硅酸盐学报

Al/Si比与冷却速率对低钙硅铝酸盐玻璃碱性溶解速率的协同影响机理及基于数据驱动的强度验证

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胡慧瑛 ¹ , 向洋生 ¹ , 叶家元 ² , 王眺 ¹ , 胡伟 ³ , 汪智勇 ⁴ , 焦诗哲 ³ , 何小鸥 ¹ , Dao VINH ⁵ , 李晨 ¹ , 蒋正武 ¹

硅酸盐学报 | 第二十八届中国科协年会智能建造关键无机非金属材料–AI驱动水泥基材料创新专题-研究论文 2026,54(10): 3426-3435

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硅酸盐学报 |第二十八届中国科协年会智能建造关键无机非金属材料–AI驱动水泥基材料创新专题-研究论文 2026 , 54 (10) : 3426 -3435

Al/Si比与冷却速率对低钙硅铝酸盐玻璃碱性溶解速率的协同影响机理及基于数据驱动的强度验证

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胡慧瑛¹, 向洋生¹, 叶家元², 王眺¹, 胡伟³, 汪智勇⁴, 焦诗哲³, 何小鸥¹, Dao VINH⁵, 李晨¹, 蒋正武¹

作者信息

^1.同济大学材料科学与工程学院，先进土木工程材料教育部重点实验室，中国　上海　201804

^2.中国建筑材料科学研究总院有限公司，水泥科学与新型建筑材料研究院，中国　北京　100024

^3.中国科学技术大学未来技术学院，中国科学技术大学化学物理系，中国　合肥　230026

^4.建筑材料工业技术情报研究所，中国　北京　100024

^5.澳大利亚昆士兰大学土木工程学院，澳大利亚　昆士兰州　4072

通讯作者:

王眺（1984-），男，博士，研究员。

作者简介:

胡慧瑛（2001-），女，硕士研究生。

Coupled Effects of Al/Si Ratio and Cooling Rate on the Alkaline Dissolution Rate of Low-Calcium Aluminosilicate Glass: Mechanism and Data-Driven Strength Validation

Huiying HU¹, Yangsheng XIANG¹, Jiayuan YE², Tiao WANG¹, Wei HU³, Zhiyong WANG⁴, Shizhe JIAO³, Xiaoou HE¹, Dao VINH⁵, Chen LI¹, Zhengwu JIANG¹

Affiliations

^1.School of Materials Science and Engineering, Key Laboratory of Advanced Civil Engineering Materials of the Ministry of Education, Tongji University, Shanghai 201804, China

^2.Institute of Cement Science and New Building Materials, China Building Materials Academy, Beijing 100024, China

^3.School of Future Technology, Department of Chemical Physics, University of Science and Technology of China, Hefei 230026, China

^4.Institute of Technical Information for Building Materials Industry of China, Beijing 100024, China

^5.School of Civil Engineering, The University of Queensland, Brisbane, Queensland 4072, Australia

Corresponding Author:

WANG Tiao (1984-), male, Ph.D., Professor. E-mail: wangtiao@tongji.edu.cn

HU Huiying (2001-), female, Master candidate. E-mail: hhy20010116@163.com

出版时间: 2026-07-29 doi: 10.14062/j.issn.0454-5648.20260324

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摘要

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为揭示低钙硅铝质固废中硅铝酸盐玻璃的溶解机制，合成了宽Al/Si比范围的玻璃，以粉煤灰为对比，结合碱性溶解实验与第一性原理分子动力学模拟，研究了Al/Si比和冷却速率对溶解速率的影响。结果表明：溶解速率随Al/Si比增大而升高，主要归因于Al-O键的解离能低于Si-O键；Al掺入引发的Si-O四面体缺陷仅起次要作用。冷却速率较慢时，平均微晶尺寸增大，溶解度降低，从而抑制溶解。以玻璃相Al/Si比为输入参数的粉煤灰混凝土强度预测的反向传播神经网络模型，其决定系数由0.484提升至0.830，验证了微观机理的工程适用性。

关键词

工业固废 / 硅铝酸盐玻璃 / 溶解速率 / 铝硅比 / 冷却速率 / 平均微晶尺寸

Abstract

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Introduction

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.

Methods

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.

Results and discussion

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.

Conclusions

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.

Key words

industrial solid waste / aluminosilicate glass / dissolution rate / alumina/silicon ratio / cooling rate / average microcrystalline size

引用本文

胡慧瑛, 向洋生, 叶家元, 王眺, 胡伟, 汪智勇, 焦诗哲, 何小鸥, Dao VINH, 李晨, 蒋正武. Al/Si比与冷却速率对低钙硅铝酸盐玻璃碱性溶解速率的协同影响机理及基于数据驱动的强度验证. 硅酸盐学报, 2026 , 54 (10) : 3426 -3435 . DOI: 10.14062/j.issn.0454-5648.20260324

Huiying HU, Yangsheng XIANG, Jiayuan YE, Tiao WANG, Wei HU, Zhiyong WANG, Shizhe JIAO, Xiaoou HE, Dao VINH, Chen LI, Zhengwu JIANG. Coupled Effects of Al/Si Ratio and Cooling Rate on the Alkaline Dissolution Rate of Low-Calcium Aluminosilicate Glass: Mechanism and Data-Driven Strength Validation[J]. Journal of the Chinese Ceramic Society, 2026 , 54 (10) : 3426 -3435 . DOI: 10.14062/j.issn.0454-5648.20260324

基金

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国家重点研发计划(2024YFF0508302)
中央高校基本科研业务费专项资金资助(22120260243)

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2026年第54卷第10期

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doi: 10.14062/j.issn.0454-5648.20260324

接收时间：2026-05-15
首发时间：2026-10-22
出版时间：2026-07-29

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收稿日期：2026-05-15
修回日期：2026-06-01

基金

国家重点研发计划(2024YFF0508302)

中央高校基本科研业务费专项资金资助(22120260243)

作者信息

^1.同济大学材料科学与工程学院，先进土木工程材料教育部重点实验室，中国　上海　201804

^2.中国建筑材料科学研究总院有限公司，水泥科学与新型建筑材料研究院，中国　北京　100024

^3.中国科学技术大学未来技术学院，中国科学技术大学化学物理系，中国　合肥　230026

^4.建筑材料工业技术情报研究所，中国　北京　100024

^5.澳大利亚昆士兰大学土木工程学院，澳大利亚　昆士兰州　4072

通讯作者:

王眺（1984-），男，博士，研究员。

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2种不同金属材料的力学参数

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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