Retraction Note: Prediction of uniaxial compressive strength of limestone from ball mill grinding characteristics using supervised machine learning techniques. [PDF]
Swamy SV +5 more
europepmc +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
Interpretable prediction of dynamic compressive strength of red sandstone under wetting-drying cycles using ensemble learning. [PDF]
Du B, Qi W, Bai H.
europepmc +1 more source
The engineering of colloidal nanocrystals with complex compositions has emerged as a highly active area of research within nanomaterials science. This review covers key aspects of colloidal solid‐solution nanocrystal formation using pulsed laser irradiation.
Marina T. Candela +4 more
wiley +1 more source
Reliability-based mix design for concrete compressive strength using a physics-prior residual-learning surrogate with calibrated uncertainty. [PDF]
Qu P, Song L, Wang S.
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
Comparative evaluation of compressive strength among different glass ionomer cements. [PDF]
Chavan P +7 more
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

