Results 161 to 170 of about 13,981 (252)
'Will polar bears melt?' A qualitative analysis of children's questions about climate change. [PDF]
Lee K, Barnett J.
europepmc +1 more source
Azobenzene photoswitches translate molecular‐scale E/Z photoisomerization into macroscopic material responses and device‐level photonic functions. This Review highlights how azobenzene research has evolved from molecular photochemistry to photoalignment, mass migration, photomechanics, and heat release, ultimately enabling holography, reconfigurable ...
Heeju Son +20 more
wiley +1 more source
Influence of sea ice dynamics on population energetics of Western Hudson Bay polar bears. [PDF]
Johnson AC +5 more
europepmc +1 more source
Controlling the protein corona formation onto carbon nanomaterials (CNMs) enhances their functionalities as platforms for cancer theranostics. Here, we reviewed the effects of the intrinsic and acquired properties of CNMs on protein corona formation, the consequent biological and toxicological outcomes, and the strategies to reshape corona formation ...
Yajuan Zou +5 more
wiley +1 more source
Faecal glucocorticoid metabolites as a measure of adrenocortical activity in polar bears (Ursus maritimus). [PDF]
Hein A +7 more
europepmc +1 more source
Associating a red‐NIR phosphorescent octahedral hexanuclear molybdenum cluster compound with hexaethyleneoxide chains bearing mesogenic units on both ends leads to an emissive hybrid liquid crystal showing mesomorphism on a very unusual temperature range down to −25°C.
Killiann Heinz +11 more
wiley +1 more source
Identifying individual polar bears at safe distances: A test with captive animals. [PDF]
Prop J, Staverløkk A, Moe B.
europepmc +1 more source
Anion‐exchange doping of conjugated polymers is an effective way to achieve high conductivities. Here, we report over 2000 S cm−1 electrical conductivity for doped P(g3BTTT). In addition, we show that P(g3BTTT) sustains exceptionally high doping levels without any drop in the charge mobility.
Basil Hunger +14 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
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 +3 more
wiley +1 more source

