Banca de DEFESA: MAYCOM CEZAR VALERIANO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
DISCENTE : MAYCOM CEZAR VALERIANO
DATA : 26/09/2023
HORA: 14:30
LOCAL: https://conferenciaweb.rnp.br/sala/monica-52
TÍTULO:

RAMAN SPECTROSCOPY ASSISTED BY MACHINE LEARNING FOR THE STUDY OF BIODIESEL STABILITY PARAMETERS

PÁGINAS: 94
RESUMO:

Being a biofuel analogous to diesel, biodiesel arose as a bio-renewable energy source. However, its use demands methodologies to keep its quality and reduce damage to the engine and the environment. In this context, spectroscopic techniques have become a suitable alternative that allows non-destructive analyses and requires minimal sample volume. Among them, Raman spectroscopy, which measures the inelastic scattering of radiation, is a promising technique for monitoring biodiesel quality.  However, due to the high amount of information stored in Raman spectra and the samples’ complexity, extracting quantitative information directly is highly challenging, making it necessary to use multivariate computational processing to model and extract the relevant information for exploratory or quantitative purposes. In this work, data mining and machine learning methods to classify soy biodiesel samples according to their humidity content and to determine oxidative stability under current legislation established by the Brazilian National Petroleum Agency (ANP), were used. The combination of Raman spectroscopy and exploratory analysis allowed the tracking of structural modifications in biodiesel molecules through changes observed mainly at the CH₂, CH₃, and -C=C vibrational modes. Multivariate classifiers such as PLS-DA, SVM, and SIMCA were applied to biodiesel samples according to their water content (limit value = 200 mg kg^-1) through their O-H, -CH₂, and -CH₃ vibrational modes. Besides, oxidative stability, defined as the biofuel resistance to oxidative degradation caused by oxygen at room temperature and measured through its induction time, was assessed by building PLS calibration models. The structural changes caused by the oxidation showed differences in -CH₂ and -CH₃ vibrational modes mainly due to C=C bond cleavage. Also, soft-modeling procedures using a multivariate curve resolution method (MCR-ALS) were applied to study its kinetics. The CH₂, CH_3, and -C=C modes allowed modeling its decomposition kinetics.

MEMBROS DA BANCA:
Presidente - Interno ao Programa - 3047441 - MONICA BENICIA MAMIAN LOPEZ
Membro Titular - Examinador(a) Interno ao Programa - 1543683 - IVANISE GAUBEUR
Membro Titular - Examinador(a) Externo à Instituição - PAULO ROBERTO FILGUEIRAS - UFES
Membro Suplente - Examinador(a) Interno ao Programa - 2351974 - JULIANA DOS SANTOS DE SOUZA
Membro Suplente - Examinador(a) Externo à Instituição - FRANCINE DALAPICOLA DOS SANTOS