A. Khetan

Zhou, X. ., Khetan, A. ., Zheng, J. ., Huijben, M. ., Janssen, R. A. J., & Er, S. . (2023). Discovery of lead quinone cathode materials for Li-ion batteries. Digital Discovery, 2(4), 1016-1025. https://doi.org/10.1039/D2DD00112H (Original work published 2023)

Zhang, Q. ., Khetan, A. ., Sorkun, E. ., Niu, F. ., Loss, A. ., Pucher, I. ., & Er, S. . (2022). Data-driven discovery of small electroactive molecules for energy storage in aqueous redox flow batteries. Energy Storage Materials, 47, 167-177. https://doi.org/10.1016/j.ensm.2022.02.013 (Original work published 2022)

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)

Zhang, Q. ., Khetan, A. ., Sorkun, E. ., & Er, S. . (2022). Discovery of aza-aromatic anolytes for aqueous redox flow batteries via high-throughput screening. Journal of Materials Chemistry A, 10(41), 22214-22227. https://doi.org/10.1039/D2TA05674G (Original work published 2022)

Zhou, X. ., Khetan, A. ., & Er, S. . (2021). Evaluation of Computational Chemistry Methods for Predicting Redox Potentials of Quinone-Based Cathodes for Li-Ion Batteries. Batteries, 7(4), 71. https://doi.org/10.3390/batteries7040071 (Original work published 2021)

Zhang, Q. ., Khetan, A. ., & Er, S. . (2021). A Quantitative Evaluation of Computational Methods to Accelerate the Study of Alloxazine-Derived Electroactive Compounds for Energy Storage. Scientific Reports, 11, 4089. https://doi.org/10.1038/s41598-021-83605-2 (Original work published 2021)

Zhang, Q. ., Khetan, A. ., & Er, S. . (2020). Comparison of computational chemistry methods for the discovery of quinone-based electroactive compounds for energy storage. Scientific Reports, 10, 22149. https://doi.org/10.1038/s41598-020-79153-w (Original work published 2020)

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)