August 17, 2018

Our recent manuscript: “Electronic properties of binary compounds with high fidelity and high…

Full article at

Full article at

Our recent manuscript: “Electronic properties of binary compounds with high fidelity and high throughput”

Full article at

This is a second study in a series of projects we did recently. This work is aimed to demonstrate the capabilities of platform and how it can be applied for high-throughput screening of electronic materials.


We present example applications of an approach to high-throughput first-principles calculations of the electronic properties of materials implemented within the platform. We deploy computational techniques based on the Density Functional Theory with both Generalized Gradient Approximation (GGA) and Hybrid Screened Exchange (HSE) in order to extract the electronic band gaps and band structures for a set of 775 binary compounds.

We find that for HSE, the average relative error fits within 22%, whereas for GGA it is 49%. We find the average calculation time on an up-to-date server centrally available from a public cloud provider to fit within 1.2 and 36 hours for GGA and HSE, respectively. The results and the associated data, including the materials and simulation workflows, are standardized and made available online in an accessible, repeatable and extensible setting.


The figure below summarizes the results:

Heatmap plot with the band gap results of this work extracted within the Generalized Gradient Approximation. Compounds are sorted by the second element in formula and the gap value starting from the top right corner

Our work provides an accessible and repeatable practical recipe for performing high-fidelity first-principles calculations of the electronic structural properties of materials in a high-throughput manner. We welcome collaborative contributions in order to further grow the online repository of high fidelity results; secondly, allow contributions from other modeling techniques beyond studied here; and, finally, facilitate the creation of statistical (machine learning) models based on the available data.

Below is an example web page for a simulation executed for the InGaAs compound available here


[1] Full manuscript available at:
[2] Simulations data available at: link