Results 141 to 150 of about 70,721 (269)

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Correction: Anesthetic and analgesic management of Svalbard rock ptarmigan (Lagopus muta hyperborea) undergoing experimental stereotaxic neurosurgery

BMC Veterinary Research
Jana Kalinová, Daniel Appenroth, Fernando Cázarez-Márquez, Renate Thorvaldsen, David G. Hazlerigg, Ingebjørg H. Nymo   +5 more
doaj   +1 more source

Correction: Erysipelothrix rhusiopathiae clone reemergence in association with a multi-year mass mortality event in high Arctic muskoxen (Ovibos moschatus). [PDF]

Sci Rep
Wooten MT, Forde TL, Roberto-Charron A, Fredlund M, Mullin T, Christensen OA, Schneider A, Radhakrishnan S, Goldsmith D, Morrison B, Lau E, Mavrot F, Seru LV, Fang T, Donovan RM, Cluff HD, van der Meer F, Kutz SJ.   +17 more
europepmc   +1 more source

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

Exploring the diversity of leafhoppers (Hemiptera: Cicadellidae) in the Eastern Canadian Arctic. [PDF]

J Insect Sci
Santos AA, Plante N, Parceaud-May S, Jacques J, Grégoire-Taillefer A, Pérez-López E.   +5 more
europepmc   +1 more source

Arctic Geology * [PDF]

Nature, 1875
openaire   +4 more sources

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Enhancing Role of Nitrogen Fixation in Biogeochemical Cycles of the Pacific Arctic. [PDF]

Glob Chang Biol
Shiozaki T, Fujiwara A, Watanabe E, Nishino S, Harada N, Makabe A.   +5 more
europepmc   +1 more source

Arctic Rivers

, 2009
Brittain, John E., Bogen, Jim, Khokhlova, Ludmila G., Melvold, Kjetil, Stenina, Angelina S., Gislason, Gisli M., Brørs, Sturla, Kochanov, Sergej K., Olafsson, Jon S., Ponomarev, Vasily I., Jensen, Arne J., Kokovkin, Alexander V., Pettersson, Lars-Evan   +12 more
openaire   +2 more sources

Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions

Advanced Functional Materials, EarlyView.
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng, Qian Yao, Yanan Sun, Hongyu Lv, Zhongchao Bai, Guoliang Zhang, Nana Wang, Jian Yang   +7 more
wiley   +1 more source