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Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil–Water Mixture (POME Model)

[Image: see text] Oil and grease remain the dominant contaminants in the palm oil mill effluent (POME) despite the conventional treatment of POME. The removal of residual oil from palm oil–water mixture (POME model) using the progressive freezing process was investigated. An optimization technique c...

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Autores principales: Anuar, Muhammad Athir Mohamed, Amran, Nurul Aini, Ruslan, Muhammad Syafiq Hazwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7860092/
https://www.ncbi.nlm.nih.gov/pubmed/33553888
http://dx.doi.org/10.1021/acsomega.0c04897
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author Anuar, Muhammad Athir Mohamed
Amran, Nurul Aini
Ruslan, Muhammad Syafiq Hazwan
author_facet Anuar, Muhammad Athir Mohamed
Amran, Nurul Aini
Ruslan, Muhammad Syafiq Hazwan
author_sort Anuar, Muhammad Athir Mohamed
collection PubMed
description [Image: see text] Oil and grease remain the dominant contaminants in the palm oil mill effluent (POME) despite the conventional treatment of POME. The removal of residual oil from palm oil–water mixture (POME model) using the progressive freezing process was investigated. An optimization technique called response surface methodology (RSM) with the design of rotatable central composite design was applied to figure out the optimum experimental variables generated by Design–Expert software (version 6.0.4. Stat-Ease, trial version). Besides, RSM also helps to investigate the interactive effects among the independent variables compared to one factor at a time. The variables involved are coolant temperature, X(A) (4–12 °C), freezing time, X(B) (20–60 min), and circulation flow, X(C) (200–600 rpm). The statistical analysis showed that a two-factor interaction model was developed using the obtained experimental data with a coefficient of determination (R(2)) value of 0.9582. From the RSM-generated model, the optimum conditions for extraction of oil from the POME model were a coolant temperature of 6 °C in 50 min freezing time with a circulation flowrate of 500 rpm. The validation of the model showed that the predicted oil yield and experimental oil yield were 92.56 and 93.20%, respectively.
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spelling pubmed-78600922021-02-05 Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil–Water Mixture (POME Model) Anuar, Muhammad Athir Mohamed Amran, Nurul Aini Ruslan, Muhammad Syafiq Hazwan ACS Omega [Image: see text] Oil and grease remain the dominant contaminants in the palm oil mill effluent (POME) despite the conventional treatment of POME. The removal of residual oil from palm oil–water mixture (POME model) using the progressive freezing process was investigated. An optimization technique called response surface methodology (RSM) with the design of rotatable central composite design was applied to figure out the optimum experimental variables generated by Design–Expert software (version 6.0.4. Stat-Ease, trial version). Besides, RSM also helps to investigate the interactive effects among the independent variables compared to one factor at a time. The variables involved are coolant temperature, X(A) (4–12 °C), freezing time, X(B) (20–60 min), and circulation flow, X(C) (200–600 rpm). The statistical analysis showed that a two-factor interaction model was developed using the obtained experimental data with a coefficient of determination (R(2)) value of 0.9582. From the RSM-generated model, the optimum conditions for extraction of oil from the POME model were a coolant temperature of 6 °C in 50 min freezing time with a circulation flowrate of 500 rpm. The validation of the model showed that the predicted oil yield and experimental oil yield were 92.56 and 93.20%, respectively. American Chemical Society 2021-01-20 /pmc/articles/PMC7860092/ /pubmed/33553888 http://dx.doi.org/10.1021/acsomega.0c04897 Text en © 2021 American Chemical Society This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
spellingShingle Anuar, Muhammad Athir Mohamed
Amran, Nurul Aini
Ruslan, Muhammad Syafiq Hazwan
Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil–Water Mixture (POME Model)
title Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil–Water Mixture (POME Model)
title_full Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil–Water Mixture (POME Model)
title_fullStr Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil–Water Mixture (POME Model)
title_full_unstemmed Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil–Water Mixture (POME Model)
title_short Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil–Water Mixture (POME Model)
title_sort optimization of progressive freezing for residual oil recovery from a palm oil–water mixture (pome model)
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7860092/
https://www.ncbi.nlm.nih.gov/pubmed/33553888
http://dx.doi.org/10.1021/acsomega.0c04897
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