ArticleChemical science2021
Leveraging autocatalytic reactions for chemical domain image classification.
Article in Chemical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed.
- Soft Hardware, Flowing Software: Reconfigurable Microfluidics for Adaptable Chemical Computation.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Is stochastic thermodynamics the key to understanding the energy costs of computation?Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Asymmetric autocatalytic reactions and their stationary distribution.Royal Society open science · 2024Article
- Exploring the programmability of autocatalytic chemical reaction networks.Nature communications · 2024Article
- The Role of Experimental Noise in a Hybrid Classical-Molecular Computer to Solve Combinatorial Optimization Problems.ACS central science · 2023Article
- Digital circuits and neural networks based on acid-base chemistry implemented by robotic fluid handling.Nature communications · 2023Article
- A single layer artificial neural network type architecture with molecular engineered bacteria for reversible and irreversible computing.Chemical science · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Autocatalysis is fundamental to many biological processes, and kinetic models of autocatalytic reactions have mathematical forms similar to activation functions used in artificial neural networks. Inspired by these similarities, we use an autocatalytic reaction, the copper-catalyzed azide-alkyne cycloaddition, to perform digital image recognition tasks. Images are encoded in the concentration of a catalyst across an array of liquid samples, and the classification is performed with a sequence of automated fluid transfers. The outputs of the operations are monitored using UV-vis spectroscopy. The growing interest in molecular information storage suggests that methods for computing in chemistry will become increasingly important for querying and manipulating molecular memory.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.