Atomic Structure Research Articles

Atomistic insights into chemical vapor deposition process of preparing silicon carbide materials using ReaxFF-MD simulation

SiC is a kind of key advanced coating material used widely. The in-depth understanding of the CVD process of preparing SiC materials at the atomic scale is beneficial for studying the CVD mechanism and then optimizing the materials. Here, a CVD model of preparing SiC materials is established based on ReaxFF-MD considering the whole pyrolysis-adsorption-desorption-growth mechanism. The accuracy of the ReaxFF potential and its parameters is verified by DFT at first. Then an energy-based Monte Carlo (EMC)-MD-CVD model is proposed based on the bonding formation energy originating from DFT. It is used to simulate the CVD process of preparing SiC materials. The CVD of MTS is studied by deposition efficiency and deposited film components at different temperatures, and it can be found it in good agreement with experimental results. Finally, the crystallization of SiC film prepared by the CVD of MTS is studied by energy evolution and atomic structure evolution. The results are helpful to understand the CVD mechanism for preparing coatings and it can be used to optimize the CVD parameters of preparing SiC materials in the future.

Analysis of extreme ultraviolet radiation and hydrodynamics simulation at the core of laser-produced nickel plasmas

The non-uniformity and transient nature of laser-produced plasma are critical factors that affect the analysis of the extreme ultraviolet spectra of highly charged ions and the diagnosis of plasma states. This paper systematically investigates the characteristics of extreme ultraviolet radiation and the hydrodynamic evolution of laser-produced nickel plasmas from two perspectives: high-spatio-temporal-resolution extreme-ultraviolet spectroscopic measurement and radiation hydrodynamics simulation. The consistency between the four-band experimental spectra and their theoretically simulated spectra confirms the accuracy of the atomic structure parameters and plasma state parameters. We also analyze the significant contribution of the 3d-4f double-excited state radiation to the spectral profile and discuss the influence of the self-absorption caused by plasma opacity on the characteristics of extreme ultraviolet radiation. The findings are crucial for accurately understanding the characteristics of extreme ultraviolet radiation, the hydrodynamic evolution, and the application of medium- and high-Z laser-produced plasma as a pulsed short-wavelength light source.

Tuning grain boundary cation segregation with oxygen deficiency and atomic structure in a perovskite compositionally complex oxide thin film

Compositionally complex oxides (CCOs) are an emerging class of materials encompassing high entropy and entropy stabilized oxides. These promising advanced materials leverage tunable chemical bond structure, lattice distortion, and chemical disorder for unprecedented properties. Grain boundary (GB) and point defect segregation to GBs are relatively understudied in CCOs even though they can govern macroscopic material properties. For example, GB segregation can govern local chemical (dis)order and point defect distribution, playing a critical role in electrochemical reaction kinetics, and charge and mass transport in solid electrolytes. However, compared with conventional oxides, GBs in multi-cation CCO systems are expected to exhibit more complex segregation phenomena and, thus, prove more difficult to tune through GB design strategies. Here, GB segregation was studied in a model perovskite CCO LaFe0.7Ni0.1Co0.1Cu0.05Pd0.05O3−x textured thin film by (sub-)atomic-resolution scanning transmission electron microscopy imaging and spectroscopy. It is found that GB segregation is correlated with cation reducibility—predicted by an Ellingham diagram—as Pd and Cu segregate to GBs rich in oxygen vacancies (VO··). Furthermore, Pd and Cu segregation is highly sensitive to the concentration and spatial distribution of VO·· along the GB plane, as well as fluctuations in atomic structure and elastic strain induced by GB local disorder, such as dislocations. This work offers a perspective of controlling segregation concentration of CCO cations to GBs by tuning reducibility of CCO cations and oxygen deficiency, which is expected to guide GB design in CCOs.

Prediction of the essential intermolecular contacts for side-binding of VASP on F-actin.

