Ultralightweight Strain-Responsive 3D Graphene Network

In this study, we fabricated a three-dimensionally assembled architecture made of reduced graphene oxide (rGO) and utilized it as an ultralightweight strain gauge. Building units for the assembly were prepared over the multiscale starting from functionalized GO nanosheets at the nanoscale to microfluidically processed solid-shelled bubbles at the microscale. These GO solid bubbles were elaborately assembled into close-packed 3D structures over the centimeter scale and then reduced by thermal treatment. Thermally reduced rGO assembly of which the internal structure was spontaneously transformed into a closed-cellular structure such as the 3D rhombic dodecahedral honeycomb lattice during thermal reduction could manifest superior elasticity against a strain of 30% by virtue of the hierarchically interconnected network while securing a low density of about 10 mg/cm3 and mechanical robustness, which was then applied as a strain gauge. The strain gauge with a thermally reduced 3D rGO structure exhibited a gauge factor of around 4 and excellent mechanical durability over 250 cycles, suggesting a new pathway for implementing ultralightweight strain-sensitive materials

Surface Topography-Adaptive Robotic Superstructures for Biofilm Removal and Pathogen Detection on Human Teeth

The eradication of biofilms remains an unresolved challenge across disciplines. Furthermore, in biomedicine, the sampling of spatially heterogeneous biofilms is crucial for accurate pathogen detection and precise treatment of infection. However, current approaches are incapable of removing highly adhesive biostructures from topographically complex surfaces. To meet these needs, we demonstrate magnetic field-directed assembly of nanoparticles into surface topography-adaptive robotic superstructures (STARS) for precision-guided biofilm removal and diagnostic sampling. These structures extend or retract at multilength scales (micro-to-centimeter) to operate on opposing surfaces and rapidly adjust their shape, length, and stiffness to adapt and apply high-shear stress. STARS conform to complex surface topographies by entering angled grooves or extending into narrow crevices and “scrub” adherent biofilm with multiaxis motion while producing antibacterial reagents on-site. Furthermore, as the superstructure disrupts the biofilm, it captures bacterial, fungal, viral, and matrix components, allowing sample retrieval for multiplexed diagnostic analysis. We apply STARS using automated motion patterns to target complex three-dimensional geometries of ex vivo human teeth to retrieve biofilm samples with microscale precision, while providing “toothbrushing-like” and “flossing-like” action with antibacterial activity in real-time to achieve mechanochemical removal and multikingdom pathogen detection. This approach could lead to autonomous, multifunctional antibiofilm platforms to advance current oral care modalities and other fields contending with harmful biofilms on hard-to-reach surfaces

Ferumoxytol Nanoparticles Target Biofilms Causing Tooth Decay in the Human Mouth

Severe tooth decay has been associated with iron deficiency anemia that disproportionally burdens susceptible populations. Current modalities are insufficient in severe cases where pathogenic dental biofilms rapidly accumulate, requiring new antibiofilm approaches. Here, we show that ferumoxytol, a Food and Drug Administration-approved nanoparticle formulation for treating iron deficiency, exerts an alternative therapeutic activity via the catalytic activation of hydrogen peroxide, which targets bacterial pathogens in biofilms and suppresses tooth enamel decay in an intraoral human disease model. Data reveal the potent antimicrobial specificity of ferumoxytol iron oxide nanoparticles (FerIONP) against biofilms harboring Streptococcus mutans via preferential binding that promotes bacterial killing through in situ free-radical generation. Further analysis indicates that the targeting mechanism involves interactions of FerIONP with pathogen-specific glucan-binding proteins, which have a minimal effect on commensal streptococci. In addition, we demonstrate that FerIONP can detect pathogenic biofilms on natural teeth via a facile colorimetric reaction. Our findings provide clinical evidence and the theranostic potential of catalytic nanoparticles as a targeted anti-infective nanomedicine

Surface Topography-Adaptive Robotic Superstructures for Biofilm Removal and Pathogen Detection on Human Teeth

The eradication of biofilms remains an unresolved challenge across disciplines. Furthermore, in biomedicine, the sampling of spatially heterogeneous biofilms is crucial for accurate pathogen detection and precise treatment of infection. However, current approaches are incapable of removing highly adhesive biostructures from topographically complex surfaces. To meet these needs, we demonstrate magnetic field-directed assembly of nanoparticles into surface topography-adaptive robotic superstructures (STARS) for precision-guided biofilm removal and diagnostic sampling. These structures extend or retract at multilength scales (micro-to-centimeter) to operate on opposing surfaces and rapidly adjust their shape, length, and stiffness to adapt and apply high-shear stress. STARS conform to complex surface topographies by entering angled grooves or extending into narrow crevices and “scrub” adherent biofilm with multiaxis motion while producing antibacterial reagents on-site. Furthermore, as the superstructure disrupts the biofilm, it captures bacterial, fungal, viral, and matrix components, allowing sample retrieval for multiplexed diagnostic analysis. We apply STARS using automated motion patterns to target complex three-dimensional geometries of ex vivo human teeth to retrieve biofilm samples with microscale precision, while providing “toothbrushing-like” and “flossing-like” action with antibacterial activity in real-time to achieve mechanochemical removal and multikingdom pathogen detection. This approach could lead to autonomous, multifunctional antibiofilm platforms to advance current oral care modalities and other fields contending with harmful biofilms on hard-to-reach surfaces

Surface Topography-Adaptive Robotic Superstructures for Biofilm Removal and Pathogen Detection on Human Teeth

The eradication of biofilms remains an unresolved challenge across disciplines. Furthermore, in biomedicine, the sampling of spatially heterogeneous biofilms is crucial for accurate pathogen detection and precise treatment of infection. However, current approaches are incapable of removing highly adhesive biostructures from topographically complex surfaces. To meet these needs, we demonstrate magnetic field-directed assembly of nanoparticles into surface topography-adaptive robotic superstructures (STARS) for precision-guided biofilm removal and diagnostic sampling. These structures extend or retract at multilength scales (micro-to-centimeter) to operate on opposing surfaces and rapidly adjust their shape, length, and stiffness to adapt and apply high-shear stress. STARS conform to complex surface topographies by entering angled grooves or extending into narrow crevices and “scrub” adherent biofilm with multiaxis motion while producing antibacterial reagents on-site. Furthermore, as the superstructure disrupts the biofilm, it captures bacterial, fungal, viral, and matrix components, allowing sample retrieval for multiplexed diagnostic analysis. We apply STARS using automated motion patterns to target complex three-dimensional geometries of ex vivo human teeth to retrieve biofilm samples with microscale precision, while providing “toothbrushing-like” and “flossing-like” action with antibacterial activity in real-time to achieve mechanochemical removal and multikingdom pathogen detection. This approach could lead to autonomous, multifunctional antibiofilm platforms to advance current oral care modalities and other fields contending with harmful biofilms on hard-to-reach surfaces

Surface Topography-Adaptive Robotic Superstructures for Biofilm Removal and Pathogen Detection on Human Teeth

The eradication of biofilms remains an unresolved challenge across disciplines. Furthermore, in biomedicine, the sampling of spatially heterogeneous biofilms is crucial for accurate pathogen detection and precise treatment of infection. However, current approaches are incapable of removing highly adhesive biostructures from topographically complex surfaces. To meet these needs, we demonstrate magnetic field-directed assembly of nanoparticles into surface topography-adaptive robotic superstructures (STARS) for precision-guided biofilm removal and diagnostic sampling. These structures extend or retract at multilength scales (micro-to-centimeter) to operate on opposing surfaces and rapidly adjust their shape, length, and stiffness to adapt and apply high-shear stress. STARS conform to complex surface topographies by entering angled grooves or extending into narrow crevices and “scrub” adherent biofilm with multiaxis motion while producing antibacterial reagents on-site. Furthermore, as the superstructure disrupts the biofilm, it captures bacterial, fungal, viral, and matrix components, allowing sample retrieval for multiplexed diagnostic analysis. We apply STARS using automated motion patterns to target complex three-dimensional geometries of ex vivo human teeth to retrieve biofilm samples with microscale precision, while providing “toothbrushing-like” and “flossing-like” action with antibacterial activity in real-time to achieve mechanochemical removal and multikingdom pathogen detection. This approach could lead to autonomous, multifunctional antibiofilm platforms to advance current oral care modalities and other fields contending with harmful biofilms on hard-to-reach surfaces

Ag Nanoparticle/Polydopamine-Coated Inverse Opals as Highly Efficient Catalytic Membranes

Polymeric three-dimensional inverse-opal (IO) structures provide unique structural properties useful for various applications ranging from optics to separation technologies. Despite vast needs for IO functionalization to impart additional chemical properties, this task has been seriously challenged by the intrinsic limitation of polymeric porous materials that do not allow for the easy penetration of waterborne moieties or precursors. To overcome this restriction, we present a robust and straightforward method of employing a dipping-based surface modification with polydopamine (PDA) inside the IO structures, and demonstrate their application to catalytic membranes via synthetic incorporation of Ag nanoparticles. The PDA coating offers simultaneous advantages of achieving the improved hydrophilicity required for the facilitated infiltration of aqueous precursors and successful creation of nucleation sites for a reduction of growth of the Ag nanoparticles. The resulting Ag nanoparticle-incorporated IO structures are utilized as catalytic membranes for the reduction of 4-nitrophenol to its amino derivatives in the presence of NaBH₄. Synergistically combined characteristics of high reactivity of Ag nanoparticles along with a greatly enhanced internal surface area of IO structures enable the implementation of remarkably improved catalytic performance, exhibiting a good conversion efficiency greater than 99% while minimizing loss in the membrane permeability

Surface Topography-Adaptive Robotic Superstructures for Biofilm Removal and Pathogen Detection on Human Teeth

The eradication of biofilms remains an unresolved challenge across disciplines. Furthermore, in biomedicine, the sampling of spatially heterogeneous biofilms is crucial for accurate pathogen detection and precise treatment of infection. However, current approaches are incapable of removing highly adhesive biostructures from topographically complex surfaces. To meet these needs, we demonstrate magnetic field-directed assembly of nanoparticles into surface topography-adaptive robotic superstructures (STARS) for precision-guided biofilm removal and diagnostic sampling. These structures extend or retract at multilength scales (micro-to-centimeter) to operate on opposing surfaces and rapidly adjust their shape, length, and stiffness to adapt and apply high-shear stress. STARS conform to complex surface topographies by entering angled grooves or extending into narrow crevices and “scrub” adherent biofilm with multiaxis motion while producing antibacterial reagents on-site. Furthermore, as the superstructure disrupts the biofilm, it captures bacterial, fungal, viral, and matrix components, allowing sample retrieval for multiplexed diagnostic analysis. We apply STARS using automated motion patterns to target complex three-dimensional geometries of ex vivo human teeth to retrieve biofilm samples with microscale precision, while providing “toothbrushing-like” and “flossing-like” action with antibacterial activity in real-time to achieve mechanochemical removal and multikingdom pathogen detection. This approach could lead to autonomous, multifunctional antibiofilm platforms to advance current oral care modalities and other fields contending with harmful biofilms on hard-to-reach surfaces

Surface Topography-Adaptive Robotic Superstructures for Biofilm Removal and Pathogen Detection on Human Teeth

The eradication of biofilms remains an unresolved challenge across disciplines. Furthermore, in biomedicine, the sampling of spatially heterogeneous biofilms is crucial for accurate pathogen detection and precise treatment of infection. However, current approaches are incapable of removing highly adhesive biostructures from topographically complex surfaces. To meet these needs, we demonstrate magnetic field-directed assembly of nanoparticles into surface topography-adaptive robotic superstructures (STARS) for precision-guided biofilm removal and diagnostic sampling. These structures extend or retract at multilength scales (micro-to-centimeter) to operate on opposing surfaces and rapidly adjust their shape, length, and stiffness to adapt and apply high-shear stress. STARS conform to complex surface topographies by entering angled grooves or extending into narrow crevices and “scrub” adherent biofilm with multiaxis motion while producing antibacterial reagents on-site. Furthermore, as the superstructure disrupts the biofilm, it captures bacterial, fungal, viral, and matrix components, allowing sample retrieval for multiplexed diagnostic analysis. We apply STARS using automated motion patterns to target complex three-dimensional geometries of ex vivo human teeth to retrieve biofilm samples with microscale precision, while providing “toothbrushing-like” and “flossing-like” action with antibacterial activity in real-time to achieve mechanochemical removal and multikingdom pathogen detection. This approach could lead to autonomous, multifunctional antibiofilm platforms to advance current oral care modalities and other fields contending with harmful biofilms on hard-to-reach surfaces