Results 221 to 230 of about 120,823 (294)

Ultra‐Low Power Consumption and Highly Durability in Sm:HfO2 Thin Film Ferroelectric Memristor for Edge Detection

Advanced Electronic Materials, EarlyView.
ABSTRACT With the continuous development of computer image processing, developing efficient and low‐power computing devices has become a key challenge. Memristors have integrated in‐situ storage and computing capabilities, making them an ideal choice for low‐power image processing computing architectures. However, current memristors are confronted with
Tengyu Li, YongRui Wang, Weifeng Zhang, Jikang Xu, Xiaobing Yan   +4 more
wiley   +1 more source

Predictive modeling for the mean diameter of carbon nanotubes produced by methane decomposition. [PDF]

Discov Nano
Almansour S, Alkwai LM, Yadav K, Zneid BA, Pashtun F.   +4 more
europepmc   +1 more source

People Counting and Positioning Using Low‐Resolution Infrared Images for FeFET‐Based In‐Memory Computing

Advanced Electronic Materials, EarlyView.
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar, Li Zhang, Alexander Rehmer, Marc Lupp, Subhashree Baskaran, Osama Abdelaal, Franz Müller, Nandakishor Yadav, Bing Li, Thomas Kämpfe   +9 more
wiley   +1 more source

The Learning Rate Is Not a Constant: Sandwich-Adjusted Markov Chain Monte Carlo Simulation. [PDF]

Entropy (Basel)
Vrugt JA, Diks CGH.
europepmc   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
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, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

Linear Dimensionality Reduction Methods for Analyzing Structured Biomedical Data: Existing Research and Future Opportunities. [PDF]

Wiley Interdiscip Rev Comput Stat
Wang Y.
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
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, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

SPARCC: Semi-Parametric Robust Estimation in a Right-Censored Covariate Model. [PDF]

J Am Stat Assoc
Lee SH, Richardson BD, Ma Y, Marder KS, Garcia TP.   +4 more
europepmc   +1 more source

Sustainable Carbon Fibers Enable Stable Long‐Term Lithium Metal Deposition for Prospective Zero‐Excess Lithium Metal Batteries

Advanced Energy Materials, EarlyView.
This work presents lightweight, lignin‐derived carbon fiber current collectors that enable controlled lithium deposition. Structural defects and intermediate‐sized pores stabilize pre‐nucleation quasi‐metallic lithium clusters, promoting uniform lithium plating and stripping.
Samantha L. S. Southern, Jonathon Cottom, Jana B. Fritzke, Emma N. Antonio, Zhenyu Guo, Bhavini Patel, Romain Tort, Ifan E. L. Stephens, Camilla Di Mino, Clare P. Grey, Rhodri Jervis, Emilia Olsson, Heather Au, Maria‐Magdalena Titirici   +13 more
wiley   +1 more source

Quantitative Kernel estimation from traffic signs using slanted edge spatial frequency response as a sharpness metric. [PDF]

Sci Rep
Pandey A, Akhtar MZ, Veettil NK, Wunderle B, Elger G.   +4 more
europepmc   +1 more source