Vasodilator-stimulated phosphoprotein (VASP) family proteins play a crucial role in mediating the actin network architecture in the cytoskeleton. The Ena/VASP homology 2 (EVH2) domain in each of the four identical arms of the tetrameric VASP consists of a loading poly-Pro region, a G-actin-binding domain (GAB), and an F-actin-binding domain (FAB). Together, the poly-Pro, GAB, and FAB domains allow VASP to bind to sides of actin filaments in a bundle, and recruit profilin-G-actin to processively elongate the filaments. The atomic resolution structure of the ternary complex, consisting of the loading poly-Pro region and GAB domain of VASP with profilin-actin, has been solved over a decade ago; however, a detailed structure of the FAB-F-actin complex has not been resolved to date. Experimental insights, based on homology of the FAB domain with the C region of WASP, have been used to hypothesize that the FAB domain binds to the cleft between subdomains 1 and 3 of F-actin. Here, in order to develop our understanding of the VASP-actin complex, we first augment known structural information about the GAB domain binding to actin with the missing FAB domain-actin structure, which we predict using homology modeling and docking simulations. In earlier work, we used mutagenesis and kinetic modeling to study the role of domain-level binding-unbinding kinetics of Ena/VASP on actin filaments in a bundle, specifically on the side of actin filaments. We further look at the nature of the side-binding of the FAB domain of VASP at the atomistic level using our predicted structure, and tabulate effective mutation sites on the FAB domain that would disrupt the VASP-actin complex. We test the binding affinity of Ena with mutated FAB domain using total internal reflection fluorescence microscopy experiments. The binding affinity of VASP is affected significantly for the mutant, providing additional support for our predicted structure.

Equivariant neural network force fields for magnetic materials

Neural network force fields have significantly advanced ab initio atomistic simulations across diverse fields. However, their application in the realm of magnetic materials is still in its early stage due to challenges posed by the subtle magnetic energy landscape and the difficulty of obtaining training data. Here we introduce a data-efficient neural network architecture to represent density functional theory total energy, atomic forces, and magnetic forces as functions of atomic and magnetic structures. Our approach incorporates the principle of equivariance under the three-dimensional Euclidean group into the neural network model. Through systematic experiments on various systems, including monolayer magnets, curved nanotube magnets, and moiré-twisted bilayer magnets of CrI3, we showcase the method’s high efficiency and accuracy, as well as exceptional generalization ability. The work creates opportunities for exploring magnetic phenomena in large-scale materials systems.

25 Years of Quasiperiodic Crystallography in Physical Space using the Average Unit Cell Approach

AbstractSince the discovery of quasicrystals 40 years ago, many new paradigms and methods have been introduced to crystallography. 25 years ago, a statistical method of structure and diffraction analysis of aperiodic materials was proposed and, over these years, developed to describe model and real systems. This short review paper briefly invokes the basic concepts of the method: a reference lattice and an average unit cell, but also gives an overview of its application to atomic structure and diffraction analysis of various systems. Results are briefly discussed for mathematical sequences (Fibonacci and Thue‐Morse), model quasilattices in 2D and 3D (Penrose and Ammann tiling), refinements of real decagonal and icosahedral quasicrystals, analysis of structure disorder in quasicrystals, description of modulated systems, including macromolecular biological systems, and beyond usual application in crystallography.

Ultralow Strain-Induced Emergent Polarization Structures in a Flexible Freestanding BaTiO3 Membrane.

The engineering of ferroic orders, which involves the evolution of atomic structure and local ferroic configuration in the development of next-generation electronic devices. Until now, diverse polarization structures and topological domains are obtained in ferroelectric thin films or heterostructures, and the polarization switching and subsequent domain nucleation are found to be more conducive to building energy-efficient and multifunctional polarization structures. In this work, a continuous and periodic strain in a flexible freestanding BaTiO3 membrane to achieve a zigzag morphology is introduced. The polar head/tail boundaries and vortex/anti-vortex domains are constructed by a compressive strain as low as ≈0.5%, which is extremely lower than that used in epitaxial rigid ferroelectrics. Overall, this study c efficient polarization structures, which is of both theoretical value and practical significance for the development of next-generation flexible multifunctional devices.

Automated Structure Discovery for Scanning Tunneling Microscopy.

Scanning tunneling microscopy (STM) with a functionalized tip apex reveals the geometric and electronic structures of a sample within the same experiment. However, the complex nature of the signal makes images difficult to interpret and has so far limited most research to planar samples with a known chemical composition. Here, we present automated structure discovery for STM (ASD-STM), a machine learning tool for predicting the atomic structure directly from an STM image, by building upon successful methods for structure discovery in noncontact atomic force microscopy (nc-AFM). We apply the method on various organic molecules and achieve good accuracy on structure predictions and chemical identification on a qualitative level while highlighting future development requirements for ASD-STM. This method is directly applicable to experimental STM images of organic molecules, making structure discovery available for a wider scanning probe microscopy audience outside of nc-AFM. This work also allows more advanced machine learning methods to be developed for STM structure discovery.

