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DNA polymerization gels are a new class of soft programmable materials capable of reversible 100-fold volumetric size changes induced by DNA-specific strand displacement reactions. By incorporating DNA circuits and spatial patterns, these gels could orchestrate complex, self-regulating processes of relevance to biosensing, robotics, and medicine. However, the ultrasoft nature of the gels and slow response times can limit applicability. We developed GO-DNA composite polymerization gels (CPGs) by blending DNA gels with graphene oxide (GO). Photopatterned ultra-thin GO-DNA CPG films, as thin as 8 μm, were achieved. Notably, GO-DNA CPGs exhibited similar rates of swelling but 60 times faster shrinking, suggesting that the introduction of inorganic nanoparticles could provide a means to tune the mechanical properties and swelling characteristics of DNA polymerization gels. 

The development of biomolecular stimuli-responsive hydrogels is important for biomimetic structures, soft robots, tissue engineering, and drug delivery. DNA polymerization gels are a new class of soft materials composed of polymer gel backbones with DNA duplex crosslinks that can be swollen by sequential strand displacement using hairpin-shaped DNA strands. The extensive swelling can be tuned using physical parameters such as salt concentration and biomolecule design. Previously, DNA polymerization gels have been used to create shape-changing gel automata with a large design space and high programmability. Here we systematically investigate how the swelling response of DNA polymerization gels can be tuned by adjusting the design and concentration of DNA crosslinks in the hydrogels or DNA hairpin triggers, and the ionic strength of the solution in which swelling takes place. We also explore the effect hydrogel size and shape have on the swelling response. Tuning these variables can alter the swelling rate and extent across a broad range and provide a quantitative connection between biochemical reactions and macroscopic material behaviour. 

The geometry of multisegmented thermo-responsive gel robots was manipulated to break symmetry and support locomotion. 

Widespread testing and isolation of infected patients is a cornerstone of viral outbreak management, as underscored during the ongoing COVID-19 pandemic. Here, we report a large-area and label-free testing platform that combines surface-enhanced Raman spectroscopy and machine learning for the rapid and accurate detection of SARS-CoV-2. Spectroscopic signatures acquired from virus samples on metal–insulator–metal nanostructures, fabricated using nanoimprint lithography and transfer printing, can provide test results within 25 min. Not only can our technique accurately distinguish between different respiratory and nonrespiratory viruses, but it can also detect virus signatures in physiologically relevant matrices such as human saliva without any additional sample preparation. Furthermore, our large area nanopatterning approach allows sensors to be fabricated on flexible surfaces allowing them to be mounted on any surface or used as wearables. We envision that our versatile and portable label-free spectroscopic platform will offer an important tool for virus detection and future outbreak preparedness.