6.3 ML-enabled MSM
As noted earlier, one of the main objectives of MSM is to couple the
physics at different scales using bridging algorithms that pass
information between two scales, such as in QM/MM, MM/CG, CG/CM, and
field-based methods discussed in section 5. However, the implementation
of this methodology on parallel supercomputing HPC architectures is
complicated and cumbersome. To address this significant limitation in
implementation, we advocate for an ML-enabled integration or bridging of
scales as a viable approach to develop the next generation of MSM
methods to achieve maximal efficiency and flexibility in integrating
scales.