(660g) Materials Simulation for Manufacturing

Manufacturing in the pharmaceutical industry can benefit from particle-based simulations. The efficiency of the unit operations handling powders and pills depend on how those powders and pills interact and flow. Simulations often model such materials as hard spheres. Adhesion, cohesion and (sliding, rolling and twisting) friction are present however, and impact their rheology. Particle-based simulations connect those interactions with emergent behavior. On a smaller scale, molecular simulations have been effective in drug discovery, yet advances in methods and computational power make simulations well poised to address formulation challenges in the pharmaceutical industry. Simulations of nanoparticle, amphiphile and small drug undergoing directed- and self-assembly give microscopic insight and design rules for formulations. I am interested in research that adds value by increasing efficiency in energy, waste and development time. I am eager to identify and support those opportunities as customer needs and market forces changes company value areas. I am qualified for such research because of my background in soft-matter and particle-based simulations.

Postdoctoral Project:

“Granular particle processing simulation”

“Polymer nanocomposite deformation and phase separation”

Under supervision of Amalie Frischknecht, Gary S. Grest and Mark S. Stevens at the Center for Integrated Nanotechnologies, Sandia National Laboratories

PhD Dissertation:

“Self-assembly of Surfactants and Colloids.”

Under supervision of Athanassios Z. Panagiotopoulos, Chemical and Biological Engineering, Princeton University

Research Experience:

I have applied particle-based simulation to various research problems in my career. I have applied many methods to different problems. I apply molecular dynamics (MD), Monte Carlo (MC), discrete-element modeling (DEM) and theoretically-inspired Langevin dynamics (TILD) to various fundamental questions and engineering problems. As a post-doc at Sandia, I learned, and helped develop methods for, DEM and TILD. I leveraged my experience in molecular dynamics from my PhD at Princeton to manufacturing challenges at Sandia. Frictional particle packing and flow, self-assembly, nanocomposites and protein binding inhibition are a few of my previous projects. I have developed new capabilities for MD and DEM (in /C++ for LAMMPS and HOOMD) and for MC (in FORTRAN for Cassandra), and analysis (mostly in python) to improve accuracy and efficiency.

Service Experience:

Assistant Scoutmaster adult volunteer, Scouts (BSA) (2019-present)

Member of Session (aka Board), La Mesa Presbyterian Church (2021-present)

President and Bolivia Project Lead, Engineers Without Borders NC State Univ. Chapter (2009-2013)

Mentor, Minority Engineering, NC State Univ. (2010-2013)

Publications:

Santos A. P., Bolintineanu D. S., Grest G. S., Lechman J. B., Plimpton, S. J., Srivastava I., Silbert L. E., “Granular packings with sliding, rolling and twisting friction.”, Physical Review E, 102, 032903 (2020)

Jiao, S., Santos, A. P., Panagiotopoulos, A. Z., “Differences in free surfactant concentration and aggregation properties for amphiphiles with the same critical micelle concentration”, Fluid Phase Equilibria 470, 126-133 (2018)

Santos, A. P., Pękalski J., Panagiotopoulos, A. Z., “Thermodynamic signatures and cluster properties of self-assembly in systems with competing interactions”, Soft Matter 13, 8055-8063 (2017)

Santos, A.P., Panagiotopoulos, A .Z., “Determination of the critical micelle concentration in simulations of surfactant systems”, J. Chemical Physics 144, 044709 (2016)

Zhang, Z., Santos, A. P., Zhou, Q., Liang, L., Wang, Q., Wu, T., Franzen, S., “Steered molecular dynamics study of inhibitor binding in the internal binding site in dehaloperoxidase-hemoglobin”, Biophysical Chemistry 211, 28-38 (2016)

French, W., Pervaje, A., Santos, A. P., Iacovella, C., Cummings, P., “Probing the statistical validity of the ductile-to-brittle transition in metallic nanowires using GPU computing”, J. Chemical Theory and Computation 9, 5558–5566 (2013)