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  1. Abstract

    Ultrahigh temperature ceramics (UHTCs) have melting points above 3000°C and outstanding strength at high temperatures, thus making them apposite structural materials for high‐temperature applications. Di‐borides, nitride, and carbide compounds—processed via various techniques—have been extensively studied and used in the manufacture of UHTCs. Current analytical models, based on our current but incomplete understanding of the theory, are unable to produce a priori predictions of mechanical properties of UHTCs based on their mixture designs and processing parameters. As a result, researchers have to rely on experiments—which are often costly and time‐consuming—to understand composition–structure–performance links in UHTCs. This study employs machine learning (ML) models (i.e., random forest and artificial neural network models) to predict Young's modulus, flexural strength, and fracture toughness of UHTCs in relation to a wide range of mixture designs, processing parameters, and testing conditions. Outcomes demonstrate that adequately trained ML models can yield reliable predictions, a priori, of the three aforesaid mechanical properties. The prediction performance on Young's modulus is superior to flexural strength and fracture toughness. Next, the ML model with the best prediction performance is utilized to evaluate and rank the impacts of input variables on Young's modulus. Finally, on the basis of such classification of consequentialmore »and inconsequential input variables, this study develops an easy‐to‐use, closed‐form analytical model to predict Young's modulus of UHTCs. Overall, this study highlights the ability of data‐driven numerical models to complement, or even replace, time‐consuming experiments, thereby accelerating the development of UHTCs.

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  2. Abstract

    Alkali‐activated mortar (AAM) is an emerging eco‐friendly construction material, which can complement ordinary Portland cement (OPC) mortars. Prediction of properties of AAMs—albeit much needed to complement experiments—is difficult, owing to substantive batch‐to‐batch variations in physicochemical properties of their precursors (i.e., aluminosilicate and activator solution). In this study, a machine learning (ML) model is employed; and it is shown that the model—once trained and optimized—can reliably predict compressive strength of AAMs solely from their initial physicochemical attributes. Prediction performance of the model improves when multiple compositional descriptors of the aluminosilicate are combined into a singular, composite chemostructural descriptor (i.e.,network ratioandnumber of constraints); thus, reducing the degrees of freedom. Through interpretation of the ML model's outcomes—specifically the variable importance for the AAMs’ compressive strength—a simple, easy‐to‐use, closed‐form analytical model is developed. Results demonstrate that the analytical model yields predictions of compressive strength of AAMs without scarifying much accuracy compared to the ML model. Overall, this study's outcomes demonstrate a roadmap—incorporates composite chemostructural descriptors in ML models—that can be employed to design AAMs to achieve targeted compressive strength.

  3. Abstract

    The hydration of the two most reactive phases of ordinary Portland cement (OPC), tricalcium silicate (C3S), and tricalcium aluminate (C3A) is successfully halted when the activity of water () falls below critical thresholds of 0.70 and 0.45, respectively. It has been established that the reduction in relative humidity (RH) and suppresses the hydration of all anhydrous phases in OPC, including less explored phases like dicalcium silicate, that is, belite (β‐C2S). However, the degree of suppression, that is, the critical threshold, for β‐C2S, standalone has yet to be established. This study utilizes isothermal microcalorimetry and X‐ray diffraction techniques to elucidate the influence ofon the hydration of‐C2S suspensions via incremental replacements of water with isopropanol (IPA). Experimentally, this study shows that with increasing IPA replacements, hydration is increasingly suppressed until eventually brought to a halt at a critical threshold of approximately 27.7% IPA on a weight basis (wt.%IPA). From thermodynamic estimations, the exact criticalthreshold and solubility product constant of‐C2S () are established as 0.913 and 10−12.68, respectively. This study enables enhanced understanding of β‐C2S reactivity and provides thermodynamic parameters during the hydration of β‐C2S‐containing cementitious systems such as OPC‐basedmore »and calcium aluminate‐based systems.

