanisms of the nanostructured Al alloy are revealed in terms of grain refinement, dislocations, precipitates, and solute atom clusters. Grain refinement and dislocation strengthening show superior outcomes and are considered to be the predominant strengthening mechanisms. These findings demonstrate that this nanostructural architecture offers a new way to design super‐strength metals and alloys by effectively controlling the processing regime of severe plastic deformation.

Effect of Strain Rate on Mechanical Deformation Behavior in CuZr Metallic Glass.

Tensile tests were performed on Cu64Zr36 metallic glass at strain rates of 107/s, 108/s, and 109/s via classical molecular dynamics simulations to explore the underlying mechanism by which strain rate affects deformation behavior. It was found that strain rate has a great impact on the deformation behavior of metallic glass. The higher the strain rate is, the larger the yield strength. We also found that the strain rate changes the atomic structure evolution during deformation, but that the difference in the atomic structure evolution induced by different strain rates is not significant. However, the mechanical response under deformation conditions is found to be significantly different with the change in strain rate. The average von Mises strain of a system in the case of 107/s is much larger than that of 109/s. In contrast, more atoms tend to participate in deformation with increasing strain rate, indicating that the strain localization degree is more significant in cases of lower strain rates. Therefore, increasing the strain rate reduces the degree of deformation heterogeneity, leading to an increase in yield strength. Further analysis shows that the structural features of atomic clusters faded out during deformation as the strain rate increased, benefiting more homogeneous deformation behavior. Our findings provide more useful insights into the deformation mechanisms of metallic glass.

Study on structure and viscosity evolution mechanism of titanium-containing iron liquid in full viscosity range

This study aims to investigate the relationship between the viscosity of Fe-4.5wt%C-0.2wt%Ti melt and its liquid structure. The actual experimental results of viscosity measurement reveal that the viscosity range of Fe-4.5wt%C-0.2wt%Ti melt can be segmented into three intervals. Through thermodynamically calculated equilibrium phases and high-temperature confocal experiments, it is observed that the abrupt change in viscosity in the lower temperature range is attributed to the precipitation of the graphite phase. Moreover, differential scanning calorimetry experiments exhibit a distinct phase transition in the liquid phase region. To delve into the atomic structure of the liquid phase region, molecular dynamics simulations are employed. The high-temperature liquid structure of Fe-4.5wt%C-0.2wt%Ti melt predominantly consists of vacancies, atomic clusters with Ti as the core, and atomic clusters with C as the core. Within the high-temperature liquid phase region, the conversion of Free-Fe and C1-Fe to Cx-Fe occurs, resulting in a reduction of free volume and enhanced stability of the cluster. Consequently, the inhomogeneity of the Fe-4.5wt%C-0.2wt%Ti melt increases, and the viscosity exhibits a significant increase with temperature, leading to a variation in the viscosity within the liquid phase interval.

Molecular dynamics simulation study on non-equilibrium melting of sodium crystals at high heating rates

ABSTRACT The non-equilibrium melting of Na crystals at high heating rates and the evolutions of the atomic clusters are studied by the MD method and PTM analysis. Results show that as the heating rate rises from 1 × 1011 K/s to 2 × 1013 K/s, the non-equilibrium melting temperature of Na increases non-linearly from 417 K to 480 K, the melting temperature difference experienced increases from 7 K to 27 K, while the melting time decreases from 70 ps to 1 ps. Through the PTM analysis, it is found that some BCC clusters transform into the disordered Other clusters through intermediate HCP and FCC clusters with increasing temperature, and the BCC cluster's reduction rate and the Other cluster's growth rate are getting slower with increasing heating rate. There is a good correspondence between the evolutions of the atomic clusters, the changes of macroscopic physical parameters, and the peaks and valleys of RDF with temperature.

