Results 191 to 200 of about 208,150 (274)

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

Associative learning by <i>C. elegans</i> is variable when butanone is paired with starvation. [PDF]

MicroPubl Biol
Tasnim S, Liu A, Jose A.
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

Preliminary Data Regarding the Alleviating Effects of Haloperidol and Risperidone on the Short-Term Memory and Associative Learning in a Zebrafish Model of Schizophrenia. [PDF]

Pharmaceuticals (Basel)
Lungu PF, Hritcu LD, Nicoara MN, Savuca A, Curpan AS, Chelaru AI, Lungu CM, Gurzu B, Balmus IM, Ciobica A, Plavan GI.   +10 more
europepmc   +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

Bold zebrafish (Danio rerio) learn faster in a classical associative learning task. [PDF]

Sci Rep
Corcoran J, Storks L, Wong RY.
europepmc   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

Enhancing Synaptic Plasticity and Multistate Retention of Organic Neuromorphic Devices Using Anion‐Excessive Gel Electrolyte

Advanced Functional Materials, EarlyView.
Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won, Jeongwoo Lee, Hyunwook Kim, Joon Hak Oh   +3 more
wiley   +1 more source

Impact of visual stimulus complexity on associative learning and associated reaction times in migraine patients. [PDF]

Sci Rep
Tót K, Eördegh G, Harcsa-Pintér N, Papp A, Bodosi B, Braunitzer G, Tajti J, Csáti A, Nagy A.   +8 more
europepmc   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

Advanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy, Chuan‐En Lu, Kai Liu, Audrey Gallud   +3 more
wiley   +1 more source