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  4. Abstract

    Carbonaceous (e.g., limestone) and aluminosilicate (e.g., calcined clay) mineral additives are routinely used to partially replace ordinary portland cement in concrete to alleviate its energy impact and carbon footprint. These mineral additives—depending on their physicochemical characteristics—alter the hydration behavior of cement; which, in turn, affects the evolution of microstructure of concrete, as well as the development of its properties (e.g., compressive strength). Numerical, reaction-kinetics models—e.g., phase boundary nucleation-and-growth models; which are based partly on theoretically-derived kinetic mechanisms, and partly on assumptions—are unable to produce a priori prediction of hydration kinetics of cement; especially in multicomponent systems, wherein chemical interactions among cement, water, and mineral additives occur concurrently. This paper introduces a machine learning-based methodology to enable prompt and high-fidelity prediction of time-dependent hydration kinetics of cement, both in plain and multicomponent (e.g., binary; and ternary) systems, using the system’s physicochemical characteristics as inputs. Based on a database comprising hydration kinetics profiles of 235 unique systems—encompassing 7 synthetic cements and three mineral additives with disparate physicochemical attributes—a random forests (RF) model was rigorously trained to establish the underlying composition-reactivity correlations. This training was subsequently leveraged by the RF model: to predict time-dependent hydration kinetics of cement in new, multicomponent systems;more »and to formulate optimal mixture designs that satisfy user-imposed kinetics criteria.

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  5. Abstract

    Froth flotation process is extensively used for selective separation of base metal sulfides from uneconomic mineral resources. Reliable prediction of process outcomes (metal recovery and grade) is vital to ensure peak performance. This work employs an innovative hybrid machine learning (ML) model—constructed by combining the random forest model and the firefly algorithm—to predict froth flotation efficiency of galena and chalcopyrite in relation to various experimental process parameters. The hybrid model's prediction performance was rigorously evaluated, and compared against four different standalone ML models. The outcomes of this study illustrate that the hybrid ML model has the prediction ability to process outcomes with high‐fidelity, while consistently outperforming the standalone ML models.

  6. Abstract

    Microcrystalline zeolites of the gismondine family are often reported in alkali‐activated and blended cement systems. However, little is known about gismondine's compatibility with other cementitious phases to determine stability in long‐term phase assemblage. Experimental studies were conducted to investigate the compositional field of gismondine stability in the lime‐alumina‐silica‐hydrate systems, with a particular focus on understanding the compatibility of gismondine with other cement phases such as C‐S‐H, ettringite, monosulfate, strätlingite, katoite, gypsum, calcite, portlandite, alkali, silica, and aluminosilicate phases. Results show that gismondine‐Ca forms readily at ~85°C in high aluminosilicate compositions; and persists in the presence of calcite, gypsum, ettringite, katoite solid solution, low Ca tobermorite‐like C‐S‐H, silica and aluminosilicate phases, at 20‐85°C. However, gismondine‐Ca reacts with: (a) monosulfate, producing ettringite‐thaumasite solid solution; (b) portlandite, forming tobermorite‐like C‐A‐S‐H gel and siliceous katoite at >55°C; (c) aqueous NaOH, generating gismondine‐(Na,Ca), a garronite‐like zeolite P solid solution; and (d) strätlingite leading to the conversion of strätlingite to gismondine indicating the metastability of strätlingite with respect to gismondine at 55°C. The outcomes are discussed to provide insights into the long‐term phase assemblage of relevant cement systems such as lime‐calcined clay, alkali‐activated materials, and potentially ancient Roman concrete.

