Results 191 to 200 of about 7,587 (302)

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

Mean and variance heterogeneity loci impact kernel compositional traits in maize. [PDF]

Plant Genome
Ismail YMA, Mujjabi C, Olatoye MO, Gray S, Lipka AE, Bohn MO.   +5 more
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

Stability and Inference of the Euler Characteristic Transform. [PDF]

Discrete Comput Geom
Marsh L, Beers D.
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

Introducing the kernel descent optimizer for variational quantum algorithms. [PDF]

Sci Rep
Simon L, Eble H, Radons M.
europepmc   +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, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Bayesian Image Mediation Analysis. [PDF]

J Am Stat Assoc
Xu Y, Johnson TD, Heitzeg M, Kang J.
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

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, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

ReBaCCA-ss: Relevance-Balanced Continuum Correlation Analysis With Smoothing and Surrogating for Quantifying Similarity Between Population Spiking Activities. [PDF]

Neural Comput
Zhang X, Xu C, Lu Z, Wang H, Song D.
europepmc   +1 more source