Willy Menacho
Instituto de Investigaciones Físicas.
Carrera de Física, Universidad Mayor de San Andrés. Campus Universitario Cota Cota. La Paz, Bolivia

Gonzalo Marcelo Ramírez-Ávila
Instituto de Investigaciones Físicas.
Carrera de Física, Universidad Mayor de San Andrés. Campus Universitario Cota Cota. La Paz, Bolivia

Horacio V. Guzman
Department of Theoretical Physics
Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
Instituto de Investigaciones Físicas.
Carrera de Física, Universidad Mayor de San Andrés. Campus Universitario Cota Cota. La Paz, Bolivia

Abstract

pyDAMPF is a tool oriented to the Atomic Force Microscopy (AFM) community, which allows the simulation of the physical properties of materials under variable relative humidity (RH). In particular, pyDAMPF is mainly focused on the mechanical properties of polymeric hygroscopic nanofibers that play an essential role in designing tissue scaffolds for implants and filtering devices. Those mechanical properties have been mostly studied from a very coarse perspective reaching a micrometer scale. However, at the nanoscale, the mechanical response of polymeric fibers becomes cumbersome due to both experimental and theoretical limitations. For example, the response of polymeric fibers to RH demands advanced models that consider sub-nanometric changes in the local structure of each single polymer chain. From an experimental viewpoint, choosing the optimal cantilevers to scan the fibers under variable RH is not trivial.

In this article, we show how to use pyDAMPF to choose one optimal nanoprobe for planned experiments with a hygroscopic polymer. Along these lines, We show how to evaluate common and non-trivial operational parameters from an AFM cantilever of different manufacturers. Our results show in a stepwise approach the most relevant parameters to compare the cantilevers based on a non-invasive criterion of measurements. The computing engine is written in Fortran, and wrapped into Python. This aims to reuse physics code without losing interoperability with high-level packages. We have also introduced an in-house and transparent method for allowing multi-thread computations to the users of the pyDAMPF code, which we benchmarked for various computing architectures (PC, Google Colab and an HPC facility) and results in very favorable speed-up compared to former AFM simulators.

Keywords

Materials science, Nanomechanical properties, AFM, f2py, multi-threading CPUs, numerical simulations, polymers

DOI

10.25080/majora-212e5952-01e

Bibtex entry

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Copyright © 2022 Willy Menacho et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.