.. _nnp:

Pure NNP simulations
====================

*ACEMD* supports running molecular dynamics simulations with neural networks in so-called pure NNP simulations.
In these simulations the whole system is described with a neural network potential without any classical force field.

You can :download:`download here <./benzamidine_nnp.zip>` the example input file for a pure NNP simulation of benzamidine in vacuum.

The input file of *ACEMD* can then be configured as follows to run a pure *NNP* simulation (see :ref:`nnp-options` for more details).
Since the whole system is described with a neural network potential, we can skip the ``sel`` option of the NNP configuration.

.. code-block:: yaml

    thermostat: true
    thermostattemperature: 300
    velocities: 300
    structure: BEN_pH7_4.cif
    coordinates: BEN_pH7_4.cif
    minimize: 500
    timestep: 2
    run: 2ns
    nnp:
        file: aceff_v1.0.ckpt
        name: TorchMD-Net
        type: torch

Compared to :ref:`nnpmm`, pure *NNP* simulations don't require a classically built system. So you can
directly use PDB, CIF, binary CIF, SDF or MOL2 files as structure and coordinate files.

A timestep of 2 fs is recommended for NNP simulations as NNP simulations are not very stable at larger timesteps.

To obtain a NNP model you can follow the instructions in :ref:`obtaining-aceff-models`.

Running the simulation
----------------------

You can execute the simulation directly with a simple ``acemd`` call:

.. code-block:: bash

    acemd