Hydration Mechanisms and Mechanical Property Evolution of Cemented Backfill Under Diverse Thermal Environments: A Review
Abstract
1. Introduction
2. Information Gathering
2.1. Search Strategy and Data Sources
2.2. Literature Screening Criteria
2.3. Data Analysis and Literature Distribution Statistics
3. Fundamental Models for the Hydration Kinetics of Backfill Materials
3.1. Nucleation and Growth (NG) Model
3.2. CEMHYD 3D Model
3.3. Krstulovic-Dabic Kinetic Model
3.4. Heat of Hydration Model
3.5. Thermodynamic Phase Equilibrium Models
3.6. Comparative Analysis of Hydration Models
4. Current Status of Research on the Influence of Temperature on the Hydration Reaction of Backfill
4.1. Accelerating Effect of Suitable Temperature on the Hydration Reaction


4.2. Deterioration Effect of Low/Extreme Low Temperatures on Hydration Reaction
5. Current Status of Research on the Influence of Temperature on the Evolution Laws of Mechanical Properties of Backfill
5.1. Influence of Temperature on the Strength Performance of Backfill
5.1.1. Macroscopic Mechanical Experimental Research
5.1.2. Micro-Scale Characterization and Mechanistic Analysis
5.1.3. Numerical Modeling and Constitutive Law Development
5.2. Influence of Temperature on Durability Performance of Backfill
6. Development Trends
- (1)
- Research on Dynamic Temperature Fields
- (2)
- Quantitative Correlation between Microscopic and Macroscopic Levels
- (3)
- Long-term Database for Extreme Environments
- (4)
- Multi-field Coupling Evolution Mechanism
- (5)
- AI-Based Prediction and Intelligent Optimization
7. Conclusions
- (1)
- The theoretical framework for temperature-regulated hydration relies on five mainstream models. While the NG, CEMHYD 3D, Krstulovic-Dabic, and Heat of Hydration models effectively cover micro-to-macro kinetics, and the Thermodynamic Phase Equilibrium model addresses dynamic phase changes, all currently exhibit limitations in fully capturing nanoscale phenomena and dynamic, non-steady-state temperature fields.
- (2)
- Backfill hydration exhibits an optimal temperature interval (typically 20 °C to 40 °C), within which the induction period is shortened and early strength develops rapidly. However, extreme environments cause severe deterioration: temperatures below −5 °C induce significant hydration lag and microstructural porosity, while temperatures exceeding 45 °C trigger a “shell effect” that encapsulates binder particles, inhibiting long-term hydration.
- (3)
- Temperature exerts a non-linear “increase-then-decrease” interval effect on mechanical performance. The peak strength threshold is highly material-dependent; for example, slag-blended systems often require higher activation energies (>50 kJ/mol) and peak at different temperatures compared to pure cement systems. Beyond critical temperatures (e.g., >100 °C to 200 °C), severe dehydration of C-S-H gel leads to structural thermal cracking and significant strength degradation.
- (4)
- Backfill durability exhibits significant time-dependent degradation under multi-field coupling (e.g., thermal stress combined with sulfate/chloride erosion). To ensure long-term stability in extreme environments, future research must transition from isothermal, trial-and-error experiments to dynamic temperature field simulations. The integration of Artificial Intelligence (AI) and Machine Learning algorithms to explore the intricate, non-linear relationships between micro-mechanisms and macro-performance is expected to become an increasingly dominant approach in the development of intelligent backfill design.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| Year Range | Percentage by Number | Key Research Areas |
|---|---|---|
| 1950–1999 | 9.6% | Proposals of grain boundary nucleation theory, early hydration kinetics equations, and initial digital simulation prototypes. |
| 2000–2015 | 32.8% | Establishment of the K-D Model System, conceptualization of deep mining heat hazards, early multi-scale experiments, and maturation of CEMHYD3D and thermodynamic phase equilibrium models. |
| 2016–2026 | 57.6% | Investigations into extreme thermal environments (freeze–thaw to ultra-high temperatures), kinetics of novel modified materials, multi-field coupling mechanisms, and AI/machine learning strength predictions. |
| Theme Categories | Percentage by Number | Document Content Verification |
|---|---|---|
| Background and Strategic Environment | 8% | Deep mining context, high-altitude extreme cold challenges, and strategic mineral security implications |
| Classical Hydration Models and Thermodynamic Simulations | 28.8% | Evolution of the NG, CEMHYD3D, K-D, Heat of Hydration and Thermodynamic Phase Equilibrium models, alongside Gibbs free energy thermodynamic calculations |
| Temperature Effects on Microstructure and Kinetics of Modified Materials | 25.6% | Hydration rate regulation, SCM/nanomaterial activation, pore structure evolution, and micro-scale characterizations (NMR, SEM) under varying temperatures |
| Macroscopic Mechanics and Intelligent Prediction Models | 28.8% | Uniaxial/triaxial strength responses, thermal crack evolution, damage constitutive laws, and AI/RSM strength predictions |
| Durability and Multi-field Degradation | 8.8% | Salt erosion modelling, sulfate/chloride leaching, carbonation, and long-term structural deterioration under complex environments |
| Model | Core Principle | Application Scale | Critical Limitations |
|---|---|---|---|
| Nucleation and Growth (NG) Model | Joint control of crystal nucleus formation and growth rates. | Microscopic | Assumes static boundaries; low adaptability for multi-particle backfill systems. |
| CEMHYD 3D Model | 3D uniform cubic lattice for visual hydration kinetics. | Micro-to-Meso | Empirical-based rules; fixed 1 μm resolution cannot capture nanoscale C-S-H evolution. |
| Krstulovic-Dabic Kinetic Model | Three stages: NG → Phase Boundary (I) → Diffusion (D) *. | Process | Restricted to constant temperatures; poor simulation of dynamic temperature fields. |
| Heat of Hydration Model | Macroscopic thermodynamic characterization and empirical fitting. | Macroscopic | Relies on macro-parameters; fails to explain microscopic intrinsic mechanisms. |
| Thermodynamic Phase Equilibrium | Gibbs free energy minimization predicting stable phase compositions | Micro-to-Meso | Assumes local equilibrium; highly dependent on completeness of complex thermodynamic data. |
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© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Share and Cite
Liu, J.; Tan, Y.; Zeng, Z.; Song, W. Hydration Mechanisms and Mechanical Property Evolution of Cemented Backfill Under Diverse Thermal Environments: A Review. Minerals 2026, 16, 276. https://doi.org/10.3390/min16030276
Liu J, Tan Y, Zeng Z, Song W. Hydration Mechanisms and Mechanical Property Evolution of Cemented Backfill Under Diverse Thermal Environments: A Review. Minerals. 2026; 16(3):276. https://doi.org/10.3390/min16030276
Chicago/Turabian StyleLiu, Jiangwei, Yuye Tan, Ziyi Zeng, and Weidong Song. 2026. "Hydration Mechanisms and Mechanical Property Evolution of Cemented Backfill Under Diverse Thermal Environments: A Review" Minerals 16, no. 3: 276. https://doi.org/10.3390/min16030276
APA StyleLiu, J., Tan, Y., Zeng, Z., & Song, W. (2026). Hydration Mechanisms and Mechanical Property Evolution of Cemented Backfill Under Diverse Thermal Environments: A Review. Minerals, 16(3), 276. https://doi.org/10.3390/min16030276

