Prevalence of multistability and nonstationarity in driven chemical networks

Abstract

External flows of energy, entropy, and matter can cause sudden transitions in the stability of biological and industrial systems, fundamentally altering their dynamical function. How might we control and design these transitions in chemical reaction networks? Here, we analyze transitions giving rise to complex behavior in random reaction networks subject to external driving forces. In the absence of driving, we characterize the uniqueness of the steady state and identify the percolation of a giant connected component in these networks as the number of reactions increases. When subject to chemical driving (influx and outflux of chemical species), the steady state can undergo bifurcations, leading to multistability or oscillatory dynamics. By quantifying the prevalence of these bifurcations, we show how chemical driving and network sparsity tend to promote the emergence of these complex dynamics and increased rates of entropy production. We show that catalysis also plays an important role in the emergence of complexity, strongly correlating with the prevalence of bifurcations. Our results suggest that coupling a minimal number of chemical signatures with external driving can lead to features present in biochemical processes and abiogenesis.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 08, 2023
Source ID
10.1063/5.0142589

Entities

People

  • Adilson E. Motter
  • Jason R Green
  • Schuyler B. Nicholson
  • Zachary Nicolaou

Organizations

  • Army Research Office
  • John Templeton Foundation
  • National Science Foundation
  • Northwestern University
  • University of Massachusetts
  • University of Washington

Tags

Fields of Study

  • Biology

Readers

  • Combustion science or combustion engineering.
  • Control Systems Engineering.
  • Neural Network Machine Learning.