Results 171 to 180 of about 3,013,271 (332)

Silver Ions as Ambipolar Dopants in InAs Nanocrystal Solids

open access: yesAdvanced Materials, EarlyView.
Ag⁺ ions post‐introduced into InAs nanocrystal films act as ambipolar dopants whose effect depends on host polarity and dopant concentration. In n‐type InAs nanocrystal films, Ag⁺ occupies interstitial sites to yield n‐type doping effect, whereas in Zn‐doped p‐type InAs nanocrystal films, it first forms p‐type surface doping effect and later induces n ...
Hwichan Cho   +11 more
wiley   +1 more source

Boosting of post‐exposure human T‐cell and B‐cell recall responses in vivo by Burkholderia pseudomallei‐related proteins [PDF]

open access: bronze, 2017
Arnone Nithichanon   +5 more
openalex   +1 more source

Scalable, Bottom‐Up Synthesis of Transition Metal–Doped Quantum Confined, 1D Titanate‐Based Lepidocrocite Nanofilaments, Their Electronic Structures and Oxygen Evolution Reactivity

open access: yesAdvanced Materials Interfaces, EarlyView.
Quantum‐confined lepidocrocite titanate nanofilaments are doped, bottom‐up, with Mn+2, Fe+2, Co+2, Ni+2, and Cu+2 to tune electronic structure and catalysis. Doping narrows the bandgap—by up to ∼0.8 eV—and extends visible absorption. Ni‐doped filaments accelerate oxygen evolution (319 mV at 10 mA cm−2) and TM‐doped samples rapidly degrade rhodamine 6G (
Mohamed A. Ibrahim   +6 more
wiley   +1 more source

Phase Diagrams Enable Solid‐State Battery Design

open access: yesAdvanced Materials Interfaces, EarlyView.
Batteries are non‐equilibrium devices with inherent thermodynamic driving forces to react at interfaces, regardless of kinetics or operating conditions. Chemical potential mismatches across interfaces are dissipated via interfacial reactions. In this work, it is illustrated how phase diagrams and chemical potential maps predict degradation pathways but
Nathaniel L. Skeele, Matthias T. Agne
wiley   +1 more source

Fluctuating Curvature and Actuation in 4D Printed Asymmetric Networks by Frontal Photopolymerization

open access: yesAdvanced Materials Interfaces, EarlyView.
Asymmetric polymer networks, fabricated by frontal photopolymerization (FPP), are shown to exhibit curvature oscillations associated with monomer‐solvent exchanges during development and drying. We introduce a theoretical model for such dynamic curvature fluctuations and demonstrate the fabrication of bistable switches and self‐propelled materials that
Muhammad Ghifari Ridwan   +3 more
wiley   +1 more source

Short-term memory load and pronunciation rate [PDF]

open access: yes
In a test of short-term memory recall, two subjects attempted to recall various lists. For unpracticed subjects, the time it took to read the list is a better predictor of immediate recall than the number of items on the list. For practiced subjects, the
Hayt, Cathrin, Schweickert, Richard
core   +1 more source

Label‐Free Sensing of Coronaviral Sequences via Kretschmann‐Configuration Reflectance Spectroscopic Ellipsometry: Sensitivity, Specificity, and Interfacial Effects

open access: yesAdvanced Materials Interfaces, EarlyView.
Spectroscopic ellipsometry in the Kretschmann‐Raether configuration (KRSE) is employed to characterize a DNA‐functionalized platform for viral sequence recognition. By merging SE with surface plasmon resonance, KRSE outperforms conventional SE, achieving nanomolar targeting through resonance wavelength shifts (δλ) measurements. Its enhanced interfacial
Silvia Maria Cristina Rotondi   +4 more
wiley   +1 more source

Assessing the involvement of long-term memory in working memory. [PDF]

open access: yesPsychon Bull Rev
Pougeon J   +3 more
europepmc   +1 more source

AI‐Enhanced Gait Analysis Insole with Self‐Powered Triboelectric Sensors for Flatfoot Condition Detection

open access: yesAdvanced Materials Technologies, Volume 10, Issue 6, March 18, 2025.
The given research presents an innovative insole‐based device employing self‐powered triboelectric nanogenerators (TENG) for flatfoot detection. By integrating TENG tactile sensors within an insole, the device converts mechanical energy from foot movements to electrical signals analyzed via machine learning, achieving an 82% accuracy rate in flatfoot ...
Moldir Issabek   +7 more
wiley   +1 more source

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