VIRTUAL

 Thursday, April 21st    2022

3:45 – 4:45 pm (MT)

WEBEX 

 Speaker:  Prof. Alejandro Strachan

School of Materials Engineering and Birck Nanotechnology Center

Purdue University, West Lafayette, Indiana, 47906 USA

“ Predictive modeling of energetic materials @ extreme conditions: physics-based and machine learning modeling towards understanding detonation initiation”

 

Abstract: 

First principles-based modeling and data science are playing an increasingly important role in the science and engineering of materials. Examples range from predictive models capable of revealing and quantifying the underlying mechanisms that govern materials properties to autonomous active learning workflows for materials discovery. I will discuss recent progress in our group on the application of these tools to high energy density (HE) materials and advances towards making materials models and data universally accessible and useful.

The shock-induced initiation of composite energetic materials involves a multitude of coupled processes occurring at extreme conditions of pressure, temperature, and ultra-high strain rates. Key among them is the interaction between the propagating shockwave and the materials microstructure and defects that results in the localization of energy into hotspots that accelerate chemistry. To date, hotspots have been described by their temperature fields but there is growing evidence that dynamically formed hotpots are unexpectedly reactive. Our large-scale molecular dynamics simulations revealed that the shock-induced collapse of porosity results in more energy localized as internal potential energy (PE) than as temperature. This leads to a complex thermo-mechanical state that has been overlooked. Reactive MD simulations show that the intra-molecular strain responsible for the potential energy hotspot affects both the decomposition kinetics and chemical paths. To quantify these observations, we extended the concept of mechanochemistry to many body strains that are prevalent in condensed matter systems. Finally, the information from atomistic simulations is coarse grained to develop reduced-order chemistry and thermo-mechanical models and used in continuum level simulations capable of capturing microstructural effects in plastic bonded explosives.

Bio:

Alejandro Strachan is a Professor of Materials Engineering at Purdue University, Director of the DoD MURI Center “Predictive Chemistry and Physics at Extreme Conditions”, and the Deputy Director of NSF’s nanoHUB. Before joining Purdue, he was a Staff Member in the Theoretical Division of Los Alamos National Laboratory and worked as a Postdoctoral Scholar and Scientist at Caltech. He received a Ph.D. in Physics from the University of Buenos Aires, Argentina. Prof. Strachan’s research focuses on the development of predictive atomistic and multiscale models to describe materials from first principles and their combination with data science to address problems of technological or scientific importance. Areas of interest include high-energy density and active materials, metallic alloys for high-temperature applications, materials and devices for nanoelectronics and energy, as well as polymers and their composites. In addition, Strachan’s scholarly work includes cyberinfrastructure to maximize the impact of and democratize access to models and data for research and education. Prof. Strachan has published over 180 peer-reviewed scientific papers and his contributions to research and education have been recognized by several awards, including the Early Career Faculty Fellow Award from TMS in 2009, his induction as a Purdue University’s Faculty Scholar (2012-2017), and the R&D 100 award in the category of software and services for nanoHUB.