Determination of the Thermal Parameters of Geopolymers Modified with Iron Powder
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Methods
3. Results and Discussion
3.1. Density Results
3.2. Results of Thermal Properties and Their Discussion
4. Conclusions
- The addition of iron to the geopolymers caused significant changes in their thermal properties, such as thermal conductivity, specific heat, and thermal diffusivity.
- It was found that the addition of sand or fireclay had a significant influence on the thermal parameters of the obtained composites. The samples after the drying process were characterized by lower values of thermal parameters. The samples with sand were characterized by higher values of thermal conductivity when compared to the samples with fireclay. The highest values of thermal conductivity λ, exceeding 1 W(m·K), were exhibited by the samples containing the geopolymer with sand in the ratio of 1:1.2. The addition of fireclay caused a decrease in the thermal conductivity of the composites by at least 30% when compared to the samples with the addition of sand.
- The lowest value of the thermal conductivity coefficient λ was obtained for the geopolymer with metakaolin and fireclay. When the ratio of these components in the composite was 1:1, the value of thermal conductivity was 0.6413 W/(m·K), while in the case of the ratio of 1:1.2, it was equal to 0.6456 W/(m·K).
- The materials with sand had a thermal conductivity within the range from 0.8865 W/(m·K) to 1.3791 W/(m·K). The thermal conductivity value with the sand in the ratio of 1:1 was 1.3791 W/(m·K) for the non-iron samples. For the samples with the addition of 2.5% Fe, the conductivity decreased to 1.2019 /(m·K). There was a decrease in this value by 12.8%. The non-iron samples containing the geopolymer with sand in the ratio of 1:1.2 had a thermal conductivity equal to 0.9657 W/(m·K), and the samples containing the geopolymer with sand in the ratio of 1:1.2 with the addition of 2.5% Fe had a thermal conductivity equal to 0.9109 W/(m·K). The addition of iron reduced the thermal conductivity by 5.7%.
- In the samples containing fireclay, there was no significant influence of the added iron on the values of thermal conductivity. In turn, in the case of the geopolymer with sand, this influence was noticeable. It was most visible in the samples containing metakaolin and sand in the ratio of 1:1.2. Therefore, it was noticed that the thermal conductivity of the composites increased with the increase in the addition of Fe.
- In the case of specific heat and thermal diffusivity, the samples with sand were also characterized by higher values of these parameters when compared to the samples with fireclay. The samples with fireclay showed very good stability, i.e., there were no changes in thermal diffusivity with regard to the addition of iron.
- For the samples containing geopolymer with sand in the ratio of 1:1.2 and with a 2% addition of iron, the specific heat value was the lowest and amounted to 830 J/(kg·K). It was an almost 15% decrease in the specific heat value when compared to the samples without the addition of iron. The materials with fireclay had a thermal diffusivity within the range from 0.3834 mm2/s to 0.4094 mm2/s. The samples containing sand had a thermal diffusivity of 0.5333–0.7706 mm2/s.
