Emmit Pert

All Publications

• Scaling Field-Theoretic Simulation for Multicomponent Mixtures with Neural Operators. Journal of chemical theory and computation Pert, E. K., Batton, C. H., Li, X., Dunne, S., Rotskoff, G. M. 2025

  Abstract

  Multicomponent polymer mixtures are ubiquitous in biological self-organization but are notoriously difficult to study computationally. Plagued by both slow single molecule relaxation times and slow equilibration within dense mixtures, molecular dynamics simulations are typically infeasible at the spatial scales required to study the stability of mesophase structure. Polymer field theories offer an attractive alternative, but analytical calculations are only tractable for mean-field theories and nearby perturbations, constraints that become especially problematic for fluctuation-induced effects such as coacervation. Here, we show that a recently developed technique for obtaining numerical solutions to partial differential equations based on operator learning, neural operators, lends itself to a highly scalable training strategy by parallelizing per-species operator maps. We illustrate the efficacy of our approach on six-component mixtures with randomly selected compositions and that it significantly outperforms the state-of-the-art pseudospectral integrators for field-theoretic simulations, especially as polymer lengths become long.

  View details for DOI 10.1021/acs.jctc.5c00102

  View details for PubMedID 40168529

• Coacervation drives morphological diversity of mRNA encapsulating nanoparticles. The Journal of chemical physics Pert, E. K., Hurst, P. J., Waymouth, R. M., Rotskoff, G. M. 2025; 162 (7)

  Abstract

  The spatial arrangement of components within an mRNA encapsulating nanoparticle has consequences for its thermal stability, which is a key parameter for therapeutic utility. The mesostructure of mRNA nanoparticles formed with cationic polymers has several distinct putative structures: here, we develop a field theoretic simulation model to compute the phase diagram for amphiphilic block copolymers that balance coacervation and hydrophobicity as driving forces for assembly. We predict several distinct morphologies for the mesostructure of these nanoparticles, depending on salt conditions and hydrophobicity. We compare our predictions with cryogenic-electron microscopy images of mRNA encapsulated by charge altering releasable transporters. In addition, we provide a graphics processing unit-accelerated, open-source codebase for general purpose field theoretic simulations, which we anticipate will be a useful tool for the community.

  View details for DOI 10.1063/5.0235799

  View details for PubMedID 39968821