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个人简介

德国埃尔朗根-纽伦堡大学博士(2013) 德国马普煤炭研究所博士后(2013-2019) 厦门大学副教授(2019-)

研究领域

机器学习,半经验量子化学方法,光谱的量子化学模拟,化学反应机理的理论研究,光物理,光化学

近期论文

查看导师最新文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

1. Tobias A. Schaub, Theresa Mekelburg, Pavlo O. Dral, Matthias Miehlich, Frank Hampel, Karsten Meyer, Milan Kivala*, A Spherically Shielded Triphenylamine and Its Persistent Radical Cation. Chem. Eur. J. 2020, Accepted Article. DOI: 10.1002/chem.202000355. 2. Pavlo O. Dral*, MLatom: A Program Package for Quantum Chemical Research Assisted by Machine Learning. J. Comput. Chem. 2019, 40, 2339–2347. DOI: 10.1002/jcc.26004. 3. Pavlo O. Dral*, Xin Wu, Walter Thiel*, Semiempirical Quantum-Chemical Methods with Orthogonalization and Dispersion Corrections. J. Chem. Theory Comput. 2019, 15, 1743–1760. DOI: 10.1021/acs.jctc.8b01265. 4. Xin Wu, Pavlo O. Dral, Axel Koslowski, Walter Thiel*, Big Data Analysis of Ab Initio Molecular Integrals in the Neglect of Diatomic Differential Overlap Approximation. J. Comput. Chem. 2019, 40, 638–649. DOI: 10.1002/jcc.25748. 5. Wen-Kai Chen, Xiang-Yang Liu, Weihai Fang, Pavlo O. Dral, Ganglong Cui*, Deep Learning for Nonadiabatic Excited-State Dynamics. J. Phys. Chem. Lett. 2018, 9, 6702–6708. DOI: 10.1021/acs.jpclett.8b03026. 6. Pavlo O. Dral*, Mario Barbatti*, Walter Thiel*, Nonadiabatic Excited-State Dynamics with Machine Learning. J. Phys. Chem. Lett. 2018, 9, 5660–5663. DOI: 10.1021/acs.jpclett.8b02469. 7. Pavlo O. Dral*, Alec Owens, Sergei N. Yurchenko, Walter Thiel, Structure-Based Sampling and Self-Correcting Machine Learning for Accurate Calculations of Potential Energy Surfaces and Vibrational Levels. J. Chem. Phys. 2017, 146, 244108. DOI: 10.1063/1.4989536. 8. Pavlo O. Dral*, Timothy Clark*, On the Feasibility of Reactions through the Fullerene Wall: A Theoretical Study of NHx@C60. Phys. Chem. Chem. Phys. 2017, 19, 17199–17209. DOI: 10.1039/C7CP02865B. 9. Pavlo O. Dral, Xin Wu, Lasse Spörkel, Axel Koslowski, Walter Thiel*, Semiempirical Quantum-Chemical Orthogonalization-Corrected Methods: Benchmarks for Ground-State Properties. J. Chem. Theory Comput. 2016, 12, 1097–1120. DOI: 10.1021/acs.jctc.5b01047. 10. Raghunathan Ramakrishnan, Pavlo O. Dral, Matthias Rupp, O. Anatole von Lilienfeld*, Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach. J. Chem. Theory Comput. 2015, 11, 2087–2096. DOI: 10.1021/acs.jctc.5b00099. 11. Pavlo O. Dral*, O. Anatole von Lilienfeld, Walter Thiel*, Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations. J. Chem. Theory Comput. 2015, 11, 2120–2125. DOI: 10.1021/acs.jctc.5b00141. 12. Raghunathan Ramakrishnan, Pavlo O. Dral, Matthias Rupp, O. Anatole von Lilienfeld*, Quantum Chemistry Structures and Properties of 134 Kilo Molecules. Sci. Data 2014, 1, 140022. DOI: 10.1038/sdata.2014.22. 13. Pavlo O. Dral*, The Unrestricted Local Properties: Application in Nanoelectronics and for Predicting Radicals Reactivity. J. Mol. Model. 2014, 20, 2134. DOI: 10.1007/s00894-014-2134-78. 14. Michael Salinas, Christof M. Jäger, Atefeh Y. Amin, Pavlo O. Dral, Timo Meyer-Friedrichsen, Andreas Hirsch, Timothy Clark, Marcus Halik*, The Relationship between Threshold Voltage and Dipolar Character of Self-assembled Monolayers in Organic Thin-Film Transistors. J. Am. Chem. Soc. 2012, 134, 12648–12652. DOI: 10.1021/ja303807u. 15. Pavlo O. Dral, Timothy Clark*, Semiempirical UNO–CAS and UNO–CI: Method and Applications in Nanoelectronics. J. Phys. Chem. A 2011, 115, 11303–11312. DOI: 10.1021/jp204939x.

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