ResearcherID: A-6089-2016
Profile on Google Scholar

Books and Book Chapters

Book (as Editor and contributor to 8 chapters):

Quantum Chemistry in the Age of Machine Learning, Pavlo O. Dral, Ed. Elsevier: 2023. ISBN: 9780323900492. Companion website to the book with complementary materials, data, codes, etc. (up-to-date mirror companion website | blog post)


  1. Jingbai Li, Morgane Vacher, Pavlo O. Dral, Steven A. Lopez. Machine learning methods in photochemistry and photophysics. In Theoretical and Computational Photochemistry: Fundamentals, Methods, Applications and Synergy with Experimentation, Cristina García-Iriepa and Marco Marazzi, Eds. Elsevier: 2023. DOI: 10.1016/B978-0-323-91738-4.00002-6. (blog post)
  2. Pavlo O. Dral*, Tetiana Zubatiuk. Improving semiempirical quantum mechanical methods with machine learning. In Quantum Chemistry in the Age of Machine Learning, Pavlo O. Dral, Ed. Elsevier: 2023. DOI: 10.1016/B978-0-323-90049-2.00014-7.
  3. Pavlo O. Dral*, Tetiana Zubatiuk, Bao-Xin Xue. Learning from multiple quantum chemical methods: Δ-learning, transfer learning, co-kriging, and beyond. ibid. DOI: 10.1016/B978-0-323-90049-2.00012-3.
  4. Julia Westermayr*, Pavlo O. Dral, Philipp Marquetand. Learning excited-state properties. ibid. DOI: 10.1016/B978-0-323-90049-2.00004-4.
  5. Lina Zhang, Arif Ullah, Max Pinheiro Jr, Mario Barbatti*, Pavlo O. Dral*. Excited-state dynamics with machine learning. ibid. DOI: 10.1016/B978-0-323-90049-2.00008-1.
  6. Yi-Fan Hou, Pavlo O. Dral*. Kernel method potentials. ibid. DOI: 10.1016/B978-0-323-90049-2.00020-2. (case study)
  7. Max Pinheiro Jr*, Pavlo O. Dral*, Kernel methods. ibid. DOI: 10.1016/B978-0-323-90049-2.00009-3.
  8. Pavlo O. Dral*, Alexei Kananenka*, Fuchun Ge, Bao-Xin Xue, Neural networks. ibid. DOI: 10.1016/B978-0-323-90049-2.00011-1.
  9. Pavlo O. Dral*, Jan Řezáč*. Semiempirical quantum mechanical methods. ibid. DOI: 10.1016/B978-0-323-90049-2.00016-0.
  10. Pavlo O. Dral*. Quantum Chemistry Assisted by Machine Learning. In Advances in Quantum Chemistry: Chemical Physics and Quantum Chemistry, Volume 81, 1st ed.; Kenneth Ruud, Erkki J. Brändas, Eds. Academic Press: 2020; Vol. 81. DOI: 10.1016/bs.aiq.2020.05.002. (blog postonline tutorial)


  1. Pavlo O. Dral*, Ben Hourahine*, Stefan Grimme*. Modern semiempirical electronic structure methods. J. Chem. Phys. 2024, 160, 040401. DOI: 10.1063/5.0196138. (special topic)
  2. Aurora E. Clark*, Pavlo O. Dral*, Isaac Tamblyn*, Olexandr Isayev*. Themed collection on Insightful Machine Learning for Physical Chemistry. Phys. Chem. Chem. Phys. 2023, 25, 22563–22564. DOI: 10.1039/d3cp90129g. (themed collection)

Peer-reviewed Articles

* marks corresponding authors. † marks equal contributions/co-first authorship.

  1. Sebastian V. Pios, Maxim F. Gelin, Arif Ullah, Pavlo O. Dral*, Lipeng Chen*. Artificial-Intelligence-Enhanced On-the-Fly Simulation of Nonlinear Time-Resolved Spectra. J. Phys. Chem. Lett. 2024, 15, 2325–2331. DOI: 10.1021/acs.jpclett.4c00107.
    Preprint on arXiv:
  2. Pavlo O. Dral*, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Olexandr Isayev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Jr, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou. MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows. J. Chem. Theory Comput. 2024, 20, 1193–1213. DOI: 10.1021/acs.jctc.3c01203. (blog post)
    Preprint on arXiv:
  3. Arif Ullah*, Pavlo O. Dral*. MLQD: A package for machine learning-based quantum dissipative dynamics. Comput. Phys. Commun. 2024, 294, 108940. DOI: 10.1016/j.cpc.2023.108940. (tutorial | video lecture | video tutorial)
    Preprint on ChemRxiv: | arXiv:
  4. Fuchun Ge, Lina Zhang, Yi-Fan Hou, Yuxinxin Chen, Arif Ullah, Pavlo O. Dral*. Four-dimensional-spacetime atomistic artificial intelligence models. J. Phys. Chem. Lett. 2023, 14, 7732–7743. DOI: 10.1021/acs.jpclett.3c01592. (blog post)
    Preprint on ChemRxiv: (ancient version) | arXiv: (more recent version).
  5. Lina Zhang, Yi-Fan Hou, Fuchun Ge, Pavlo O. Dral*. Energy-conserving molecular dynamics is not energy conserving. Phys. Chem. Chem. Phys. 2023, 25, 23467–23476. DOI: 10.1039/D3CP03515H. (blog post)
    Preprint on arXiv:
  6. Arif Ullah, Luis E. Herrera Rodríguez, Pavlo O. Dral*, Alexei A. Kananenka*. QD3SET-1: A Database with Quantum Dissipative Dynamics Data Sets. Front. Phys. 2023, 11, 1223973. DOI: 10.3389/fphy.2023.1223973. (blog post)
    Preprint on ChemRxiv: | arXiv:
  7. Xuefeng He, Lina Zhang, Jiawei Chen, Huichong Liu, Yuming Su, Han Li, Yonghua Cao, Pavlo O. Dral*, Cheng Wang*. Photo-Driven Aerobic Methane Nitration. Inorg. Chem. 2023, 62, 10343–10350. DOI: 10.1021/acs.inorgchem.3c01210. (blog post)
  8. Yi-Fan Hou, Fuchun Ge, Pavlo O. Dral*. Explicit learning of derivatives with the KREG and pKREG models on the example of accurate representation of molecular potential energy surfaces. J. Chem. Theory Comput2023, 19, 2369–2379. DOI: 10.1021/acs.jctc.2c01038. (blog post)
    Preprint on ChemRxiv:
  9. Tobias A. Schaub*, Anna Zieleniewska, Ramandeep Kaur, Martin Minameyer, Wudi Yang, Christoph M. Schüßlbauer, Lina Zhang, Markus Freiberger, Lev N. Zakharov, Thomas Drewello, Pavlo O. Dral, Dirk Guldi, Ramesh Jasti*. Tunable Macrocyclic Polyparaphenylene Nanolassos via Copper‐Free Click Chemistry. Chem. Eur. J. 2023, 29, e202300668. DOI: 10.1002/chem.202300668. (blog post)
  10. Max Pinheiro Jr*, Shuang Zhang, Pavlo O. Dral, Mario Barbatti*. WS22 database: combining Wigner Sampling and geometry interpolation towards configurationally diverse molecular datasets. Sci. Data 2023, 10, 95. DOI: 10.1038/s41597-023-01998-3. (blog post)
    Preprint on ChemRxiv:
  11. Yuxinxin Chen, Yanchi Ou, Peikun Zheng, Yaohuang Huang, Fuchun Ge, Pavlo O. Dral*. Benchmark of General-Purpose Machine Learning-Based Quantum Mechanical Method AIQM1 on Reaction Barrier Heights. J. Chem. Phys. 2023, 158, 074103. DOI: 10.1063/5.0137101. (blog post)
  12. Yuming Su, Yiheng Dai, Yifan Zeng, Caiyun Wei, Yangtao Chen, Fuchun Ge, Peikun Zheng, Da Zhou*, Pavlo O. Dral*, Cheng Wang*. Interpretable Machine Learning of Two-Photon Absorption. Adv. Sci. 2023, 2204902. DOI: 10.1002/advs.202204902. (blog post | tutorial)
    Preprint on ChemRxiv:
  13. Francesco Bosia, Peikun Zheng, Alain Vaucher, Thomas Weymuth, Pavlo O. Dral*, Markus Reiher*. Ultra-Fast Semi-Empirical Quantum Chemistry for High-Throughput Computational Campaigns with Sparrow. J. Chem. Phys. 2023, 158, 054118. DOI: 10.1063/5.0136404.
