Results 161 to 170 of about 66,767 (293)

Opportunities of Semiconducting Oxide Nanostructures as Advanced Luminescent Materials in Photonics

Advanced Materials, EarlyView.
The review discusses the challenges of wide and ultrawide bandgap semiconducting oxides as a suitable material platform for photonics. They offer great versatility in terms of tuning microstructure, native defects, doping, anisotropy, and micro‐ and nano‐structuring. The review focuses on their light emission, light‐confinement in optical cavities, and
Ana Cremades, Pedro Hidalgo, David Maestre, Ruth Martínez‐Casado, Emilio Nogales, Beatriz Rodríguez, G. Cristian Vásquez, Bianchi Méndez   +7 more
wiley   +1 more source

Sampled-data fuzzy [Formula: see text] estimators for control of nonlinear parabolic partial differential equations. [PDF]

Sci Rep
Sivakumar M, Dharani S, Cao J.
europepmc   +1 more source

Spin‐Split Edge States in Metal‐Supported Graphene Nanoislands Obtained by CVD

Advanced Materials, EarlyView.
Combining STM measurements and ab‐initio calculations, we show that zig‐zag edges in graphene nanoislands grown on Ni(111) by CVD retrieve their spin‐polarized edge states after intercalation of a few monolayers of Au. ABSTRACT Spin‐split states localized on zigzag edges have been predicted for different free‐standing graphene nanostructures.
Michele Gastaldo, Masoud Mansouri, Carlos Garcia‐Fernandez, Daniel Sánchez‐Portal, Aran Garcia‐Lekue, Gustavo Ceballos, Aitor Mugarza   +6 more
wiley   +1 more source

Noise effects on soliton structures of nonlinear Schrödinger equation with generalized Kudryashov's law non-linearity using modified extended mapping technique. [PDF]

Sci Rep
Mshary N, Bossly R, Ahmed HM.
europepmc   +1 more source

Polymorph‐Specific Electronic Transduction in WO3 during Molecular Sensing

Advanced Materials, EarlyView.
Metal‐oxide polymorphs with similar surface chemistry can nevertheless exhibit distinct sensing properties. In γ‐ and ε‐WO3, analyte adsorption appears comparable; yet, only ε‐WO3 induces a pronounced lattice electronic perturbation that accommodates charge in sub‐conduction band minimum states.
Matteo D'Andria, Meng Yin, Stefan Neuhauser, Vlasis G. Mavrantzas, Ying Chen, Ken Suzuki, Andreas T. Güntner   +6 more
wiley   +1 more source

Modeling of gene regulatory networks: an annotated glossary. [PDF]

Trends Plant Sci
Singh Yadav A, Russell NJ, Hernández AI, Petlewski AR, Johnson AR, Grinage AD, Banuna B, Guan CJ, Mahood EH, Younkin GC, Thomas HR, Phillips HR, Harline K, Flasco M, Miller MB, Scinto-Madonich NJ, Szeluga NM, Mendoza PN, Formosa-Jordan P, Roeder AHK.   +19 more
europepmc   +1 more source

Energetic Offset in Organic Solar Cells‐ Importance, Confusion and Outlook

Advanced Materials, EarlyView.
Energetic offsets in organic solar cells (OSCs) remain a subject of debate due to measurement‐ and lab‐dependent discrepancies. This Perspective clarifies the physical origins of these variations and identifies temperature‐dependent electro‐optical methods as a reliable approach to obtain consistent offset values.
Nakul Jain, Xian'e Li, Mats Fahlman, Olle Inganäs, Koen Vandewal, Feng Gao   +5 more
wiley   +1 more source

The Emergence of Turing Instability and Pattern Formation in a Nonlinear Stochastic Spatiotemporal Epidemic Model with Reinfections. [PDF]

Acta Biotheor
Singh AK, Almshekhs R, Kumar M, Ramakrishnan S.   +3 more
europepmc   +1 more source

Elastomeric Micro‐Balloons for Remote Control of Cerebral Blood Flow and Real‐Time In vivo Imaging of Rodent Brain Response to Hypoperfusion

Advanced Materials, EarlyView.
This study reports the fabrication of MRI‐compatible elastomeric micro‐balloons via a multi‐step bubble casting process, where the monolithic elastomeric wall is selectively stiffened for reversible and controlled inflation and elasticity, depending on the target vessels for graded occlusion of cerebral arteries.
Jong Bin Kim, Jinghui Wang, Yinding Chi, Jingxian Wu, Alicia Ng, Guanda Qiao, Honglin Tan, Miroslaw Janowski, Piotr Walczak, Yajie Liang, Shu Yang   +10 more
wiley   +1 more source

Implementing physics-informed neural networks with deep learning for differential equations. [PDF]

Front Artif Intell
Emmert-Streib F, Tripathi S, Farea A, Holzinger A.   +3 more
europepmc   +1 more source