Triggering the Selective Reading of Sequence-Defined Oligourethanes: An Example Using Computer Scripts, Representing the Next Step in Chemical Logic Gates

Over the past decades, various types of sequence-defined polymers (SDPs) have been explored for use in information storage. However, unlike conventional digital systems, abiotic SDPs commonly lack a means for selective data retrieval. Here, we introduce a set of orthogonally protected linkers that function as molecular logic gates when integrated with sequence-defined oligourethanes (OUs). These linkers enable selective "reading" of specific OUs in response to distinct chemical triggers. Beyond demonstrating selective retrieval, our platform allows OUs to encode executable computer instructions, such as matrix multiplication in Python, thereby interfacing chemical specificity with digital computation. Different chemical triggers yield different computational outputs, illustrating that chemical inputs can control which Python code is run. This work establishes a new paradigm for chemically addressable molecular data storage and its extension toward digital computation.

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Publication Details

Journal
Journal of the American Chemical Society
Published
2026-03-24
DOI
https://doi.org/10.1021/jacs.5c21819
Primary Topic
Supramolecular Chemistry and Complexes
Type
article
Field-Weighted Citation Impact
0.00
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article

Triggering the Selective Reading of Sequence-Defined Oligourethanes: An Example Using Computer Scripts, Representing the Next Step in Chemical Logic Gates

Journal of the American Chemical Society
Supramolecular Chemistry and Complexes
article

Triggering the Selective Reading of Sequence-Defined Oligourethanes: An Example Using Computer Scripts, Representing the Next Step in Chemical Logic Gates

article en

Abstract

Over the past decades, various types of sequence-defined polymers (SDPs) have been explored for use in information storage. However, unlike conventional digital systems, abiotic SDPs commonly lack a means for selective data retrieval. Here, we introduce a set of orthogonally protected linkers that function as molecular logic gates when integrated with sequence-defined oligourethanes (OUs). These linkers enable selective "reading" of specific OUs in response to distinct chemical triggers. Beyond demonstrating selective retrieval, our platform allows OUs to encode executable computer instructions, such as matrix multiplication in Python, thereby interfacing chemical specificity with digital computation. Different chemical triggers yield different computational outputs, illustrating that chemical inputs can control which Python code is run. This work establishes a new paradigm for chemically addressable molecular data storage and its extension toward digital computation.

Journal of the American Chemical Society
The University of Texas at Austin (US)
Quality Education
Openalex Percentile: Top 9%
Supramolecular Chemistry and Complexes
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