- The calculated densities ρb1 and ρb2 of the obtained geopolymer composites did not differ significantly, despite the use of different calculation methods. In the first case, the density was calculated on the basis of the known weight and volume of the samples. In the second case, the density calculations were based on the known thermal properties of the samples.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Davidovits, J. Geopolymers: Ceramic-like inorganic polymers. J. Ceram. Sci. Technol. 2017, 8, 335–350. [Google Scholar]
- Kalaw, M.E.; Culaba, A.; Hinode, H.; Kurniawan, W.; Gallardo, S.; Promentilla, M.A. Optimizing and Characterizing Geopolymers from Ternary Blend of Philippine Coal Fly Ash, Coal Bottom Ash and Rice Hull Ash. Materials 2016, 9, 580. [Google Scholar] [CrossRef] [PubMed]
- Hájková, P. Kaolinite claystone-based geopolymer materials: Effect of chemical composition and curing conditions. Minerals 2018, 8, 444. [Google Scholar] [CrossRef] [Green Version]
- Prochon, P.; Zhao, Z.; Courard, L.; Piotrowski, T.; Michel, F.; Garbacz, A. Influence of activators on mechanical properties of modified fly ash based geopolymer mortars. Materials 2020, 13, 1033. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Samantasinghar, S.; Singh, S.P. Effect of synthesis parameters on compressive strength of fly ash-slag blended geopolymer. Constr. Build. Mater. 2018, 170, 225–234. [Google Scholar] [CrossRef]
- Rocha, S.; Martin-del-Rio, J.J.; Alejandre, F.J.; García-Heras, J.; Jimenez-Aguilar, A. Metakaolin-based geopolymer mortars with different alkaline activators (Na+ and K+). Constr. Build. Mater. 2018, 178, 453–461. [Google Scholar] [CrossRef]
- Glukhovsky, Y.D.; Rostovskaja, G.S.; Rumyna, G.V. High-strength Slag-Alkaline Cements. In Proceedings of the 7th International Congress on the Chemistry of Cement, Geophysics and Space Physics, Paris, France, 30 June–4 July 1980; Volume 13, pp. 64–168. [Google Scholar]
- Vohlídal, J.; Julák, A.; Štulík, K. Chemické a Analytické Tabulky; Grada Publishing: Praha, Czechia, 1999. [Google Scholar]
- Peng, X.; Shuai, Q.; Li, H.; Ding, Q.; Gu, Y.; Cheng, C.; Xu, Z. Fabrication and Fireproofing Performance of the Coal Fly Ash-Metakaolin-Based Geopolymer Foams. Materials 2020, 13, 1750. [Google Scholar] [CrossRef] [Green Version]
- Davidovits, J. Geopolymer Chemistry and Applications, 5th ed.; Geopolymer Institute: Saint-Quentin, France, 2020. [Google Scholar]
- **, J.; Huisken, P.W.M.; Deutou, J.; Courard, L. Iron-rich laterite-bagasse fibers based geopolymer composite: Mechanical, durability and insulating properties. Appl. Clay Sci. 2019, 183, 105333. [Google Scholar] [CrossRef] [Green Version]
Tested Sample | Metakaolin [g] | Activator [g] | Sand [g] | Fireclay [g] | Fe Powder [g] |
---|---|---|---|---|---|
Reference sample (RSS1) | 100 | 90 | 100 | - | 0 |
Geopolymer: Sand (1:1) + Fe0.5% (GS1Fe0.5) | 100 | 90 | 100 | - | 0.5 |
Geopolymer: Sand (1:1) + Fe1.0% (GS1Fe1.0) | 100 | 90 | 100 | - | 1.0 |
Geopolymer: Sand (1:1) + Fe1.5% (GS1Fe1.5) | 100 | 90 | 100 | - | 1.5 |
Geopolymer: Sand (1:1) + Fe2.0% (GS1Fe2.0) | 100 | 90 | 100 | - | 2.0 |
Geopolymer: Sand (1:1) + Fe2.5% (GS1Fe2.5) | 100 | 90 | 100 | - | 2.5 |
Reference sample (RSS1.2) | 100 | 90 | 120 | - | 0 |
Geopolymer: Sand (1:1.2) + Fe0.5% (GS1.2Fe0.5) | 100 | 90 | 120 | - | 0.5 |
Geopolymer: Sand (1:1.2) + Fe1.0% (GS1.2Fe1.0) | 100 | 90 | 120 | - | 1.0 |
Geopolymer: Sand (1:1.2) + Fe1.5% (GS1.2Fe1.5) | 100 | 90 | 120 | - | 1.5 |
Geopolymer: Sand (1:1.2) + Fe2.0% (GS1.2Fe2.0) | 100 | 90 | 120 | - | 2.0 |
Geopolymer: Sand (1:1.2) + Fe2.5% (GS1.2Fe2.0) | 100 | 90 | 120 | - | 2.5 |
Reference sample (RSF1) | 100 | 90 | - | 100 | 0 |
Geopolymer: Fireclay (1:1) + Fe0.5% (GF1Fe0.5) | 100 | 90 | - | 100 | 0.5 |
Geopolymer: Fireclay (1:1) + Fe1.0% (GF1Fe1.0) | 100 | 90 | - | 100 | 1.0 |
Geopolymer: Fireclay (1:1) + Fe1.5% (GF1Fe1.5) | 100 | 90 | - | 100 | 1.5 |
Geopolymer: Fireclay (1:1) + Fe2.0% (GF1Fe2.0) | 100 | 90 | - | 100 | 2.0 |
Geopolymer: Fireclay (1:1) + Fe2.5% (GF1Fe2.5) | 100 | 90 | - | 100 | 2.5 |
Reference sample (RSF1.2) | 100 | 90 | - | 120 | 0 |
Geopolymer: Fireclay (1:1.2) + Fe0.5% (GF1.2Fe0.5) | 100 | 90 | - | 120 | 0.5 |
Geopolymer: Fireclay (1:1.2) + Fe1.0% (GF1.2Fe1.0) | 100 | 90 | - | 120 | 1.0 |
Geopolymer: Fireclay (1:1.2) + Fe1.5% (GF1.2Fe1.5) | 100 | 90 | - | 120 | 1.5 |
Geopolymer: Fireclay (1:1.2) + Fe2.0% (GF1.2Fe2.0) | 100 | 90 | - | 120 | 2.0 |
Geopolymer: Fireclay (1:1.2) + Fe2.5% (GF1.2Fe2.5) | 100 | 90 | - | 120 | 2.5 |
Tested Sample | Before Drying | After Drying | ||
---|---|---|---|---|
ρb1 [kg/m3] | ρb2 [kg/m3] | ρb1 [kg/m3] | ρb2 [kg/m3] | |
RSS1 | 1894 | 1899 | 1854 | 1854 |
GS1Fe0.5 | 1872 | 1868 | 1840 | 1841 |
GS1Fe1.0 | 1844 | 1831 | 1818 | 1818 |
GS1Fe1.5 | 1860 | 1861 | 1842 | 1824 |
GS1Fe2.0 | 1876 | 1876 | 1768 | 1716 |
GS1Fe2.5 | 1880 | 1743 | 1854 | 1854 |
RSS1.2 | 1926 | 1926 | 1846 | 1845 |
GS1.2Fe0.5 | 1838 | 1845 | 1822 | 1811 |
GS1.2Fe1.0 | 1882 | 1775 | 1866 | 1866 |
GS1.2Fe1.5 | 1922 | 1903 | 1860 | 1859 |
GS1.2Fe2.0 | 1974 | 1959 | 1946 | 1875 |
GS1.2Fe2.5 | 1997 | 1996 | 1953 | 1953 |
RSF1 | 1926 | 1857 | 1900 | 1900 |
GF1Fe0.5 | 1866 | 1888 | 1840 | 1840 |
GF1Fe1.0 | 1912 | 1904 | 1886 | 1886 |
GF1Fe1.5 | 1921 | 1913 | 1889 | 1890 |
GF1Fe2.0 | 1930 | 1990 | 1918 | 1918 |
GF1Fe2.5 | 1922 | 2132 | 1892 | 1892 |
RSF1.2 | 1914 | 1911 | 1880 | 1880 |
GF1.2Fe0.5 | 1976 | 1976 | 1942 | 1942 |
GF1.2Fe1.0 | 1906 | 1894 | 1876 | 1876 |
GF1.2Fe1.5 | 1988 | 1988 | 1954 | 1954 |
GF1.2Fe2.0 | 1940 | 1937 | 1854 | 1859 |
GF1.2Fe2.5 | 1970 | 1959 | 1940 | 1940 |
Tested Sample | Designated Confidence Intervals | |
---|---|---|
Samples Conditioned in Hygrothermal Conditions | Samples Conditioned in the Dryer | |
RSS1 | P (1.3787 ≤ λ ≤ 1.7545) = 1 − α | P (0.9622 ≤ λ ≤ 0.9691) = 1 − α |
P (914.0 ≤ Cp ≤ 999.4) = 1 − α | P (976.0 ≤ Cp ≤ 977.4) = 1 − α | |
P (0.7951 ≤ a ≤ 0.9298) = 1 − α | P (0.5307 ≤ a ≤ 0.5359) = 1 − α | |
GS1Fe0.5 | P (1.4302 ≤ λ ≤ 1.5226) = 1 − α | P (0.9416 ≤ λ ≤ 0.9559) = 1 − α |
P (934.4 ≤ Cp ≤ 1003.1) = 1 − α | P (866.3 ≤ Cp ≤ 866.9) = 1 − α | |
P (0.8091 ≤ a ≤ 0.8229) = 1 − α | P (0.5902 ≤ a ≤ 0.5997) = 1 − α | |
GS1Fe1.0 | P (0.9957 ≤ λ ≤ 1.0664) = 1 − α | P (0.9056 ≤ λ ≤ 0.9116) = 1 − α |
P (817.6 ≤ Cp ≤ 933.4) = 1 − α | P (935.2 ≤ Cp ≤ 936.9) = 1 − α | |
P (0.6193 ≤ a ≤ 0.6672) = 1 − α | P (0.5326 ≤ a ≤ 0.5353) = 1 − α | |
GS1Fe1.5 | P (1.1346 ≤ λ ≤ 1.3772) = 1 − α | P (1.0864 ≤ λ ≤ 1.0896) = 1 − α |
P (885.7 ≤ Cp ≤ 922.0) = 1 − α | P (901.9 ≤ Cp ≤ 930.8) = 1 − α | |
P (0.6844 ≤ a ≤ 0.8086) = 1 − α | P (0.6489 ≤ a ≤ 0.6533) = 1 − α | |
GS1Fe2.0 | P (0.9975 ≤ λ ≤ 1.2343) = 1 − α | P (0.8840 ≤ λ ≤ 0.8889) = 1 − α |
P (915.4 ≤ Cp ≤ 917.8) = 1 − α | P (921.9 ≤ Cp ≤ 924.7) = 1 − α | |
P (0.5806 ≤ a ≤ 0.7171) = 1 − α | P (0.5167 ≤ a ≤ 0.6023) = 1 − α | |
GS1Fe2.5 | P (1.0430 ≤ λ ≤ 1.0505) = 1 − α | P (0.9096 ≤ λ ≤ 0.9122) = 1 − α |
P (868.6 ≤ Cp ≤ 878.1) = 1 − α | P (899.6 ≤ Cp ≤ 902.4) = 1 − α | |
P (0.5585 ≤ a ≤ 0.8166) = 1 − α | P (0.5438 ≤ a ≤ 0.5466) = 1 − α | |
RSS1.2 | P (1.9437 ≤ λ ≤ 1.9710) = 1 − α | P (1.3765 ≤ λ ≤ 1.3817) = 1 − α |
P (969.4 ≤ Cp ≤ 987.3) = 1 − α | P (969.3 ≤ Cp ≤ 970.7) = 1 − α | |
P (1.0350 ≤ a ≤ 1.0425) = 1 − α | P (0.7684 ≤ a ≤ 0.7727) = 1 − α | |
GS1.2Fe0.5 | P (1.0935 ≤ λ ≤ 1.4564) = 1 − α | P (1.0202 ≤ λ ≤ 1.0389) = 1 − α |
P (870.6 ≤ Cp ≤ 984.0) = 1 − α | P (910.8 ≤ Cp ≤ 916.6) = 1 − α | |
P (0.6843 ≤ a ≤ 0.8062) = 1 − α | P (0.6150 ≤ a ≤ 0.6296) = 1 − α | |
GS1.2Fe1.0 | P (1.4347 ≤ λ ≤ 1.4384) = 1 − α | P (0.9854 ≤ λ ≤ 1.1019) = 1 − α |
P (870.9 ≤ Cp ≤ 934.3) = 1 − α | P (829.9 ≤ Cp ≤ 831.6) = 1 − α | |
P (0.8947 ≤ a ≤ 0.8982) = 1 − α | P (0.6386 ≤ a ≤ 0.7081) = 1 − α | |
GS1.2Fe1.5 | P (1.7000 ≤ λ ≤ 1.8362) = 1 − α | P (1.0523 ≤ λ ≤ 1.0560) = 1 − α |
P (896.1 ≤ Cp ≤ 1066.9) = 1 − α | P (895.6 ≤ Cp ≤ 898.2) = 1 − α | |
P (0.8620 ≤ a ≤ 1.0311) = 1 − α | P (0.6305 ≤ a ≤ 0.6339) = 1 − α | |
GS1.2Fe2.0 | P (1.2145 ≤ λ ≤ 1.4333) = 1 − α | P (1.1701 ≤ λ ≤ 1.1952) = 1 − α |
P (797.8 ≤ Cp ≤ 911.4) = 1 − α | P (828.3 ≤ Cp ≤ 832.3) = 1 − α | |
P (0.6733 ≤ a ≤ 0.9080) = 1 − α | P (0.7148 ≤ a ≤ 0.8045) = 1 − α | |
GS1.2Fe2.5 | P (1.3518 ≤ λ ≤ 1.5082) = 1 − α | P (1.2001 ≤ λ ≤ 1.2037) = 1 − α |
P (825.8 ≤ Cp ≤ 845.3) = 1 − α | P (846.6 ≤ Cp ≤ 849.3) = 1 − α | |
P (0.8007 ≤ a ≤ 0.9141) = 1 − α | P (0.7234 ≤ a ≤ 0.7285) = 1 − α | |
RSF1 | P (0.8500 ≤ λ ≤ 1.0576) = 1 − α | P (0.6374 ≤ λ ≤ 0.6451) = 1 − α |
P (887.8 ≤ Cp ≤ 943.2) = 1 − α | P (860.6 ≤ Cp ≤ 861.4) = 1 − α | |
P (0.5500 ≤ a ≤ 0.5717) = 1 − α | P (0.3891 ≤ a ≤ 0.3950) = 1 − α | |
GF1Fe0.5 | P (0.8099 ≤ λ ≤ 0.8442) = 1 − α | P (0.6593 ≤ λ ≤ 0.6619) = 1 − α |
P (909.4 ≤ Cp ≤ 914.0) = 1 − α | P (935.4 ≤ Cp ≤ 936.4) = 1 − α | |
P (0.4573 ≤ a ≤ 0.5035) = 1 − α | P (0.3819 ≤ a ≤ 0.3853) = 1 − α | |
GF1Fe1.0 | P (0.9089 ≤ λ ≤ 0.9483) = 1 − α | P (0.6884 ≤ λ ≤ 0.6904) = 1 − α |
P (824.9 ≤ Cp ≤ 937.8) = 1 − α | P (863.5 ≤ Cp ≤ 864.4) = 1 − α | |
P (0.5062 ≤ a ≤ 0.6005) = 1 − α | P (0.4223 ≤ a ≤ 0.4239) = 1 − α | |
GF1Fe1.5 | P (0.7955 ≤ λ ≤ 0.9988) = 1 − α | P (0.7021 ≤ λ ≤ 0.7100) = 1 − α |
P (834.3 ≤ Cp ≤ 898.8) = 1 − α | P (862.1 ≤ Cp ≤ 863.0) = 1 − α | |
P (0.4605 ≤ a ≤ 0.6218) = 1 − α | P (0.4306 ≤ a ≤ 0.4356) = 1 − α | |
GF1Fe2.0 | P (0.8748 ≤ λ ≤ 0.8954) = 1 − α | P (0.6781 ≤ λ ≤ 0.8791) = 1 − α |
P (902.2 ≤ Cp ≤ 934.6) = 1 − α | P (892.4 ≤ Cp ≤ 896.7) = 1 − α | |
P (0.4447 ≤ a ≤ 0.5240) = 1 − α | P (0.3930 ≤ a ≤ 0.3980) = 1 − α | |
GF1Fe2.5 | P (0.9129 ≤ λ ≤ 0.9616) = 1 − α | P (0.6633 ≤ λ ≤ 0.6655) =1 − α |
P (884.3 ≤ Cp ≤ 945.7) = 1 − α | P (915.2 ≤ Cp ≤ 916.8) = 1 − α | |
P (0.4548 ≤ a ≤ 0.5061) = 1 − α | P (0.3826 ≤ a ≤ 0.3841) = 1 − α | |
RSF1.2 | P (0.9425 ≤ λ ≤ 0.9534) = 1 − α | P (0.6427 ≤ λ ≤ 0.6485) = 1 − α |
P (870.7 ≤ Cp ≤ 952.5) = 1 − α | P (876.0 ≤ Cp ≤ 880.2) = 1 − α | |
P (0.5198 ≤ a ≤ 0.5684) = 1 − α | P (0.3888 ≤ a ≤ 0.3935) = 1 − α | |
GF1.2Fe0.5 | P (0.9468 ≤ λ ≤ 0.9556) = 1 − α | P (0.6435 ≤ λ ≤ 0.6448) = 1 − α |
P (922.6 ≤ Cp ≤ 954.8) = 1 − α | P (844.3 ≤ Cp ≤ 846.4) = 1 − α | |
P (0.5048 ≤ a ≤ 0.5210) = 1 − α | P (0.3916 ≤ a ≤ 3932) = 1 − α | |
GF1.2Fe1.0 | P (0.9991 ≤ λ ≤ 1.0046) = 1 − α | P (0.6673 ≤ λ ≤ 0.6728) = 1 − α |
P (839.7 ≤ Cp ≤ 1009.5) = 1 − α | P (898.8 ≤ Cp ≤ 900.7) = 1 − α | |
P (0.5195 ≤ a ≤ 0.6248) = 1 − α | P (0.3935 ≤ a ≤ 0.4003) = 1 − α | |
GF1.2Fe1.5 | P (0.9561 ≤ λ ≤ 0.9639) = 1 − α | P (0.6775 ≤ λ ≤ 0.6793) = 1 − α |
P (867.4 ≤ Cp ≤ 887.0) = 1 − α | P (854.3 ≤ Cp ≤ 855.2) = 1 − α | |
P (0.5461 ≤ a ≤ 0.5551) = 1 − α | P (0.4052 ≤ a ≤ 0.4072) = 1 − α | |
GF1.2Fe2.0 | P (0.8385 ≤ λ ≤ 1.0716) = 1 − α | P (0.6924 ≤ λ ≤ 0.6992) = 1 − α |
P (807.4 ≤ Cp ≤ 858.4) = 1 − α | P (909.7 ≤ Cp ≤ 918.9) = 1 − α | |
P (0.5102 ≤ a ≤ 0.6738) = 1 − α | P (0.4048 ≤ a ≤ 0.4139) = 1 − α | |
GF1.2Fe2.5 | P (0.9380 ≤ λ ≤ 0.9588) = 1 − α | P (0.6691 ≤ λ ≤ 0.6740) = 1 − α |
P (786.7 ≤ Cp ≤ 944.2) = 1 − α | P (852.0 ≤ Cp ≤ 857.5) = 1 − α | |
P (0.5145 ≤ a ≤ 0.6041) = 1 − α | P (0.4017 ≤ a ≤ 4083) = 1 − α |
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Prałat, K.; Ciemnicka, J.; Koper, A.; Szczypiński, M.M.; Łoś, P.; Nguyen, V.V.; Le, V.S.; Rapiejko, C.; Ercoli, R.; Buczkowska, K.E. Determination of the Thermal Parameters of Geopolymers Modified with Iron Powder. Polymers 2022, 14, 2009. https://doi.org/10.3390/polym14102009
Prałat K, Ciemnicka J, Koper A, Szczypiński MM, Łoś P, Nguyen VV, Le VS, Rapiejko C, Ercoli R, Buczkowska KE. Determination of the Thermal Parameters of Geopolymers Modified with Iron Powder. Polymers. 2022; 14(10):2009. https://doi.org/10.3390/polym14102009
Chicago/Turabian StylePrałat, Karol, Justyna Ciemnicka, Artur Koper, Michał Marek Szczypiński, Piotr Łoś, Van Vu Nguyen, Van Su Le, Cezary Rapiejko, Roberto Ercoli, and Katarzyna Ewa Buczkowska. 2022. "Determination of the Thermal Parameters of Geopolymers Modified with Iron Powder" Polymers 14, no. 10: 2009. https://doi.org/10.3390/polym14102009