Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of organic materials and conditions.
Oxidation can degrade the properties and functionality of metals. However, a research team co-led by scientists from City University of Hong Kong (CityU) recently discovered that severely oxidized metallic glass nanotubes ...
Ubiquitination—the addition of the protein ubiquitin—is a key stage in many cell processes, such as protein degradation, DNA repairs, and signal transduction. Using high-speed atomic force microscopy (HS-AFM) and molecular ...
Skoltech researchers have explained why very weak friction obeys different laws than those governing regular friction as we know it from school physics. Among other unexpected and counterintuitive features, the alternative ...
Our ability to detect different sounds intensities and pitches with great sensitivity is largely due to the inner ear's ability to decode sound waves and amplify individual frequencies. Since the discovery of the anion transporter ...
Magnesium alloys hold promise as a lightweight material to reduce weight in automobiles and transportation systems, offering potential to enhance fuel economy and reduce emissions, but low formability and strength prevent ...
Electrochemical reactions are central to green transitions. These reactions use electric current and potential difference to carry out chemical reactions, which enables binding and realizing electric energy from chemical ...
Prof. Jiang Bin's research team at the University of Science and Technology of China (USTC) have developed a universal field-induced recursively embedded atom neural network (FIREANN) model, which can accurately simulate ...
Tuberculosis is a severe infectious disease that claims about 1.3 million lives annually world-wide. This dismal toll is caused by the notorious pathogen Mycobacteria tuberculosis, whose bitter success depends on its formidable ...
Researchers led by Giulia Galli at University of Chicago's Pritzker School of Molecular Engineering report a computational study that predicts the conditions to create specific spin defects in silicon carbide. Their findings, ...
