Results 201 to 210 of about 2,318,151 (292)

Intermixing‐Driven Growth of Highly Oriented Indium Phosphide on Black Phosphorus

Advanced Functional Materials, EarlyView.
This study demonstrates controlled intermixing and compound formation at the In/black phosphorus (BP) interface, leading to highly oriented InP formation. Comprehensive structural and electrical analyses reveal tunable bandgap behavior governed by competing BP thinning and charge‐transfer effects, underscoring the critical role of interfacial compound ...
Tae Keun Yun, Min Gyeong Shin, Uje Choi, Jieun Yeon, Jae Joon Kim, Yangjin Lee, Kwanpyo Kim   +6 more
wiley   +1 more source

Editorial: Cortico-hippocampal interactions during learning and memory

Frontiers in Behavioral Neuroscience
Travis P. Todd, Christian Bravo-Rivera, Karyn M. Frick, Sharon C. Furtak   +3 more
doaj   +1 more source

An interpretable machine learning framework for adverse drug reaction prediction from drug-target interactions. [PDF]

PLoS One
Roberts-Nuttall J, Jones AM, Castellani M, Pham D.   +3 more
europepmc   +1 more source

Electron–Matter Interactions During Electron Beam Nanopatterning

Advanced Functional Materials, EarlyView.
This article reviews the electron–matter interactions important to nanopatterning with electron beam lithography (EBL). Electron–matter interactions, including secondary electron generation routes, polymer radiolysis, and electron beam induced charging, are discussed.
Camila Faccini de Lima, Prathiba Thamizhavel, Taylor J. Woehl   +2 more
wiley   +1 more source

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

Towards Multi-Brain Decoding in Autism: A Self-Supervised Learning Approach. [PDF]

Neuroinformatics
Ranjabaran G, Moreau Q, Dubois A, Dumas G.   +3 more
europepmc   +1 more source

Toward Scalable Solutions for Silver‐Based Gas Diffusion Electrode Fabrication for the Electrochemical Conversion of CO2 – A Perspective

Advanced Functional Materials, EarlyView.
In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken, K. Ashoke Raman, Alexander Bauer, Violeta Karyofylli, Eva Jodat, André Karl, Rüdiger‐A. Eichel   +6 more
wiley   +1 more source

Social interaction shapes and boosts second language learning: virtual reality can show us how. [PDF]

NPJ Sci Learn
Zappa A, Slater M, Rodriguez-Fornells A.
europepmc   +1 more source

Bio‐Orthogonally Crosslinked Supramolecular Polymer Bottlebrush Hydrogels for Long‐Term 3D Cell Culture

Advanced Functional Materials, EarlyView.
Fibrous benzenetrispeptide (BTP) hydrogels, fabricated via strain‐promoted azide‐alkyne cycloaddition (SPAAC) crosslinking, form robust, bioinert networks. These hydrogels can support 3D cell culture, where cell viability and colony growth depend on the fiber content.
Ceren C. Pihlamagi, David Pretzel, Peer Nölte, Kourosh Rezaei, Ulrich S. Schubert, Johannes C. Brendel   +5 more
wiley   +1 more source

Recomposable Layered Metasurfaces for Wavelength‐Multiplexed Optical Encryption via Modular Diffractive Deep Neural Networks

Advanced Functional Materials, EarlyView.
Modular diffractive deep neural network metasurfaces encode and reconstruct holograms across layer combinations and wavelengths, enabling secure, multifunctional operation. Each layer acts independently yet composes jointly, yielding up to m(2N −1) channels for m wavelengths and N layers.
Cherry Park, Youngsun Jeon, Seokho Lee, Yeseul Kim, Junsuk Rho   +4 more
wiley   +1 more source