Computational Materials Science最新文献

The practical applications of nanoalloys, which are known for their exceptional catalytic activity, are difficult to realize owing to their intricate stability of these systems, which is influenced by structural variations, configurational nuances, and elemental interactions. Many combinations resulting from the inclusion of many different possible constituent elements intensifies the complexity of their analysis, emphasizing the need for accurate stability prediction methods. This study investigated the stability of A−B binary nanoalloys composed of 3d, 4d, and 5d late transition metal elements such as Ni, Cu, Ru, Rh, Pd, Ag, Os, Ir, Pt, and Au. Density functional theory (DFT) calculations and supervised learning (SL) were employed to predict the stability of these alloys. The excess energy, an indicator used to evaluate the stability of nanoalloys, was predicted using the structure- and element-specific descriptors in a two-stage SL method. The first SL stage involves expressing the excess energy through structure-specific descriptors such as bond fractions and element deviation within each coordination number (CN). The second SL stage involves expressing the regression coefficients of the structure-specific descriptors using element-specific descriptors. The element-specific descriptors predicting the element deviation in each CN correspond to differences in melting point and atomic radius. Simultaneously, the prediction of bond fractions relies on factors such as electronegativity difference and electron density discontinuity between the constituent elements. The study findings suggest that the stability of a nanoalloy can be broadly categorized into that of its surface and inner components. Monte Carlo simulations based on structure- and element-specific descriptors exhibit the capability to predict the stable configurations of binary nanoalloys without the need for DFT. The approach described in this study significantly enhances the efficiency with which these calculations may be executed, thereby expediting the analysis of the properties of these alloys.

Agglomeration of carbon nanotubes (CNTs) refers to their tendency to form clusters, an inevitable phenomenon that markedly influences the performance of composite/nanocomposite materials. Comprehending and managing agglomeration are crucial for tailoring the effective properties of nanocomposites, especially those reinforced with high concentrations of nanofillers. Incorporating this anomaly in numerical simulations can yield significant cost and time savings, while also providing valuable insights into this marvel. This pioneering study explores a promising avenue for a more realistic simulation of CNT-loaded polymer nanocomposites. In the present micromechanics-grounded finite element model, representative volume elements (RVEs) containing CNT agglomerates are ingeniously generated in a three-step stochastic-iterative process. These RVEs are subsequently challenged under commonly encountered engineering scenarios, encompassing elastic, thermoelastic, and viscoelastic aspects. In this case, the precise determination of boundary and loading conditions is accomplished by assessing the constitutive equations associated with each characteristic. Through comparison with available experimental measurements, it has been demonstrated that authoritative prediction of Young’s moduli, thermal expansion coefficients, and creep strains necessitates the simulation of building blocks with agglomerated CNTs.

We investigate van der Waals (vdW) heterojunctions by combining InSe and zigzag carbon nanotubes (CNT(n,0)) by first-principle calculations. When n ranges from 5 to 7, The heterojunctions show n-type Schottky contact. However, for n of 8, 9, and 11, the heterojunctions still retain the characteristic of semiconductors with bandgaps. The metallized InSe/CNT(10,0) heterojunction has the most amount of charge transfer and the highest tunneling probability. Ohmic contact can be formed in InSe/CNT(n,0) (n = 5–7) heterojunctions under the external electric field. The charge transfer is enhanced and Schottky barrier heights are significantly reduced in heterojunctions with Se vacancy defect. In vacancy defect causes the disappearance of Schottky barrier because of metallization of InSe and more charge transfer than Se vacancy defect in InSe/CNT. Our findings provide a direction for the application of InSe/CNT in tunable nanoelectronic devices.

The elasto-viscoplastic response of irradiated bainitic steels for pressure vessels of light water reactors is described by a multiscale micromechanical model. The model relies on a simplified set of complex constitutive equations describing intragranular flow under a wide range of temperatures, strain rates, and irradiation levels. These equations were themselves partially calibrated by multiscale analyses based on dislocation dynamics calculations, atomistic calculations, and experimental measurements. They include the contribution of jog drag, lattice friction, evolution of dislocation microstructures, and irradiation hardening. The scaling up of these intragranular laws to polycrystalline samples relies on a computational homogenization method which solves the field equations within periodic representative volume elements by means of Fast Fourier Transforms. This computational method proves advantageous relative to the finite element method in handling the complex microstructural morphology of the model required to achieve overall constitutive isotropy. Macroscopic simulations for uniaxial curves under different irradiation levels are first confronted to experimental curves to identify certain microscopic material parameters employed to describe the evolution of the mean-free path of dislocations with deformation. Subsequent comparisons for the evolution of the yield stress, irradiation hardening and the response to sudden strain-rate variations are then reported for a class of steels with various chemical compositions under wide ranges of temperature, loading rate and irradiation level. Good agreement is obtained in all cases. Finally, simulations are employed to explore the influence of the initial dislocation density on the intragranular stress and strain fields. An appreciable influence on the fields is observed during the elasto-viscoplastic transition but not deep in the plastic range.

Hexagonal boron nitride (hBN), a promising 2D nanomaterial, has potential applications in desalination and osmotic energy harvesting. In all these applications, surface roughness significantly impacts fluid flow in nanomaterial, but its precise effect remains unclear. This creates a knowledge gap in understanding how surface roughness influences water flow at the water-hBN interface, which hinders the development of accurate molecular dynamics (MD) simulations. Here, we address this gap by employing density functional theory (DFT) to calculate atomic charges on rough hBN surfaces. These charges are incorporated into MD simulations, revealing a strong influence on the water-hBN interface. This combined approach accurately predicts experimental water slip length. We further quantify the water flow behavior on hBN using established force fields. Incorporating surface roughness into the model yields results in close agreement with the experimental slip length of $\sim$1 nm for water using FF-2 force fields, validating the simulation approach. Our findings highlight the importance of incorporating realistic surface roughness and force field models in MD simulations of water-nanomaterial interfaces. This work underscores the critical role of accurate 2D material models for understanding fluid flow in nanofluidic applications.

