Statistical analysis of the performance of a variety of first-principles schemes for accurate prediction of binary semiconductor band gaps.

Standard density functional theory (DFT) approximations tend to strongly underestimate band gaps, while the more accurate GW and hybrid functionals are much more computationally demanding and unsuitable for high-throughput screening. In this work, we have performed an extensive benchmark of several approximations with different computational complexity [G0W0@PBEsol, HSE06, PBEsol, modified Becke-Johnson potential (mBJ), DFT-1/2, and ACBN0] to evaluate and compare their performance in predicting the bandgap of semiconductors. The benchmark is based on 114 binary semiconductors of different compositions and crystal structures, for about half of which experimental band gaps are known.

Prediction of novel two-dimensional Dirac nodal line semimetals in AlB and AlB monolayers.

Topological semimetal phases in two-dimensional (2D) materials have gained widespread interest due to their potential applications in novel nanoscale devices. Despite the growing number of studies on 2D topological nodal lines (NLs), candidates with significant topological features that combine nontrivial topological semimetal phase with superconductivity are still rare. Herein, we predict AlB and AlB monolayers as new 2D nonmagnetic Dirac nodal line semimetals with several novel features.

An study of antileishmanial effect of extract.

Background & Objectives: Leishmaniasis is caused by protozoa of Leishmania genus and is considered as a zoonotic disease. It is a major public health problem worldwide, with high endemicity in developing countries like Iran. Various chemical drugs are used for leishmaniasis treatment, but their side-effects and the emergence of drug resistance have led to look for new effective compounds.