Multifunctional sequence-defined macromolecules for chemical data storage

Steven Martens, Annelies Landuyt, Pieter Espeel, Bart Devreese, Peter Dawyndt and Filip Du Prez ()
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Steven Martens: Ghent University
Annelies Landuyt: Ghent University
Pieter Espeel: Ghent University
Bart Devreese: Ghent University
Peter Dawyndt: Ghent University
Filip Du Prez: Ghent University

Nature Communications, 2018, vol. 9, issue 1, 1-8

Abstract: Abstract Sequence-defined macromolecules consist of a defined chain length (single mass), end-groups, composition and topology and prove promising in application fields such as anti-counterfeiting, biological mimicking and data storage. Here we show the potential use of multifunctional sequence-defined macromolecules as a storage medium. As a proof-of-principle, we describe how short text fragments (human-readable data) and QR codes (machine-readable data) are encoded as a collection of oligomers and how the original data can be reconstructed. The amide-urethane containing oligomers are generated using an automated protecting-group free, two-step iterative protocol based on thiolactone chemistry. Tandem mass spectrometry techniques have been explored to provide detailed analysis of the oligomer sequences. We have developed the generic software tools Chemcoder for encoding/decoding binary data as a collection of multifunctional macromolecules and Chemreader for reconstructing oligomer sequences from mass spectra to automate the process of chemical writing and reading.

Date: 2018
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DOI: 10.1038/s41467-018-06926-3

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