Proper orthogonal descriptors for multi-element chemical systems

We introduce the proper orthogonal descriptors for efficient and accurate interatomic potentials of multi-element chemical systems. The potential energy surface of a multi-element system is represented as a many-body expansion of parametrized potentials which are functions of atom positions, atom types, and parameters. The proper orthogonal decomposition is employed to decompose the parametrized potentials as a linear combination of orthogonal basis functions. The orthogonal basis functions are used to construct proper orthogonal descriptors based on the elements of atoms, thus leading to multi-element descriptors. We compose the multi-element proper orthogonal descriptors to develop linear and quadratic interatomic potentials. We devise an algorithm to efficiently compute the total energy and forces of the interatomic potentials constructed from the proper orthogonal descriptors. The potentials are demonstrated for indium phosphide and titanium dioxide in comparison with the spectral neighbor analysis potential (SNAP) and atomic cluster expansion (ACE) potentials.

Unveiling inherent features of medium-range connections between atomic clusters in Fe-Ni amorphous alloys

Molecular dynamics simulations have been carried out to explore the inherent connection features between the atomic clusters of Fe-Ni amorphous alloys in medium range. Voronoi polyhedron analysis shows that there are four types of short-range clusters in the Fe-Ni amorphous alloys. The analysis of the connection between these clusters reveals that the closer the structural properties of clusters, the stronger the connection tendency between them, and the connection modes between clusters are influenced by their types. Finally, we clarify the mechanism for the effect of two-connected clusters on the connection modes between them and their surrounding clusters, i.e., as the number of the clusters surrounding two-connected clusters increases, the fraction of the number of their surrounding clusters first increases and then decreases, and the more the atoms shared in two-connected clusters, the more the clusters simultaneously connecting with them. We believe that these are the inherent connection features of medium-range structures in Fe-Ni amorphous alloys, which can also be extended to other amorphous alloys.

MolDStruct: Modeling the dynamics and structure of matter exposed to ultrafast x-ray lasers with hybrid collisional-radiative/molecular dynamics.

We describe a method to compute photon-matter interaction and atomic dynamics with x-ray lasers using a hybrid code based on classical molecular dynamics and collisional-radiative calculations. The forces between the atoms are dynamically determined based on changes to their electronic occupations and the formation of a free electron cloud created from the irradiation of photons in the x-ray spectrum. The rapid transition from neutral solid matter to dense plasma phase allows the use of screened potentials, reducing the number of non-bonded interactions. In combination with parallelization through domain decomposition, the hybrid code handles large-scale molecular dynamics and ionization. This method is applicable for large enough samples (solids, liquids, proteins, viruses, atomic clusters, and crystals) that, when exposed to an x-ray laser pulse, turn into a plasma in the first few femtoseconds of the interaction. We present four examples demonstrating the applicability of the method. We investigate the non-thermal heating and scattering of bulk water and damage-induced dynamics of a protein crystal using an x-ray pump-probe scheme. In both cases, we compare to the experimental data. For single particle imaging, we simulate the ultrafast dynamics of a methane cluster exposed to a femtosecond x-ray laser. In the context of coherent diffractive imaging, we study the fragmentation as given by an x-ray pump-probe setup to understand the evolution of radiation damage in the time range of hundreds of femtoseconds.

Structural Properties of Amorphous Vanadium Pentoxide Under Compression

Structural properties of amorphous vanadium pentoxide (V2O­5) under compression investigated by molecular dynamics simulation. The simulated amorphous V2O5 is composed of basic structural units of type VO5, VO6 at low-pressure and VO6, VO7 at high-pressure. These basic structural units connected by vertex-, edge- and face- shared links to form a structural network. The random distribution of atom and void clusters leading to a high degree of disorder in the V2O5 structure. Under compression, the fraction of average vertex-, edge- and face- shared links increased strongly. The number of VCs and VTs also increases as the large voids are divided into smaller voids. Our results also elucidated the decreasing of cross-section and increasing of length in VTs are main causes for increasing ion conductivity of the amorphous V2O5.