查看更多>>摘要：Defect engineering using self-doping or creating vacancies in polycrystalline oxide based materials has profound influence on optical absorption, UV photo detection, and electrical switching. However, defects induced semiconducting oxide devices show enhancement in photo detection and photosensitivity, and hence still remain interesting in the field of optoelectronics. In this study, defect engineering in semiconducting oxide materials is discussed along with their roles in optoelectronic device-based applications. Theoretical investigations have been done for identifying defect states by performing first-principles electronic structure calculations, employing the density-functional theory. Particularly, in this work we have focused on probing the defect-induced changes in optical and electrical processes by means of experimental as well as computational investigations. Hence, systematic experimental measurements of optical absorption, electrical switching, charge density, and photocurrent in defect-rich semiconducting oxide samples have been performed. Our results suggest that defects can lead to enhancement of optoelectronic properties such as photocurrent, switching speed, optical absorption etc. for semiconducting oxide based devices.
查看更多>>摘要：Microstructure-based process design is one of the main ingredients for materials design, under the integrated computational materials engineering paradigm, which relies on inverting process-structure-property linkages. The specific inverse problem connecting microstructure to processing conditions is exceedingly difficult to solve, even in a computational setting. The difficulty arises from the challenges associated with properly representing the microstructure space as well as the computational cost of the simulations used to connect process conditions to microstructure evolution. In this work, we attempt to invert a process-microstructure problem by implementing and deploying a search scheme based on multi-scale batch Bayesian optimization. We employ this framework to efficiently navigate the microstructure manifold in two examples involving phase field simulations. In these examples, the volume fraction and characteristic length scale of phases resulting from spinodal decompositions are considered in different objective functions to find synthetic target microstructures. We show how this batch Bayesian optimization can be used to efficiently uncover process-microstructure connections through optimal parallel querying of the process space, providing a new pathway for solving inverse problems in materials design.
查看更多>>摘要：Non-equilibrium molecular dynamics simulations were carried out to explore the effects of the shock intensity and loading duration on the spallation fracture mechanisms for single-crystal aluminum. First, the dynamic applicability of the potential function was validated by the shock Hugoniot relation. It was then found that compression waveforms ranging from triangular to rectangular closely depended on the loading duration. Coupled with atomic structural evolution, the spatio-temporal planes characterized by the density and stress well reproduced the spallation process dominated by void nucleation, growth, and coalescence. A larger shock velocity could accelerate the increase in the void volume fraction, while a larger loading duration could postpone the void nucleation but did not affect the variation trend of the void volume fraction. Based on the void morphology evolution at shock velocities of 1-3 km/s, the void volume fraction in the nucleation and growth (NAG) stages were effectively demarcated and then obtained, and the numerical values agreed closely with theoretical values calculated via the NAG model. The NAG model parameters were subsequently acquired, wherein the nucleation rate threshold and pressure sensitivity parameter were basically independent of the loading duration and shock velocity. However, they largely affected the nucleation threshold, growth threshold, and viscosity coefficient. In addition, the variation trend of the spallation strength depended on the predominance of the strain hardening and temperature softening effects. Finally, the correlation between the slope of the velocity pullback and damage rate was preliminarily discussed based on the NAG model.
查看更多>>摘要：A phase-field model is developed to simulate the hardening effect of sessile loops (vacancy and interstitial discs) resulted from neutron irradiation in tungsten. According to experimental observations, the gliding dislocations on the {1 1 0} prism planes and the Burgers vector is 1/2 < 1 1 1 >, while the sessile damage loops are perpendicular to the slip plane and the Burgers vector is same with gliding dislocation. It is found that the size and spatial distribution of the damage loops as well as their amount have strong impact on their hindrance to dislocation glide. The increases in the number density and radius of damage loops enhance the hardening effect. As the edge dislocation glides through the top and bottom of the damage loop, the hardening effect is more pronounced than that in other cross section. With same stress field, the edge dislocation gliding through the bottom of damage loop requires higher critical resolved shear stress than that through the top of the damage loop, due to the sequential change in the force direction. The stress fields of two loops along < 1 1 0 > direction cancel out each other to some extent. Hence the hardening effect increases with increasing distance between the two loops.
查看更多>>摘要：The thorium compounds are promising candidates for the new generation nuclear fuels. Using first-principles and particle swarm optimization methods, we have explored geometrical structures and physical characteristics of thorium carbonitrides (Th2CN) in the extensive pressure range from ambient pressure to 100 GPa. At ambient pressure, we have predicted a new phase I4(1)/amd, which is energetically more favorable than the previously known phases P 4/mmm and R3m. Moreover, a series of pressure-induced phase transitions have been predicted. The thermodynamics, mechanical stabilities, elastic properties, electronic structures and chemical bonds of all these newly predicted phases have been investigated. Our predictions on the new structures at ambient and high pressures would expand the structural phase diagram of thorium carbonitrides.
查看更多>>摘要：Machine-learning potentials for materials, namely the moment tensor potentials (MTPs), were validated using experimental EXAFS spectra for the first time. The MTPs for four metals (bcc W and Mo, fcc Cu and Ni) were obtained by the active learning algorithm of fitting to the results of the calculations using density functional theory (DFT). The MTP accuracy was assessed by comparing metal K-edge EXAFS spectra obtained experimentally and computed from the results of molecular dynamics (MD) simulations. The sensitivity of the method to various aspects of the MD and DFT models was demonstrated using Ni as an example. Good agreement was found for W, Mo and Cu using the recommended PAW pseudopotentials, whereas a more accurate pseudopotential with 18 valence electrons was required for Ni to achieve a similar agreement. The use of EXAFS spectra allows one to estimate the MTP ability in reproducing both average and dynamic atomic structures.
