Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
The enzymatic and bio-enzymatic saccharification of waste broken rice (79.8% of starch) was successfully carried out to produce a reducible sugar solution (160 g/L). Bioethanol of concentration 71.2 g/L (9.0% v/v) was prepared by fermentation of reducing sugar solution, using the commercially available waste brewer's yeast (Saccharomyces cerevisiae). The fermentation process parameters were optimized through response surface methodology (RSM) and hybrid artificial neural network-genetic algorithm (ANN-GA) for optimizing the ethanol concentration. The hybrid ANN-GA model predicted a maximum concentration of 71.9 g/L with a deviation of only 0.97% from the experimental value (71.2 g/L). Four different kinetic models were attempted to fit the experimental time evolution of concentrations with the kinetic parameters estimated by the Levenberg-Marquardt optimization technique. The 4th order Runge-Kutta algorithm was implemented through a C program module. The accuracy of each model was checked against coefficient of determination R, adjusted R, the absolute mean deviation (AMD), and root mean square deviation (RMSD). The Andrew-Levenspiel kinetics produced the best performance criteria at two initial substrate concentrations of 160 and 170 g/L. Finally, the FTIR analysis of 781.2 g/L (98.5% v/v) bioethanol (concentrated by two-stage vacuum distillation followed by treatment with 3A molecular sieve) showed a favorable blending possibility with the commercial gasoline (petrol) as a green fuel.
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Source |
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http://dx.doi.org/10.1007/s12010-022-03858-z | DOI Listing |
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