Dan Lewis

Associate Professor
Materials Science and Engineering
Prior to joining Rensselaer, Dr. Lewis was a researcher at GE Global Research. His work focused on oxidation performance and deformation processing of advanced ferritic materials for SOFC interconnects. In addition, he studied the metallurgy and electrical properties of amorphous and nano-crystalline soft magnetic materials, oxidation resistant coatings for superalloys, and infrared heating technology development. Prior to joining GE Global Research, he was awarded a two-year National Research Council post-doctoral fellowship. Under this award, he worked at the National Institute of Standards and Technology (NIST) to study eutectic solidification microstructures using experimental and computational techniques. While at NIST he co-developed a technique for quantifying solidification microstructures in ternary eutectics. He also studied the effect of solidification velocity on the phase distribution in low-volume fraction ternary eutectics containing intermetallic phases. His computational work involves study of morphological evolution during processing and image driven machine learning.


Ph.D. Materials Science and Engineering (Lehigh University, 2001), M.S. Materials Science and Engineering (Lehigh University, 1997), B.S. Materials Science and Engineering (Lehigh University, 1995)

Focus Area

Mesoscopic Modeling, Microstructure Science and Microscopy, Image Driven Machine Learning, Solidification and Phase Transformations

Selected Scholarly Works

M. Casteel, D. Lewis, P. Willson, and M. Alinger. "Ionic Conductivity Method for measuring vaporized chromium species from solid oxide fuel cell interconnects," International Journal of Hydrogen Energy, doi:10.1016/j.ijhydene.2012.01.016 (2012)

Determination of the eutectic structure in the Ag-Cu-Sn system D Lewis, S Allen, M Notis, A Scotch, Journal of electronic materials 31 (2), 161-167 (2004)

Image driven machine learning methods for microstructure recognition A Chowdhury, E Kautz, B Yener, D Lewis, Computational Materials Science 123, 176-187 (2016)

An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction, E Kautz, W Ma, S Jana, A Devaraj, V Joshi, B Yener, D Lewis, arXiv preprint arXiv:1906.05496 (2019)

M. Casteel, P. Willson, T. Goren, P. O'Brien, and D. Lewis, “Novel Method for Measuring Chromia Evaporation from SOFC Interconnect Materials,” ECS Transactions, 25(2), p. 1411-1416 (2009)

M. Glicksman, P. Rios, and D. Lewis, “Linear Measures for Polyhedral Networks,” International Journal of Materials Research, 100(4), p. 536-542 (2009)

M. Glicksman, P. Rios, and D. Lewis, “Mean-width and Caliper Characteristics of Network Polyhedra,” Philosophical Magazine, 89(4), p. 389-403 (2009)

Stochasticity in materials structure, properties, and processing—A review R Hull, P Keblinski, D Lewis, A Maniatty, V Meunier, AA Oberai, CR Picu, ... Applied physics reviews 5 (1), 011302 (2018)