查看更多>>摘要：Bimetallic clusters received tremendous interest because the unusual physicochemical properties vary sensitively depending on their geometry, size, and composition. Here, we combined an efficient CALYPSO structural searching code and DFT calculations to study the structures and properties of magnesium clusters doped with two Li atoms, Li(2)Mgn (n = 1-11). Compared with pure Mgn clusters, it is found that Li doping induces a significant influence on the geometry and stability of the host. The structures of Li(2)Mgn are present a 2D to 3D transition at n = 3, slightly later than pure and single Li doped magnesium clusters. Localized sites of two Li atoms change from the convex position to the external capped position at n = 11. All positive charges on Li atoms illustrate a charge transfer from Li to Mg in doped clusters. Analysis of internal charges on the atomic orbitals shows an increased metallicity for Li(2)Mgn with increasing cluster size. Two triangular bipyramid structures, Li2Mg3 and Li2Mg9, were uncovered and proved to be the magic number ones with outstanding stability. The study of molecular orbitals and bonding nature implies that their higher stability is associated with the 1S(2)1P(6) and 1S(2)1P(6)1D(10)2S(2) closed-shell together with more strong Li-Mg bonds caused by sp hybridization. The simulated IR and Raman spectra could provide additional ways to identify the structure of these clusters in the following experiments.
查看更多>>摘要：In this study, first-principles calculations were carried out for the first time to systematically investigate the grain boundary segregation of transition metal alloying elements (Ti, V, Cr, Mn, Co, Ni, Cu, Nb, and Mo) in paramagnetic gamma Fe and its dependence on the grain boundary character. The segregation energies of each element and site were comprehensively calculated for nine [001] symmetric tilt grain boundary models with Sigma values from 5 to 41; the paramagnetic state was simulated by the antiferromagnetic double-layer (AFMD). By calculating the effective segregation energy for each grain boundary model from the obtained segregation energies, the grain boundary segregation behavior for each alloying element and its dependence on the grain boundary character were investigated. The segregation energy of transition metal elements is dominated by the Vomnoi volume of Fe at the segregation site and arises from the elastic energy derived from the difference in atomic radii between the host and solute metals. Ti, Cu, Nb, and Mo have negative effective segregation energies (indicating a tendency toward segregation) at all investigated grain boundaries, and the absolute values of the effective segregation energy increase in the order of Cu < Mo < Ti < Nb in all of the grain boundary models. In contrast, the sign of the effective segregation energies for V, Ni, and Co changes depending on the grain boundary, and the effective segregation energies for Cr and Mn are positive at all grain boundaries. These results corresponded well with the experimental results. The results obtained in this study provide important basic data for the material design of high-strength steels and are useful for understanding the effects of alloying elements in gamma Fe.
查看更多>>摘要：It has been known for many years that mixtures of lanthanum chloride (LaCl3) with alkali chlorides in spent nuclear fuel show severe departures from ideality. To go deep into this non-ideality, the local structure of molten LaCl3 was investigated by experiments and classic molecular dynamics simulations. However, there appears to be some controversy concerning conclusions of these research methodology such as coordination numbers of the first coordination shell. In this work, interatomic potential driven by machine learning is developed based on data sets generated by ab initio calculations in order to research the local structure and property of molten LaCl3 at 1200 K, 1300 K, 1400 K and 1500 K. The machine learning potential enables higher efficiency and similar accuracy relative to DFT and yields precise descriptions of microstructures and properties. Microstructural evolution with target temperatures is analyzed through partial radial distribution functions, coordination numbers, angular distribution functions and total neutron structural factors. We observe short- and intermediaterange order and the latter disappears at high temperature. The sevenfold and eightfold coordinated structures are dominant in LaCl3 melt and the network structure is composed of corner-sharing, edge-sharing and face-sharing configurations. Evolution of properties including density and self-diffusion coefficient over the entire operating temperature range are documented. This work exhibits a thorough understanding of the local structure and property of LaCl3 melt and reveals the accuracy of machine learning potential on molten trivalent metal chlorides for first time.
查看更多>>摘要：Nickel and its alloys are often used in the form of nanostructured materials, e.g., as catalysts for hydrogenation reactions, for hydrogen-storage applications, and as battery materials. This study focuses on subsurface hydride (NiHx) formation in Ni nanoparticles. The pressure at which hydrogen is incorporated within the nanoparticle surface is probed using grand canonical Monte Carlo (GCMC) simulations. An important observation is that the Ni nanoparticle size can have a significant effect on the hydride formation. Unlike bulk Ni, which forms the hydride phase at very high H-2 pressures, subsurface NiHx can form at significantly lower pressures with 2.7-9.1 nm particles. The (1 1 1) and (100) facets and facet edges of these nanoparticles possess remarkably different H incorporation characteristics compared to the nanoparticle core. The easier H-absorption in Ni nanoparticles is explained in terms of a nucleation-and-growth process, which begins at the facet edges and proceeds towards the interior of the nanoparticle. The NiHx and Ni phases co-exist in nanoparticle systems, which is not observed in bulk Ni. A computational characterization approach is used to gain insights into the layer-by-layer H incorpo-ration, which can be valuable for devising material preparation strategies for adsorption-based hydrogen storage and catalysis.
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Elsevier