Temperature-dependent local structure and lattice dynamics of 1T-TiSe[formula omitted] and 1T-VSe[formula omitted] probed by X-ray absorption spectroscopy

The local atomic structure and lattice dynamics of two isostructural layered transition metal dichalcogenides (TMDs), 1T-TiSe2 and 1T-VSe2, were studied using temperature-dependent X-ray absorption spectroscopy at the Ti, V, and Se K-edges. Analysis of the extended X-ray absorption fine structure (EXAFS) spectra, employing reverse Monte Carlo (RMC) simulations, enabled tracking of the temperature evolution of the local environment in the range of 10–300 K. The atomic coordinates derived from the final atomic configurations obtained using the RMC method were used to calculate the partial radial distribution functions (RDFs) and the mean-square relative displacement (MSRD) factors for the first ten coordination shells around the absorbing atoms. Characteristic Einstein frequencies and effective force constants were determined for TiSe, TiTi, VSe, VV, and SeSe atom pairs from the temperature dependencies of MSRDs. The obtained results reveal differences in the temperature evolution of lattice dynamics and the strengths of intralayer and interlayer interactions in TiSe2 and VSe2.

Expression of concern: A molecular dynamic approach to a hypothesis on the dynamical behavior of Rosuvastatin on Alzheimer's disease Amyloid beta-peptide interactions in the atomic structures

Expression of concern: A molecular dynamic approach to a hypothesis on the dynamical behavior of Rosuvastatin on Alzheimer's disease Amyloid beta-peptide interactions in the atomic structures

Ultra strong FCC structured Ni8Cr4Co4Fe6W2 high entropy alloys with high strength and ductility by laser powder bed fusion

The high entropy alloys (HEAs) are widely used in high temperature service environment (such as aviation engine blades) with bright application potential in additive manufacturing. Laser powder bed fusion (LPBF) is technology currently offers the best reproducibility and dimensional accuracy for part production. The unique atomic lattice structure of HEA makes its plastic deformation mechanism different from that of traditional dilution alloy, resulting in the strengthening effect of face-centered cubic high-entropy alloy different from that of traditional metal alloy materials. In this paper, Ni8Cr4Co4Fe6W2 was designed by means of composition control. Its spherical powders with uniform composition were successfully prepared by high temperature remelting spheroidization (PHTR) method, compared with gas atomization (GA) method. The strain rate sensitivity m values of GA-Selective Laser Melting and PHTR-Selective Laser Melting samples were 0.030 and 0.027, respectively. The hardness of Ni8Cr4Co4Fe6W2 high-entropy alloy showed a trend of continuous increase with the decrease of grain size, while the elastic modulus didn’t change much (PHTR-SLM is 193 Gpa and GA-SLM is 189 Gpa). The simulated value of the contact stress decreased by 23 % compared with the theoretical value. The contact radius increased with the increase of plastic deformation in addition to the reduction of contact pressure. The printing sample value of the elongation, yield strength (YS) and Ultimate Tensile Strength (UTS) on PHTR-SLM has increased by 39.6 %, 33.7 % and 25.9 %, respectively in additive manufacturing, compared to GA-SLM. The ability to produce refractory HEAs through PHTR method will make it possible to manufacture complex geometry shapes at a reasonable cost.

Fabrication of cisplatin-loaded core–shell Fe3O4@UiO-66-NH2 magnetic nanocomposite for potential drug delivery

In this study, we developed a biocompatible core–shell magnetic Fe3O4@UiO-66-NH2@CisPt nanocomposite loaded with cisplatin as a therapeutic agent for drug delivery and cancer treatment. The nanocomposite was synthesized using a step-by-step method resulting in the formation of two phases within the core–shell structure. Advanced analytical techniques, such as XRD, HR TEM, TEM, FTIR, and VSM, were used to thoroughly analyze the structural properties, morphology, magnetic characteristics, and atomic structure of the core–shell nanocomposite. Fe3O4@UiO-66-NH2@CisPt nanocomposite exhibits superparamagnetic behavior, which is advantageous for controlled drug delivery and release by applying an external magnetic field. This study presents a significant contribution to the development of effective drug delivery systems for cancer treatment.

Growth Process of Fe-O Nanoclusters with Different Sizes Biosynthesized by Protein Nanocages.

All protein-directed syntheses of metal nanoclusters (NCs) and nanoparticles (NPs) have attracted considerable attention because protein scaffolds provide a unique metal coordination environment and can adjust the shape and morphology of NCs and NPs. However, the detailed formation mechanisms of NCs or NPs directed by protein templates remain unclear. In this study, by taking advantage of the ferritin nanocage as a biotemplate to monitor the growth of Fe-O NCs as a function of time, we synthesized a series of iron NCs with different sizes and shapes and subsequently solved their corresponding three-dimensional atomic-scale structures by X-ray protein crystallography and cryo-electron microscopy. The time-dependent structure analyses revealed the growth process of these Fe-O NCs with the 4-fold channel of ferritin as nucleation sites. To our knowledge, the newly biosynthesized Fe35O23Glu12 represents the largest Fe-O NCs with a definite atomic structure. This study contributes to our understanding of the formation mechanism of iron NCs and provides an effective method for metal NC synthesis.

