GN7                         My Program 


Self-assemblies, Gels and Networks


Role of non-central forces on the structure and mechanics of colloidal gels


October 20, 2025 (Monday) 1:30


Track 2 / Sweeney Ballroom B

(Click on name to view author profile)

  1. Haghighi, Paniz (Northeastern University, Mechanical and Industrial Engineering)
  2. Jamali, Safa (Northeastern University, Mechanical and Industrial Engineering)

(in printed abstract book)
Paniz Haghighi and Safa Jamali
Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115


Haghighi, Paniz


theoretical methods; computational methods; colloids; gels; methods; networks; non-Newtonian fluids; particualte systems


Colloidal gels, known for their rich rheological features and broad applicability, have been extensively studied both experimentally and through simulations. Generally, the space-spanning network formed by physical bonds between individual colloids governs the mechanics of colloidal gels. As a result, topological changes of this particulate network directly influence the rheology and mechanics of the colloidal gel. On the other hand, meso- and macro-scale features of the network are direct results of interactions at the microscopic level. Beyond the strength of range of interparticle attraction, additional characteristics such as surface roughness, uneven charge distribution, or the presence of surface-bound polymers introduce geometric and energetic constraints that influence how and where bonds form. In this study, we investigate the extent to which particle connections in colloidal gels are truly random, and how built-in physical constraints influence the formation and architecture of the network. Specifically, we introduce a methodology that limits connectivity through bending rigidity, but without prescribing the number or angles of bonds that form. Although computationally expensive, this approach captures the disordered yet non-arbitrary nature of gel networks, offering a more realistic representation of interparticle forces. Our results demonstrate that this method not only improves the accuracy of network characterization but also reveals how different gel morphologies arise from the interplay of microscopic interactions and kinetic assembly processes.