DIFFER

M. C. Sorkun

First name
M.
Middle name
C.
Last name
Sorkun
ORCID
0000-0002-5531-0802
Sorkun, M. C. (2022). Artificial Intelligence-driven Discovery of Materials for Energy Applications (Eindhoven University of Technology). Eindhoven University of Technology, Eindhoven, Netherlands. Retrieved de https://research.tue.nl/nl/publications/artificial-intelligence-driven-discovery-of-materials-for-energy- (Original work published 01 C.E.)
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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
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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)
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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
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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)
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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)
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Sorkun, M. C., Khetan, A., & Er, S. (2019). AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds. Nature Scientific Data, 6, 143. https://doi.org/10.1038/s41597-019-0151-1 (Original work published 2019)
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