Emerging nanoscale applications in energy, electronics, optics, and medicine can exhibit enhanced performance by incorporating nanoshaped structures (nanoshape structures here are defined as shapes enabled by sharp corners with radius of curvature < 5 nm). Nanoshaped fabrication at high-throughput is well beyond the capabilities of advanced optical lithography. Although the highest-resolution e-beams and large-area e-beams have a resolution limit of 5 and 18 nm half-pitch lines or 20 nm half-pitch holes, respectively, their low throughput necessitates finding other fabrication techniques. By using nanoimprint lithography followed by metal-assisted chemical etching, diamond-like nanoshapes with ~3 nm radius corners and 100 nm half-pitch over large areas have been previously demonstrated to improve the nanowire capacitor performance (by ~90%). In future dynamic random-access memory (DRAM) nodes (with DRAM being an exemplar CMOS application), the implementation of nanowire capacitors scaled to <15 nm half-pitch is required. To scale nanoshape imprint lithography down to these half-pitch values, the previously established atomistic simulation framework indicates that the current imprint resist materials are unable to retain the nanoshape structures needed for DRAM capacitors. In this study, the previous simulation framework is extended to study improved shape retention by varying the resist formulations and by introducing novel bridge structures in nanoshape imprinting. This simulation study has demonstrated viable approaches to sub-10 nm nanoshaped imprinting with good shape retention, which are matched by experimental data.
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http://dx.doi.org/10.1038/s41378-020-00225-y | DOI Listing |
Langmuir
January 2025
Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112-0850, United States.
Modification of silica interfaces by covalent attachment of functional ligands is a primary means of controlling the interfacial chemistry of porous silicas used in separations, environmental cleanup, and biosensing. Recently, modification of hydrophobic, -alkyl-silane-functionalized interfaces has been achieved through self-assembly of zwitterionic phospholipids or mixed-charged surfactants to form "hybrid bilayers", producing interfaces that mimic lipid-bilayer partitioning and provide shape-selective partitioning of aromatic hydrocarbons. Charged headgroups, however, introduce electrostatic interactions that strongly influence the retention of ionizable solutes and require careful control over pH and ionic strength in the solution phase.
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January 2025
University of Connecticut, Storrs, CT, USA.
Printed Circuit Board (PCB) design reconstruction is essential for addressing part obsolescence, intellectual property recovery, compliance, quality assurance, and enhancing national capabilities. Traditional methods for PCB design extraction, both non-geometry-based and geometry-based, have limitations in accuracy, efficiency, and scalability. This paper presents an automated approach, combining image processing and machine learning, to achieve 3D semantic segmentation of PCB X-ray Computed Tomography (X-ray CT) images and subsequent netlist extraction.
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January 2025
Department of Ophthalmology, Harvard Medical School, Boston, MA, United States.
We employed high-resolution fMRI to distinguish the impacts of anisometropia and strabismus amblyopia on the evoked ocular dominance (OD) response. Sixteen amblyopic participants (8 females) plus 8 individuals with normal vision (1 female), participated in this study for whom, we measured the difference between the response to stimulation of the two eyes, across areas V1-V4.In controls, the evoked OD response formed the expected striped pattern within V1.
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January 2025
National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, PR China.
Transition-metal layered double hydroxides are widely utilized as electrocatalysts for the oxygen evolution reaction (OER), undergoing dynamic transformation into active oxyhydroxides during electrochemical operation. Nonetheless, our understanding of the non-equilibrium structural changes that occur during this process remains limited. In this study, utilizing in situ energy-dispersive X-ray absorption spectroscopy and machine learning analysis, we reveal the occurrence of deprotonation and elucidate the role of incorporated iron in facilitating the transition from nickel-iron layered double hydroxide (NiFe LDH) into its active oxyhydroxide.
View Article and Find Full Text PDFNat Commun
January 2025
Frontiers Science Center for Flexible Electronics, Xi'an Institute of Flexible Electronics (IFE) and Xi'an Institute of Biomedical Materials & Engineering, Northwestern Polytechnical University, Xi'an, China.
Mitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image segmentation and function prediction. Trained on a dataset of 20,000 manually labeled mitochondria from super-resolution (SR) images, MoDL achieves superior segmentation accuracy, enabling comprehensive morphological analysis.
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