TY - JOUR

T1 - Thermodynamic stabilityversuskinetic accessibility

T2 - Pareto fronts for programmable self-assembly

AU - Trubiano, Anthony

AU - Holmes-Cerfon, Miranda

N1 - Funding Information:
The authors are grateful to Eric Vanden-Eijnden for introducing them to this problem. This work was supported by the Research Training Group in Modeling and Simulation funded by the National Science Foundation via grant RTG/DMS – 1646339, and by the United States Department of Energy under Award no. DE-SC0012296. M. H.-C. acknowledges support from the Alfred P. Sloan Foundation.
Funding Information:
The authors are grateful to Eric Vanden-Eijnden for introducing them to this problem. This work was supported by the Research Training Group in Modeling and Simulation funded by the National Science Foundationviagrant RTG/DMS - 1646339, and by the United States Department of Energy under Award no. DE-SC0012296. M. H.-C. acknowledges support from the Alfred P. Sloan Foundation.
Publisher Copyright:
© The Royal Society of Chemistry 2021.

PY - 2021/7/28

Y1 - 2021/7/28

N2 - A challenge in designing self-assembling building blocks is to ensure the target state is both thermodynamically stable and kinetically accessible. These two objectives are known to be typically in competition, but it is not known how to simultaneously optimize them. We consider this problem through the lens of multi-objective optimization theory: we develop a genetic algorithm to compute the Pareto fronts characterizing the tradeoff between equilibrium probability and folding rate, for a model system of small polymers of colloids with tunable short-ranged interaction energies. We use a coarse-grained model for the particles' dynamics that allows us to efficiently search over parameters, for systems small enough to be enumerated. For most target states there is a tradeoff when the number of types of particles is small, with medium-weak bonds favouring fast folding, and strong bonds favouring high equilibrium probability. The tradeoff disappears when the number of particle types reaches a valuem*, that is usually much less than the total number of particles. This general approach of computing Pareto fronts allows one to identify the minimum number of design parameters to avoid a thermodynamic-kinetic tradeoff. However, we argue, by contrasting our coarse-grained model's predictions with those of Brownian dynamics simulations, that particles with short-ranged isotropic interactions should generically have a tradeoff, and avoiding it in larger systems will require orientation-dependent interactions.

AB - A challenge in designing self-assembling building blocks is to ensure the target state is both thermodynamically stable and kinetically accessible. These two objectives are known to be typically in competition, but it is not known how to simultaneously optimize them. We consider this problem through the lens of multi-objective optimization theory: we develop a genetic algorithm to compute the Pareto fronts characterizing the tradeoff between equilibrium probability and folding rate, for a model system of small polymers of colloids with tunable short-ranged interaction energies. We use a coarse-grained model for the particles' dynamics that allows us to efficiently search over parameters, for systems small enough to be enumerated. For most target states there is a tradeoff when the number of types of particles is small, with medium-weak bonds favouring fast folding, and strong bonds favouring high equilibrium probability. The tradeoff disappears when the number of particle types reaches a valuem*, that is usually much less than the total number of particles. This general approach of computing Pareto fronts allows one to identify the minimum number of design parameters to avoid a thermodynamic-kinetic tradeoff. However, we argue, by contrasting our coarse-grained model's predictions with those of Brownian dynamics simulations, that particles with short-ranged isotropic interactions should generically have a tradeoff, and avoiding it in larger systems will require orientation-dependent interactions.

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U2 - 10.1039/d1sm00681a

DO - 10.1039/d1sm00681a

M3 - Article

C2 - 34223604

AN - SCOPUS:85111123037

SN - 1744-683X

VL - 17

SP - 6797

EP - 6807

JO - Soft Matter

JF - Soft Matter

IS - 28

ER -