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GSNP Short Course on Adventures with Computational Modeling and Machine Learning

From Grains to Bits (Part I): Deformable Particle Model and Applications to Soft and Biological Materials

Room 222/223, Caesars Forum

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  • Students: $40
  • Early Career: $60
  • Regular Members: $75
  • Non-APS Members: $100

Additional Details

  • Attendees may register for this event only or may register to attend in addition to their March Meeting 2023 registration.
  • This event is sponsored by Statistical and Nonlinear Physics (GSNP).


The collective dynamics of packings of grains, colloids, and emulsions are strongly influenced by the deformability of the constituent particles. Numerous theoretical and computational studies have employed the “soft particle model” to describe these systems, where deformability is treated as shared volume between overlapping particles. However, the soft particle model does not conserve particle volume and does not explicitly model changes in the shape of deformable particles. In this tutorial, we will introduce the deformable particle model (DPM), which includes energy costs for particle compressibility, surface tension, and bending rigidity to enable the explicit modeling of changes in particle shape.

The DPM allows researchers to study a wide range of phenomena spanning soft and biological materials including jamming of emulsion droplets, growth of biofilms, and collective cell motion in monolayers and tissues. We will implement the deformable particle model in hands-on exercises and present the latest results on the mechanical, vibrational, and dynamical properties of collections of deformable particles. In addition, we will show that when active forces are added to the DPM, it can be used to describe biological processes such as embryogenesis and cancer invasion. We believe that researchers in the soft matter and biological physics communities will benefit from learning state-of-the-art tools for modeling collections of thermal and active deformable particles.

Who Should Attend?

Graduate students and postdoctoral research associates in GSNP, DSOFT, and DBIO should attend this course.

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