Add support for nanoparticle models

[pm-blanco]

Support for colloidal models of nanoparticles (modelled as a rigid object with functional groups on its surface) has been requested by our users. To implement such feature we would need to:

• Define a function that defines a nanoparticle object in pyMBE define_nanoparticle given a molecule name, a model type (homogenous, Janus, Belt, patchy), surface group density, and identity of the functional groups and stores this information in the pyMBE dataframe.
• Define a function that creates such object into ESPResSo taking the information defined in the dataframe.
• Create unit tests to check that the above functions work properly.
• Create a sample script to showcase the functionality.

[pm-blanco]

Aftermath of the online discussion with @pinedaps:

• We create a dedicated module in pyMBE with various functions to create specific models of NPs
• For now, we only support NPs with a uniform distribution of sites and two different kinds of sites (one main site and a secondary site)
• Notes for define_nanoparticle:
  • It should calculate the real surface charge density for the NP radius and the resulting integer number of sites, print it to screen, save it on the df and return it to the user

Conceptual draft of the user usage of the NP feature:

# Define particles
pmb.define_particle(“central_particle”, sigma, )
pmb.define_particle(“site_1”, pka…)
pmb.define_particle(“site_2”, pka…)

# Define nanoparticle

pmb.define_nanoparticle(name = nanoparticle_name,
                        core_particle_name= central_particle_name,
                        sites_properties = {“main” : {“particle_name” = “site_1”,
                                                       “fraction” = 0.7,
                                                       “number_of_patches” = 3},
                                           “secondary”: {“particle_name” = “site_2”}},
                        surface_density_of_sites)


pmb.create_nanoparticle(name=nanoparticle_name)

Conceptual draft of the pyMBE functions

def define_nanoparticle(name, core_particle_name, sites_properties, surface_density_of_sites)

# Sanity checks 

…
radius = pmb.get_radius_map()
S_sphere = 4* [np.pi](http://np.pi/) * radius[“core_particle_name”]**2
N_sites =  int(S_sphere  * surface_charge_density)
real_surface_charge_density = N_sites / S_sphere 

# Store inputs in the [pmb.df](http://pmb.df/) (including real_surface_charge_density)

return real_surface_charge_density


def  create_nanoparticle(name=nanoparticle_name)
    # Get info about the NP properties from the df

    # Call specific nanoparticle builder depending on the NP properties