Results 151 to 160 of about 56,731 (216)

A DC Compact Model of an Organic Electrochemical Transistor Based on a Semiconductor Physics and Thermodynamic Approach

open access: yesAdvanced Electronic Materials, EarlyView.
This work presents a physics‐based DC compact model of an Organic Electrochemical Transistor (OECT) that takes into account the faradaic redox reaction in the above threshold regime and incorporates the diffusive current of the subthreshold regime based on semiconductor physics.
Ermias Telahun Teka   +6 more
wiley   +1 more source

Conformal Reconfigurable Intelligent Surfaces: A Cylindrical Geometry Perspective

open access: yesAdvanced Electronic Materials, EarlyView.
Cylindrical reconfigurable intelligent surfaces are explored for low‐complexity beam steering using one‐bit meta‐atoms. A multi‐level modeling approach, including optimization‐based synthesis, demonstrates that even minimal hardware can support directive scattering.
Filippo Pepe   +4 more
wiley   +1 more source

Exceptional Antimodes in Multi‐Drive Cavity Magnonics

open access: yesAdvanced Electronic Materials, EarlyView.
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith   +4 more
wiley   +1 more source

Solving the where problem and quantifying geometric variation in neuroanatomy using generative diffeomorphic mapping. [PDF]

open access: yesNat Commun
Tward DJ   +9 more
europepmc   +1 more source

Inversion of the Impedance Response Towards Physical Parameter Extraction Using Interpretable Machine Learning

open access: yesAdvanced Energy Materials, EarlyView.
ABSTRACT Interpreting the impedance response of perovskite solar cells (PSCs) is challenging due to the complex coupling of ionic and electronic motion. While drift‐diffusion (DD) modelling is a reliable method, its mathematical complexity makes directly extracting physical parameters from experimental data infeasible.
Mahmoud Nabil   +4 more
wiley   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi   +5 more
wiley   +1 more source

Viscoelastic differences between isolated and live MCF7 cancer cell nuclei resolved with AFM microrheology. [PDF]

open access: yesJ R Soc Interface
Juel Pørtner E   +5 more
europepmc   +1 more source

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