Hydrogen is rapidly gaining popularity as an energy carrier, largely expected to replace fossil fuels for many applications. As the hydrogen economy grows and the need for high purity hydrogen increases, better materials for high selectivity, high temperature hydrogen separation will be needed. In this theoretical investigation, InVO₄ was explored for use as a novel high temperature dense hydrogen separation membrane. The kinetics of hydrogen transport through an indium vanadate membrane (as it would be utilized in a membrane reactor) were modeled by leveraging density functional theory calculations. Structural features that control the kinetics were identified, from which material selection and modification for future experiments requiring high temperature hydrogen transport through solids can be better informed. The results of this investigation bring to light the importance of surface effects and reinforce the idea that surface and subsurface interactions must not be neglected when investigating hydrogen transport through solids.

We present the results of computational micromagnetic simulations at zero temperature under free boundary conditions for Permalloy nanodots. The nanodot’s diameter ($D$) was varied from 20 to 120 nm, and the thickness ($t$) ranged from 4 to 120 nm, which allows to obtain different aspect ratios $t/D$. Simulations were conducted using the Ubermag platform and the Object Oriented Micromagnetic Framework (OOMMF). The hysteresis loops exhibited a strong dependence on the aspect ratio ($t/D$), which was evident in the narrowing of the hysteresis curves as this ratio approached unity. This phenomenon led to the formation of nucleation and annihilation fields, resulting in the formation of vortex-type magnetic textures with a central core capable of moving within the basal plane. Furthermore, the time dynamics at each step of the magnetic field were addressed by solving the time-dependent Landau–Lifshitz–Gilbert differential equation, where the system’s Hamiltonian is defined in terms of magnetocrystalline anisotropy, demagnetization, exchange, and Zeeman contributions. Energy diagrams illustrate the competition among these energies, attempting to attain their equilibrium state, thereby creating a complex energy landscape. Moreover, they operate on different orders of magnitude, whence their relative importance is discussed. Final results are summarized in a proposal of phase diagrams.

The magnetic stability and electronic properties of a new MAX phase Cr₂Ge₂C are investigated using density functional theory (DFT) with the generalized gradient approximation GGA and GGA+U. Our work conducted predictive calculation of new nanolaminate Cr₂Ge₂C followed comparison with Ge-containing M₂AX phases, the magnetic ground states are predicted as NM with GGA approximation and AFM configuration with GGA+U method. Our result have shown that the total and partial magnetic moment are greatly decreased rapidly to zero by adding Ge layer. Due to the extra Ge-layers, the TDOS of the Cr₂Ge₂C at the Fermi level reduces slightly compared with Cr₂GeC and the Cr–C bond becomes more covalent compared with another study Cr₂GeC. Finally, we hope that the theoretical study of the new MAX phase material is the first of a large family, which will give a plus in the future for experimenters and theoreticians.

Perfluoroalkyl substances (PFAS) are a family of chemical species consisting of a perfluorinated C-F bonded backbone, granting high thermal and aqueous stability. However, as they have been found to cause deleterious health effects in humans, their lack of degradation in air or water has led to the desire for new remediation technology, and absorptive removal by porous materials has been found to be a promising way to accomplish this. In this work, we investigate the metal organic framework (MOF) family known as $M$-MOF-74 ($M$ = Cu, Mg, Zn, Pt) as potential adsorbents for the PFAS molecules PFOA, PFOS, and TFA. Using a combination of density functional theory (DFT) and ab initio molecular dynamics (AIMD) calculations, we find that protonated PFAS molecules can adsorb strongly in the $M$-MOF-74 frameworks, and that changing the $M$ site results in tunability of the adsorption energy. Second, we find that, given the same length of the C backbone, those terminated by a -COOH group versus a -SO${}_3$H group binds more strongly; furthermore, the C backbone length has an effect as well, with long-chain PFAS adsorbing more strongly than short-chain. Finally, we find that deprotonated PFAS molecules do not interact with MOF compounds and display a positive adsorption energy, with Bader charge calculations show a distinct difference between protonated and deprotonated PFAS molecules. Through this work, we disentangle how MOF and PFAS chemistry affects adsorption in this family of compounds.

The modulation of perovskite oxide thin films’ properties, through both intrinsic and extrinsic methods, has been extensively studied to enhance their photocatalytic performance. We employed ab initio density functional theory calculations to investigate the layer-dependent structural and electronic properties of orthorhombic NaTaO${}_3$ thin films. Our findings reveal that slabs comprising five, four, and three layers retain the non-magnetic and semiconducting characteristics of the bulk material, with their properties progressively converging towards those of an infinite-surface slab as the number of layers increases. Biaxial in-plane strain induces a linear change in the structure of surface TaO${}_4$ tetrahedra, thereby altering the film’s band gap. Notably, the two-layer slab exhibits a transitional behavior between the bulk-like nature of thicker films and the unique features of a NaTaO${}_3$ monolayer, showing heightened sensitivity to strain. Under compression, this bilayered system acquires bulk-like properties, whereas its strain-free state is magnetic and metallic akin to the monolayer. Similar transitions are observed in the latter, though under higher compression values. We provide an in-depth discussion of the structural and electronic mechanisms underlying these transitions. Additionally, the relative band-edge alignment with water-splitting photocatalytic potentials underscores the complex interplay between strain and dimensionality. This work offers valuable insights towards the design of more efficient photocatalysts, highlighting the potential of engineered NaTaO${}_3$ thin-film structures for advancing photocatalytic applications.