Results 161 to 170 of about 279,507 (217)
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
“Smelltronics”—From Gas to Smell Sensing
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono +7 more
wiley +1 more source
How language modulates color perception in a brain-constrained deep neural network. [PDF]
Tomasello R +3 more
europepmc +1 more source
Sub‐stoichiometric amounts of Na+ or K+ enhance defect healing during Silicalite‐1 (MFI) and TS‐1 calcination by promoting Si–O–Si annealing and healing framework vacancies. The resulting defect‐free zeolites are more hydrophobic and show improved butanol/water separation and improved activity and selectivity in the epoxidation of 1‐hexene, offering a ...
Christos Kanteler +14 more
wiley +1 more source
PneumoNet: Deep Neural Network for Advanced Pneumonia Detection. [PDF]
Mahesh TR +5 more
europepmc +1 more source
We show that sol‐gel‐fractured indium–magnesium oxide combines deep‐ultraviolet responsivity, high carrier mobility, and an excellent memory dynamic range. This unique materials platform enables deep‐ultraviolet long‐afterglow light‐emitting devices with multifunctional integration.
Zhongshi Ju +9 more
wiley +1 more source
A deep neural network model for heat transfer in darcy-forchheimer hybrid nanofluid flow with activation energy. [PDF]
Ayman-Mursaleen M +4 more
europepmc +1 more source
This work introduces sustainable PLA/graphene oxide bioelectronic interfaces featuring electrodes with tunable conductivity and strong electrocatalytic performance. These platforms were used to implement a new method for tuning astrocyte Ca2+ signaling and for the efficient detection of key biomarkers.
Alessandra Scidà +15 more
wiley +1 more source
A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study. [PDF]
Rantula OA +11 more
europepmc +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
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

