Results 101 to 110 of about 253,866 (247)

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

The Comparison of Human and Machine Performance in Object Recognition. [PDF]

Behav Sci (Basel)
Kul G, Wills AJ.
europepmc   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Confidence-weighted integration of human and machine judgments for superior decision-making. [PDF]

Patterns (N Y)
Yáñez F, Luo X, Valerio Minero O, Love BC.   +3 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

A deep neural network model of audiovisual speech recognition reports the McGurk effect. [PDF]

Psychon Bull Rev
Ma H, Wang Z, Zhang X, Magnotti JF, Beauchamp MS.   +4 more
europepmc   +1 more source

Quantifying Evolving Defect Parameters in Metal Halide Perovskites via the Measurement and Modeling of Power‐Dependent Transient Photoluminescence

Advanced Energy Materials, EarlyView.
ABSTRACT Dynamic photoinduced defect states in metal halide perovskites (MHPs) critically govern the non‐equilibrium photophysics, metastability, and long‐term performance of optoelectronic devices, such as solar cells. This metastability is evident in steady‐state photoluminescence experiments, where the amplitudes increase or decrease depending on ...
Maxim Simmonds, Yanyan Duan, Manuel F. Vasquez‐Montoya, Rowan W. MacQueen, Vincent M. Le Corre, Eva Unger, Thomas Kirchartz   +6 more
wiley   +1 more source

Roadmap for High‐Throughput Ceramic Materials Synthesis and Discovery for Batteries

Advanced Energy Materials, EarlyView.
This work examines ceramic synthesis through the lens of high‐throughput synthesis and optimization, identifying opportunities for faster, adaptable routes. It emphasizes flexible liquid precursor–to–solid film methods over slower solid‐state approaches and highlights computer‐aided decision making to optimize both material properties and device ...
Jesse J. Hinricher, Katarzyna P. Sokol, Philipp Simons, Kun Joong Kim, Michael Foshey, Yunsheng Tian, Thorben Prein, Lincoln J. Miara, Elsa Olivetti, Wojciech Matusik, Jennifer L. M. Rupp   +10 more
wiley   +1 more source

Emotion Processing in Schizophrenia: Insights From a Brain Imaging Study Comparing Patients, Siblings, and Healthy Controls. [PDF]

Hum Brain Mapp
Fiorito AM, Kheireddine A, Han H, Morel-Prieur C, Oriol N, Schneider FC, Sescousse G, Fakra E.   +7 more
europepmc   +1 more source

Inversion of the Impedance Response Towards Physical Parameter Extraction Using Interpretable Machine Learning

Advanced Energy Materials, EarlyView.
ABSTRACT Interpreting the impedance response of perovskite solar cells (PSCs) is challenging due to the complex coupling of ionic and electronic motion. While drift‐diffusion (DD) modelling is a reliable method, its mathematical complexity makes directly extracting physical parameters from experimental data infeasible.
Mahmoud Nabil, Isel Grau, Ricardo Grau‐Crespo, Said Hamad, Juan A. Anta   +4 more
wiley   +1 more source