Results 111 to 120 of about 829,474 (301)

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Semantic Referee : A Neural-Symbolic Framework for Enhancing Geospatial Semantic Segmentation

, 2019
Understanding why machine learning algorithms may fail is usually the task of the human expert that uses domain knowledge and contextual information to discover systematic shortcomings in either the data or the algorithm.
Alirezaie, Marjan,, Sioutis, Michael,, Längkvist, Martin,, Loutfi, Amy,   +3 more
core   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Evaluating lexical resources for a semantic tagger [PDF]

, 2004
Semantic lexical resources play an important part in both linguistic study and natural language engineering. In Lancaster, a large semantic lexical resource has been built over the past 14 years, which provides a knowledge base for the USAS semantic ...
Rayson, P., Piao, S, McEnery, AM, Piao, S., Archer, Dawn, Archer, DE, McEnery, A. M., Rayson, P   +7 more
core  

Semantic Web Technologies for Digital Libraries: From Libraries to Social Semantic Digital Libraries (SSDL), Over Semantic Digital Libraries (SDL)

, 2010
Digital libraries have been an important source of information throughout the history of mankind. It has been present in our societies in different forms. Notably, traditional libraries have found their on the desktops of internet users.
Alotaibi, Sara
core   +1 more source

A Domain-Agnostic Neuro-Symbolic Architecture for Multimodal Human-in-the-Loop Anomaly Detection and Complex Fault Diagnosis

IEEE Access
This paper presents a general architecture for iterative, hybrid neuro-symbolic anomaly detection and complex fault diagnosis, in which symbolic knowledge-based methods and neural machine learning methods reinforce each other.
Tim Bohne, Anne-Kathrin Patricia Windler, Martin Atzmueller   +2 more
doaj   +1 more source

Closed‐Loop Solid‐State Synthesis Planning for Materials Discovery With Large Language Models

Advanced Materials, EarlyView.
Leveraging literature data, we build a large‐language‐model‐driven workflow that extracts synthesis steps from 4407 papers, retrieves similar precedents, and generates candidate solid‐state synthesis recipes. The system benchmarks against ground‐truth and then operates in a closed loop with experiments to synthesize oxy‐selenide electrolyte materials ...
Dong Won Jeon, Dong Hwi Kim, Taeyang Jeon, Joo Yeong Na, Heegyu Kim, Hyunsouk Cho, Dae Soo Jung, Ju Li, Jin‐Sung Park, Sung Beom Cho   +9 more
wiley   +1 more source

Controlled Synthesis of Tri‐ and Multi‐Doped Graphene

Advanced Materials Interfaces, EarlyView.
This review systematically evaluates synthesis routes for tri‐ and multi‐doped graphene, from hydrothermal and pyrolysis methods to flash Joule heating, critically assessing how each governs dopant incorporation, bonding configuration, and resulting electronic properties.
Maria Hasan, Alicja Bachmatiuk, Gražyna Simha Martynková, Karla Čech Barabaszová, Mark Hermann Rümmeli   +4 more
wiley   +1 more source