Results 231 to 240 of about 46,859 (313)
Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses
Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol +7 more
wiley +1 more source
Genetic Algorithm-Optimized CNN-BiLSTM Framework for Predicting the Remaining Useful Life of IGBT Modules. [PDF]
Hao Y +5 more
europepmc +1 more source
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
Mid-term power load forecasting using an ensemble deep learning model with BKA and CWGAN-GP enhancements. [PDF]
Luo S, Chen X, Pang X, Wang B, Zheng Z.
europepmc +1 more source
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin +7 more
wiley +1 more source
Prediction of Ligand Binding to Transthyretin Using Machine Learning Algorithms and Low-Dimensional Molecular Descriptors: A Tox24 Challenge Study. [PDF]
Stefaniak F.
europepmc +1 more source
Accelerating hyperparameter optimization with a secretary
Víctor Muñoz +4 more
openaire +1 more source
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu +6 more
wiley +1 more source
Harnessing hybrid stacking ensemble learning for accurate pulmonary embolism diagnosis using tabular clinical data. [PDF]
Abdelhamid A +5 more
europepmc +1 more source

