atom in a clathrate-like cage

A final draft of my Ph.D. thesis can be downloaded here: (11 Mb PDF):

Understanding the Dielectric Properties of Water

For publications, see also Google Scholar

Peer reviewed journal articles

D. C. Elton, Z. Boukouvalas, M. D. Fuge, and P. W. Chung, “Deep learning for molecular generation - a review of the state of the art” (in prep)

D. C. Elton, Z. Boukouvalas, M. S. Butrico, M. D. Fuge, and P. W. Chung, “Applying machine learning techniques to predict the properties of energetic materials”, Scientific Reports 8, 9059 (2018).

D. C. Elton, M. Fritz, and M.-V Fernández-Serra. “Using a monomer potential energy surface to perform approximate path integral molecular dynamics simulation of ab-initio water at near-zero added cost”, (arXiv), forthcoming in Phys. Chem. Chem. Phys (2018)

D.C. EltonThe microscopic origin of the Debye relaxation in liquid water and fitting the high frequency excess response”, Phys. Chem. Chem. Phys., 19, 18739 (2017) [arXiv]

D.C. Elton and M.-V Fernández-Serra. “The hydrogen bond network of water supports propagating optical phonon-like modes”, Nat. Comm. 7, 10913 (2016)

D.C. Elton and M.-V Fernández-Serra. “Polar nanoregions in water – a study of the dielectric properties of TIP4P/2005,TIP4P/2005f and TTM3F”, J. Chem. Phys., 140, 124504 (2014) [arXiv]

J. J. Podesta, M. A. Forman, C. W. Smith, D. C. Elton, and Y. Malecot, “Accurate Estimation of Third-Order Moments from Turbulence Measurements“, Nonlin. Proc. Geophys., 16, 99 (2009) [arXiv]

Peer reviewed conference proceedings

D. C. Elton, D. Turakhia, N. Reddy, Z. Boukouvalas, R. M. Doherty, M. D. Fuge, and P. W. Chung. “Using natural language processing techniques to extract information on the properties and functionalities of energetic materials from large text corpora”. New Trends in Research of Energetic Materials, 2018 (in prep, abstract submitted)

G. Kumar, F. G. VanGessel, D. C. Elton, and P. W. Chung. “Prediction of Phonon Relaxation Times in α-RDX’’ MRS 2019 proceedings (in prep, abstract submitted)

Z. Boukouvalas, D. C. Elton, M. D. Fuge, and P. W. Chung. “Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine Learning”. Proceedings of the 2018 Neural Information Processing Systems (NeurIPS) workshop on Machine Learning for Molecules and Materials. [arXiv]

B. C. Barnes, D. C. Elton, Z. Boukouvalas, D. E. Taylor, W. D. Mattson, M. D. Fuge, and P.W. Chung, “Machine Learning of Energetic Material Properties”, Proceedings of the 16th International Detonation Symposium, Cambridge MD, USA, July 2018, [arXiv]

F. G. VanGessel, G. Kumar, D. C. Elton, and P. W. Chung, “A Phonon Boltzmann Study of Microscale Thermal Transport in α-RDX Cook-Off”, Proceedings of the 16th International Detonation Symposium, Cambridge MD, USA, July 2018. [arXiv]

M. A. Forman, C. W. Smith, B. J. Vasquez, B. T. MacBride, J. E. Stawarz, J. J. Podesta, D. C. Elton, U. Y. Malecot, and Y. Gagne. “Using Third‐Order Moments of Fluctuations in V and B to Determine Turbulent Heating Rates in the Solar Wind”, AIP Conference Proceedings 1216, 12th International Solar Wind Conference, 176 (2010)

Science notes

feedback on these is always appreciated.