Darren Pagan earned a B.S. degree in mechanical engineering from Columbia University in 2010 and his Ph.D. in mechanical engineering from Cornell University in 2016. His dissertation research focused on developing crystal kinematic and scattering models for quantifying heterogeneous plastic deformation in single crystals during thermo-mechanical loading from in-situ X-ray data. As a postdoctoral researcher at Lawrence Livermore National Laboratory, Darren developed new methods for integrating diffraction data with crystal plasticity finite element modeling and used X-ray techniques to characterize granular material deformation in-situ under quasi-static and dynamic loading conditions.
Prior to joining Penn State, Darren Pagan was a staff scientist overseeing the structural materials and mechanics program at the Cornell High Energy Synchrotron Source (CHESS). At CHESS, he oversaw the design, construction, and commissioning of the Structural Materials Beamline (SMB) and the Forming and Shaping Technology Beamline (FAST). Darren joined the faculty of the Department of Materials Science and Engineering at Penn State in 2020.
This faculty member is associated with the Penn State Intercollege Graduate Degree Program (IGDP) in Materials Science and Engineering (MatSE) where a multitude of perspectives and cross-disciplinary collaboration within research is highly valued. Graduate students in the IGDP in MatSE may work with faculty members from across Penn State.
Darren’s research focuses on developing data analysis methods for quantifying material deformation, integrating mechanical and scattering models, and expanding experimental capabilities for characterizing microstructure evolution during processing and performance testing of metallic alloys and composites. The goal of this research is to extract quantitative measures of microstructure evolution in-situ to develop, calibrate, and validate computational models and to accelerate the design of superior material systems.
A current research focus is developing connections between the output of machine learning data dimensionality techniques and more traditional physics-based modeling approaches. The traditional approach to extracting material information from data is to hypothesize a material response, model the material response and probe interactions, and then compare or fit the model to the data. One downside to such an approach is that the material response must be assumed a priori, naturally limiting the information that can be extracted. A compelling alternative approach is to apply unsupervised learning techniques to the raw data to distill the encoded information down to its lowest dimensional descriptors. Analyzing how these low dimensional descriptors are grouped spatially and/or evolve with time can provide insights into exactly how and when the most critical portions of microstructure develop, with new fundamental science coming from prediction of how physical quantities evolve in-line with more traditional, physically-based state descriptors.
Nair, S.D., Nygren, K.E., Pagan, D.C., “Probing the Micromechanical Response of Crystalline Phases in Alternate Cementitious Materials using 3-Dimensional X-ray Techniques” Scientific Reports. Volume 9. 18456 (2019)
Pagan, D.C., Phan, T.Q., Weaver, J.S., Benson, A.R., Beaudoin, A.J., “Unsupervised Learning of Dislocation Motion” Acta Materialia. Volume 181. 510-518 (2019)
Pagan, D.C., Kaminsky, J., Tayon, W.A.‡, Nygren, K.E., Beaudoin, A.J., Benson, A.R., “Automated Grain Yield Behavior Classification” JOM. Volume 71 (10). 3513-3520 (2019)
Phan, T.Q., Kim, F.H., Pagan, D.C., “Micromechanical response quantification using high-energy X-rays during phase transformations in additively manufactured 17-4 stainless steel” Materials Science and Engineering A. Volume 759. 565-573 (2019)
Tayon, W.A., Nygren, K.E., Pagan, D.C., “In-situ Study of Planar Slip in a Commercial Aluminum-Lithium Alloy using High Energy X-ray Diffraction Microscopy” Acta Materialia. Volume 173. 231-241 (2019)
Pagan, D.C., Beaudoin, A.J., “Utilizing a Novel Lattice Orientation Based Stress Characterization Method to Study Stress Fields of Shear Bands” Journal of the Mechanics and Physics of Solids Volume 128. 105-116 (2019)
Hurley, R.C., Pagan, D.C., “An in-situ study of stress evolution and fracture growth during compression of concrete” International Journal of Solids and Structures. Volume 168 (15). 26-40 (2019)
Pagan, D.C., Obstalecki, M., Park, J.-S., Miller, M.P., “Analyzing Shear Band Formation Using High Resolution X-ray Diffraction” Acta Materialia. Volume 147. 133-148 (2018)
Pagan, D.C., Bernier, J.V., Dale, D., Ko, J.Y.P., Turner, T.J., Blank, B., Shade, P.A., “Measuring Ti-7Al slip system strengths at elevated temperature using high-energy X-ray diffraction” Scripta Materialia. Volume 142. 96-100 (2018)
Pagan, D.C., Shade, P.A., Barton, N.R., Park, J.-S., Kenesei, P., Menasche, D.B., Bernier, J.V., “Modeling slip system strength evolution in Ti-7Al informed by in-situ grain stress measurements” Acta Materialia. Volume 128. 406-417 (2017)