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We propose a scheme for ab initio configurational sampling in multicomponent crystalline solids using Behler-Parinello type neural network potentials (NNPs) in an unconventional way: the NNPs are trained to predict the energies of relaxed structures from the perfect lattice with configurational disorder instead of the usual way of training to predict energies as functions of continuous atom coordinates. An active learning scheme is employed to obtain a training set containing configurations of thermodynamic relevance. This enables bypassing of the structural relaxation procedure that is necessary when applying conventional NNP approaches to the lattice configuration problem. The idea is demonstrated on the calculation of the temperature dependence of the degree of A/B site inversion in three spinel oxides, MgAl2O4, ZnAl2O4, and MgGa2O4. The present scheme may serve as an alternative to cluster expansion for "difficult" systems, e.g., complex bulk or interface systems with many components and sublattices that are relevant to many technological applications today.
Assuntos
Redes Neurais de Computação , Óxidos , Temperatura , TermodinâmicaRESUMO
We theoretically revisit the proton diffusivity in yttrium-doped barium zirconate (Y-doped BaZrO3) with realistic dopant configurations under processing conditions. In a recent study employing the replica exchange Monte Carlo method, the equilibrium Y configurations at typical sintering temperatures were shown to deviate from the random configuration assumed in earlier theoretical studies. In the present study, we took this observation into account and evaluated the effect of the Y configuration on the proton diffusivity. Using the master equation approach based on local diffusion barriers calculated from first principles, the proton diffusivities under realistic Y configurations were estimated to be higher than those in the random configuration. This is explained by the fact that realistic Y configurations have fewer trap sites with deep potential wells compared to the random configuration due to the isolation trend of Y dopants. In addition, the effects of proton-proton interaction and the abundance of preferential conduction pathways are discussed; it is found that both are relatively minor factors compared to the trap site effect in determining the dependence of the proton diffusivity on the Y configurations.
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We report first-principles simulation of polarization mechanisms in hydroxyapatite to explain the underlying mechanism behind the reported ion conductivities and polarization under electrical poling at elevated temperatures. It is found that ion conduction occurs mainly in the column of OH- ions along the c-axis through a combination of the flipping of OH- ions, exchange of proton vacancies between OH- ions, and the hopping of the OH- vacancy. The calculated activation energies are consistent with those found in conductivity measurements and thermally stimulated depolarization current measurements.
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Hydrogen adsorption on Pt(111) has been actively studied using semilocal approximations within the density functional theory featuring simultaneous adsorption of hydrogen on multiple sites, i.e., fcc, atop, and hcp. Considering the accuracy needed to detail the feature, we revisit this problem with the help of higher level of theory, the adiabatic connection fluctuation dissipation theorem within the random phase approximation. Our simulation emphasizes important roles played by the equilibrium lattice parameter of the surface, mass of the hydrogen isotope, and hydrogen coverage. The insight acquired in this study provides a way to consistently interpret electrochemical and spectroscopic data.
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The origin of electrical resistance at the interface between the positive electrode and solid electrolyte of an all-solid-state Li battery has not been fully determined. It is well known that the interface resistance increases when the electrode surface is exposed to air. However, an effective method of reducing this resistance has not been developed. This report demonstrates that drastic reduction of the resistance is achievable by annealing the entire battery cell. Exposing the LiCoO2 positive electrode surface to H2O vapor increases the resistance by more than 10 times (to greater than 136 Ω cm2). The magnitude can be reduced to the initial value (10.3 Ω cm2) by annealing the sample in a battery form. First-principles calculations reveal that the protons incorporated into the LiCoO2 structure are spontaneously deintercalated during annealing to restore the low-resistance interface. These results provide fundamental insights into the fabrication of high-performance all-solid-state Li batteries.
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Spatiotemporal changes in general transcription levels play a vital role in the dynamic regulation of various critical activities. Phosphorylation levels at Ser2 in heptad repeats within the C-terminal domain of RNA polymerase II, representing the elongation form, is an indicator of transcription. However, rapid transcriptional changes during tissue development and cellular phenomena are difficult to capture in living organisms. We introduced a genetically encoded system termed modification-specific intracellular antibody (mintbody) into Arabidopsis thaliana. We developed a protein processing- and 2A peptide-mediated two-component system for real-time quantitative measurement of endogenous modification level. This system enables quantitative tracking of the spatiotemporal dynamics of transcription. Using this method, we observed that the transcription level varies among tissues in the root and changes dynamically during the mitotic phase. The approach is effective for achieving live visualization of the transcription level in a single cell and facilitates an improved understanding of spatiotemporal transcription dynamics.
Assuntos
Arabidopsis/enzimologia , Imagem Molecular/métodos , Processamento de Proteína Pós-Traducional , RNA Polimerase II/química , Análise Espaço-Temporal , FosforilaçãoRESUMO
We demonstrate the feasibility of performing sufficient configurational sampling of disordered oxides directly from first-principles without resorting to the use of fitted models such as cluster expansion. This is achieved by harnessing the power of modern-day cluster supercomputers using the replica exchange Monte Carlo method coupled directly with structural relaxation and energy calculation performed by density functional codes. The idea is applied successfully to the calculation of the temperature-dependence of the degree of inversion in the cation sublattice of MgAl2O4 spinel oxide. The possibility of bypassing fitting models will lead to investigation of disordered systems where cluster expansion is known to perform badly, for example, systems with large lattice deformation due to defects, or systems where long-range interactions dominate such as electrochemical interfaces.
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Topological nodal line semimetals, a novel quantum state of materials, possess topologically nontrivial valence and conduction bands that touch at a line near the Fermi level. The exotic band structure can lead to various novel properties, such as long-range Coulomb interaction and flat Landau levels. Recently, topological nodal lines have been observed in several bulk materials, such as PtSn4, ZrSiS, TlTaSe2 and PbTaSe2. However, in two-dimensional materials, experimental research on nodal line fermions is still lacking. Here, we report the discovery of two-dimensional Dirac nodal line fermions in monolayer Cu2Si based on combined theoretical calculations and angle-resolved photoemission spectroscopy measurements. The Dirac nodal lines in Cu2Si form two concentric loops centred around the Γ point and are protected by mirror reflection symmetry. Our results establish Cu2Si as a platform to study the novel physical properties in two-dimensional Dirac materials and provide opportunities to realize high-speed low-dissipation devices.
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The emergence of negative capacitance in an ultrathin ferroelectric/paraelectric bilayer capacitor under electrical bias is examined using first-principles simulation. An antiferroelectric-like behavior is predicted, and negative capacitance is shown to emerge when the monodomain state becomes stable after bias application. The polydomain-monodomain transition is also shown to be a source of capacitance enhancement.