Jie Jiang

TL;DR: In this article, the largest inorganic solar-cell material search using density functional theory (DFT) and machine-learning approaches was presented, where the authors calculated the spectroscopic limited maximum efficiency (SLME) using Tran-Blaha modified Becke-Johnson potential for 5097 non-metallic materials and identified 1997 candidates with an SLME higher than 10%, including 934 candidates with suitable convex-hull stability and effective carrier mass.

TL;DR: The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory, classical force-fields, and machine learning techniques.

TL;DR: In this paper, a method combining first principles density functional theory and tight-binding was developed to distinguish defects in defective single-layer graphene (DSLG) by quantifying defect-induced Raman intensities.

TL;DR: In this paper, a method for photo-thermal oxidation of graphene is presented for the first time that suggests absence of pores in the graphene layer during atomic force microscopy, and the mechanism of oxidation is studied on CVD-grown graphene using in situ Raman spectroscopy.

TL;DR: First-order Raman intensity calculations demonstrate that a comparison between pristine and defective monolayer WSe2 with a single vacancy can provide a fingerprint for defect characterization, and will encourage experimental defect engineering to enable the development of red-shifted single-photon emitters.