Found 19 results
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2021
W. Chen, Cohen, M., Yu, K., Wang, H. Lan, Zheng, W., and Vlachos, D. G., “Experimental data-driven reaction network identification and uncertainty quantification of CO2-assisted ethane dehydrogenation over Ga2O3/Al2O3”, Chemical Engineering Science, vol. 237, p. 116534, 2021.
W. Chen, Cohen, M., Yu, K., Wang, H. Lan, Zheng, W., and Vlachos, D. G., “Experimental data-driven reaction network identification and uncertainty quantification of CO2-assisted ethane dehydrogenation over Ga2O3/Al2O3”, Chemical Engineering Science, vol. 237, p. 116534, 2021.
W. Chen, Cohen, M., Yu, K., Wang, H. Lan, Zheng, W., and Vlachos, D. G., “Experimental data-driven reaction network identification and uncertainty quantification of CO2-assisted ethane dehydrogenation over Ga2O3/Al2O3”, Chemical Engineering Science, vol. 237, p. 116534, 2021.
H. Bhattacharjee, Anesiadis, N., and Vlachos, D. G., “Regularized machine learning on molecular graph model explains systematic error in DFT enthalpies”, Scientific Reports 2021 11:1, vol. 11, pp. 1–10, 2021.
H. Bhattacharjee, Anesiadis, N., and Vlachos, D. G., “Regularized machine learning on molecular graph model explains systematic error in DFT enthalpies”, Scientific Reports 2021 11:1, vol. 11, pp. 1–10, 2021.
J. L. Lansford, Kurdziel, S. J., and Vlachos, D. G., “Scaling of Transition State Vibrational Frequencies and Application of d-Band Theory to the Brønsted-Evans-Polanyi Relationship on Surfaces”, Journal of Physical Chemistry C, 2021.
J. L. Lansford, Kurdziel, S. J., and Vlachos, D. G., “Scaling of Transition State Vibrational Frequencies and Application of d-Band Theory to the Brønsted-Evans-Polanyi Relationship on Surfaces”, Journal of Physical Chemistry C, 2021.
2020
J. Feng, Lansford, J. L., Katsoulakis, M. A., and Vlachos, D. G., “Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences”, Science Advances, vol. 6, pp. 3204–3218, 2020.
J. Feng, Lansford, J. L., Katsoulakis, M. A., and Vlachos, D. G., “Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences”, Science Advances, vol. 6, pp. 3204–3218, 2020.
E. J. M. Hensen, Vlachos, D. G., Wang, Y., and Su, Y. Qiong, “Finite-temperature structures of supported subnanometer catalysts inferred via statistical learning and genetic algorithm-based optimization”, ACS Nano, vol. 14, pp. 13995–14007, 2020.
E. J. M. Hensen, Vlachos, D. G., Wang, Y., and Su, Y. Qiong, “Finite-temperature structures of supported subnanometer catalysts inferred via statistical learning and genetic algorithm-based optimization”, ACS Nano, vol. 14, pp. 13995–14007, 2020.
J. Lym, Wittreich, G. R., and Vlachos, D. G., “A Python Multiscale Thermochemistry Toolbox (pMuTT) for thermochemical and kinetic parameter estimation”, Computer Physics Communications, vol. 247, p. 106864, 2020.
J. Lym, Wittreich, G. R., and Vlachos, D. G., “A Python Multiscale Thermochemistry Toolbox (pMuTT) for thermochemical and kinetic parameter estimation”, Computer Physics Communications, vol. 247, p. 106864, 2020.
U. Gupta and Vlachos, D. G., “Reaction Network Viewer (ReNView): An open-source framework for reaction path visualization of chemical reaction systems”, SoftwareX, vol. 11, p. 100442, 2020.
U. Gupta and Vlachos, D. G., “Reaction Network Viewer (ReNView): An open-source framework for reaction path visualization of chemical reaction systems”, SoftwareX, vol. 11, p. 100442, 2020.
Y. Qiong Su, Zhang, L., Wang, Y., Liu, J. Xun, Muravev, V., Alexopoulos, K., Filot, I. A. W., Vlachos, D. G., and Hensen, E. J. M., “Stability of heterogeneous single-atom catalysts: a scaling law mapping thermodynamics to kinetics”, npj Computational Materials, vol. 6, p. 144, 2020.
Y. Qiong Su, Zhang, L., Wang, Y., Liu, J. Xun, Muravev, V., Alexopoulos, K., Filot, I. A. W., Vlachos, D. G., and Hensen, E. J. M., “Stability of heterogeneous single-atom catalysts: a scaling law mapping thermodynamics to kinetics”, npj Computational Materials, vol. 6, p. 144, 2020.
H. Bhattacharjee and Vlachos, D. G., “Thermochemical data fusion using graph representation learning”, Journal of Chemical Information and Modeling, vol. 60, pp. 4673–4683, 2020.
H. Bhattacharjee and Vlachos, D. G., “Thermochemical data fusion using graph representation learning”, Journal of Chemical Information and Modeling, vol. 60, pp. 4673–4683, 2020.