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
Decision tree with randomized grid search-based hyperparameter tuning and optimal feature scaling for diabetes diagnosis. [PDF]
Al-Slivani MM +8 more
europepmc +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
ASWBoost: Classification algorithm for noisy and imbalanced data based on parametric exponential loss. [PDF]
Meng F, Yan M, Liu H, Xu W, Li H.
europepmc +1 more source
Phase Engineering of Atomically Precise Nanoclusters (APNCs) of Gold and Beyond
Engineering the structural phase of materials is of paramount importance for both fundamental research and practical applications. In this Review, we summarize the recent progress in controlling the phases of atomically precise nanoclusters (APNCs) of gold, silver and copper, as well as bimetallic systems. The phase‐enabled material properties of APNCs
Yitong Wang +4 more
wiley +1 more source
SEFA: Semantic Embedding-Based Feature Augmentation of Biomedical Language-Model Embeddings Improves Interpretable Metabolomic Prediction of Lung Cancer. [PDF]
Wu J +6 more
europepmc +1 more source
A dual‐timescale reservoir based on monolithically 3D (M3D)‐integrated CNT solid ion‐gated transistors is demonstrated. Tunable ionic dynamics and pulse‐engineered operation enable linear and symmetric synaptic updates. The M3D‐integrated array achieves robust temporal encoding and accurate classification of moving MNIST sequences, highlighting its ...
Haksoon Jung +9 more
wiley +1 more source
Ensemble learning-based online sequential pre-interference extreme learning for concept drifting and class imbalanced data streams. [PDF]
Huang Y, Wen H, Tang Q, Liu H.
europepmc +1 more source
Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen +7 more
wiley +1 more source
Circulating neuron-derived cfDNA for blood-based detection of Alzheimer's and other neurodegenerative conditions. [PDF]
Pollard C +7 more
europepmc +1 more source

