Researchers have developed a framework that uses machine learning to accelerate the search for new proton-conducting materials, that could potentially improve the efficiency of hydrogen fuel cells.

Figure 1. This figure depicts the four categories of protein druggability target screening tools discussed in this section, which include structure-based methods, sequence-based methods, machine ...

Overview Artificial intelligence seems to be transforming drug discovery in 2026, enabling faster molecule design, smarter clinical trials, and reduced R&D ...

High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could dramatically slash the cost and energy required to develop new lithium-ion ...