Results 171 to 180 of about 8,119,426 (288)

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

The role of graph topology in the performance of biomedical Knowledge Graph Completion models. [PDF]

Bioinformatics
Cattaneo A, Bonner S, Martynec T, Morrissey E, Luschi C, Barrett IP, Justus D.   +6 more
europepmc   +1 more source

Single‐Cell Dissection of Microglial Dysfunction in Diabetes‐Associated Neurodegenerative Vulnerability

Advanced Science, EarlyView.
Using single‐cell transcriptomic and epigenomic profiling, researchers mapped microglial dysfunction across the lifespan of db/db mice. The authors uncovered a nonlinear microglial remodeling featuring early inflammatory priming, a mid‐stage transcriptional inflection, and late dysfunction.
Jizhou Zhang, Tsz Kwan Yau, Joyce Tse, Tsz Ho Li, Dongjie Hu, Yong Juan Zhao, Ting‐Fung Chan   +6 more
wiley   +1 more source

Learning temporal granularity with quadruplet networks for temporal knowledge graph completion. [PDF]

Sci Rep
Geng R, Luo C.
europepmc   +1 more source

Friend, Not Foe: Lowered Tissue Reactivity to Long‐Term Polyimide Implants

Advanced Science, EarlyView.
The choice of optimal neural probe designs remains a major challenge in the field of neurotechnology. This study investigated the biocompatibility of several probe variations, including material, thickness, width, and implantation strategy. It highlights the clear advantage of soft polyimide probes over stiff silicon probes for better device ...
Corinne Orlemann, Laura M. De Santis, Paul Neering, Christian Boehler, Kirti Sharma, Arno Aarts, Tobias Holzhammer, Rik J. J. van Daal, Patrick Ruther, Maria Asplund, Roxana N. Kooijmans, Pieter R. Roelfsema   +11 more
wiley   +1 more source

JGURD: joint gradient update relational direction-enhanced method for knowledge graph completion. [PDF]

PeerJ Comput Sci
Ding L, Li M, Gao S, Li J, Yuan R, Yu J.
europepmc   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

MERGE: A Modal Equilibrium Relational Graph Framework for Multi-Modal Knowledge Graph Completion. [PDF]

Sensors (Basel)
Shang Y, Fu K, Zhang Z, Jin L, Liu Z, Wang S, Li S.   +6 more
europepmc   +1 more source

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

Advanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su, Yanda Zhu, Hao Peng, Manman Li, Xuzihan Zhang, Meixiao Wu, Siyuan Zhang, Yuhan Zeng, Jiwen Liao, Ming Luo, Hetaishan Huang, Yutong Wang, Sean Li, Wenxian Li   +13 more
wiley   +1 more source

A Generative Neuro‐Symbolic AI for Protein Sequence Design

Advanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne, Delphine Dessaux, Samuel Buchet, Lucie Barthe, Liza Ammar‐Khodja, Bessam Azizi, Valentin Durante, Gianluca Cioci, Simon de Givry, Alain Roussel, Luis F. Garcia‐Alles, Thomas Schiex, Sophie Barbe   +12 more
wiley   +1 more source