M. C. Sorkun

Sorkun, M. C., Zhou, X., Murigneux, J., Menegazzo, N., Narsaria, A., Thanoon, D., … Er, S. (2025). RedCat, an automated discovery workflow for aqueous organic electrolytes. Digital Discovery, 4(7), 1844-1855. https://doi.org/10.1039/D5DD00111K

Sorkun, M. C., Saliou, B., & Er, S. (2025). ChemPrice, a Python Package for Automated Chemical Price Search. Chemistry-Methods, 5(2), e202400005. https://doi.org/10.1002/cmtd.202400005

Wang, Y., Sorkun, M. C., Brocks, G., & Er, S. (2024). ML-Aided Computational Screening of 2D Materials for Photocatalytic Water Splitting. Journal of Physical Chemistry Letters, 15(18), 4983-4991. https://doi.org/10.1021/acs.jpclett.4c00425 (Original work published 2024)

Sorkun, M. C., Ghassemi, E., Yatbaz, C., Koelman, J., & Er, S. (2024). RedPred, a machine learning model for the prediction of redox reaction energies of the aqueous organic electrolytes. Artificial Intelligence Chemistry, 2(1), 100064. https://doi.org/10.1016/j.aichem.2024.100064 (Original work published 2024)

Sorkun, M. C. (2022). Artificial Intelligence-driven Discovery of Materials for Energy Applications (Eindhoven University of Technology). Eindhoven University of Technology, Eindhoven, Netherlands. Retrieved from https://research.tue.nl/nl/publications/artificial-intelligence-driven-discovery-of-materials-for-energy- (Original work published)

Sorkun, M. C., Mullaj, D., Koelman, J. M. V. A., & Er, S. (2022). ChemPlot, a Python Library for Chemical Space Visualization. Chemistry-Methods, 2(7), e202200005. https://doi.org/10.1002/cmtd.202200039

Sorkun, E., Zhang, Q., Khetan, A., Sorkun, M. C., & Er, S. (2022). RedDB, a computational database of electroactive molecules for aqueous redox flow batteries. Nature Scientific Data, 9, 718. https://doi.org/10.1038/s41597-022-01832-2 (Original work published 2022)

Sorkun, M. C., Koelman, J. M. V. A., & Er, S. (2021). Pushing the limits of solubility prediction via quality-oriented data selection. IScience, 24(1), 101961. https://doi.org/10.1016/j.isci.2020.101961

Sorkun, M. C., Incel, O. D., & Paoli, C. (2020). Time series forecasting on multi-variate solar radiation data using deep learning (LSTM). Turkish Journal of Electrical Engineering & Computer Sciences , 28, 211-223. https://doi.org/10.3906/elk-1907-218 (Original work published 2020)

Sorkun, M. C., Astruc, S., Koelman, J. M. V. A., & Er, S. (2020). An artificial intelligence-aided virtual screening recipe for two-dimensional materials discovery. NPJ Computational Materials, 6(1), 106. https://doi.org/10.1038/s41524-020-00375-7 (Original work published 2020)