1. Advances in Methods for Bridging Spatiotemporal Scales in Soft Matter, Polymer and Network Materials
  2. Bridging scales in the microstructure modeling of nuclear materials
  3. Computer modeling of laser and ion beam interactions with materials
  4. Contact, Friction, Adhesion: Mechanics of Interfaces across Scales
  5. Data-driven and physics-informed multiscale materials modelling
  6. Defects and Microstructure Complexity in Materials: Experiments and Multiscale Modeling
  7. Dislocation Glide, Deformation Twinning, Phase Transition, Phonon Transport, and Their Interactions in Heterogeneous Materials
  8. Fatigue and Fracture of Materials: from Micro to Macroscale Modeling and Experimentation
  9. Integrated Multiscale/Multiphysics Modeling of Structural Materials
  10. Interface-driven Phenomena in Condensed Matter Systems: Thermodynamics, Kinetics, and Chemistry
  11. Materials for microelectronics: manufacturing process, implantation and reliability, from atomic scale to industrial design.
  12. Mechanics and Physics of Defects in Crystals: A Symposium in Honor of Professor Nasr Ghoniem
  13. Mechanics and Physics of Material Failure
  14. Metals at the nanoscale and metals-based nanoparticles: environmental, mechanical and kinetic properties
  15. Modeling and Design of Architected Materials
  16. Modeling and Experimental Measurements for Metal Additive Manufacturing
  17. Multiscale and Multifield Modeling of Composites: from Atomic to Continuum Scale
  18. Multiscale Materials Modeling using Ab-initio Accuracy Methods
  19. Multiscale Mechanics of Fibrous Materials
  20. Multiscale Modeling of Battery Materials
  21. Multiscale Modeling of Glasses and Structurally Disordered Materials
  22. Multiscale Modeling of Polymers and Soft Materials
  23. Multiscale Solidification Modeling
  24. Scale Bridging in Materials Science
  25. Stochastic methods in materials simulation
  26. Strategic Materials Across Scales (SMAS): experimental and simulation approaches for bridging length and time scales
  27. Uncertainty Quantification, Sensitivity Analysis, and Machine Learning in Materials Modeling