Results 111 to 120 of about 1,446 (247)
SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel +6 more
wiley +1 more source
Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation
A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang +6 more
wiley +1 more source
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
Controllable Superconductivity in Suspended NbSe2
Suspended NbSe2${\rm NbSe}_2$ provides two complementary routes for controlling superconducting transport. Gate‐driven deformation strains the suspended crystal and tunes its critical temperature and current. Weak thermal anchoring enhances thermal feedback, contributing to multistep hysteresis and negative differential resistance.
Ruihuan Fang +14 more
wiley +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
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
The error correction model’s main purpose in heavy hexagonal quantum codes is to improve their reliability for quantum computing applications. Existing challenges include finding the optimal decoder for quantum error correction in heavy hexagonal codes ...
Umesh Uttamrao Shinde, Ravikumar Bandaru
doaj +1 more source
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
Stabilizer Entanglement Distillation and Efficient Fault-Tolerant Encoders
Entanglement is essential for quantum information processing, but is limited by noise. We address this by developing high-yield entanglement distillation protocols with several advancements.
Yu Shi, Ashlesha Patil, Saikat Guha
doaj +1 more source
The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source

