Designing an Efficient Surfactant–Polymer–Oil–Electrolyte System: A Multi-Objective Optimization Study Article Swipe
M. Nedjhioui
,
Noureddine Nasrallah
,
Mohammed Kebir
,
Hichem Tahraoui
,
Rachida Bouallouche
,
Aymen Amine Assadi
,
Abdeltif Amrane
,
Bassem Jaouadi
,
Jie Zhang
,
Lotfi Mouni
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/pr11051314
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/pr11051314
This research aimed to study the effects of individual components on the physicochemical properties of systems composed of surfactants, polymers, oils, and electrolytes in order to maximize the recovery efficiency of kerosene while minimizing the impact on the environment and human health. Four independent factors, namely anionic surfactant sodium dodecylbenzene sulfonate (X1) (SDBS), oil (X2) (kerosene), water-soluble polymer poly(ethylene glycol) (X3) (PEG), and sodium chloride (X4) (NaCl), were studied using the full factorial design (FFD) model. Four output variables, namely conductivity (Y1), turbidity (Y2), viscosity (Y3), and interfacial tension (IFT) (Y4), were taken as the response variables. All four FFD models have high coefficients of determination and low errors. The developed models were used in a multi-objective optimization (MOO) framework to determine the optimal conditions. The obtained optimal conditions are X1 = 0.01, X2 = 50, X3 = 5, and X4 = 0.1, with an error of 0.9414 between the predicted and experimental objective function values. This result shows the efficiency of the model developed and the system used for the recovery of kerosene, while also having a positive effect on the protection of the environment.
Related Topics
Concepts
Kerosene
Dodecylbenzene
Pulmonary surfactant
Electrolyte
Factorial experiment
Polymer
Ethylene glycol
Chemical engineering
PEG 400
Sodium
Response surface methodology
Chemistry
Surface tension
Sulfonate
Materials science
Chromatography
Thermodynamics
Polyethylene glycol
Mathematics
Organic chemistry
Biochemistry
Electrode
Physics
Physical chemistry
Engineering
Statistics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/pr11051314
- https://www.mdpi.com/2227-9717/11/5/1314/pdf?version=1682333414
- OA Status
- gold
- Cited By
- 29
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4366830146
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4366830146Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/pr11051314Digital Object Identifier
- Title
-
Designing an Efficient Surfactant–Polymer–Oil–Electrolyte System: A Multi-Objective Optimization StudyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-04-24Full publication date if available
- Authors
-
M. Nedjhioui, Noureddine Nasrallah, Mohammed Kebir, Hichem Tahraoui, Rachida Bouallouche, Aymen Amine Assadi, Abdeltif Amrane, Bassem Jaouadi, Jie Zhang, Lotfi MouniList of authors in order
- Landing page
-
https://doi.org/10.3390/pr11051314Publisher landing page
- PDF URL
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https://www.mdpi.com/2227-9717/11/5/1314/pdf?version=1682333414Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2227-9717/11/5/1314/pdf?version=1682333414Direct OA link when available
- Concepts
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Kerosene, Dodecylbenzene, Pulmonary surfactant, Electrolyte, Factorial experiment, Polymer, Ethylene glycol, Chemical engineering, PEG 400, Sodium, Response surface methodology, Chemistry, Surface tension, Sulfonate, Materials science, Chromatography, Thermodynamics, Polyethylene glycol, Mathematics, Organic chemistry, Biochemistry, Electrode, Physics, Physical chemistry, Engineering, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
29Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 14, 2024: 12, 2023: 3Per-year citation counts (last 5 years)