Electrochemical Generation of Te Vacancy Pairs in PtTe for Efficient Hydrogen Evolution.

Two-dimensional (2D) van der Waals materials are increasingly seen as potential catalysts due to their unique structures and unmatched properties. However, achieving precise synthesis of these remarkable materials and regulating their atomic and electronic structures at the most fundamental level to enhance their catalytic performance remain a significant challenge. In this study, we synthesized single-crystal bulk PtTe crystals via chemical vapor transport and subsequently produced atomically thin, large PtTe nanosheets (NSs) through electrochemical cathode intercalation. These NSs are characterized by a significant presence of Te vacancy pairs, leading to undercoordinated Pt atoms on their basal planes. Experimental and theoretical studies together reveal that Te vacancy pairs effectively optimize and enhance the electronic properties (such as charge distribution, density of states near the Fermi level, and d-band center) of the resultant undercoordinated Pt atoms. This optimization results in a significantly higher percentage of dangling O-H water, a decreased energy barrier for water dissociation, and an increased binding affinity of these Pt atoms to active hydrogen intermediates. Consequently, PtTe NSs featuring exposed and undercoordinated Pt atoms demonstrate outstanding electrocatalytic activity in hydrogen evolution reactions, significantly surpassing the performance of standard commercial Pt/C catalysts.

Theoretical and Experimental Analysis of Hydroxyl and Epoxy Group Effects on Graphene Oxide Properties.

In this study, we analyzed the impact of hydroxyl and epoxy groups on the properties of graphene oxide (GO) for the adsorption of methylene blue (MB) dye from water, addressing the urgent need for effective water purification methods due to industrial pollution. Employing a dual approach, we integrated experimental techniques with theoretical modeling via density functional theory (DFT) to examine the atomic structure of GO and its adsorption capabilities. The methodology encompasses a series of experiments to evaluate the performance of GO in MB dye adsorption under different conditions, including differences in pH, dye concentration, reaction temperature, and contact time, providing a comprehensive view of its effectiveness. Theoretical DFT calculations provide insights into how hydroxyl and epoxy modifications alter the electronic properties of GO, improving adsorption efficiency. The results demonstrate a significant improvement in the dye adsorption capacity of GO, attributed to the interaction between the functional groups and MB molecules. This study not only confirms the potential of GO as a superior adsorbent for water treatment, but also contributes to the optimization of GO-based materials for environmental remediation, highlighting the synergy between experimental observations and theoretical predictions in advances in materials science to improve sustainability.

Sulfidation-Induced Surface Local Electronic and Atomic Structures in a Silver Catalyst Enables Silicon Photocathode for Selective and Efficient Photoelectrochemical CO2 Reduction.

Converting CO2 to value-added chemicals through a photoelectrochemical (PEC) system is a creative approach toward renewable energy utilization and storage. However, the rational design of appropriate catalysts while being effectively integrated with semiconductor photoelectrodes remains a considerable challenge for achieving single-carbon products with high efficiency. Herein, we demonstrate a novel sulfidation-induced strategy for in situ grown sulfide-derived Ag nanowires on a Si photocathode (denoted as SD-Ag/Si) based on the standard crystalline Si solar cells. Such an exquisite design of the SD-Ag/Si photocathode not only provides a large electrochemically active surface area but also endows abundant active sites of Ag2S/Ag interfaces and high-index Ag facets for PEC CO production. The optimized SD-Ag/Si photocathode displays an ideal CO Faradic efficiency of 95.2% and an onset potential of +0.26 V versus the reversible hydrogen electrode, ascribed to the sulfidation-induced synergistic effect of the surface atomic arrangement and electronic structure in Ag catalysts that promote charge transfer, facilitate CO2 adsorption and activation, and suppress hydrogen evolution reaction. This sulfidation-induced strategy represents a scalable approach for designing high-performance catalysts for electrochemical and PEC devices with efficient CO2 utilization.

Axially Modified Square-Pyramidal CoN4-F1 Sites Enabling High-Performance Zn-Air Batteries.

