Results 171 to 180 of about 68,928 (344)
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
Structure Influences Case Processing: Electrophysiological Insights from Hindi Light Verb Constructions. [PDF]
Mathew AM +3 more
europepmc +1 more source
Why Is the Mechanism Underlying the Chiral‐Induced Selectivity Effect Still Challenging?
The chiral‐induced spin selectivity (CISS) effect is observed in many experimental configurations and for different materials. However, there are theoretical challenges in attempting to explain those results. A qualitative framework for explaining all the results is presented.
Ron Naaman, Yossi Paltiel
wiley +1 more source
The influence of aspect markers and tense on the action-sentence compatibility effect in Mandarin action sentence comprehension. [PDF]
Fan N, Zhu H, Cai Z.
europepmc +1 more source
Narrative Elicitation as Ethnography: Methodological Insights From the Examination of Children's Perspective Marking in Amdo Tibetan. [PDF]
Ward SM.
europepmc +1 more source
No practice and still perfect: Different routes for promoting offline gains in perceptual learning
Ylka Kolken +5 more
openalex +1 more source
Rethinking Charge Transport and Recombination in Donor‐Diluted Organic Solar Cells
Organic solar cells with 1–45% PM6 content in Y12 were studied to link structure and charge dynamics to performance. The conductivity follows a 3D percolation model without a sharp threshold. Donor dilution preserves the photogeneration yield, but limits the fill factor due to transport resistance losses.
Chen Wang +14 more
wiley +1 more source

