Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros











Base de dados
Intervalo de ano de publicação
1.
Bioresour Technol ; 243: 760-770, 2017 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-28711805

RESUMO

The present study examines the use of Artificial Neural Networks (ANN) as prediction and fault detection tools for the delignification process of sugarcane bagasse via hydrogen peroxide (H2O2). Experimental conditions varied from 25 to 45°C for temperature and from 1.5% to 7.5% (v/v) for H2O2 concentrations. Analytical results for the delignification were obtained by Fourier Transform Infrared (FT-IR) analysis and used for the ANN training and testing steps, allowing for the development of ANN models. The condition experimentally identified as the most suitable for the delignification process was of 25°C with 4.5% (v/v) H2O2, oxidizing 54% of total lignin. An ANN topology was selected for each proposed model, whose performance was evaluated by the correlation coefficient (R2) and error indices (MSE and SSE). The values obtained for R2 and the error indices indicated good agreements of the theoretical and actual data, of close to 1 and close to 0, respectively.


Assuntos
Peróxido de Hidrogênio , Lignina , Saccharum , Celulose , Espectroscopia de Infravermelho com Transformada de Fourier
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA