Emergence of complexity in hierarchically organized chiral particles

Jiang, Wenfeng; Qu, Zhi‐bei; Kumar, Prashant; Vecchio, Drew; Wang, Yuefei; Ma, Yu; Bahng, Joong Hwan; Bernardino, Kalil; Gomes, Weverson R.; Colombari, Felippe Mariano; Lozada-Blanco, Asdrubal; Veksler, M. A.; Marino, Emanuele; Simon, Alex; Murray, Christopher B.; Muniz, Sérgio Ricardo; Moura, André Farias de; Kotov, Nicholas A.

doi:10.1126/science.aaz7949

Cited by 234 publications

(265 citation statements)

References 50 publications

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“…[ 13–20 ] This multiscale assembly of atomically precise ultrasmall particles provides a reliable platform for the bottom‐up construction of artificial functional materials across all scales, which is an intrinsic requirement for manifesting universal functionality in nature and life. [ 21–23 ] In addition, it also enables the assembly to have imposed stability, collective (and often synergistic) functionality, and expected processability, thereby increasing their acceptance in various fields of practical applications. [ 22 ]…”

Section: Figurementioning

confidence: 99%

Multiscale Assembly of [AgS₄] Tetrahedrons into Hierarchical Ag–S Networks for Robust Photonic Water

Yao

Liu

et al. 2021

Advanced Materials

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One of the latest developments in the field of materials science is the successful synthesis of ultrasmall particles with atomic precision, such as monolayer-protected metal clusters, metal chalcogenides, polyoxometalates, and polynuclear There is an urgent need to assemble ultrasmall metal chalcogenides (with atomic precision) into functional materials with the required anisotropy and uniformity, on a micro-or even macroscale. Here, a delicate yet simple chemistry is developed to produce a silver-sulfur network microplate with a high monodispersity in size and morphology. Spanning from the atomic, molecular, to nanometer, to micrometer scale, the key structural evolution of the obtained microplates includes 2D confinement growth, edge-sharing growth mode, and thermodynamically driven layer-by-layer stacking, all of which are derived from the [AgS 4 ] tetrahedron unit. The key to such a high hierarchical, complex, and accurate assembly is the dense deprotonated ligand layer on the surface of the microplates, forming an infinite surface with high negative charge density. This feature operates at an orderly distance to allow further hierarchical self-assembly on the microscale to generate columnar assemblies composed of microplate components, thereby endowing the feature of the 1D photonic reflector to water (i.e., photonic water). The reflective color of the resulting photonic water is highly dependent on the thickness of the building blocks (i.e., silver-sulfur microplates), and the coexistent order and fluidity help to form robust photonic water.

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Section: Figurementioning

confidence: 99%

Multiscale Assembly of [AgS₄] Tetrahedrons into Hierarchical Ag–S Networks for Robust Photonic Water

Yao

Liu

et al. 2021

Advanced Materials

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“…Note that GT descriptions of other materials, where inorganic nanoparticles (NPs) serve as nodes and edges are formed from the organic interfaces or filaments between them, ki = 2 can be quite common when describing the formation of NP chains. 54 The density (ρ) of a graph is a ratio of the number of edges in network to the number of Parameter Formula (n = # of nodes, e = # of edges, i = pertaining to node i)…”

Section: Gt Parameter Calculationmentioning

confidence: 99%

Automatic structural analysis of bioinspired percolating network materials using graph theory

Vecchio

Hammig

et al. 2021

Preprint

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Mimicking numerous biological membranes and nanofiber-based tissues, there are multiple materials that are structured as percolating nanoscale networks (PPNs). They reveal unique combination of properties and the family of PNN-based composites and nanoporous materials is rapidly expanding. Their technological significance requires a unifying approach for their structural description. However, their complex aperiodic architectures are difficult to describe using traditional methods that are tailored for crystals. A related problem is the lack of computational tools that enable one to capture and enumerate the patterns of stochastically branching fibrils that are typical for these composites. Here, we describe a conceptual methodology and a computational package, StructuralGT, to automatically produce a graph theoretical (GT) description of PNNs from various micrographs. Using nanoscale networks formed by aramid nanofibers (ANFs) as examples, we demonstrate structural analysis of PNNs with 13 GT parameters. Unlike qualitative assessments of physical features employed previously, StructuralGT allows quantitative description of the complex structural attributes of PNNs enumerating the network morphology, connectivity, and transfer patterns. Accurate conversion and analysis of micrographs is possible for various levels of noise, contrast, focus, and magnification while a dedicated graphical user interface provides accessibility and clarity. The GT parameters are expected to be correlated to material properties of PNNs (e.g. ion transport, conductivity, stiffness) and utilized by machine learning tools for effectual materials design.

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“…Despite the synthetic simplicity of this approach, exceptionally complex structures can be produced following the self‐limited mechanism when the competition of several restrictions takes place. [ 6,7 ]…”

Section: Introductionmentioning

confidence: 99%

Metal‐Bridged Graphene–Protein Supraparticles for Analog and Digital Nitric Oxide Sensing

Zhou

Zhang

et al. 2021

Advanced Materials

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Self‐limited nanoassemblies, such as supraparticles (SPs), can be made from virtually any nanoscale components, but SPs from nanocarbons including graphene quantum dots (GQDs), are hardly known because of the weak van der Waals attraction between them. Here it is shown that highly uniform SPs from GQDs can be successfully assembled when the components are bridged by Tb3+ ions supplementing van der Waals interactions. Furthermore, they can be coassembled with superoxide dismutase, which also has weak attraction to GQDs. Tight structural integration of multilevel components into SPs enables efficient transfer of excitonic energy from GQDs and protein to Tb3+. This mechanism is activated when Cu2+ is reduced to Cu1+ by nitric oxide (NO)—an important biomarker for viral pulmonary infections and Alzheimer's disease. Due to multipronged fluorescence enhancement, the limit of NO detection improves 200 times reaching 10 × 10–12 m. Furthermore, the uniform size of SPs enables digitization of the NO detection using the single particle detection format resulting in confident registration of as few as 600 molecules mL−1. The practicality of the SP‐based assay is demonstrated by the successful monitoring of NO in human breath. The biocompatible SPs combining proteins, carbonaceous nanostructures, and ionic components provide a general path for engineering uniquely sensitive assays for noninvasive tracking of infections and other diseases.

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Emergence of complexity in hierarchically organized chiral particles

Cited by 234 publications

References 50 publications

Multiscale Assembly of [AgS₄] Tetrahedrons into Hierarchical Ag–S Networks for Robust Photonic Water

Multiscale Assembly of [AgS₄] Tetrahedrons into Hierarchical Ag–S Networks for Robust Photonic Water

Automatic structural analysis of bioinspired percolating network materials using graph theory

Metal‐Bridged Graphene–Protein Supraparticles for Analog and Digital Nitric Oxide Sensing

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Emergence of complexity in hierarchically organized chiral particles

Cited by 234 publications

References 50 publications

Multiscale Assembly of [AgS4] Tetrahedrons into Hierarchical Ag–S Networks for Robust Photonic Water

Multiscale Assembly of [AgS4] Tetrahedrons into Hierarchical Ag–S Networks for Robust Photonic Water

Automatic structural analysis of bioinspired percolating network materials using graph theory

Metal‐Bridged Graphene–Protein Supraparticles for Analog and Digital Nitric Oxide Sensing

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Product

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Multiscale Assembly of [AgS₄] Tetrahedrons into Hierarchical Ag–S Networks for Robust Photonic Water

Multiscale Assembly of [AgS₄] Tetrahedrons into Hierarchical Ag–S Networks for Robust Photonic Water