Reaction Boost (targeted MD): RMSD
**********************************

MLPotential ForceField ParAMS Accelerated MD

Important:

  This tutorial requires AMS2024 or later.

The reaction boost (targeted MD) feature can be used to gradually
transform one system into another during molecular dynamics.

This feature can be used, for example, to

* sample an interesting range of structures for training machine
  learning potentials,

* get reasonable initial guesses for transition states

In this tutorial we will set the reaction boost method to "RMSD",
which means that the method will transform the cartesian coordinates
of one system into the target system.

This can push the simulation over the (possibly large) reaction
barriers.

**For more information** about reaction boost (targeted MD) and how to
set up these calculations, see Reaction Boost (targeted MD): bond-
making and breaking.


Cu atom diffusion on/in Ag(110)
===============================

   Open AMSinput
   File → Open → "ReactionBoostSurfaceRMSD.run"

The example loads the **ASE** (Atomic Simulation Environment) engine
with the EMT calculator.

ASE is a Python library that is included with AMS.


AT base pair dissociation in water
==================================

   Open AMSinput
   File → Open → "ReactionBoostATDissociation.run"

The example loads the **ForceField** engine with the GAFF force force
field, including automatic atom typing.

On the **Model → MD... → Reaction Boost** panel, you can see that the
reaction boost is only applied to the **AT** region, which contains
the the two AT molecules.

When you switch the view between the two input structures, you can see
that the water molecules are in completely different positions.
However, no restraints are applied to the water molecules, so it
doesn't matter where they are located in the target structure.

You can also see that **Pre equilibration steps** is set to "5000".
This means that the first 5000 steps of the MD simulation are run
without any restraints. The boosting only starts at step 5000.
