Octahedral Distortion and Displacement-Type Ferroelectricity with Switchable Photovoltaic Effect in a 3d^{3}-Electron Perovskite System

Because of the half-filled t_{2g}-electron configuration, the BO_{6} octahedral distortion in a 3d^{3} perovskite system is usually very limited. In this Letter, a perovskitelike oxide Hg_{0.75}Pb_{0.25}MnO_{3} (HPMO) with a 3d^{3} Mn^{4+} state was synthesized by using high pressure and high temperature methods. This compound exhibits an unusually large octahedral distortion enhanced by approximately 2 orders of magnitude compared with that observed in other 3d^{3} perovskite systems like RCr^{3+}O_{3} (R=rare earth). Essentially different from centrosymmetric HgMnO_{3} and PbMnO_{3}, the A-site doped HPMO presents a polar crystal structure with the space group Ama2 and a substantial spontaneous electric polarization (26.5  μC/cm^{2} in theory) arising from the off-center displacements of A- and B-site ions. More interestingly, a prominent net photocurrent and switchable photovoltaic effect with a sustainable photoresponse were observed in the current polycrystalline HPMO. This Letter provides an exceptional d^{3} material system which shows unusually large octahedral distortion and displacement-type ferroelectricity violating the "d^{0}-ness" rule.

Flatband in a three-dimensional tungsten nitride compound

Herein, the flatband of a W₁N₂ crystal is theoretically investigated. It is revealed that the flatband can be well-described by a tight-binding model of the N₁₂ skeleton, where the dispersion of the flatband is governed by both the ppσ bonding strength (V_ppσ) and the ppπ bonding strength (V_ppπ) between the nearest-neighbor N atoms. It is also found that the proper strength of the ppπ bonding between neighboring N atoms plays a prime role in the formation of the flatband. In addition, when the compound is doped with holes, the electrons at the flatband are fully polarized, showing a ferromagnetic character. This behavior has a weak correlation with the on-site Coulomb interaction U. Moreover, several three-dimensional compounds possessing flatbands in the whole k space are predicted.

A machine learning based deep potential for seeking the low-lying candidates of Al clusters

A Machine-Learning based Deep Potential (DP) model for Al clusters is developed through training with an extended database including ab initio data of both bulk and several clusters in only 6 CPU/h. This DP model has good performance in accurately predicting the low-lying candidates of Al clusters in a broad size range. Based on our developed DP model, the low-lying structures of 101 different sized Al clusters are extensively searched, among which the lowest-energy candidates of 69 sized clusters are updated. Our calculations demonstrate that machine-learning is indeed powerful in generating potentials to describe the interaction of atoms in complex materials.

Linear scaling algorithm for tight-binding molecular dynamics simulations

The linear scaling or O(N) methods, which exhibit linear scaling with respect to the size of system, are a powerful tool for theoretically treating a huge system containing many atoms. We present a new linear scaling algorithm for large-scale tight-binding molecular dynamics simulations based on the divide-and-conquer approach, in which a system is divided into subsystems and each subsystem is calculated separately. Different from the common realization of the divide-and-conquer approach, our proposed method avoids building the density matrix or electronic density and gives a new strategy to access the physical properties of a large system. We apply this method to the tungsten metallic system and show that this method very effectively yields the same results including the atomic structures, the melting point, the formation energy of defects, and the electronic properties as those obtained from the exact diagonalization of tight-binding Hamiltonian matrix of a whole system. This method has the advantages of linear scaling complexity, less memory consumption, and high parallel efficiency, which make it to be used for the large-scale simulations.

A study on oxidative stress in lead-exposed workers

To explore the possible oxidative stress induced by lead, heparinized whole blood and urine of 66 secondary smelter lead workers (46 for Comet assay) and 28 controls were collected. The concentrations of blood lead (BPb) and urinary lead (UPb) and alpha-aminolevulinic acid (alpha-ALA), indices of lead exposure level of the body, were determined. Malondialdehyde (MDA) concentrations and superoxide dismutase (SOD) activity of plasma were also measured. Single-cell gel (SCG, Comet assay) was used to measure the DNA damage of peripheral blood cells. There was a positive correlation between the presence of Pb in blood and significant increases in MDA levels and SOD activity. Alcohol consumption and smoking with increased exposure to Pb was associated with enhanced DNA damage. A positive correlation was found between MDA and DNA damage.