  7. Abstract

    Early‐age hydration of cement is enhanced by slightly soluble mineral additives (ie, fillers, such as quartz and limestone). However, few studies have attempted to systematically compare the effects of different fillers on cementitious hydration rates, and none have quantified such effects using fillers with comparable, size‐classified particle size distributions (PSDs). This study examines the influence of size‐classified fillers [ie, limestone (CaCO3), quartz (SiO2), corundum (Al2O3), and rutile (TiO2)] on early‐age hydration kinetics of tricalcium silicate (C3S) using a combination of experimental methods, while also employing a modified phase boundary and nucleation and growth model. In prior studies, wherein fillers with broad PSDs were used, it has been reported that between quartz and limestone, the latter is a superior filler due to its ability to partake in anion‐exchange reactions with C‐S‐H. Contrary to prior investigations, this study shows that when size‐classified andarea matchedfillers are used—which, essentially, eliminate degrees of freedom associated with surface area and agglomeration of filler particulates—the filler effect of quartz is broadly similar to that of limestone as well as rutile. Results also show that unlike quartz, limestone, and rutile—which enhance C3S hydration kinetics—corundum suppresses hydration of C3S during the first several hours after mixing. Such decelerationmore »in C3S hydration kinetics is attributed to the adsorption of aluminate anions—released from corundum's dissolution—onto anhydrous particulates’ surfaces, which impedes both the dissolution of C3S and heterogeneous nucleation of C‐S‐H.

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  8. Abstract

    The hydration of tricalcium silicate (C3S)—the major phase in cement—is effectively arrested when the activity of water (aH) decreases below the critical value of 0.70. While it is implicitly understood that the reduction inaHsuppresses the hydration of tricalcium aluminate (C3A: the most reactive phase in cement), the dependence of kinetics of C3A hydration onaHand the criticalaHat which hydration of C3A is arrested are not known. This study employs isothermal microcalorimetry and complementary material characterization techniques to elucidate the influence ofaHon the hydration of C3A in [C3A + calcium sulfate (C$) + water] pastes. Reductions in water activity are achieved by partially replacing the water in the pastes with isopropanol. The results show that with decreasingaH, the kinetics of all reactions associated with C3A (eg, with C$, resulting in ettringite formation; and with ettringite, resulting in monosulfoaluminate formation) are proportionately suppressed. WhenaH ≤0.45, the hydration of C3A and the precipitation of all resultant hydrates are arrested; even in liquid saturated systems. In addition to—and separate from—the experiments, a thermodynamic analysis also indicates that the hydration of C3A does not commence or advance whenaH ≤0.45. On the basis of this criticalaH, the solubility product of C3A (KC3A) was estimated as 10−20.65. The outcomes of this work articulatemore »the dependency of C3A hydration and its kinetics on water activity, and establish—for the first time—significant thermodynamic parameters (ie, criticalaHandKC3A) that are prerequisites for numerical modeling of C3A hydration.

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  9. Free, publicly-accessible full text available March 1, 2024
  10. To promote the sustainable development of eco-efficient calcium sulfoaluminate (CSA) cements through the partial replacement of the CSA clinker with supplementary cementitious waste products, the effects of coal fly ashes on the early-age and mature-age properties of a calcium sulfoaluminate (CSA)-based cement paste were investigated. The impacts of both Class C and Class F fly ashes on the rheological properties, hydration kinetics, and compressive strength development of CSA cement paste were studied. Rheology-based workability parameters, representing the rate of loss of flowability, the rate of hardening, and the placement limit, were characterized for the pastes prepared with fixed water-to-cement (w/c) and fixed water-to-binder (w/b) ratios. The results indicate a slight improvement in the workability of the CSA paste by fly ash addition at a fixed w/b ratio. The isothermal calorimetry studies show a higher heat of hydration for the Class C fly ash-modified systems compared to the Class F-modified systems. The results show that fly ash accelerates the hydration of the calcium sulfoaluminate cement pastes, chiefly due to the filler effects, rather than the pozzolanic effects. In general, ettringite is stabilized more by the addition of Class F fly ash than Class C fly ash. Both fly ashes reduced themore »1-day compressive strength, but increased the 28-day strength of the CSA cement paste; meanwhile, the Class C modified pastes show a higher strength than Class F, which is attributed to the higher degree of reaction and potentially more cohesive binding C-S-H-based gels formed in the Class C fly ash modified systems. The results provide insights that support that fly ash can be employed to improve the performance of calcium sulfoaluminate cement pastes, while also enhancing cost effectiveness and sustainability.« less
    Free, publicly-accessible full text available February 1, 2024