Banca de QUALIFICAÇÃO: ARIVONALDO BEZERRA DA SILVA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : ARIVONALDO BEZERRA DA SILVA
DATE: 30/11/2023
TIME: 10:00
LOCAL: videoconferência
TITLE:

Bibliometric Analysis and Machine Learning to determine an optimized manganese-based oxygen carrier for application in Chemical Looping processes.

KEY WORDS:

Oxygen transporter; Manganese; Bibliometric Analysis; CL, Machine Learning

PAGES: 73
BIG AREA: Ciências Exatas e da Terra
AREA: Química
SUBÁREA: Química Inorgânica
SPECIALTY: Físico Química Inorgânica
SUMMARY:

The scope of this dissertation consists of determining an optimized manganese-based oxygen carrier for application in Chemical Looping processes using bibliometric analysis and a Machine Learning platform. The bibliometric analysis performed in this study provides a comprehensive view of statistical data and trends related to manganese-based oxygen carriers for applications in Chemical Looping (CL) processes from 2006 to 2023. The search carried out in the Web of Science database resulted in a total of 426 documents, of which 65 were carefully selected using the ProKnow-C method to compose the study portfolio. Then, to carry out the bibliometric analysis (construction of tables, graphs and bibliometric maps) the Web of Science platform, VOSviewer and Excel were used. Soon after, an Excel spreadsheet was created containing the input and output data referring to the articles in the bibliographic portfolio for application on the Machine Learning platform developed for CLC, to determine an optimized manganese-based oxygen carrier. Then, the oxygen carrier determined by the platform will be experimentally reproduced and XRF, XRD, SEM and thermobalance reactivity analyzes will be carried out. Soon after, a comparison will be made between the oxygen carrier indicated by the platform and the one synthesized experimentally. Regarding the results of the bibliometric analysis, it is noteworthy that the author with the largest number of documents was A. Abad, with a total of 27 published articles. Furthermore, the area of Chemical Engineering was the most prominent, with 58 associated documents. It was observed that the period of greatest prolificacy in publications occurred between the years 2014 and 2022, with 2017 and 2018 being the years with the highest number of publications, with 8 and 10 documents, respectively. With regard to research sources, the magazine "Fuel" stood out in the last five years, with the identification of 7 relevant studies. Regarding the institutional affiliation of the authors, the majority of publications (30 documents) originated from research institutions based in Spain. The most cited document, with a total of 244 citations, was the work by Abad et al. (2006). It is worth mentioning that the most frequent keyword in the titles and abstracts of the articles selected for the portfolio was "Chemical-Looping Combustion", with 45 occurrences. Consequently, this bibliometric analysis reveals the considerable potential of manganese-based synthetic oxygen carriers for application in Chemical Looping processes. According to analyzes of the most relevant articles, these materials have been shown to have reduced friction rates and a low tendency to agglomerate in continuous fluidized bed reactors. Furthermore, the analysis will contribute to the optimization of the physicochemical properties of oxygen carriers, as it considered the influence of the type of active phase and support on reactivity tests, oxygen transport capacity, friction rate and agglomeration in continuous fluidized bed reactors in CL processes. The results of the Machine Learning platform are currently being implemented by the responsible company.

COMMITTEE MEMBERS:
Externo à Instituição - DENER DA SILVA ALBUQUERQUE - IFRN
Presidente - 349770 - DULCE MARIA DE ARAUJO MELO
Externo ao Programa - 3304576 - RODOLFO LUIZ BEZERRA DE ARAÚJO MEDEIROS - nullExterno à Instituição - TIAGO ROBERTO DA COSTA - IFRN