Editorials

101.   J. Pfaendtner and A.L. Ferguson* “Characteristics of Impactful Machine Learning Contributions to The Journal of Physical Chemistry” J. Phys. Chem. A 127 2 415–417(2022) [ https://dx.doi.org/10.1021/acs.jpca.2c08702 ] J. Phys. Chem. B 127 2 427–429(2022) [ https://dx.doi.org/10.1021/acs.jpcb.2c08703 ] J. Phys. Chem. C 127 2 849–851(2022) [ https://dx.doi.org/10.1021/acs.jpcc.2c08704 ]

77.     A.L. Ferguson*, J. Hachmann, T.F. Miller, and J. Pfaendtner “Editorial: The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry” J. Phys. Chem B 124 9767−9772 (2020) [ https://dx.doi.org/10.1021/acs.jpcb.0c09206 ]

→ Invited editorial for the “Virtual Special Issue on Machine Learning in Physical Chemistry”

58.     A.L. Ferguson*, T. Mueller, S. Rajasekaran, and B.J. Reich “Conference report: 2018 materials and data science hackathon (MATDAT18)” Mol. Syst. Des. Eng. 4 462-468 (2019) [ https://doi.org/10.1039/c9me90018g ]

51.      A.L. Ferguson* “Editorial: ACS Central Science Virtual Issue on Machine Learning” ACS Cent. Sci. 4 8 938-941 (2018) [ http://dx.doi.org/10.1021/acscentsci.8b00528 ]

→ Invited editorial for the ” Virtual Issue on Machine Learning”

42.     A.L. Ferguson* and J. Hachmann “Machine learning and data science in materials design: a themed collection” Mol. Syst. Des. Eng. 3 429-430 (2018) [ https://doi.org/10.1039/C8ME90007H ]

→ Editorial for invited themed collection “Machine Learning and Data Science in Materials Design”