Results 61 to 70 of about 11,813 (260)
Advanced Electronic Materials, EarlyView.A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun +5 more
wiley +1 more source
Atomic Scale Control of Thermal Conductivity in LaMnO3/SrMnO3 Superlattices
Advanced Electronic Materials, EarlyView.Interface‐dominated cross‐plane thermal transport in [(LaMnO3)m/(SrMnO3)n]10 superlattices can be controlled by the octahedral rotation/tilt angle φOOR of the MnO6 octahedra, which as well is controlled by the “m/n” ratio. ABSTRACT We report atomic scale structure and phonon thermal transport in (LaMnO3)m/(SrMnO3)n/SrTiO3(100) superlattices (LMO/SMO ...
H. Ulrichs +12 more
wiley +1 more source
Advanced Electronic Materials, EarlyView.A high‐performance strain‐compensated InGaAs/GaAsP superlattice SWIR photodetector was successfully grown by MOCVD on a scalable 100 mm GaAs platform. Combining excellent structural quality with strong optoelectronic performance, the device delivers a low dark current density of 2.3 × 10−7 A/cm2 and a detectivity of 1.9 × 1011 Jones at 1100 nm ...
Rémy Tribout +19 more
wiley +1 more source
Физика волновых процессов и радиотехнические системы, 2013 Field and volume charge structure in the junction between semiinsulating chrome doped substrate and n-channel of GaAs MESFET was analyzed by means of a computational modeling. It was used a four-level model of semiinsulating GaAs with deep levels.
A.M. Bobreshov +2 more
doaj
Advancing Energy Materials by In Situ Atomic Scale Methods
Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss +21 more
wiley +1 more source
Study of Nanoscratching Process of GaAs Using Molecular Dynamics
Crystals, 2018 In this paper, molecular dynamics method was employed to investigate the nanoscratching process of gallium arsenide (GaAs) in order to gain insights into the material deformation and removal mechanisms in chemical mechanical polishing of GaAs.
Defu Yi, Jianyong Li, Pengzhe Zhu
doaj +1 more source
Advanced Energy Materials, EarlyView.A flexible InGaP/GaAs/InGaAs triple‐junction platform encapsulated with ultrathin glass enables unassisted electrocatalysis and space applications by providing robust protection against chemically aggressive and radiation‐rich environments. This work establishes a unified III–V multijunction photovoltaic platform that bridges space photovoltaics and ...
Sukkyu Hong +10 more
wiley +1 more source
Angewandte Chemie, EarlyView.A 310‐helix‐mediated conformational switch promotes a front‐face SNi‐like catalysis by human A4GALT. Mechanism‐guided design identifies AdaGalCer as a selective modulator of globotriaosylceramide (Gb3) biosynthesis, opening a clear route toward new Fabry disease therapeutics.
Nicky de Koster +13 more
wiley +2 more sources
Advanced Energy Materials, EarlyView.Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
Advanced Intelligent Discovery, EarlyView.We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source