Results 121 to 130 of about 193,926 (266)
Universal Conductance Fluctuations in Quantum Anomalous Hall Insulators
Universal conductance fluctuations are observed in mesoscopic quantum anomalous Hall insulators. Two distinct fluctuation patterns are identified, arising from different interference processes of bulk and chiral edge states, respectively. These findings unveil rich quantum interference phenomena in quantum anomalous Hall insulators and provide insights
Peng Deng +11 more
wiley +1 more source
A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning. [PDF]
Alon L, Dehkharghani S.
europepmc +1 more source
We demonstrate a neuromorphic synapse in 2D Fe3GaTe2 flakes. The device operates via a current‐driven transformation from a skyrmion‐lattice to a stripe‐domain state, yielding a linear anomalous Hall resistance response with a tunable slope to enable multiply‐accumulate operations. Simulations confirm its viability in artificial neural networks.
Jixiang Huang +20 more
wiley +1 more source
A Nb‐proximitized Josephson junction based on a WTe2/α‐Fe2O3 heterostructure exhibits a robust superconducting diode effect with programmable polarity. The diode direction can be trained by magnetic fields and switched by temperature cycling, revealing tunable finite‐momentum pairing states and competing superconducting states in symmetry‐broken ...
Enze Zhang +9 more
wiley +1 more source
A novel approach for discovering stochastic models behind data applied to El Niño-Southern Oscillation. [PDF]
Olson R, An SI, Kim SK, Fan Y.
europepmc +1 more source
ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh +2 more
wiley +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Path‐decoupled III–V van der Waals memtransistors spatially separate ionic and electronic transport to overcome the conventional trade‐off between accuracy and energy in neuromorphic hardware. Mobile K+ ions in the vdW gaps set a wide conductance window, Gmax/Gmin, while gate‐tunable hole conduction lowers programming energy, enabling reliable ...
Jihong Bae +13 more
wiley +1 more source
Mathematical perspective of Covid-19 pandemic: Disease extinction criteria in deterministic and stochastic models. [PDF]
Adak D, Majumder A, Bairagi N.
europepmc +1 more source

