Results 161 to 170 of about 3,413,435 (251)

Alkali Ion‐Incorporated HfO2 Dielectrics for Reconfigurable Neuromorphic Computing

open access: yesAdvanced Functional Materials, EarlyView.
This work presents an indium gallium zinc oxide (IGZO) transistor with an alkali cation‐integrated hafnium dioxide (HfO2) dielectric exhibiting synaptic behavior via ion retention. The solution‐based film fabrication strategy overcomes the limitations of atomic layer deposition (ALD) and precursor coating, enabling the control of synaptic retention ...
Seung Yeon Ki   +7 more
wiley   +1 more source

Structure–Transport–Ion Retention Coupling for Enhanced Nonvolatile Artificial Synapses

open access: yesAdvanced Functional Materials, EarlyView.
Nitrogen incorporation into the conjugated backbone of donor–acceptor polymers enables efficient charge transfer and deep ion embedding in organic electrochemical synaptic transistors (OESTs). This molecular‐level design enhances non‐volatile synaptic properties, providing a new strategy for developing high‐performance and reliable neuromorphic devices.
Donghwa Lee   +5 more
wiley   +1 more source

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

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