Molecular computation at equilibrium via programmable entropy

Synthetic molecular information processing is typically designed through programming kinetic pathways, so that molecules bind, unbind, or incur conformational changes in some desired order. We demonstrate an alternative paradigm in dynamic DNA nanotechnology that programs the thermodynamic equilibrium state directly, with computation emerging from entropic driving forces. Like declarative programming in computer science, this approach emphasizes desired outcomes rather than specific steps, simplifying molecular programming and avoiding errors caused when thermodynamic forces work against programmed kinetics. We show broad applicability through three distinct applications: reversible signal propagation with fan-in and fan-out, algorithmic self-assembly performing Boolean logic, and synthesis of molecular chains (concatemers) of programmable length, illustrating how thermodynamic computation can enable practical molecular engineering tasks. Our work may enable previously unexplored ways to engineer complex molecular behaviors and help inform the understanding of the computational power of thermodynamics versus kinetics for molecular systems.

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Publication Details

Journal
Science Advances
Published
2026-01-09
DOI
https://doi.org/10.1126/sciadv.adx3969
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
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article

Molecular computation at equilibrium via programmable entropy

Boya Wang, Cameron Chalk, David Soloveichik, David Doty
Science Advances
Advanced biosensing and bioanalysis techniques
article

Molecular computation at equilibrium via programmable entropy

Boya Wang, Cameron Chalk, David Soloveichik, David Doty
article en

Abstract

Synthetic molecular information processing is typically designed through programming kinetic pathways, so that molecules bind, unbind, or incur conformational changes in some desired order. We demonstrate an alternative paradigm in dynamic DNA nanotechnology that programs the thermodynamic equilibrium state directly, with computation emerging from entropic driving forces. Like declarative programming in computer science, this approach emphasizes desired outcomes rather than specific steps, simplifying molecular programming and avoiding errors caused when thermodynamic forces work against programmed kinetics. We show broad applicability through three distinct applications: reversible signal propagation with fan-in and fan-out, algorithmic self-assembly performing Boolean logic, and synthesis of molecular chains (concatemers) of programmable length, illustrating how thermodynamic computation can enable practical molecular engineering tasks. Our work may enable previously unexplored ways to engineer complex molecular behaviors and help inform the understanding of the computational power of thermodynamics versus kinetics for molecular systems.

Science AdvancesVol. 12(2)
University of California, Davis (US), The University of Texas at Austin (US)
Openalex Percentile: Top 92%
Advanced biosensing and bioanalysis techniques
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Molecular computation at equilibrium via programmable entropy — Boya Wang, Cameron Chalk, et al. · Science Advances (2026) | TGRS Research Map | TGRS