Avaliação de fragmentos de lenhos carbonizados de araucariaceae por meio de termogravimetria e infravermelho associadas à análise multivariada

The aim of the study is to evaluate the physical and chemical changes that occur on wood fragments submitted to different temperatures, verifying their influence on significant chemical characteristics in the forming process. Carbonization process in muffle associated to the techniques of Thermograv...

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Detalles Bibliográficos
Autores: Lara, Daniela Muller de, Bresciani, Laís, Osterkamp, Isa Carla, Hilgemann, Maurício, Ethur, Eduardo Miranda, Jasper, André, Ferrão, Marco Flôres, Uhl, Dieter, Stulp, Simone
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:Brasil
Institución:Universidade Federal do Rio Grande do Sul (UFRGS)
Repositorio:Repositório Institucional da UFRGS
Idioma:portugués
OAI Identifier:oai:www.lume.ufrgs.br:10183/170668
Acceso en línea:http://hdl.handle.net/10183/170668
Access Level:acceso abierto
Palabra clave:Termogravimetria
Infravermelho
Análise multivariada
Descripción
Sumario:The aim of the study is to evaluate the physical and chemical changes that occur on wood fragments submitted to different temperatures, verifying their influence on significant chemical characteristics in the forming process. Carbonization process in muffle associated to the techniques of Thermogravimetry, Fourier Transform Infrared Spectroscopy (FTIR) and multivariate analysis. The analyses were performed on 3 replicates for each burn temperature. The temperature of the thermal muffle process was in every 50 °C, from 200 °C to 600 °C. TGA were performed under nitrogen atmosphere, using a heating ramp from 25 °C min-1 to 995 °C. A range between 1900 to 650 cm-1 was used, with a resolution of 4 cm-1 and 64 scans. The PCA showed that it is possible to describe 95.73% of the data, grouping the samples into three main clusters. These clusters were used to build a SIMCA (Soft Independent Modeling of Class Analogy) model, enabling to predict with 100%. Results showed that technical associations, such as TGA, FTIR and multivariate analysis may help to characterize the natural carbonization process and, in future works, contribute to significant (paleo)environmental inferences.