Not long ago, science followed a fairly natural rule: to predict a property of a substance or material, you had to understand ...
Tohoku University researchers propose a framework called Physics-Grounded Materials AI that embeds thermodynamic, kinetic, ...
A machine learning framework combining random forest prediction, neural network defect screening, and evolutionary ...
Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions ...
Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions ...
The Pioneer on MSNOpinion
From vultures to bustards: Reversing avian decline needs habitats, not robots
India, Oct. 5 -- The worldwide decline of bird populations signals a deeper breakdown of the ecosystems on which human life ...
Major depressive disorder (MDD) is a common mental health condition primarily characterized by persistent low mood or loss of ...
China has embraced open-weight models, a development that researchers say is closing the AI capability gap between the ...
Whether in drug discovery, environmental analysis or metabolomics: anyone analyzing complex biological samples often needs to ...
Researchers propose a machine learning methodology to accelerate the design of erosion-resistant paint coatings. Their work ...
Governments must stop viewing the sharing of chemical data as a surrender of sovereignty and instead appreciate it as the ...
Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions ...
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