Spring-loaded DNA origami arrays as energy-supplied hardware for modular nanorobots

DNA origami nanorobots allow for the rational design of nanomachines that respond to environmental stimuli with preprogrammed tasks. To date, this mostly is achieved by constructing two-state switches that, upon activation, change their conformation, resulting in the performance of an operation. Their applicability is often limited to a single, specific stimulus-output combination because of their intrinsic properties as two-state systems only. This makes expanding them further challenging. Here, we addressed this limitation by introducing reconfigurable DNA origami arrays as networks of coupled two-state systems. This universal design strategy enables the integration of various operational units into any two-state system within the nanorobot, allowing it to process multiple stimuli, compute responses using multilevel Boolean logic, and execute a range of operations with controlled order, timing, and spatial position. We anticipate that this strategy will be instrumental in further developing DNA origami nanorobots for applications in various technological fields.

Authors

Institutions

Publication Details

Journal
Science Robotics
Published
2025-10-22
DOI
https://doi.org/10.1126/scirobotics.adu3679
Citations
2
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
1.61
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spring-loaded DNA origami arrays as energy-supplied hardware for modular nanorobots

Philip Tinnefeld, Yonggang Ke, Fiona Cole, Martina Pfeiffer et al.
2 citations
Science Robotics
Advanced biosensing and bioanalysis techniques
1.61
article

Spring-loaded DNA origami arrays as energy-supplied hardware for modular nanorobots

Philip Tinnefeld, Yonggang Ke, Fiona Cole, Martina Pfeiffer, Dongfang Wang
article en
2 citations

Abstract

DNA origami nanorobots allow for the rational design of nanomachines that respond to environmental stimuli with preprogrammed tasks. To date, this mostly is achieved by constructing two-state switches that, upon activation, change their conformation, resulting in the performance of an operation. Their applicability is often limited to a single, specific stimulus-output combination because of their intrinsic properties as two-state systems only. This makes expanding them further challenging. Here, we addressed this limitation by introducing reconfigurable DNA origami arrays as networks of coupled two-state systems. This universal design strategy enables the integration of various operational units into any two-state system within the nanorobot, allowing it to process multiple stimuli, compute responses using multilevel Boolean logic, and execute a range of operations with controlled order, timing, and spatial position. We anticipate that this strategy will be instrumental in further developing DNA origami nanorobots for applications in various technological fields.

Science RoboticsVol. 10(107)
University of Science and Technology of China (CN), Georgia Institute of Technology (US), Hefei University of Technology (CN), Center for NanoScience (DE), The Wallace H. Coulter Department of Biomedical Engineering (US), Suzhou University of Science and Technology (CN), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 14%
Advanced biosensing and bioanalysis techniques
1.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Spring-loaded DNA origami arrays as energy-supplied hardware for modular nanorobots — Philip Tinnefeld, Yonggang Ke, et al. · Science Robotics (2025) | TGRS Research Map | TGRS