3.8 Proceedings Paper

Monte Carlo Assisted FTIR Spectroscopy: A Python Tool for the Determination of the Constituents in Blended Biopolymer Samples

Journal

MACROMOLECULAR SYMPOSIA
Volume 398, Issue 1, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/masy.202000174

Keywords

biopolymer composition; FTIR; Monte Carlo; RMSE; Software

Funding

  1. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico [304500/2019-4]
  2. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior [001]
  3. Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ)

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This study developed a Python code for composition analysis of biopolymers using FTIR spectra, comparing signals and calculating errors to determine the final composition of the material.
A massive number of biopolymers and complex polymer blends are being developed every day. One of the significant challenges related to these materials is their characterization. In more specific terms, estimating the composition of polymeric mixtures is a substantial challenge for the technologist, who must understand the nuances of the material's composition for its proper application. Thus, this work develops a Python code capable of handling the composition analysis using the FTIR spectra of some biopolymers found in the literature. Through the Monte Carlo method associated with the Mixture Rule, these spectra are combined, generating a myriad of signals referring to different compositions. These signals are compared with the one from the FTIR spectrum of the mixture, allowing the root-mean-square error (RMSE) calculation. Finally, minimizing the RMSE value leads to the final composition of the material, which is presented and saved in a text file.

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