    Preprint on arXiv:
  14. Luis E. Herrera Rodríguez, Arif Ullah, Kennet J. Rueda Espinosa, Pavlo O. Dral*, Alexei A. Kananenka*. A comparative study of different machine learning methods for dissipative quantum dynamics. Mach. Learn. Sci. Technol. 2022, 3, 045016. DOI: 10.1088/2632-2153/ac9a9d. (blog post)
    Preprint on ChemRxiv: | arXiv:
  15. Mario Barbatti*, Mattia Bondanza, Rachel Crespo-Otero, Baptiste Demoulin, Pavlo O. Dral, Giovanni Granucci, Fábris Kossoski, Hans Lischka, Benedetta Mennucci, Saikat Mukherjee, Marek Pederzoli, Maurizio Persico, Max Pinheiro Jr, Jiri Pittner, Felix Plasser, Eduarda Sangiogo Gil, Lijljana Stojanovic. The Newton-X platform: new software developments for surface hopping and nuclear ensembles. J. Chem. Theory Comput. 2022, 18, 6851–6865. DOI: 10.1021/acs.jctc.2c00804. (blog post)
    Preprint on ChemRxiv:
  16. Armando de Rezende, Mahdi Malmali, Pavlo O. Dral, Hans Lischka*, Daniel Tunega*, Adelia A. J. Aquino*. Machine Learning for Designing Mixed Metal Halides for Efficient Ammonia Separation and Storage. J. Phys. Chem. C, 2022, 126, 12184–12196. DOI: 10.1021/acs.jpcc.2c02586. (blog post | 50 free copies of paper)
  17. Arif Ullah*, Pavlo O. Dral*. One-shot trajectory learning of open quantum systems dynamics. J. Phys. Chem. Lett. 2022, 13, 6037–6041. DOI: 10.1021/acs.jpclett.2c01242. (blog post)
    Preprint on ChemRxiv: | arXiv:
  18. Peikun Zheng, Wudi Yang, Wei Wu, Olexandr Isayev*, Pavlo O. Dral*. Toward Chemical Accuracy in Predicting Enthalpies of Formation with General-Purpose Data-Driven Methods. J. Phys. Chem. Lett. 2022, 13, 3479–3491. DOI: 10.1021/acs.jpclett.2c00734. (blog post | tutorial)
  19. Arif Ullah*, Pavlo O. Dral*. Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics. Nat. Commun. 2022, 13, 1930. DOI: 10.1038/s41467-022-29621-w. (blog post)
    Preprint on ChemRxiv:
  20. Lina Zhang, Shuang Zhang, Alec Owens*, Sergei N. Yurchenko, Pavlo O. Dral*. VIB5 database with accurate ab initio quantum chemical molecular potential energy surfaces. Sci. Data 2022, 9, 84. DOI: 10.1038/s41597-022-01185-w. (blog post)
  21. Peikun Zheng, Roman Zubatyuk, Wei Wu, Olexandr Isayev*, Pavlo O. Dral*. Artificial Intelligence-Enhanced Quantum Chemical Method with Broad Applicability. Nat. Commun. 2021, 12, 7022. DOI: 10.1038/s41467-021-27340-2. (blog post | tutorial)
    Preprint on ChemRxiv
  22. Arif Ullah*, Pavlo O. Dral*. Speeding up quantum dissipative dynamics of open systems with kernel methods. New J. Phys. 2021, 23, 113019. DOI: 10.1088/1367-2630/ac3261. (blog post)
    Preprint on ChemRxiv
  23. Max Pinheiro Jr*, Fuchun Ge, Nicolas Ferré, Pavlo O. Dral*, Mario Barbatti*. Choosing the right molecular machine learning potential. Chem. Sci. 2021, 12, 14396–14413. DOI: 10.1039/D1SC03564A. (blog post | tutorial)
    Preprint on ChemRxiv:
  24. Pavlo O. Dral*, Fuchun Ge, Bao-Xin Xue, Yi-Fan Hou, Max Pinheiro Jr, Jianxing Huang, Mario Barbatti. MLatom 2: An Integrative Platform for Atomistic Machine Learning. Top. Curr. Chem. 2021, 379, 27. DOI: 10.1007/s41061-021-00339-5. (blog post | tutorial)
  25. Pavlo O. Dral*, Mario Barbatti*, Molecular excited states through a machine learning lens. Nat. Rev. Chem. 2021, 5, 388–405. DOI: 10.1038/s41570-021-00278-1. (blog post)
  26. Bao-Xin Xue, Mario Barbatti*, Pavlo O. Dral*, Machine Learning for Absorption Cross Sections. J. Phys. Chem. A 2020, 124, 7199–7210. DOI: 10.1021/acs.jpca.0c05310. (blog post | tutorial)
    Preprint on ChemRxiv, DOI: 10.26434/chemrxiv.12594191.
