Results 111 to 120 of about 2,599,171 (311)

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

Interesting Concept Mining With Concept Lattice Convolutional Networks

IEEE Access
The extraction of meaningful conceptual structures is often a critical task in many scientific and engineering disciplines, as it enables a comprehensive analysis of complex data in terms of both context and content.
Mohamed Hamza Ibrahim, Rokia Missaoui, Pedro Henrique B. Ruas   +2 more
doaj   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Flexible constrained sampling with guarantees for pattern mining [PDF]

, 2017
Pattern sampling has been proposed as a potential solution to the infamous pattern explosion. Instead of enumerating all patterns that satisfy the constraints, individual patterns are sampled proportional to a given quality measure.
Vladimir Dzyuba, Leeuwen, M. van, Dzyuba, Vladimir, Dzyuba, V., Matthijs van Leeuwen, Dzyuba, Vladimir,, De Raedt, Luc,, Luc De Raedt, van Leeuwen, Matthijs, De Raedt, L., van Leeuwen, Matthijs,, De Raedt, Luc   +11 more
core   +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

MinerLSD: efficient mining of local patterns on attributed networks

Applied Network Science, 2019
Local pattern mining on attributed networks is an important and interesting research area combining ideas from network analysis and data mining. In particular, local patterns on attributed networks allow both the characterization in terms of their ...
Martin Atzmueller, Henry Soldano, Guillaume Santini, Dominique Bouthinon   +3 more
doaj   +1 more source

Anisotropic Masked Mycobacterium Potentiates Amplified Antitumor Trained Immunity via Spleen Targeting and Myelopoiesis Conversion

Advanced Materials, EarlyView.
An engineered Trojan Mycobacterium, developed via a “peeling‐off and masking‐up” strategy, functions as a powerful splenic myelopoiesis converter. This spleen‐targeted nanomedicine induces trained immunity to reprogram immunosuppressive myeloid reservoirs into antitumoral effectors.
Jin‐Ho Choi, Sang Nam Lee, Jang Hun Heo, Soyoung Park, Sei Hyun Park, Yong Taik Lim   +5 more
wiley   +1 more source

Frequent Pattern Mining for IoT Big Streaming Data Based on Short-Pattern Graph

Big Data Mining and Analytics
Internet of things (IoT) technology is important in the era of big data, and in most IoT scenarios, data are constantly arriving in the form of streams.
Guang Yang, Xia Wu, Jing Zhang
doaj   +1 more source

Leveraging Data‐Driven and Fundamental Insights for Electrolyte Innovation in Lithium Metal Batteries

Advanced Materials, EarlyView.
Using 640 curated electrolyte formulations, we apply data‐driven analysis to reveal how molecular features govern coulombic efficiency (CE) in lithium metal batteries. Fluorine content correlates positively with CE, while oxygen, carbon, and higher boiling points correlate negatively.
Minh Van Duong, Mitchell Kaiser, Xia Cao, Trung Thien Nguyen, Au Nguyen, Phung My Loan Le, Jun Liu   +6 more
wiley   +1 more source

Efficient Hydroxyl Diffusion Triggers Surface Hydronium Enrichment and Bulk Proton Participation to Boost Alkaline Hydrogen‐Evolving Reaction

Advanced Materials, EarlyView.
For the first time, we shed light on the surface‐to‐bulk diffusion, induction, and reaction behaviors of OH−, H+, and H2O species on model oxides for alkaline hydrogen‐evolving reaction (HER). We first demonstrate that bulk OH− diffusion significantly affects the generation of proton sources and the diffusion/reaction behaviors of protons, thus ...
Daqin Guan, Hengyue Xu, Xiao Sun, Leqi Zhao, Chun‐Kuo Peng, Chao Jing, Yu‐Cheng Huang, Jiayi Tang, Nai Shi, Zezhou Lin, Xiaomin Xu, Zhiwei Hu, Zongping Shao   +12 more
wiley   +1 more source