Cobalt-nitrogen-carbon (Co-N-C) catalysts with a CoN4 structure exhibit great potential for oxygen reduction reaction (ORR), but the imperfect adsorption energy toward oxygen species greatly limits their reduction efficiency and practical application potential. Here, F-coordinated Co-N-C catalysts with square-pyramidal CoN4-F1 configuration are successfully synthesized using F atoms to regulate the axial coordination of Co centers via hydrothermal and chemical vapor deposition methods. During the synthesis process, the geometry structure of the Co atom converts from six-coordinated Co-F6 to square-pyramidal CoN4-F1 in the coordinatively unsaturated state, which provides an open binding site for the O2. The introduction of axial F atoms into the CoN4 plane alters the local atomic environment around Co, significantly improving the ORR activity and Zn-air batteries performance. In situ spectroscopy proves that CoN4-F1 sites strongly combine with the OOH* intermediate and facilitate the splitting of O-O bond, making OOH* readily decompose into O* and OH* via a dissociative pathway. Theoretical calculations confirm that the axial F atom effectively reduces the electronic density of the Co centers and facilitates the desorption of the OH* intermediate, efficiently accelerating the overall ORR kinetics. This work advances a feasible synthesis mechanism of axial ligands and provides a route to construct efficient high-coordination catalysts.

Influence of Chemical Composition and Structure on the Cooperative Fluctuation in Supercooled Glass-Forming Liquids.

The kinetics of the glass transition and the characteristic size of the fluctuating spatio-temporal domains in supercooled glass-forming liquids, i.e., the Cooperatively Rearranging Regions (CRR), were measured upon cooling over a broad range of cooling rates using Differential Scanning Calorimetry (DSC) and chip-based Fast Scanning Calorimetry (FSC). The investigations were conducted on a selection of fragile glass formers (fragility indices between 80 and 140), with a large variance in the atomic or molecular structure but comparable thermal glass transition temperatures Tg, with the aim of evaluating the influence of chemical composition and structure on the CRR size and the associated temperature fluctuation. The selected materials are two polymers (poly(vinyl acetate) (PVAc), poly(lactic acid) (PLA)) as well as the simplest chalcogenide glass-former (selenium). It turned out that the CRR size plotted against the reduced temperature T/Tg follows the same trend, irrespective of the considered glass-former.

Transferring predictions of formation energy across lattices of increasing size*

In this study, we show the transferability of graph convolutional neural network (GCNN) predictions of the formation energy of the nickel-platinum solid solution alloy across atomic structures of increasing sizes. The original dataset was generated with the large-scale atomic/molecular massively parallel simulator using the second nearest-neighbor modified embedded-atom method empirical interatomic potential. Geometry optimization was performed on the initially randomly generated face centered cubic crystal structures and the formation energy has been calculated at each step of the geometry optimization, with configurations spanning the whole compositional range. Using data from various steps of the geometry optimization, we first trained our open-source, scalable implementation of GCNN called HydraGNN on a lattice of 256 atoms, which accounts well for the short-range interactions. Using this data, we predicted the formation energy for lattices of 864 atoms and 2048 atoms, which resulted in lower-than-expected accuracy due to the long-range interactions present in these larger lattices. We accounted for the long-range interactions by including a small amount of training data representative for those two larger sizes, whereupon the predictions of HydraGNN scaled linearly with the size of the lattice. Therefore, our strategy ensured scalability while reducing significantly the computational cost of training on larger lattice sizes.

Tailored Two‐Dimensional Transition Metal Dichalcogenides for Water Electrolysis: Doping, Defect, Phase, and Heterostructure

AbstractThe demand for hydrogen production technology to replace fossil fuels and address the global climate crisis has become one of the most urgent tasks in the modern era. Among the promising breakthroughs, electrochemical water splitting using renewable energy sources offers a path to green hydrogen production that is both feasible and economically viable. However, the current state‐of‐the‐art catalysts for the water‐splitting reaction predominantly rely on scarce and costly noble metals, posing a significant challenge to the mass production of green hydrogen. In this context, two‐dimensional transition metal dichalcogenides (2D TMDs) have emerged as compelling candidates to replace noble metals, owing to their impressive reactivity and cost‐effectiveness. These TMD‐based electrocatalysts demonstrate exceptional reactivity at their active edge sites, while the basal planes remain catalytically inert. Several tailored strategies can activate these basal planes by modifying the chemical bonding nature and electronic band structure of the constituent atoms, thus enhancing the overall reactivity of TMDs. This review summarizes recent advancements in the modulation methodologies of 2D TMDs to enhance their water‐splitting reactivity. We highlight various chemical modification strategies, including heteroatom doping, defect‐engineering, and heterostructure formation, and provide insights into future research directions for the development of advanced 2D TMD‐based water‐splitting catalysts.