Dynamic modelling and analysis of hoisting systems constitute a critical research domain that bridges theoretical mechanics with practical engineering applications. This field aims to accurately ...
A newly developed generative AI model is helping researchers explore protein dynamics with increased speed. The deep learning system, called BioEmu, predicts the full range of conformations a protein ...
Theory, computation, and simulation are foundational to modern energy research. Theoretical understanding reveals why materials and systems behave as they do, predicting performance before experiments ...
Researchers from BIFOLD and Google DeepMind have developed MD-ET, a transformer-based molecular dynamics model that achieves state-of-the-art results without encoding traditional physical constraints ...
Computational analysis using rigidity-theory indicates that activation of the human adenosine A 2A receptor (shown here) is regulated by long-range allosteric communication pathways (highlighted in ...
Equipment failures emerge from complex system interactions in real-world conditions that simulation cannot fully predict or ...
Researchers from BIFOLD and Google DeepMind have developed MD-ET, a transformer-based molecular dynamics model that omits traditional physics constraints like energy conservation and equivariance.
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