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AdsorPy: A Python Package for Lattice-Based Random Sequential Adsorption Simulations
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DOI：10.1021/acs.jctc.5c01967.png)
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Abstract
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Lattice-based random sequential adsorption (RSA) simulations can be used to investigate the random packing of shapes on a surface, in particular the adsorption of molecules on a crystalline lattice in 2D. Atomic layer deposition (ALD) and by extension area-selective ALD (AS-ALD) have found applications in the manufacturing of nanoelectronics in the semiconductor industry. During deposition with these techniques, the packing of molecules on a surface─in terms of density and arrangement─largely determines the growth rate and selectivity, respectively. The packaged AdsorPy script performs RSA simulations of molecules represented by their 2D footprints and provides quantitative information about the packing properties. The script provides easy integration of other computational methods used in material science, such as density functional theory calculations. RSA simulations can for example be used to make informed decisions on the choice of inhibitor species in AS-ALD processes. Various case scenarios are demonstrated using the script in order to match the conditions of relevant experiments, such as different dosing schemes.
Keywords:
Adsorption
Atomic layer deposition
Inhibitors
Molecules
Precursors
Journal
IF:
5.5
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1.1W
Citations:
5.4W
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