Issue 15, 2022

A high-fidelity light-powered nanomotor from a chemically fueled counterpart via site-specific optomechanical fuel control

Abstract

Optically powered nanomotors are advantageous for clean nanotechnology over chemically fuelled nanomotors. The two motor types are further bounded by different physical principles. Despite the gap, we show here that an optically powered DNA bipedal nanomotor is readily created from a high-performing chemically fuelled counterpart by subjecting its fuel to cyclic site-specific optomechanical control – as if the fuel is optically recharged. Optimizing azobenzene-based control of the original nucleotide fuel selects a light-responsive fuel analog that replicates the different binding affinity of the fuel and reaction products. The resultant motor largely retains high-performing features of the original chemical motor, and achieves the highest directional fidelity among reported light-driven DNA nanomotors. This study thus demonstrates a novel strategy for transforming chemical nanomotors to optical ones for clean nanotechnology. The strategy is potentially applicable to many chemical nanomotors with oligomeric fuels like nucleotides, peptides and synthetic polymers, leading to a new class of light-powered nanomotors that are akin to chemical nanomotors and benefit from their generally high efficiency mechanistically. The motor from this study also provides a rare model system for studying the subtle boundary between chemical and optical nanomotors – a topic pertinent to chemomechanical and optomechanical energy conversion at the single-molecule level.

Graphical abstract: A high-fidelity light-powered nanomotor from a chemically fueled counterpart via site-specific optomechanical fuel control

Supplementary files

Article information

Article type
Paper
Submitted
04 Dec 2021
Accepted
28 Mar 2022
First published
30 Mar 2022

Nanoscale, 2022,14, 5899-5914

A high-fidelity light-powered nanomotor from a chemically fueled counterpart via site-specific optomechanical fuel control

X. R. Liu, X. Hu, I. Y. Loh and Z. Wang, Nanoscale, 2022, 14, 5899 DOI: 10.1039/D1NR07964F

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