  27. Miriam Hauschild, Michal Borkowski, Pavlo O. Dral, Tomasz Marszalek, Frank Hampel, Gaozhan Xie, Jan Freudenberg, Uwe H. F. Bunz*, Milan Kivala*. 5,7,12,14-Tetraphenyl-Substituted 6,13-Diazapentacenes as Versatile Organic Semiconductors: Characterization in Field Effect Transistors. Org. Mater. 2020, 3, 204–213. DOI: 10.1055/s-0040-1713856. (blog post)
  28. Marcel Krug, Maximilian Wagner, Tobias A. Schaub, Wen-Shan Zhang, Christoph M. Schüßlbauer, Johannes D. R. Ascherl, Peter M. Münich, Rasmus R. Schröder, Franziska Gröhn, Pavlo O. Dral, Mario Barbatti, Dirk M. Guldi*, Milan Kivala*. The Impact of Aggregation on the Photophysics of Spiro-bridged Heterotriangulenes. Angew. Chem. Int. Ed. 2020, 59, 16233–16240. DOI: 10.1002/anie.202003504. (blog post)
    Der Einfluss von Aggregation auf die Photophysik von spiroverbrückten HeterotriangulenenAngew. Chem. 2020132, 16368–16376. DOI: 10.1002/ange.202003504.
  29. Pavlo O. Dral*, Alec Owens, Alexey Dral, Gábor Csányi*. Hierarchical Machine Learning of Potential Energy Surfaces. J. Chem. Phys. 2020, 152, 204110. DOI: 10.1063/5.0006498. (blog post)
  30. Pavlo O. Dral*, Quantum Chemistry in the Age of Machine Learning. J. Phys. Chem. Lett. 2020, 11, 2336–2347. DOI: 10.1021/acs.jpclett.9b03664. (blog post | video | LiveSlides)
  31. 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, 26, 3264–3269. DOI: 10.1002/chem.202000355. (blog post)
  32. 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. (blog post)
  33. Johannes T. Margraf*, Pavlo O. Dral. What Is Semiempirical Molecular Orbital Theory Approximating? J. Mol. Model. 2019, 25, 119. DOI: 10.1007/s00894-019-4005-8. (blog post)
  34. 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. (blog post)
  35. 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. (blog post)
  36. 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. (blog post)
  37. 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. (blog post)
  38. Nico Fritsch, Christian R. Wick, Thomas Waidmann, Stephan Pflock, Pavlo O. Dral, Johannes Tucher, Christian Steiner, Tatyana E. Shubina, Sabine Maier*, Timothy Clark*, Nicolai Burzlaff*. 1D Chains of Diruthenium Tetracarbonyl Sawhorse Complexes. Eur. J. Inorg. Chem. 2018, 54–61. DOI: 10.1002/ejic.201701246.
  39. 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. (blog post)
    arXiv:1808.05806v1 [physics.chem-ph].
  40. 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.
  41. Bettina D. Gliemann, Volker Strauss, Jakob F. Hitzenberger, Pavlo O. Dral, Frank Hampel, Jean-Paul Gisselbrecht, Thomas Drewello, Walter Thiel, Dirk M. Guldi*, Milan Kivala*. Dithiafulvenyl-Extended N-Heterotriangulenes and Their Interaction with C60: Cooperative Fluorescence. Chem. Eur. J. 2017, 23, 12353–12362. DOI: 10.1002/chem.201701625.
  42. Tobias A. Schaub, Steffen M. Brülls, Pavlo O. Dral, Frank Hampel, Harald Maid, Milan Kivala*. Organic Electron Acceptors Comprising a Dicyanomethylene-Bridged Acridophosphine Scaffold: The Impact of the Heteroatom. Chem. Eur. J. 2017, 23, 6988–6992. DOI: 10.1002/chem.201701412. (blog post)
  43. Bettina D. Gliemann, Ana G. Petrovic, Eva M. Zolnhofer, Pavlo O. Dral, Frank Hampel, Georg Breitenbruch, Schulze Philipp, Vijay Raghavan, Karsten Meyer, Prasad L. Polavarapu, Nina Berova*, Milan Kivala*. Configurationally Stable Chiral Dithia-Bridged Hetero[4]helicene Radical Cation: Electronic Structure and Absolute Configuration. Chem. Asian J. 2017, 12, 31–35. DOI: 10.1002/asia.201601452. (blog post)
  44. Jakob F. Hitzenberger, Pavlo O. Dral, Ute Meinhardt, Timothy Clark, Walter Thiel, Milan Kivala*, Thomas Drewello*. Stability of Odd- Versus Even-Electron Gas-Phase (Quasi)Molecular Ions Derived from Pyridine-Substituted N-Heterotriangulenes. ChemPlusChem 2017, 82, 204–211. DOI: 10.1002/cplu.201600416. (blog post)
