Results 111 to 120 of about 32,315 (261)

A Review on Catalytic Nanostructured Electrodes for Wearable and Implantable Abiotic Glucose Fuel Cells

open access: yesAdvanced Science, EarlyView.
This review identifies current and future directions in abiotic nanostructured catalysts to develop reliable and sustainable glucose fuel cells to power the next generation of bioelectronic devices. ABSTRACT The global rise in incidence of chronic diseases has led to the demand for innovative solutions that help patients manage their conditions with ...
Asghar Niyazi   +3 more
wiley   +1 more source

Highly Flexible and Conformable ZnO/FeGa Magnetoelectric Heterostructures for Skin wound Healing

open access: yesAdvanced Science, EarlyView.
The magnetic field‐induced electric field generated by a highly flexile ZnO(piezoelectric)/FeGa(magnetostrictive) magnetoelectric heterostructure embedded in the low Young's modulus elastomer PDMS has been used to stimulate the wound healing processes.
Filippos Perdikos   +17 more
wiley   +1 more source

Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing

open access: yesAdvanced Science, EarlyView.
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale   +6 more
wiley   +1 more source

Photovoltaic Systems. Measurement and Evaluation of Photovoltaic Power Systems.

open access: yesJournal of The Society of Instrument and Control Engineers, 1996
MINE, Hisaichi, IMATAKI, Mitsumasa
openaire   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

open access: yesAdvanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin   +12 more
wiley   +1 more source

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