Results 181 to 190 of about 179,280,476 (281)
Advanced Science, EarlyView.An MTJ‐based probabilistic processing‐in‐memory architecture unites nonvolatile storage, local entropy generation, and stochastic computation within each memory cell. Stored multi‐bit weights are converted directly into programmable stochastic bitstreams, enabling neural‐network inference, adaptive Ising optimization, and uncertainty‐aware Bayesian ...
Qiuyuan Wang +6 more
wiley +1 more source
Mode‐Resolved Phonon Dynamics Under Chemical Pressure in SnTe Thermoelectrics
Advanced Science, EarlyView.Chemical pressure reshapes low‐energy optical phonons in SnTe, altering their dispersion and scattering with heat‐carrying acoustic modes. Positive and negative pressure states modify phonon frequencies and lifetimes in distinct ways, revealing how mode‐selective lattice perturbations regulate acoustic–optical interactions and suppress lattice thermal ...
Zhihao Li +7 more
wiley +1 more source
Cr1/4NbSe2‐Single Crystal Growth and Evolution of Antiferromagnetic Correlated States
Advanced Science, EarlyView.High‐quality single crystals Cr1/4NbSe2 were synthesized and comprehensively characterized for the first time. Advanced structural, electronic, and magnetic measurements uncover a correlated antiferromagnetic state, resolving longstanding inconsistencies regarding magnetic behavior derived from earlier polycrystal studies.
Nour Abdelrahman +16 more
wiley +1 more source
A Dual‐Branch Flux‐Based Extended Memristor Model With Machine‐Learning‐Assisted Calibration
Advanced Electronic Materials, EarlyView.Multilayer oxide memristors integrated in crossbar arrays are described through a dual‐branch, flux‐controlled compact model. A three‐stage calibration workflow combining Latin hypercube sampling, Bayesian optimization, and gradient‐based refinement extracts device parameters from experimental data.
Davide Rossetti +6 more
wiley +1 more source
Advanced Electronic Materials, EarlyView.Self‐compensation effects attributed to doping‐dependent shift‐defects at APBs Validation of Hall data for VRH transport near the MIT Persistence of VRH transport for any SiH4 flow in Si‐doped κ‐Ga2O3 due to high compensation coupling transport and EPR data as strategy to study electronic properties and doping T‐dependence of transport data agrees with
Antonella Parisini +9 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
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
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
Advanced Energy Materials, EarlyView.In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
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