    Appeared as the front cover in ChemPlusChem (p. 161, DOI: 10.1002/cplu.201600597) with the associated cover profile (p. 163, DOI: 10.1002/cplu.201600596).
  45. Gerhard König*, Frank C. Pickard IV, Jing Huang, Andrew C. Simmonett, Florentina Tofoleanu, Juyong Lee, Pavlo O. Dral, Samarjeet Prasad, Michael Jones, Yihan Shao, Walter Thiel, Bernard R. Brooks, Calculating Distribution Coefficients Based on Multi-Scale Free Energy Simulations: An Evaluation of MM and QM/MM Explicit Solvent Simulations of Water-Cyclohexane Transfer in the SAMPL5 Challenge. J. Comput. Aided Mol. Des. 2016, 30, 989–1006. DOI: 10.1007/s10822-016-9936-x. (blog post)
  46. Ute Meinhardt, Fabian Lodermeyer, Tobias A. Schaub, Andreas Kunzmann, Pavlo O. Dral, Anna Chiara Sale, Frank Hampel, Dirk M. Guldi*, Ruben D. Costa*, Milan Kivala*. N-Heterotriangulene Chromophores with 4-Pyridyl Anchors for Dye-Sensitized Solar Cells. RSC Adv. 2016, 6, 67372–67377. DOI: 10.1039/C6RA14799B. (blog post)
  47. 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. (blog post)
  48. Pavlo O. Dral, Xin Wu, Lasse Spörkel, Axel Koslowski, Wolfgang Weber, Rainer Steiger, Mirjam Scholten, Walter Thiel*. Semiempirical Quantum-Chemical Orthogonalization-Corrected Methods: Theory, Implementation, and Parameters. J. Chem. Theory Comput. 2016, 12, 1082–1096. DOI: 10.1021/acs.jctc.5b01046. (blog post)
  49. 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. (blog post 1 | blog post 2)
    arXiv:1503.04987 [physics.chem-ph].
  50. 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. (blog post)
  51. Nico Fritsch, Christian R. Wick, Thomas Waidmann, Pavlo O. Dral, Johannes Tucher, Frank W. Heinemann, Tatyana E. Shubina, Timothy Clark*, Nicolai Burzlaff*. Multiply Bonded Metal(II) Acetate (Rhodium, Ruthenium, and Molybdenum) Complexes with the trans-1,2-Bis(N-methylimidazol-2-yl)ethylene Ligand. Inorg. Chem. 2014, 53, 12305–12314. DOI: 10.1021/ic501435a. (blog post)
  52. 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. (blog post)
    Data set download link: figshare.
  53. 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. (blog post)
  54. Hui Li, Christina Schubert, Pavlo O. Dral, Rubén Costa, Andrea La Rosa, Jürg Thüring, Shi-Xia Liu*, Chenyi Yi, Salvatorre Filippone, Nazario Martin, Silvio Decurtins, Timothy Clark, Dirk M. Guldi*. Probing Charge Transfer in Benzodifuran–C60 Dumbbell-Type Electron Donor–Acceptor Conjugates: Ground- and Excited-State Assays. ChemPhysChem 2013, 14, 2910–2919. DOI: 10.1002/cphc.201300378.
    Appeared as an inside cover in ChemPhysChem (page 2870, DOI: 10.1002/cphc.201390062).
  55. Pavlo O. Dral, Milan Kivala*, Timothy Clark*. Doped Polycyclic Aromatic Hydrocarbons as Building Blocks for Nanoelectronics: A Theoretical Study. J. Org. Chem. 2013, 78, 1894–1902. DOI: 10.1021/jo3018395.
  56. Alina Ciammaichella, Pavlo O. Dral, Timothy Clark, Pietro Tagliatesta*, Michael Sekita, Dirk M. Guldi*. A π-Stacked Porphyrin–Fullerene Electron Donor–Acceptor Conjugate that Features a Surprising Frozen Geometry. Chem. Eur. J. 2012, 18, 14008–14016. DOI: 10.1002/chem.201202245.
  57. 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.
  58. Pavlo O. Dral, Tatyana E. Shubina, Andreas Hirsch, Timothy Clark*. Influence of Electron Doping on the Hydrogenation of Fullerene C60: A Theoretical Investigation. ChemPhysChem 2011, 12, 2581–2589. DOI: 10.1002/cphc.201100529.
  59. 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.
  60. Andrey A. Fokin*, Tatyana S. Zhuk, Alexander E. Pashenko, Pavlo O. Dral, Pavel A. Gunchenko, Jeremy E. P. Dahl, Robert M. K. Carlson, Tatyana V. Koso, Michael Serafin, Peter R. Schreiner*. Oxygen-Doped Nanodiamonds: Synthesis and Functionalizations. Org. Lett. 2009, 11, 3068–3071. DOI: 10.1021/ol901089h.


