Results 191 to 200 of about 246,074 (294)

Advancing Energy Materials by In Situ Atomic Scale Methods

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss   +21 more
wiley   +1 more source

Two relations for generalized discrete Fourier transform coefficients

open access: yesBulletin of the Polish Academy of Sciences: Technical Sciences, 2018
openaire   +1 more source

Spin Matters: A Multidisciplinary Roadmap to Understanding Spin Effects in Oxygen Evolution Reaction During Water Electrolysis

open access: yesAdvanced Energy Materials, EarlyView.
This roadmap offers a forward‐looking perspective on spin enhancement in the oxygen evolution reaction. It highlights how combining systematic experiments, advanced computational modeling, and novel magnetic, chiral, or hybrid materials can deepen the understanding of spin‐dependent catalytic mechanisms.
Emma van der Minne   +29 more
wiley   +1 more source

Wearable Thermoelectric Generators for In Vivo Modulation of Insulin Release

open access: yesAdvanced Energy Materials, EarlyView.
This work presents a wearable, self‐powered thermoelectric system (IGNITE) that sustainably harvests body heat to electrically stimulate engineered human cells for insulin release. Operating autonomously without batteries, IGNITE achieves glycemic control in diabetic mice, demonstrating a significant advance in bioelectronic medicine and setting the ...
Debasis Maity   +2 more
wiley   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

open access: yesAdvanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu   +4 more
wiley   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

open access: yesAdvanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee   +3 more
wiley   +1 more source

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