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A supramolecular aggregation-based constitutional dynamic network for information processing
Concepts and strategies offered by constitutional dynamic chemistry (CDC) hold great promise for designing molecular computing systems adaptive to external environments. Despite demonstrable success in storing and processing chemical information using CDC, further employment of such constitutional d...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161677/ https://www.ncbi.nlm.nih.gov/pubmed/34094228 http://dx.doi.org/10.1039/d0sc03392h |
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author | Lin, Xiao Yang, Shu Huang, Dan Guo, Chen Chen, Die Yang, Qianfan Li, Feng |
author_facet | Lin, Xiao Yang, Shu Huang, Dan Guo, Chen Chen, Die Yang, Qianfan Li, Feng |
author_sort | Lin, Xiao |
collection | PubMed |
description | Concepts and strategies offered by constitutional dynamic chemistry (CDC) hold great promise for designing molecular computing systems adaptive to external environments. Despite demonstrable success in storing and processing chemical information using CDC, further employment of such constitutional dynamic networks (CDNs) for processing more complex digital information has not been realized yet. Herein, we introduced a supramolecular CDN based on the aggregation of cyanine MTC (Agg-CDN), which is composed of four reversibly interconvertible constituents, i.e. monomers, dimers, J-aggregates, and H-aggregates. We demonstrated that the equilibrated Agg-CDN is reconfigurable through constituent exchange in response to well-defined chemical inputs. More importantly, the equilibrated states of the Agg-CDN are spectroscopically distinguishable because of the unique optical properties of MTC. We further tuned the Agg-CDN to at least nine unique states for transforming the chemical inputs into digital outputs, and successfully employed it for encoding and encrypting complex digital information, such as multi-pixel images. |
format | Online Article Text |
id | pubmed-8161677 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-81616772021-06-04 A supramolecular aggregation-based constitutional dynamic network for information processing Lin, Xiao Yang, Shu Huang, Dan Guo, Chen Chen, Die Yang, Qianfan Li, Feng Chem Sci Chemistry Concepts and strategies offered by constitutional dynamic chemistry (CDC) hold great promise for designing molecular computing systems adaptive to external environments. Despite demonstrable success in storing and processing chemical information using CDC, further employment of such constitutional dynamic networks (CDNs) for processing more complex digital information has not been realized yet. Herein, we introduced a supramolecular CDN based on the aggregation of cyanine MTC (Agg-CDN), which is composed of four reversibly interconvertible constituents, i.e. monomers, dimers, J-aggregates, and H-aggregates. We demonstrated that the equilibrated Agg-CDN is reconfigurable through constituent exchange in response to well-defined chemical inputs. More importantly, the equilibrated states of the Agg-CDN are spectroscopically distinguishable because of the unique optical properties of MTC. We further tuned the Agg-CDN to at least nine unique states for transforming the chemical inputs into digital outputs, and successfully employed it for encoding and encrypting complex digital information, such as multi-pixel images. The Royal Society of Chemistry 2020-08-21 /pmc/articles/PMC8161677/ /pubmed/34094228 http://dx.doi.org/10.1039/d0sc03392h Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Lin, Xiao Yang, Shu Huang, Dan Guo, Chen Chen, Die Yang, Qianfan Li, Feng A supramolecular aggregation-based constitutional dynamic network for information processing |
title | A supramolecular aggregation-based constitutional dynamic network for information processing |
title_full | A supramolecular aggregation-based constitutional dynamic network for information processing |
title_fullStr | A supramolecular aggregation-based constitutional dynamic network for information processing |
title_full_unstemmed | A supramolecular aggregation-based constitutional dynamic network for information processing |
title_short | A supramolecular aggregation-based constitutional dynamic network for information processing |
title_sort | supramolecular aggregation-based constitutional dynamic network for information processing |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161677/ https://www.ncbi.nlm.nih.gov/pubmed/34094228 http://dx.doi.org/10.1039/d0sc03392h |
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