Full
HU Huiying (2001-), female, Master candidate. E-mail: hhy20010116@163.com
Outline
Concrete is the most widely used construction material, and its production accounts for about 8% of global CO2emissions. Supplementary cementitious materials (SCMs), such as fly ash, are therefore essential for low-carbon concrete. However, SCMs are highly heterogeneous. Their chemical composition, especially the Al/Si ratio, varies substantially, and the cooling rate during production further affects glass structure and reactivity.
The performance of SCMs is primarily governed by the alkaline dissolution of the aluminosilicate glass phase. Although dissolution mechanisms in high-calcium glasses have been studied, low-calcium systems remain less understood. In particular, the coupled effects of composition and cooling rate on dissolution are still unclear. Topological constraint theory and molecular dynamics simulations provide a useful framework for linking atomic structure to macroscopic behavior, but their application to low-calcium systems remains limited.
This study investigates how the Al/Si ratio and cooling rate jointly affect alkaline dissolution in synthetic low-calcium aluminosilicate glass and fly ash. A mechanistic descriptor based on the glass-phase Al/Si ratio is further introduced into a prediction model to assess its engineering relevance.
Synthetic glasses with different Al/Si ratios were synthesized by melt quenching. To investigate cooling-rate effects, a glass-mullite composite (GM) was produced by slow cooling, while a pure glass (AM) with the same glass-phase Al/Si ratio was prepared for comparison. Three industrial fly ashes (FA1-FA3) were also examined. Dissolution experiments were conducted at pH 13.2 (0.14 mol/L NaOH, 20 °C) with a solid-to-liquid ratio of 1:2000. Ion concentrations were determined by inductively coupled plasma optical emission spectrometry, and dissolution rates were obtained by fitting the concentration-time curves. Ab initio molecular dynamics (AIMD) simulations were performed using the HONPAS platform to characterize the atomic-scale structure. average microcrystalline sizes were calculated from X-ray diffraction data using the Scherrer equation. Finally, a three-layer backpropagation neural network was developed using the glass-phase Al/Si ratio as the key mechanistic descriptor for compressive-strength prediction.
The dissolution rate increased linearly with the Al/Si ratio on a logarithmic scale. However, GM and fly ash dissolved more slowly than synthetic glasses with similar Al/Si ratios. Topological constraint analysis showed that this trend mainly results from the lower Al-O bond dissociation energy (501.9 kJ/mol) than Si-O (799.6 kJ/mol). AIMD results showed that increasing the Al/Si ratio reduced the coordination number of Si, while the coordination of Al remained nearly unchanged. This indicates that Al incorporation introduces tetrahedral defects in the Si-O network and weakens topological constraints. Even so, the decrease in topological bond strength was limited, suggesting that Al-O bond weakening is the dominant factor, whereas network defects play a secondary role.
Cooling rate also had a strong effect. Slower cooling increased the coordination number and the topological bond strength index, but the measured dissolution rate of AM was still lower than that predicted from topological parameters alone. Solubility analysis showed that AM and G5 had the same glass-phase Al/Si ratio, but AM had lower final solubility. According to the Ostwald-Freundlich relation, larger crystallites reduce solubility, which is consistent with slower cooling. Therefore, slow cooling suppresses dissolution through three mechanisms: mullite crystallization lowers the glass-phase Al/Si ratio, increased coordination strengthens the network, and larger crystallites reduce solubility.
Finally, incorporating the glass-phase Al/Si ratio into the BP neural network model increased the R2 value from 0.484 to 0.830, confirming the key role of the microscopic Al/Si ratio in macroscopic performance evolution.
The alkaline dissolution rate of low-calcium aluminosilicate glass increases with the Al/Si ratio primarily due to the lower bond dissociation energy of Al-O (501.9 kJ/mol) compared to Si-O (799.6 kJ/mol). Tetrahedral defects and weakened topological constraints play only a secondary role. Slow cooling suppresses dissolution by reducing the glass-phase Al/Si ratio, strengthening topological constraints, and increasing average microcrystalline size. The backpropagation neural network with the glass-phase Al/Si ratio as a mechanistic input markedly improves prediction accuracy, supporting the engineering relevance of the proposed microscopic mechanism and providing a basis for the intelligent design of low-carbon concrete.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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