First-principles screening of surface-charge-transfer molecular dopants for n-type diamond.

Surface charge transfer doping (SCTD) is an alternative approach to achieving n-type doped diamonds since the n-type bulk doping of diamonds remains a challenge, but so far efficient diamond n-type SCTD has not been achieved. Here we provide a comprehensive study of the n-type SCTD of the diamond by using first-principles calculations based on the density functional theory. Taking the principle that ionization potentials of the dopants must be higher than those of the diamond, we screened a series of molecules that may be suitable for diamond n-type SCTD doping.

Mechanically and operationally stable flexible inverted perovskite solar cells with 20.32% efficiency by a simple oligomer cross-linking method.

Due to their great potential in wearable and portable electronics, flexible perovskite solar cells (FPSCs) have been extensively studied. The major challenges in the practical applications of FPSCs are efficiency, operational stability, and mechanical stability. Herein, we developed a facile approach by incorporating a cross-linking oligomer of trimethylolpropane ethoxylate triacrylate (TET) into perovskite films to simultaneously enhance the power conversion efficiency (PCE) and stability of FPSCs.

Inorganic Crystal Structure Prototype Database Based on Unsupervised Learning of Local Atomic Environments.

Recognition of structure prototypes from tremendous known inorganic crystal structures has been an important subject beneficial for materials science research and new materials design. The existing databases of inorganic crystal structure prototypes were mostly constructed by classifying materials in terms of the crystallographic space group information. Herein, we employed a distinct strategy to construct the inorganic crystal structure prototype database, relying on the classification of materials in terms of local atomic environments (LAEs) accompanied by unsupervised machine learning method.

Entropy-Driven Stabilization of Multielement Halide Double-Perovskite Alloys.

Currently, a major obstacle restricting the commercial application of halide perovskites is their low thermodynamic stability. Herein, inspired by the high-stability high-entropy alloys, we theoretically investigated a variety of multielement double-perovskite alloys. First-principles calculations show that the entropy contribution to Gibbs free energy, which offsets the positive enthalpy contribution by up to 35 meV/f.

Metal Halide Semiconductors beyond Lead-Based Perovskites for Promising Optoelectronic Applications.

In recent decades, metal halide semiconductors represented by lead-based halide perovskites have shown broad potential in optoelectronic applications. This family of semiconductors differs from traditional tetrahedral semiconductors in crystalline structure, chemical bonding, electronic-structure features, optoelectronic properties, as well as material fabrication method. At present, difficulties arising from both intrinsic material properties (including Pb toxicity and long-term stability) and technological aspects hinder their large-scale commercialization.

JAMIP: an artificial-intelligence aided data-driven infrastructure for computational materials informatics.

Materials informatics has emerged as a promisingly new paradigm for accelerating materials discovery and design. It exploits the intelligent power of machine learning methods in massive materials data from experiments or simulations to seek new materials, functionality, and principles, etc. Developing specialized facilities to generate, collect, manage, learn, and mine large-scale materials data is crucial to materials informatics.