A framework for modeling and inferring tracer diffusion in crowded environments

Fuente: arXiv
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Autori principali: Lee, Jinseok, Lin, Tong, Gu, Mengyang, Luo, Yimin
Natura: Preprint
Pubblicazione: 2026
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author Lee, Jinseok
Lin, Tong
Gu, Mengyang
Luo, Yimin
author_facet Lee, Jinseok
Lin, Tong
Gu, Mengyang
Luo, Yimin
contents Tracer diffusion in crowded environments is central to many biological and soft matter systems, but quantitative frameworks for linking tracer motion to environmental structure remain limited. Here, we study the transport of rigid tracers in suspensions of soft particles and within living cells. Experiments reveal a transition from diffusive to confined motion as the matrix area fraction increases. We develop a minimal simulation that incorporates steric exclusion and hydrodynamic hindrance to reproduce the observed mean-squared displacements (MSDs). Using simulation outputs, we train a parallel partial Gaussian process (PPGP) model that rapidly predicts MSDs from matrix geometric variables, including area fraction, particle size, and polydispersity. The PPGP model accelerates predictions by several orders of magnitude relative to simulation and experiments. Analysis reveals that tracer transport is primarily governed by accessible pore sizes and that distinct global structures can produce indistinguishable MSDs. We find that the minimal model can also capture the MSDs of internalized tracer particles in cells. The framework enables rapid inference of structural properties in crowded environments, including transport in the intracellular environment.
format Preprint
id arxiv_https___arxiv_org_abs_2605_04216
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A framework for modeling and inferring tracer diffusion in crowded environments
Lee, Jinseok
Lin, Tong
Gu, Mengyang
Luo, Yimin
Soft Condensed Matter
Biological Physics
Tracer diffusion in crowded environments is central to many biological and soft matter systems, but quantitative frameworks for linking tracer motion to environmental structure remain limited. Here, we study the transport of rigid tracers in suspensions of soft particles and within living cells. Experiments reveal a transition from diffusive to confined motion as the matrix area fraction increases. We develop a minimal simulation that incorporates steric exclusion and hydrodynamic hindrance to reproduce the observed mean-squared displacements (MSDs). Using simulation outputs, we train a parallel partial Gaussian process (PPGP) model that rapidly predicts MSDs from matrix geometric variables, including area fraction, particle size, and polydispersity. The PPGP model accelerates predictions by several orders of magnitude relative to simulation and experiments. Analysis reveals that tracer transport is primarily governed by accessible pore sizes and that distinct global structures can produce indistinguishable MSDs. We find that the minimal model can also capture the MSDs of internalized tracer particles in cells. The framework enables rapid inference of structural properties in crowded environments, including transport in the intracellular environment.
title A framework for modeling and inferring tracer diffusion in crowded environments
topic Soft Condensed Matter
Biological Physics
url https://arxiv.org/abs/2605.04216