Results 151 to 160 of about 23,335 (263)

Atomically Dispersed Ni Site Catalysts Accelerating Sluggish Sulfur Redox Kinetics in Nonaqueous Zn‐S Batteries

Advanced Functional Materials, EarlyView.
An atomically dispersed Ni catalyst featuring Ni‐N4 coordination is developed as a sulfur host for nonaqueous Zn─S batteries. This configuration modulates the electronic structure to lower activation barriers during rate‐limiting steps and promotes a robust ZnF2‐rich cathode‐electrolyte interphase, thereby accelerating sulfur redox kinetics ...
Junhyuk Ji, Dongwoo Kim, Nuri Moon, Daehwan Kim, Keon Kim, Nahyung Kim, Young Yong Kim, Won Bae Kim   +7 more
wiley   +1 more source

The Scaled Hirshfeld Partitioning: Mathematical Development and Information-Theoretic Foundation. [PDF]

Entropy (Basel)
Heidar-Zadeh F.
europepmc   +1 more source

Cellular Responses to Mechanical Cues Across Scales: From Fundamental Insights to Translational Potential

Advanced Healthcare Materials, EarlyView.
This review examines how cellular behavior is regulated by mechanical cues transmitted through soft biomaterials, from single‐cell mechanosensing to tissue‐level adaptation. It highlights why physiological relevance, rather than model complexity alone, is critical for translational mechanobiology and introduces a scoring framework linking material ...
Mathias Polz, Manuel P. Kainz, Niklas Haider, Theresa Rienmüller, Kerstin Lenk, Rupert Kargl, Michele Terzano, Gerhard Sommer, Gerhard A. Holzapfel, Julia Fuchs   +9 more
wiley   +1 more source

Multiclass portfolio optimization via variational quantum Eigensolver with Dicke state ansatz. [PDF]

Sci Rep
Scursulim JVS, Langeloh GM, Beltran VL, Brito S.   +3 more
europepmc   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Data-driven, ML-assisted approaches to problem well-posedness. [PDF]

PNAS Nexus
Bertalan T, Kevrekidis GA, Koronaki ED, Mishra S, Rebrova E, Kevrekidis IG.   +5 more
europepmc   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

A Supervised Contrastive Variational Autoencoder with Probabilistic Latent Alignment for Cross-Domain EEG Emotion Recognition. [PDF]

Sensors (Basel)
Wu L, Yang Y, Wang W, Xie Y, Zhou N, Shi K.   +5 more
europepmc   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Interval Prediction of Remaining Useful Life Based on Uncertainty Quantification with Bayesian Convolutional Neural Networks Featuring Dual-Output Units. [PDF]

Sensors (Basel)
Qu Z, He J, Liu Y, Mao S, Han X.
europepmc   +1 more source