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Multiscale, hierarchically patterned surfaces, such as lotus leaves, butterfly wings, adhesion pads of gecko lizards are abundantly found in nature, where microstructures are usually used to strengthen the mechanical stability while nanostructures offer the main functionality, i.e., wettability, structural color, or dry adhesion. To emulate such hierarchical structures in nature, multiscale, multilevel patterning has been extensively utilized for the last few decades towards various applications ranging from wetting control, structural colors, to tissue scaffolds. In this review, we highlight recent advances in scalable multiscale patterning to bring about improved functions that can even surpass those found in nature, with particular focus on the analogy between natural and synthetic architectures in terms of the role of different length scales. This review is organized into four sections. First, the role and importance of multiscale, hierarchical structures is described with four representative examples. Second, recent achievements in multiscale patterning are introduced with their strengths and weaknesses. Third, four application areas of wetting control, dry adhesives, selectively filtrating membranes, and multiscale tissue scaffolds are overviewed by stressing out how and why multiscale structures need to be incorporated to carry out their performances. Finally, we present future directions and challenges for scalable, multiscale patterned surfaces.
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http://dx.doi.org/10.1002/adma.201303412 | DOI Listing |
J Chem Theory Comput
September 2025
Institute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria.
We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. This framework streamlines the development of new interfaces by providing a reusable and extendable code base. It supports the computation of energies, gradients, various couplings─like spin-orbit couplings, nonadiabatic couplings, and transition dipole moments─and other properties for an arbitrary number of states with any multiplicities and charges.
View Article and Find Full Text PDFNanoscale
September 2025
Department of Materials Science and Engineering, National University of Singapore, 9 Engineering Drive 1, 117575, Singapore.
Electromagnetic pollution poses significant risks to electronic devices and human health, highlighting the need for mechanically robust, lightweight, and cost-effective electromagnetic interference (EMI) shielding materials. 3D-printed structures with nanomaterial-engineered surfaces offer a promising method for tailoring mechanical and electrical properties through multiscale design. Herein, we present a facile strategy for fabricating lightweight and flexible EMI shielding structures by chemical deposition of nanostructured metal coatings onto 3D-printed polymeric substrates.
View Article and Find Full Text PDFFront Plant Sci
August 2025
College of Engineering, Qinghai Institute of Technology, Xining, China.
The plateau pika () is a keystone species on the Qinghai-Tibet Plateau, and its population density-typically inferred from burrow counts-requires rapid, low-cost monitoring. We propose YOLO-Pika, a lightweight detector built on YOLOv8n that integrates (1) a Fusion_Block into the backbone, leveraging high-dimensional mapping and fine-grained gating to enhance feature representation with negligible computational overhead, and (2) an MS_Fusion_FPN composed of multiple MSEI modules for multi-scale frequency-domain fusion and edge enhancement. On a plateau pika burrow dataset, YOLO-Pika increases mAP50 by 3.
View Article and Find Full Text PDFAdv Healthc Mater
September 2025
School of Chemistry and Chemical Engineering, Guangdong Provincial Key Lab of Green Chemical Product Technology, South China University of Technology, Guangzhou, 510640, P. R. China.
Photonic crystal (PC) hydrogel-based sensors with visual signal outputs have attracted attention for wearable motion monitoring, but current devices suffer from low spatial resolution, small-scale design, and poor signal consistency. Herein, we present a combined and scalable PC sensing platform that includes a single-point sensor (100 × 400 mm) and an 8 × 8 multipixel array (100 × 100 mm) for dual-mode visual-electrical feedback. The array achieves 2D strain mapping on the arm with a spatial resolution of 0.
View Article and Find Full Text PDFFront Neurosci
August 2025
Department of Neuroscience, Brown University, Providence, RI, United States.
The expansion of large-scale neural recording capabilities has provided new opportunities to examine multi-scale cortical network activity at single neuron resolution. At the same time, the growing scale and complexity of these datasets introduce new conceptual and technical challenges beyond what can be addressed using traditional analysis techniques. Here, we present the Similarity Networks (SIMNETS) analysis framework: an efficient and scalable pipeline designed to embed simultaneously recorded neurons into low dimensional maps according to the intrinsic relationship between their spike trains, making it possible to identify and visualize groups of neurons performing similar computations.
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