Multifunctional sequence-defined macromolecules for chemical data storage

Steven Martens; Annelies Landuyt; Pieter Espeel; Bart Devreese; Peter Dawyndt; Filip Du Prez

doi:10.1038/s41467-018-06926-3

Nature Communications (Oct 2018)

Multifunctional sequence-defined macromolecules for chemical data storage

Steven Martens,
Annelies Landuyt,
Pieter Espeel,
Bart Devreese,
Peter Dawyndt,
Filip Du Prez

Affiliations

Steven Martens: Department of Organic and Macromolecular Chemistry, Polymer Chemistry Research Group, Centre of Macromolecular Chemistry (CMaC), Ghent University
Annelies Landuyt: Department of Organic and Macromolecular Chemistry, Polymer Chemistry Research Group, Centre of Macromolecular Chemistry (CMaC), Ghent University
Pieter Espeel: Department of Organic and Macromolecular Chemistry, Polymer Chemistry Research Group, Centre of Macromolecular Chemistry (CMaC), Ghent University
Bart Devreese: Department of Biochemistry and Microbiology, Laboratory for Protein Biochemistry and Biomolecular Engineering, Ghent University
Peter Dawyndt: Department of Applied Mathematics, Computer Science and Statistics, Ghent University
Filip Du Prez: Department of Organic and Macromolecular Chemistry, Polymer Chemistry Research Group, Centre of Macromolecular Chemistry (CMaC), Ghent University

DOI: https://doi.org/10.1038/s41467-018-06926-3
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 8

Abstract

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Sequence-defined macromolecules consist of a defined chain length and topology and can be used in applications such as antibiotics and data storage. Here the authors developed two algorithms to encode text fragments and QR codes as a collection of oligomers and to reconstruct the original data.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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