2021
DOI: 10.1016/j.fuel.2021.121448
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The fusion mechanism of complex minerals mixture and prediction model for flow temperature of coal ash for gasification

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Cited by 14 publications
(6 citation statements)
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“…A high ionic potential element with high tendency combined with oxygen can generate high MP silicate and alumino-silicate stable networks and results in an increase in AFT, while the low ionic potential element can convert a bridge–oxygen bond into a no bridge–oxygen bond and result in AFT decrease . Recently, several correlations to predict the AFTs according to the ionic potential have been explored. ,, Li et al presented a predicting model between FT and its average mole ionic potentials of Mg 2+ , Fe 2+ , Ca 2+ , and Al 3+ ( I normala normalv normale normalr normalg normale = normalΣ M i I i normalΣ M i , where M i stands for the each ionic mole fraction and I i stands for the ionic potential of each ion). Xiao et al added the ionic potentials of K + , Na + , Ti 4+ , and Mg 2+ and obtained the correlation model between the FT and its C MP ( C normalM normalP = normalΣ w i I i n i r i normalΣ normalw normali n i , where w i is the mass fraction of the corresponding metal oxide after normalization, n i is the relative molecular mass of the corresponding metal oxide, z i is the charge number, and r i is the ionic radius of the corresponding metal oxide) normalF normalT = 509.12 + 17.98 I normala normalv normale normalr normala normalg normale …”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…A high ionic potential element with high tendency combined with oxygen can generate high MP silicate and alumino-silicate stable networks and results in an increase in AFT, while the low ionic potential element can convert a bridge–oxygen bond into a no bridge–oxygen bond and result in AFT decrease . Recently, several correlations to predict the AFTs according to the ionic potential have been explored. ,, Li et al presented a predicting model between FT and its average mole ionic potentials of Mg 2+ , Fe 2+ , Ca 2+ , and Al 3+ ( I normala normalv normale normalr normalg normale = normalΣ M i I i normalΣ M i , where M i stands for the each ionic mole fraction and I i stands for the ionic potential of each ion). Xiao et al added the ionic potentials of K + , Na + , Ti 4+ , and Mg 2+ and obtained the correlation model between the FT and its C MP ( C normalM normalP = normalΣ w i I i n i r i normalΣ normalw normali n i , where w i is the mass fraction of the corresponding metal oxide after normalization, n i is the relative molecular mass of the corresponding metal oxide, z i is the charge number, and r i is the ionic radius of the corresponding metal oxide) normalF normalT = 509.12 + 17.98 I normala normalv normale normalr normala normalg normale …”
Section: Resultsmentioning
confidence: 99%
“…29 Recently, several correlations to predict the AFTs according to the ionic potential have been explored. 14,15,30…”
Section: Comparison Between Differentmentioning
confidence: 99%
“…At this time, because the density of mullite was higher than that of the liquid melt, mullite sank in the melt. Therefore, the existence of refractory mullite led to the ash melting process following the “melting–sinking–dissolving” mechanism, as shown in Figure . Meanwhile, Ge et al conducted research on the impact of the Ca–Fe composite flux on coal ash slag fluidity .…”
Section: Effect Of Alkali-rich Industrial Solid Waste Addition On Coa...mentioning
confidence: 99%
“…Zhang et al 21 studied the effect of adding coal indirect liquefaction residue (LR) on the melting fluidity of coal ash through AFT and explained the melting mechanism of coal ash by using the change rate of ash cone height. Shi et al 22 analyzed fusion mechanisms of coal ashes with the help of thermomechanical analysis, high‐temperature scanning electron microscope, and predicted FT by chemical composition according to the ash fusion characteristics and mechanism. Du and Xu et al 17,18 observed the morphological changes of the ash samples at high temperatures through the heating stage microscope; then, the flow characteristics of samples were evaluated by their area shrinkage.…”
Section: Introductionmentioning
confidence: 99%