Author Correction: Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides

Correction to: npj Computational Materials, published online 23 April 2020

The authors became aware of a mistake in the original version of this Article. Specifically, some of the band gap values plotted and reported in Fig. 1c and Table SI-1 were incorrect. This error originated because two different types of k-point meshes were used in DFT computations performed on CdTe, CdSe and CdS: one which is gamma-centered and one which is not gamma-centered. The gamma-centered calculation results are the correct quantities; the non-gamma-centered results were mistakenly reported in the original versions of Fig. 1 and Table SI-1. As a result of this, the following changes have been made to the originally published version of this Article:

The correct version of Fig. 1:

replaces the previous incorrect version:

The correct version of Table SI-1:

replaces the previous incorrect version:

These errors have been corrected in the PDF and HTML versions of the Article, and the HTML has been updated to include a corrected version of the Supplementary Information.

The band gaps and band edges used in the remainder of the manuscript are correct and no other results are affected. We thank Maciej Piotr Polak of the University of Wisconsin Madison for the reporting of this error.

Author information



Corresponding authors

Correspondence to Arun Mannodi-Kanakkithodi or Maria K. Y. Chan.

Additional information

The original article can be found online at

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mannodi-Kanakkithodi, A., Toriyama, M.Y., Sen, F.G. et al. Author Correction: Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides. npj Comput Mater 6, 134 (2020).

Download citation


Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing