| Literature DB >> 34883646 |
Mubarak Usman Kankia1, Lavania Baloo1, Nasiru Danlami2, Bashar S Mohammed1, Sani Haruna1,2, Mahmud Abubakar3, Ahmad Hussaini Jagaba1, Khalid Sayed1, Isyaka Abdulkadir1, Ibrahim Umar Salihi2.
Abstract
Petroleum sludge is a waste product resulting from petroleum industries and it is a major source of environmental pollution. Therefore, developing strategies aimed at reducing its environmental impact and enhance cleaner production are crucial for environmental mortar. Response surface methodology (RSM) was used in designing the experimental work. The variables considered were the amount of petroleum sludge ash (PSA) in weight percent and the ratio of sodium silicate to sodium hydroxide, while the concentration of sodium hydroxide was kept constant in the production of geopolymer mortar cured at a temperature of 60 °C for 20 h. The effects of PSA on density, compressive strength, flexural strength, water absorption, drying shrinkage, morphology, and pore size distribution were investigated. The addition of PSA in the mortar enhanced the mechanical properties significantly at an early age and 28 days of curing. Thus, PSA could be used as a precursor material in the production of geopolymer mortar for green construction sustainability. This study aimed to investigate the influence of PSA in geopolymer mortar.Entities:
Keywords: fly ash; geopolymer mortar; mechanical properties; microstructural properties; petroleum sludge ash; response surface methodology
Year: 2021 PMID: 34883646 PMCID: PMC8659964 DOI: 10.3390/polym13234143
Source DB: PubMed Journal: Polymers (Basel) ISSN: 2073-4360 Impact factor: 4.329
Chemical composition of PSA and fly ash (%).
| Al2O3 | SiO2 | Fe2O3 | CaO | MgO | P2O5 | SO3 | K2O | TiO2 | Others | LOI | Blaine Fineness (m2/kg) | Specific Gravity | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PSA | 10.00 | 14.90 | 45.90 | 9.26 | 2.41 | 1.75 | 11.5 | 1.08 | 0.41 | 2.70 | 0.09 | 117 | 2.35 |
| FA | 17.40 | 36.40 | 20.20 | 14.5 | 2.40 | 1.27 | 2.01 | 2.31 | 1.59 | 1.64 | 0.28 | 384 | 2.68 |
Figure 1FESEM image of (a) PSA (b) FA.
Figure 2XRD graph of PSA.
RSM boundaries of variables.
| Factors | Code | Units | Levels | ||
|---|---|---|---|---|---|
| −1 | 0 | +1 | |||
| PSA | A | % | 0 | 10 | 20 |
| NS: NH | B | 1.5 | 2.0 | 2.5 | |
Mix formulations of modified geopolymer mortar.
| Mixtures | P20R2 | P10R2 | P10R2 | P20R1.5 | P0R2 | P0R1.5 | P10R2 | P20R2.5 | P10R2 | P10R2 | P10R1.5 | P10R2.5 | P0R2.5 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| A: PSA (%) | 20 | 10 | 10 | 20 | 0 | 0 | 10 | 20 | 10 | 10 | 10 | 10 | 0 |
| B: NS: NH | 2 | 2 | 2 | 1.5 | 2 | 1.5 | 2 | 2.5 | 2 | 2 | 1.5 | 2.5 | 2.5 |
Mixture proportion of geopolymer mortar.
| Sand (kg/m3) | Alkaline Solution (kg/m3) | PSA (%) | Fly Ash (kg/m3) | PSA Content (kg/m3) |
|---|---|---|---|---|
| 1314.29 | 328.57 | 0 | 657.14 | 0 |
| 1314.29 | 328.57 | 10 | 591.43 | 65.71 |
| 1314.29 | 328.57 | 20 | 525.71 | 131.43 |
Figure 3Densities of geopolymer mortar samples.
Figure 4Compressive strength growth of geopolymer mortar.
Figure 52-D and 3-D plots for flexural strength of geopolymer mortar.
Figure 6Water absorption of geopolymer mortar at 28 days.
Figure 7Drying shrinkage of geopolymer mortar.
Figure 8FESEM images with EDX (a) P0R2, (b) P10R2, (c) P20R2 geopolymer mortar.
Figure 9Pore size distribution for P0R2, P10R2, and P20R2 geopolymer mortar.
Pore structure properties of geopolymer mortar.
| Mixture | Modal Pore Diameter D10 | Median Pore Diameter D90 | Average Pore Diameter D50 | Total Surface Area | Porosity |
|---|---|---|---|---|---|
| P0R2 | 11,746.79 | 13,619.79 | 118.66 | 2.355 | 12.89 |
| P10R2 | 16.69 | 3166.26 | 135.90 | 1.155 | 0.25 |
| P20R2 | 18,151.37 | 2418.80 | 119.93 | 2.017 | 13.01 |
Polycyclic aromatics hydrocarbons (PAHs) mg/kg.
| Parameters | Abbreviation | No. of PAHs Rings | PSA | P10R2 | P20R2 | Permissible Limits [ |
|---|---|---|---|---|---|---|
| Naphthalene | Nap | 2 | <0.5 | <0.5 | <0.5 | 5.52 |
| Acenaphthylene | Acy | 3 | <0.5 | <0.5 | <0.5 | NA |
| Acenaphthene | Ace | 3 | <0.5 | <0.5 | <0.5 | 3590 |
| Fluorene | Fle | 3 | <0.5 | <0.5 | <0.5 | 2390 |
| Phenanthrene | Phe | 3 | 1.9 | <0.5 | <0.5 | NA |
| Anthracene | Ant | 3 | <0.5 | <0.5 | <0.5 | 17,900 |
| Fluoranthene | Fla | 4 | <0.5 | <0.5 | <0.5 | 2390 |
| Pyrene | Pyr | 4 | <0.5 | <0.5 | <0.5 | 1790 |
| Benz(a)anthracene | BaA | 4 | <0.5 | <0.5 | <0.5 | 1.14 |
| Chrysene | Chr | 4 | <0.5 | <0.5 | <0.5 | 115 |
| Benzo(b)fluoranthene | BbF | 5 | <1.0 | <1.0 | <1.0 | 1.15 |
| Benzo(k)fluoranthene | BkF | 5 | <1.0 | <1.0 | <1.0 | 11.5 |
| Benzo(a)pyrene | BaP | 5 | <0.05 | <0.05 | <0.05 | 0.115 |
| Indeno(1.2.3.cd)pyrene | IcdP | 6 | <0.5 | <0.5 | <0.5 | 1.15 |
| Dibenzo(a.h)anthracene | DahA | 5 | <0.5 | <0.5 | <0.5 | 0.115 |
| Benzo(g.h.i)perylene | BghiP | 6 | <0.5 | <0.5 | <0.5 | NA |
Analysis of variance for response models.
| Responses | Factors | SS | Df | MS | F-Value | Remarks | |
|---|---|---|---|---|---|---|---|
| Flexural strength (MPa) | Model | 7.58 | 2 | 3.79 | 59.31 | <0.0001 | Significant |
| A-PSA | 3.32 | 1 | 3.32 | 51.87 | <0.0001 | ||
| B- NS: NH | 4.27 | 1 | 4.27 | 66.76 | <0.0001 | ||
| Lack of Fit | 0.48 | 6 | 0.080 | 2.03 | 0.2567 | Not significant | |
| Water absorption (%) | Model | 1.14 | 2 | 0.57 | 136.65 | <0.0001 | Significant |
| A-PSA | 4.167 × 10−4 | 1 | 4.167 × 10−4 | 0.10 | 0.7580 | ||
| B- NS: NH | 1.14 | 1 | 1.14 | 273.21 | <0.0001 | ||
| Lack of Fit | 0.013 | 6 | 2.139 × 10−3 | 0.30 | 0.9094 | Not significant |
Where SS: the sum of squares; Df: the degree of freedom, P: Probability; F: Fisher statistical value; MS: mean square.
Validation properties of response models.
| Response variable | SD | Mean | R2 | Adj. R2 | Pred. R2 | AP |
|---|---|---|---|---|---|---|
| Flexural strength (MPa) | 0.25 | 5.29 | 0.9223 | 0.9067 | 0.8597 | 26.128 |
| Water absorption (%) | 0.064 | 4.71 | 0.9647 | 0.9576 | 0.9487 | 28.632 |
Where SD: Standard deviation, R2: correlation coefficient, Adj. R2: adjusted correlation coefficient, Pred. R2: predicted R2, AP: adequate precision.
Figure 10Predicted vs. actual and normal plot of residuals for output variables.
Optimization benchmarks.
| Variables and Responses | Unit | Goals | Lower Limit | Upper Limit |
|---|---|---|---|---|
| PSA | % | In range | 0 | 20 |
| NS to NH ratio | In range | 1.5 | 2.5 | |
| Flexural strength (MPa) | MPa | Maximize | 3.4 | 6.61 |
| Water absorption | (%) | Minimize | 4.3 | 5.18 |
Figure 11Desirable combination of PSA with the ratio of sodium silicate to sodium hydroxide.
Figure 12Optimization ramps of the geopolymer mortar.
Model validation.
| Responses | PSA (%) | NS To NH Ratio | Predicted Outcomes | Experimental Outcomes | Error (%) |
|---|---|---|---|---|---|
| Flexural | 18.58 | 2.5 | 6.76 | 6.90 | 2.03 |
| 10 | 2 | 5.29 | 5.61 | 5.70 | |
| 20 | 2 | 6.03 | 5.70 | 5.79 | |
| Water absorption (%) | 18.58 | 2.5 | 4.29 | 4.48 | 4.24 |
| 10 | 2 | 4.71 | 5.0 | 5.8 | |
| 20 | 2 | 4.72 | 5.0 | 5.6 |