The article discusses the challenges of designing materials for electrostatic capacitor devices that can withstand extreme electric fields and temperatures. It highlights the advantages…
Browsing: Materials Science
The use of data-driven materials informatics, which integrates computational materials science with machine learning, has shown great potential in the discovery and design of…
This article discusses the use of graphene nanoplatelets (GrNs) in cementitious composites and the development of machine learning models to predict their compressive strength.…
This article discusses the use of generative learning models to accelerate the discovery of high-entropy dielectrics (HEDs) with high energy density. The authors use…
This article discusses the fabrication of conductive aerogels using a combination of TiCT MXene nanosheets, carbon nanofibers, gelatin, and glutaraldehyde. By varying the ratios…
This article provides an overview of the materials genome strategy (MGS) applied in high-entropy alloys (HEAs). It discusses the development of HEAs, the application…
DeepCNT-22 is a machine learning force field that enables near-microsecond timescale simulations of single-walled carbon nanotube (SWCNT) growth on iron catalysts. This work reveals…
LLNL scientists have developed a new approach that combines machine learning with X-ray absorption spectroscopy to rapidly predict the structure and chemical composition of…