Published August 24, 2017 | Version public
Book Section - Chapter

Thermodynamic Binding Networks

  • 1. ROR icon University of California, Davis
  • 2. ROR icon University of Arkansas at Fayetteville
  • 3. ROR icon The University of Texas at Austin
  • 4. ROR icon California Institute of Technology
  • 5. ROR icon French Institute for Research in Computer Science and Automation

Contributors

Abstract

Strand displacement and tile assembly systems are designed to follow prescribed kinetic rules (i.e., exhibit a specific time-evolution). However, the expected behavior in the limit of infinite time—known as thermodynamic equilibrium—is often incompatible with the desired computation. Basic physical chemistry implicates this inconsistency as a source of unavoidable error. Can the thermodynamic equilibrium be made consistent with the desired computational pathway? In order to formally study this question, we introduce a new model of molecular computing in which computation is driven by the thermodynamic driving forces of enthalpy and entropy. To ensure greatest generality we do not assume that there are any constraints imposed by geometry and treat monomers as unstructured collections of binding sites. In this model we design Boolean AND/OR formulas, as well as a self-assembling binary counter, where the thermodynamically favored states are exactly the desired final output configurations. Though inspired by DNA nanotechnology, the model is sufficiently general to apply to a wide variety of chemical systems.

Additional Information

© Springer International Publishing AG 2017. First Online: 24 August 2017. D. Doty—Supported by NSF grant CCF-1619343. T.A. Rogers—Supported by the NSF Graduate Research Fellowship Program under Grant No. DGE-1450079, NSF Grant CAREER-1553166, and NSF Grant CCF-1422152. D. Soloveichik—Supported by NSF grants CCF-1618895 and CCF-1652824. C. Thachuk—Supported by NSF grant CCF-1317694. D. Woods—Part of this work was carried out at California Institute of Technology. Supported by Inria (France) as well as National Science Foundation (USA) grants CCF-1219274, CCF-1162589, CCF-1317694.

Additional details

Identifiers

Eprint ID
91148
Resolver ID
CaltechAUTHORS:20181126-082746938

Funding

NSF
CCF-1619343
NSF Graduate Research Fellowship
DGE-1450079
NSF
CCF-1553166
NSF
CCF-1422152
NSF
CCF-1618895
NSF
CCF-1652824
NSF
CCF-1317694
Institut national de recherche en informatique et en automatique (INRIA)
NSF
CCF-1219274
NSF
CCF-1162589

Dates

Created
2018-11-26
Created from EPrint's datestamp field
Updated
2021-11-16
Created from EPrint's last_modified field

Caltech Custom Metadata

Series Name
Lecture Notes in Computer Science
Series Volume or Issue Number
10467