  1. Pavlo O. Dral, Theoretical study of electronic properties of carbon allotropes. Friedrich-Alexander-Universität Erlangen-Nürnberg, Dissertation (Dr. rer. nat.), 2013,
  2. Pavlo O. Dral, Comparative DFT and Ab Initio Study of Nitrogen-Containing Electrophiles. Department of Organic Chemistry and Organic Compounds, National Technical University of Ukraine “Kiev Polytechnic Institute”, Magister dissertation, 2010.
  3. Pavlo O. Dral, Hydrogen Chemisorption on Neutral and Electron-Doped Graphenic Surfaces: A Theoretical Investigation. Friedrich-Alexander-Universität Erlangen-Nürnberg, Master thesis, 2010.
  4. Pavlo O. Dral, Production of 1,2-dibromocyclohexane with productivity of 270 t/year. Department of Organic Chemistry and Organic Compounds, National Technical University of Ukraine “Kiev Polytechnic Institute”, Bachelor thesis, 2008.


  1. P. O. Dral, F. Ge, Y.-F. Hou, P. Zheng, Y. Chen, B.-X. Xue, M. Pinheiro Jr, Y. Su, Y. Dai, Y. Chen, S. Zhang, L. Zhang, A. Ullah, Y. Ou, MLatom: A Package for Atomistic Simulations with Machine Learning, Xiamen University, Xiamen, China, 2013–2024.
  2. W. Thiel, with contributions from M. Beck, S. Billeter, R. Kevorkiants, M. Kolb, A. Koslowski, S. Patchkovskii, A. Turner, E.-U. Wallenborn, W. Weber, L. Spörkel, and P. O. Dral, MNDO 2020, Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, 2019.
  3. T. Clark, M. Hennemann, P. O. Dral, EMPIRE 2013, unreleased development version, Universität Erlangen-Nürnberg and Cepos InSilico Ltd. (, 2013.
  4. T. Clark, A. Alex, B. Beck, F. Burkhardt, J. Chandrasekhar, P. Gedeck, A. Horn, M. Hutter, B. Martin, P. O. Dral, G. Rauhut, W. Sauer, T. Schindler, T. Steinke, VAMP 11.0, University of Erlangen, Germany, 2011.

White papers

  1. Pavlo O. Dral*, Arif Ullah. Call for Urgent Regulations on Artificial Intelligence. Preprints 2023. DOI: 10.20944/preprints202304.0429.v1.