- References (count)
-
42Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.study | 4 |
| abstract_inverted_index.taken | 92 |
| abstract_inverted_index.using | 69 |
| abstract_inverted_index.while | 32, 174 |
| abstract_inverted_index.(PEG), | 61 |
| abstract_inverted_index.0.9414 | 147 |
| abstract_inverted_index.design | 73 |
| abstract_inverted_index.effect | 179 |
| abstract_inverted_index.having | 176 |
| abstract_inverted_index.impact | 35 |
| abstract_inverted_index.model. | 75 |
| abstract_inverted_index.models | 100, 111 |
| abstract_inverted_index.namely | 45, 79 |
| abstract_inverted_index.output | 77 |
| abstract_inverted_index.result | 157 |
| abstract_inverted_index.sodium | 48, 63 |
| abstract_inverted_index.system | 167 |
| abstract_inverted_index.(NaCl), | 66 |
| abstract_inverted_index.(SDBS), | 52 |
| abstract_inverted_index.anionic | 46 |
| abstract_inverted_index.between | 148 |
| abstract_inverted_index.effects | 6 |
| abstract_inverted_index.errors. | 108 |
| abstract_inverted_index.glycol) | 59 |
| abstract_inverted_index.health. | 41 |
| abstract_inverted_index.optimal | 123, 127 |
| abstract_inverted_index.polymer | 57 |
| abstract_inverted_index.studied | 68 |
| abstract_inverted_index.systems | 15 |
| abstract_inverted_index.tension | 88 |
| abstract_inverted_index.values. | 155 |
| abstract_inverted_index.chloride | 64 |
| abstract_inverted_index.composed | 16 |
| abstract_inverted_index.factors, | 44 |
| abstract_inverted_index.function | 154 |
| abstract_inverted_index.kerosene | 31 |
| abstract_inverted_index.maximize | 26 |
| abstract_inverted_index.obtained | 126 |
| abstract_inverted_index.positive | 178 |
| abstract_inverted_index.recovery | 28, 171 |
| abstract_inverted_index.research | 1 |
| abstract_inverted_index.response | 95 |
| abstract_inverted_index.determine | 121 |
| abstract_inverted_index.developed | 110, 164 |
| abstract_inverted_index.factorial | 72 |
| abstract_inverted_index.framework | 119 |
| abstract_inverted_index.kerosene, | 173 |
| abstract_inverted_index.objective | 153 |
| abstract_inverted_index.polymers, | 19 |
| abstract_inverted_index.predicted | 150 |
| abstract_inverted_index.sulfonate | 50 |
| abstract_inverted_index.turbidity | 82 |
| abstract_inverted_index.viscosity | 84 |
| abstract_inverted_index.components | 9 |
| abstract_inverted_index.conditions | 128 |
| abstract_inverted_index.efficiency | 29, 160 |
| abstract_inverted_index.individual | 8 |
| abstract_inverted_index.minimizing | 33 |
| abstract_inverted_index.properties | 13 |
| abstract_inverted_index.protection | 182 |
| abstract_inverted_index.surfactant | 47 |
| abstract_inverted_index.variables, | 78 |
| abstract_inverted_index.variables. | 96 |
| abstract_inverted_index.(kerosene), | 55 |
| abstract_inverted_index.conditions. | 124 |
| abstract_inverted_index.environment | 38 |
| abstract_inverted_index.independent | 43 |
| abstract_inverted_index.interfacial | 87 |
| abstract_inverted_index.coefficients | 103 |
| abstract_inverted_index.conductivity | 80 |
| abstract_inverted_index.electrolytes | 22 |
| abstract_inverted_index.environment. | 185 |
| abstract_inverted_index.experimental | 152 |
| abstract_inverted_index.optimization | 117 |
| abstract_inverted_index.surfactants, | 18 |
| abstract_inverted_index.determination | 105 |
| abstract_inverted_index.poly(ethylene | 58 |
| abstract_inverted_index.water-soluble | 56 |
| abstract_inverted_index.dodecylbenzene | 49 |
| abstract_inverted_index.multi-objective | 116 |
| abstract_inverted_index.physicochemical | 12 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 5 |
| institutions_distinct_count | 10 |
| citation_normalized_percentile.value | 0.9622803 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |