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Abstract Magnesium silicate hydrate (M‐S‐H) represents a promising alternative to traditional cement, particularly for low‐pH construction applications such as nuclear waste encapsulation and carbon dioxide injection. The durability of construction materials, a critical aspect of their suitability for various purposes, is primarily governed by the kinetics of dissolution of the binder phase under service conditions. In this study, we employed in situ atomic force microscopy to assess the dissolution rates of M‐S‐H in water equilibrated with air. Quantitative analysis based on changes in volume and height revealed dissolution rates ranging from 0.18 to 3.09 × 10−12 mol/cm2/s depending on the precipitate Mg/Si ratio and morphology. This rate surpasses its crystalline analogs, talc (Mg3Si4O10(OH)2) and serpentine (Mg3(Si2O5)(OH)4), by about three to five orders of magnitude. Interestingly, oriented M‐S‐H dissolved faster than non‐oriented M‐S‐H. Spatially resolved assessments of dissolution rates facilitated a direct correlation between rates and morphology, showing that edges and smaller crystallites dissolve at a faster pace compared to facets and larger crystallites. The outcomes of this study provide insights into the mechanisms governing the dissolution of M‐S‐H and the factors dictating its durability. These findings hold implications for the strategic design and optimization of M‐S‐H for various applications.
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Literature mining for alternative cementitious precursors and dissolution rate modeling of glassy phases
Abstract Efforts to reduce the carbon footprint associated with cement and concrete production have resulted in a number of promising lower‐emission alternatives. Still, research has emphasized a small subset of potentially useful precursor materials. With the goal of expanding the precursor pool, this work presents results of parallel literature mining and rate modeling activities. As a result of literature mining, materials with appropriate SiO2, Al2O3, and CaO concentrations were assembled into a comprehensive, representative ternary diagram. 23 000+ materials were extracted from 7000 journal articles, and 7500 materials from 6000 articles with 80 ≤ SiO2 + Al2O3 + CaO ≤105 wt% automatically classified. Both supervised and semi‐supervised models were used for dissolution rate prediction of glassy materials with all models pulling from a single data set (n = 802 reported dissolution rates from 105 different glasses). Supervised modeling utilized linear and decision tree regressions to determine features most predictive of dissolution rate, resulting in log‐linear relationships between rate and pH, inverse temperature (1/K), and non‐bridging oxygen per tetrahedron (NBO/T). Semi‐supervised modeling was observed to be more robust to broader feature inclusion, providing similar predictive ability with a relatively larger set of descriptive features. Most importantly, results indicated that models trained on data from disparate scientific communities were adequately predictive (RMSE ≈ 1), particularly under pH ≥7 conditions relevant to the cement and alkali activation communities.
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- Award ID(s):
- 1922311
- PAR ID:
- 10442892
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of the American Ceramic Society
- Volume:
- 104
- Issue:
- 7
- ISSN:
- 0002-7820
- Page Range / eLocation ID:
- p. 3042-3057
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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