Highlights with ‘solar cells’

Halide perovskites: efficient & accurate DFTB simulations

The fundamental understanding of the material properties of metal halide perovskites is critical to improving the stability and efficiency of future solar cells devices. Computational simulations have been proven to be a valuable tool to...

Insights into the instabilities of halide perovskite with ReaxFF

Halide perovskites have attracted enormous attention over the recent years. The combination of their high conversion efficiencies, low production costs, and ease of fabrication make them ideal candidates for use in solar cell technology. Despite...

Microstructure of doped lead halide perovskites from solid-state NMR

Multi-component lead halide perovskites have recently emerged as new promising materials for solar cells and light emitting devices. Essential to their remarkable performance is the notion of doping with inorganic and organic cations such as...

SCM at 9th China International OLEDs Summit

Fedor will be presenting at the Emerging Technologies 2020 conference in Shanghai. If you’re there, check out his talk in the OLEDs Summit track on January 15th. Learn how using simulations can accelerate new material...

Understanding Band Structures – “Mirrors of Bonding” in Perovskite Crystals

Band structures are a widely used tool in solid state physics and materials science to analyze the electronic structure of crystalline materials. However, the band structure of materials relevant for actual applications are often rather...

Perovskite Band Structure & COOP Analysis – Advanced Tutorial

Whether you are a solid state physicist thinking of chemistry as too arcane or a chemist puzzled by band structure theory: Try out our new tutorial and learn how to neatly link these two fields,...

Photoinduced Charge Separation in Organic Photovoltaics: Effect of Dispersion

The effects of dispersion forces on the structure and charge separation (CS) in the P3HT/PCBM dimer were studied using state-of-the-art computational methods in ADF (DFT-D3, TDDFT–CAMYB3LYP). The authors demonstrate the importance to properly account for...

PhD position computational material science: designing quantum dots

A PhD position is available with Ivan Infante to use machine learning and advanced python workflows for predicting suitable precursors for new and improved quantum dots for solar cells and displays. The work will be...