Particula is a Python-based aerosol particle simulator. Its goal is to provide a robust aerosol simulation (including both gas and particle phases) that can be used to answer scientific questions arising from experiments and research endeavors.

The Particula website https://uncscode.github.io/particula contains the API reference, how-to guides, and tutorials.

If your Python environment is already set up, you can install particula via pip using the following command:

pip install particula

Or install via conda:

conda install -c conda-forge particula

The particula.dynamics namespace collects time-dependent processes such as dilution, condensation, coagulation, and wall loss.

For wall loss there are two complementary APIs:

• Function-based rates (legacy):
  • particula.dynamics.get_spherical_wall_loss_rate(...)
  • particula.dynamics.get_rectangle_wall_loss_rate(...)
  • particula.dynamics.get_charged_wall_loss_rate(...) – charged/image-charge wall loss helper with optional electric-field drift.
• Strategy-based API (preferred):
  • particula.dynamics.WallLossStrategy – abstract base class for wall loss models.
  • particula.dynamics.SphericalWallLossStrategy – spherical chamber strategy.
  • particula.dynamics.RectangularWallLossStrategy – rectangular chamber strategy with (x, y, z) dimensions in meters.
  • particula.dynamics.ChargedWallLossStrategy – charged wall loss for spherical or rectangular chambers; includes image-charge enhancement even when wall_potential=0, optional wall_electric_field drift, and reduces to the neutral coefficient when charge and field are zero.

Wall loss strategies operate directly on particula.particles.representation.ParticleRepresentation instances and support all three distribution types: "discrete", "continuous_pdf", and "particle_resolved". The charged strategy uses particle charge; when charge and wall_electric_field are zero, it reduces to the neutral coefficient while preserving image-charge effects when wall_potential is zero.

import particula as par

# Assume `particle` is a ParticleRepresentation
spherical_loss = par.dynamics.SphericalWallLossStrategy(
    wall_eddy_diffusivity=0.001,  # m^2/s
    chamber_radius=0.5,  # m
    distribution_type="discrete",
)

rectangular_loss = par.dynamics.RectangularWallLossStrategy(
    wall_eddy_diffusivity=0.001,  # m^2/s
    chamber_dimensions=(1.0, 0.5, 0.3),  # m
    distribution_type="discrete",
)

charged_loss = par.dynamics.ChargedWallLossStrategy(
    wall_eddy_diffusivity=0.001,  # m^2/s
    chamber_geometry="rectangular",
    chamber_dimensions=(1.0, 0.5, 0.3),  # m
    wall_potential=0.05,  # V (image-charge active even if set to 0)
    wall_electric_field=(50.0, 0.0, 0.0),  # V/m; set to 0 to disable drift
    distribution_type="discrete",
)

rate = charged_loss.rate(
    particle=particle,
    temperature=298.15,
    pressure=101325.0,
)

particle = charged_loss.step(
    particle=particle,
    temperature=298.15,
    pressure=101325.0,
    time_step=1.0,
)

Wall loss builders mirror other dynamics builders and handle unit conversion and validation for geometry, diffusivity, and charged parameters (wall_potential, wall_electric_field). The charged builder requires chamber_geometry plus a matching size field (chamber_radius for spherical or chamber_dimensions for rectangular). The factory accepts strategy_type="charged" with the same parameters if you prefer name-based selection.

import particula as par

builder = (
    par.dynamics.ChargedWallLossBuilder()
    .set_wall_eddy_diffusivity(0.001, "m^2/s")
    .set_chamber_geometry("rectangular")
    .set_chamber_dimensions((1.0, 0.5, 0.3), "m")
    .set_wall_potential(0.05, "V")
    .set_wall_electric_field((50.0, 0.0, 0.0), "V/m")
    .set_distribution_type("particle_resolved")
)
charged_loss = builder.build()

factory = par.dynamics.WallLossFactory()
charged_from_factory = factory.get_strategy(
    strategy_type="charged",
    parameters={
        "chamber_geometry": "spherical",
        "chamber_radius": 0.5,
        "wall_eddy_diffusivity": 0.001,
        "wall_potential": 0.0,
        "wall_electric_field": 0.0,
        "distribution_type": "continuous_pdf",
    },
)

When charges and wall_electric_field are zero, charged wall loss matches the neutral coefficient; non-zero charge retains image-charge effects even when wall_potential is zero.

See the online documentation for more examples and background theory. For a complete walkthrough comparing spherical and rectangular chambers (with coagulation/condensation chaining), see the Wall Loss Tutorial notebook.