Tin-based perovskites with narrow bandgaps and high charge-carrier mobilities are promising candidates for the preparation of efficient lead-free perovskite solar cells (PSCs). However, crystalline rate tin-based is much faster, leading to abundant trap states lower open-circuit voltage (Voc ). Here, hydrogen bonding introduced retard FASnI3 perovskite. By adding poly(vinyl alcohol) (PVA), OH…I- interactions between PVA have effects introducing nucleation sites, slowing down crystal growth,...

<title>Abstract</title> The segregation of Cr at grain boundaries (GBs) critically influences the mechanical properties high-strength steels, but it challenges Monte Carlo (MC) optimization based on density-functional theory calculations due to high computational costs. For Σ5(310) GB, we have compared efficiency MC with emerging factorization-machine quantum-annealing (FMQA) algorithm using Ising-machines. We find FMQA is more effective in low-concentration scenarios, while retains...

We survey the underlying theory behind large-scale and linear scaling density functional code, conquest, which shows excellent parallel can be applied to thousands of atoms with diagonalization millions scaling. give details representation matrix approach finding electronic ground state discuss implementation molecular dynamics an overview performance focusing in particular on scaling, provide examples recent developments applications.

Searching for high-performance anode materials and CO2 adsorption are key factors next-generation renewable energy technologies mitigation of the greenhouse effect. Herein, we report a novel two-dimensional (2D) BC2P monolayer with great potential as an material lithium-ion batteries (LIBs) adsorption. The energies Li atoms molecules on supercell negative enough to assure stability safety under operating conditions. More intriguingly, possesses very high theoretical capacity 1018.8 mA g h-1...

Given the widespread use of density functional theory (DFT), there is an increasing need for ability to model large systems (beyond 1,000 atoms). We present a brief overview large-scale DFT code Conquest, which capable modelling such systems, and discuss approaches generation consistent, well-converged pseudo-atomic basis sets will allow scale calculations. tests these variety materials, comparing fully converged plane wave results using same pseudopotentials grids.

The sensitive detection of n-propanol, a typical marker molecule in respiratory gases for lung cancer, has attracted much attention from the consideration health modern society. However, identification n-propanol at sub-ppm level with rapid responsive ability is significant challenge but very critical early diagnosis cancer. Herein, we demonstrate unique chromosome-like HoFeO3 nanostructure material, prepared by annealing self-sacrificial template easily accessible HoFe(CN)6,...

By using first principles calculations, we study the interlayer distance of two-layer graphene. We use a recently developed van der Waals density functional theory (VDWDFT) as well local approximation (LDA). Both methods give successful results for graphite; i.e., calculated distances are comparable with experimental value. find that graphene is close to graphite. also AA stacking structure has higher energy than AB one and layer larger stacking. It thus suggested becomes somewhat large when...

We reveal by first-principles calculations that the interlayer binding in a twisted MoS2/MoTe2 heterobilayer decreases with increasing twist angle, due to increase of overlapping degree, geometric quantity describing well steric effect. The energy is found be Gaussian-type function angle. resistance rotation, an analogue sliding barrier, can also defined accordingly. In sharp contrast case MoS2 homobilayer, here band gap reduces find remarkable charge transfer from MoTe2 MoS2, which enlarges...

We carry out spin-polarized positron lifetime calculations for ferromagnetic metals using the electron–positron density functional theory (DFT). investigate Fe, Co, and Ni find that differences between lifetimes their minority majority spins (τ↓ − τ↑) are 11.85, 3.75, −4.37 ps, respectively. The negative difference of is presumed to originate from an unlocalized distribution electrons.

The atomic descriptors used in machine learning to predict forces are often high dimensional. In general, by retrieving a significant amount of structural information from these descriptors, accurate force predictions can be achieved. On the other hand, acquire higher robustness for transferability without overfitting, sufficient reduction should necessary. this study, we propose method automatically determine hyperparameters aiming obtain while using small number descriptors. Our focuses on...

We propose a methodology based on unsupervised learning with the two-step locality preserving projections (TS-LPP) method to detect differences in local structures silica. Subtle changes can be detected.

Stable proton configurations in solid-state materials are a prerequisite for the theoretical microscopic investigation of proton-conductive materials. However, large number initial atomistic should be considered to find stable configurations, and relaxation calculations using density functional theory approach required each configuration. Consequently, determination is difficult time-consuming task. Furthermore, when size simulation cells or doped atoms increases, leads combinatorial...

By using first principles calculations, we study the interlayer distance of two-layer graphene. We use a recently developed van der Waals density functional theory (VDWDFT) as well local approximation (LDA). Both methods give successful results for graphite; i.e., calculated distances are comparable with experimental value. find that graphene is close to graphite. also AA stacking structure has higher energy than AB one and layer larger stacking. It thus suggested becomes somewhat large when...

We study a generalization performance of the machine learning (ML) model to predict atomic forces within density functional theory (DFT). The targets are Si and Ge single component systems in liquid state. To train model, Gaussian process regression is performed with fingerprints which express local structure around target atom. training test data generated by molecular dynamics (MD) based on DFT. first report accuracy ML when both from DFT-MD simulations at same temperature. By comparing...

Owing to the advances in computational techniques and increase power, atomistic simulations of materials can simulate large systems with higher accuracy. Complex phenomena be observed such state-of-the-art simulations. However, it has become increasingly difficult understand what is actually happening mechanisms, for example, molecular dynamics (MD) We propose an unsupervised machine learning method analyze local structure around a target atom. The proposed method, which uses two-step...

With the goal of understanding invalidation problem irradiated Hastelloy N alloy under condition intense irradiation and severe corrosion, corrosion behavior after He+ ion was investigated in molten fluoride salt at 700 °C for 500 h. The virgin samples were by 4.5 MeV ions room temperature. First, studied using positron annihilation lifetime spectroscopy (PALS) to analyze influence dose on vacancies. PALS results showed that changed size concentration vacancies which seriously affected...