machball 0.2.0

self-limited (ALD, ALE) reactive transport in nanostructures

# What is Machball?

Machball models the reactive transport inside high aspect ratio and nanostructured materials for self-limited processes such as atomic layer deposition (ALD) and atomic layer etching (ALE).

# Documentation

Machball’s documentation can be found under docs and in [readthedocs](https://machball.readthedocs.io/en/latest/)

# Install instructions

Using pip: ` pip install machball `

From github: ` git clone https://github.com/aldsim/machball.git cd machball/ pip install -e . `

# Quickstart

You can model ALD inside a high aspect ratio feature with just a few lines of code: ` from machball import ALDIdeal from machball.ballistic import Via ald = ALDIdeal(1e-2, 100, 473, 10, 10e-20, betarec=0) st = Via(50, 100) # Aspect ratio, and number of segments dose_times, coverages = ald.saturation_ballistic(st) `

# Authors

Machball was developed at Argonne National Laboratory. Currently the team comprises:

• Angel Yanguas-Gil, <[e-mail]>, Lead and founder

• Jeffrey W Elam

# Citing

If you are referencing Machball in a publication, please cite the following paper:

• Ballistic transport model:

  A. Yanguas-Gil and J. W. Elam, A Markov chain approach to simulate Atomic Layer Deposition chemistry and transport inside nanostructured substrates, Theoretical Chemistry Accounts 133, Article number: 1465 (2014). http://dx.doi.org/10.1007/s00214-014-1465-x

# Acknowledgements

Machball development was partially funded through Argonne’s Laboratory Directed Research and Development program.

# Copyright and license

Copyright (2013), UChicago Argonne, LLC

Machball is distributed under the terms of the BSD License. A copy of the license can be found [here](https://github.com/aldsim/machball/blob/master/LICENSE)

Argonne Software Number: SF-13-072