Results 291 to 300 of about 833,540 (375)

Vertical Nanostructures as Novel Interfaces for Brain Research

open access: yesAdvanced Materials Interfaces, EarlyView.
This review highlights the unique features of vertical nanostructures (nanoneedles, nanostraws, nanopillars, and nanowires) for applications in brain research. Various characteristics of nanostructures, including material selection, fabrication methodology, and geometric designs, are discussed for their specific use in neurite guidance, neuron pinning,
Hao Nguyen Tran   +3 more
wiley   +1 more source

Astrocyte Interactions With Ti3C2Tx MXene Flakes: Insights Into Viability, Morphology, and Functionality

open access: yesAdvanced Materials Interfaces, EarlyView.
This study presents the first systematic evaluation of interactions between astrocytes and Ti3C2TX MXene flakes, a 2D nanomaterial with emerging neuroelectronic applications. Using a multimodal approach, including viability assays, morphometric analysis, and calcium imaging, this work demonstrates high biocompatibility and preserved function in ...
Dimitris Boufidis   +7 more
wiley   +1 more source

Deciphering the Interactions of Carbon Nanotubes and Super P with Silicon and Graphite Active Materials in Silicon‐Graphite Negative Electrode‐Based Lithium‐Ion Batteries

open access: yesAdvanced Materials Interfaces, EarlyView.
Although defect‐rich Multi‐walled Carbon Nanotubes (MWCNTs) are generally associated with reduced electronic conductivity, our findings uncover a different role: they act as interfacial mediators in Silicon (Si) negative electrode‐based lithium‐ion batteries. Their defect sites and surface functional groups reinforce particle contact, markedly boosting
Leyla Ünal   +4 more
wiley   +1 more source

Halide Perovskite Quantum Dots Form a Scalable Unified Platform for Resistive Memories, Crossbar Networks, Neuromorphic Synapses, and Field Effect Transistors

open access: yesAdvanced Materials Interfaces, EarlyView.
Halide perovskite quantum dots, with their flexible ABX3 lattice enabling collaborative electronic and ionic transport, offer scalable, low‐cost routes to resistive memories, opto‐electronic control, neuromorphic devices, and field‐effect transistors.
Hyojung Kim
wiley   +1 more source

Deep Learning Analysis of Solid‐Electrolyte Interphase Microstructures in Lithium‐Ion Batteries

open access: yesAdvanced Materials Interfaces, EarlyView.
A transformer‐based deep learning model is developed for segmenting and analyzing high‐resolution TEM images of the solid‐electrolyte interphase (SEI) in lithium‐ion batteries. The model is trained on DFT‐based simulated images and predicts SEI grain and grain boundaries, revealing key microstructural features that govern ion transport and degradation.
Ishraque Zaman Borshon   +4 more
wiley   +1 more source

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