Effect of CaO/Fe2O3 ratio on slag viscosity behavior under entrained flow gasification conditions

Ge, Zefeng; Kong, Lingxue; Bai, Jin; Zhao, Huiling; Cao, Xi; Li, Huaizhu; Bai, Zongqing; Meyer, Bernd; Guhl, Stefan; Li, Ping; Li, Wen

doi:10.1016/j.fuel.2019.116129

Cited by 49 publications

(19 citation statements)

References 35 publications

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“…Chinese standard DL/T660-2007 were used to divide slags among glassy/non-glassy. The criteria can also be seen in the literature [24,31,49]. As shown Figure 3a, the viscosity of glassy slags decreases with increasing temperature in a gradual manner without abrupt changes (curve A).…”

Section: Model Development For the Classification Of Slagssupporting

confidence: 67%

“…The artificially prepared samples were meant to match the compounds of hazardous waste or to simulate slags with additions of fluxing agents [7,21,44]. In order to investigate the influence of a specific or several components on the viscosity, and make the measurement easier, samples with less components were often artificially prepared to simplify the ash system [18,25,49]. Artificial preparation of samples with corresponding components is more conducive to the smooth progress of the verification experiment [49,51,54].…”

Section: Model Development For the Classification Of Slagsmentioning

confidence: 99%

“…In order to investigate the influence of a specific or several components on the viscosity, and make the measurement easier, samples with less components were often artificially prepared to simplify the ash system [18,25,49]. Artificial preparation of samples with corresponding components is more conducive to the smooth progress of the verification experiment [49,51,54]. It can be seen from Table 1 that a wide range of experimental data have been used, which should have made the model perform well.…”

Section: Model Development For the Classification Of Slagsmentioning

confidence: 99%

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Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes

Lin

Dai

et al. 2020

Energies

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Molten gasification is considered as a promising technology for the processing and safe disposal of hazardous wastes. During this process, the organic components are completely converted while the hazardous materials are safely embedded in slag via the fusion-solidification-vitrification transformation. Ideally, the slag should be glassy with low viscosity to ensure the effective immobilization and steady discharge of hazardous materials. However, it is very difficult to predict the characteristics of slag using existing empirical equations or conventional mathematical methods, due to the complex non-linear relationship among the phase transformation, vitrification transition and chemical composition of slag. Equipped with a strong nonlinear mapping ability, an artificial neural network may be able to predict the properties of slags if a large amount of data is available for training. In this work, over 10,000 experimental data points were used to train and develop a slag classification model (glassy vs. non-glassy) based on a neural network. The optimal structure of the neural network was figured out and validated. The results suggest that the classification accuracy for the independent test samples reached 93.3%. Using 1 and 0 as model inputs to represent mildly reducing and inert atmospheres, a double hidden layer structure in the neural network enabled the accurate classification of slags under various atmospheres. Furthermore, the neural network for the prediction of glassy slag viscosity was optimized; it featured a double hidden layer structure. Under a mildly reducing atmosphere, the absolute error from the independent test data was generally within 4 Pa·s. By adding a gas atmosphere into the input of the neural network using a simple normalization method, a multi-atmosphere slag viscosity prediction model was developed. Said model is much more accurate than its counterpart that does not consider the effect of the atmosphere. In summary, the artificial neural network proved to be an effective approach to predicting the slag properties under different atmospheres. The data-driven models developed in this work are expected to facilitate the commercial deployment of molten gasification technology.

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Section: Model Development For the Classification Of Slagssupporting

confidence: 67%

Section: Model Development For the Classification Of Slagsmentioning

confidence: 99%

Section: Model Development For the Classification Of Slagsmentioning

confidence: 99%

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Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes

Lin

Dai

et al. 2020

Energies

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“…The stretching vibrations for silicate tetrahedral with different numbers (n = 0, 1, 2, 3) of bridging oxygen are referred to as Q 0 (monomer structure), Q 1 (dimer structure), Q 2 (chain structure), and Q 3 (sheet structure), respectively. According to literature studies, 30,31 19 The Raman band intensity for the range of 500 and 650 cm −1 changes slightly, which indicates that the number of bridging oxygen atoms connected with Si and Al atoms is not significantly affected by the introduction of Cr 2 O 3 .…”

Section: Methodsmentioning

confidence: 84%

“…The stretching vibrations for silicate tetrahedral with different numbers ( n = 0, 1, 2, 3) of bridging oxygen are referred to as Q 0 (monomer structure), Q 1 (dimer structure), Q 2 (chain structure), and Q 3 (sheet structure), respectively. According to literature studies, , the four bands for Q n ( n = 0, 1, 2, 3) are 840–870, 900–930, 950–980, and 1060 cm –1 , respectively. With the addition of Cr 2 O 3 , the band around 950 cm –1 turns to a high frequency, and this indicates that the introduction of Cr 2 O 3 acts as network formers in the silicate network, which increases the degree of polymerization.…”

