A programmable chemical computer with memory and pattern recognition

Cronin, Leroy; Gutiérrez, Juan Manuel; Tsuda, Soichiro; Sharma, Alpana; Cooper, Geoffrey; Aragon-Camarasa, Gerardo; Donkers, Kevin

doi:10.26434/chemrxiv.7712564.v1

Cited by 3 publications

(2 citation statements)

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“…Chemical reactions are fundamentally slow, so when it isn't possible to take advantage of parallel processing chemical computers can't keep pace. Extracting answers from chemical computers can also be difficult, since measuring results visually requires the addition of indicator chemicals that may be slow or unreliable [13]. The major hurdle, however, is the difficulty of programming chemical computers with useful or lengthy instructions, as the molecules required to do this may be unstable or hard to synthesize.…”

Section: Disadvantagesmentioning

confidence: 99%

Alternative Paradigms of Computation

Gasarch¹,

Hayes²,

Kaplitz³

et al. 2021

Preprint

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Section: Disadvantagesmentioning

confidence: 99%

Alternative Paradigms of Computation

Gasarch¹,

Hayes²,

Kaplitz³

et al. 2021

Preprint

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show abstract

“…Proposals for computers that exploit chemical processes have taken one or both of two broad approaches: 1) using chemistry and biochemistry to emulate circuit components or cellular automata, and 2) employing a large number of molecules to explore a combinatorial space in parallel. Examples for the first include reaction-diffusion systems (7), Belousov-Zhabotinsky oscillatory reaction (8), memristive polymers (9), and transcription regulation for cellular signaling (10,11), and other chemical and biochemical analogues of logic gates (12,13). In the second category of parallelized computing, we find microfluidic devices (14), nanofabricated networks (15)(16)(17), and adaptive amoebal networks (18).…”

Section: Introductionmentioning

confidence: 99%

A Molecular Computing Approach to Solving Optimization Problems via Programmable Microdroplet Arrays

Guo¹,

Friederich²,

Cao³

et al. 2019

Preprint

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The search for novel forms of computing that show advantages as alternatives to the dominant von-Neuman model-based computing is important as it will enable different classes of problems to be solved. By using droplets and room-temperature processes, molecular computing is a promising research direction with potential biocompatibility and cost advantages. In this work, we present a new approach for computation using a network of chemical reactions taking place within an array of spatially localized droplets whose contents represent bits of information. Combinatorial optimization problems are mapped to an Ising Hamiltonian and encoded in the form of intra- and inter- droplet interactions. The problem is solved by initiating the chemical reactions within the droplets and allowing the system to reach a steady-state; in effect, we are annealing the effective spin system to its ground state. We propose two implementations of the idea, which we ordered in terms of increasing complexity. First, we introduce a hybrid classical-molecular computer where droplet properties are measured and fed into a classical computer. Based on the given optimization problem, the classical computer then directs further reactions via optical or electrochemical inputs. A simulated model of the hybrid classical-molecular computer is used to solve boolean satisfiability and a lattice protein model. Second, we propose architectures for purely molecular computers that rely on pre-programmed nearest-neighbour inter-droplet communication via energy or mass transfer.

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