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Published May 1, 2020 | Published
Journal Article Open

Programming and simulating chemical reaction networks on a surface

Abstract

Models of well-mixed chemical reaction networks (CRNs) have provided a solid foundation for the study of programmable molecular systems, but the importance of spatial organization in such systems has increasingly been recognized. In this paper, we explore an alternative chemical computing model introduced by Qian & Winfree in 2014, the surface CRN, which uses molecules attached to a surface such that each molecule only interacts with its immediate neighbours. Expanding on the constructions in that work, we first demonstrate that surface CRNs can emulate asynchronous and synchronous deterministic cellular automata and implement continuously active Boolean logic circuits. We introduce three new techniques for enforcing synchronization within local regions, each with a different trade-off in spatial and chemical complexity. We also demonstrate that surface CRNs can manufacture complex spatial patterns from simple initial conditions and implement interesting swarm robotic behaviours using simple local rules. Throughout all example constructions of surface CRNs, we highlight the trade-off between the ability to precisely place molecules and the ability to precisely control molecular interactions. Finally, we provide a Python simulator for surface CRNs with an easy-to-use web interface, so that readers may follow along with our examples or create their own su

Additional Information

© 2020 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. Manuscript received 23/11/2019; Manuscript accepted 30/04/2020; Published online 27/05/2020; Published in print 27/05/2020. The authors thank Philip F. Petersen, Matthew M. Cook, András Cook, Chigozie Nri, Adam Butler, Gokul Gowri, Wei Li, Robert F. Johnson, Stefan Badelt and Constantine G. Evans for discussion, feedback and encouragement. P.F.P. contributed several example surface CRN programs to the online simulator, and helped optimize the line-building example presented here. M.M.C. taught us about synchronization mechanisms for cellular automata. Kudos to molecular rugby team captains P.F.P., M.M.C., A.C., C.N., A.B., G.G., S.B., L.Q., S.C. and E.W. Data accessibility: Simulator code, including examples used in this paper, can be found in the 'paper-release' branch of the GitHub repository at https://github.com/sclamons/surface_crns, a fork of which is also available from the DNA and Natural Algorithms Group on GitHub (https://github.com/DNA-and-Natural-Algorithms-Group). A browser interface to the simulator is also available, along with examples from this paper and others, at http://www.dna.caltech.edu/Surface_CRN_Simulator/. Authors' contributions: S.C. wrote the simulation software and online interfaces used in this paper. L.Q. and E.W. conceived the study. All authors constructed examples and wrote and revised substantial portions of the manuscript. All authors gave final approval for publication and agree to be held accountable for the work performed therein. We declare we have no competing interests. This work was supported in part by NSF grant nos. CCF-1317694 to E.W. and L.Q., CCF-1813550 and CCF-1351081 to L.Q. S.C. was supported by the Human Frontiers Research Science Program and the Institute for Collaborative Biotechnologies through contract W911NF-19-D-0001 from the U.S. Army Research Office to Richard M. Murray.

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Created:
August 22, 2023
Modified:
December 22, 2023