Section: Resultsmentioning

confidence: 96%

Dissolution of Cr₂O₃ into Coal Slag and Its Impact on Slag Flow Properties

et al. 2020

Self Cite

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In an entrained-flow coal gasifier, gasification slag derived from the melting of mineral matter in coal flows along the refractory wall and is tapped out. The refractory of spallation and dissolution enters into coal slag and can affect the slag flow properties, which are crucial for the entrained-flow gasifier's smooth operation. Cr 2 O 3 is one of the most common compositions of refractory materials and is selected to research the effect of refractory on the flow properties of slag. In this work, the dissolution of Cr 2 O 3 into coal slag is calculated by FactSage software, and its impact on ash fusion temperatures and slag viscosity are investigated. The Cr 2 O 3 concentration of coal slag increases from 0.5 to 4 wt % as the operation temperature rises (1300−1600 °C). Cr 2 O 3 reacts with FeO to form the high-melting point mineral donathite during the ash melting process, and the retention of FeO reduces the formation of low-melting point clinopyroxene, leading to the increase of ash fusion temperatures with the Cr 2 O 3 content. In addition, the slag viscosity increases with the Cr 2 O 3 content because of the increasing polymerization degree of the slag structure. Crystalline donathite formed by Cr 2 O 3 is precipitated first during the cooling process, and the precipitated donathite acts as the heterogeneous nucleus, promoting the precipitation of troilite and anorthite and thus increasing the critical viscosity temperature. This suggests that the high-chromia refractory material corrosion can cause the fluctuation of slag flowability and even lead to slag blockage. Therefore, the gasifier cannot be operated beyond the upper limit of operation temperature (1600 °C) for a long time to avoid the severe dissolution of refractory materials.

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The wetting process and crystallisation of Al₂O₃ substrate with molten slags: Addition of CaO‐Fe₂O₃

Baoliang

Jiao

et al. 2022

Asia-Pacific J Chem Eng

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As fluxes, CaO and Fe2O3 are widely applied to effectively improve the melting characteristics of coal ash. However, there are few studies on the effects of CaO and Fe2O3 contents in coal ash on the wetting of refractories used in entrained‐flow slagging gasifiers. This paper investigates the melting properties of ash slag and the wetting process in corundum‐based refractories in relation to the total amount of CaO and Fe2O3 and their proportions in coal ash. The rates of change of the apparent contact angle (ACA) and differential contact angle (DCA) as a function of temperature are employed to evaluate the wetting behaviour of the coal ash during the heating process. The results demonstrate that changes in the ACA result from the expansion or shrinkage of the slag. In particular, two abrupt changes in the ACA are observed at an Fe2O3/CaO ratio of .25. The wettability deteriorates after quenching at ratios ranging from .13 to .67. Differences in the crystal structure and elemental distribution along with the spreading direction are observed. X‐ray diffraction and FactSage calculations show that temperature changes the crystal composition and solid–liquid phase content, supporting the slag wetting process from the perspective of ash fusibility. A fraction of the liquid phase increases twice with increases in temperature, explaining the abrupt change in the ACAs. Overall, the wetting process of the slag can be explained by the surface tension and DCA. The wetting begins at 430 mN m−1 and becomes the most prominent at 435 mN m−1. Finally, an Fe2O3/CaO ratio of .25 is found to be more suitable for the long‐term operation of corundum‐based refractories.

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Effect of CaO/Fe2O3 ratio on slag viscosity behavior under entrained flow gasification conditions

Cited by 49 publications

References 35 publications

Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes

Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes

Dissolution of Cr₂O₃ into Coal Slag and Its Impact on Slag Flow Properties

The wetting process and crystallisation of Al₂O₃ substrate with molten slags: Addition of CaO‐Fe₂O₃

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Effect of CaO/Fe2O3 ratio on slag viscosity behavior under entrained flow gasification conditions

Cited by 49 publications

References 35 publications

Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes

Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes

Dissolution of Cr2O3 into Coal Slag and Its Impact on Slag Flow Properties

The wetting process and crystallisation of Al2O3 substrate with molten slags: Addition of CaO‐Fe2O3

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Product

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Dissolution of Cr₂O₃ into Coal Slag and Its Impact on Slag Flow Properties

The wetting process and crystallisation of Al₂O₃ substrate with molten slags: Addition of CaO‐Fe₂O₃