Structure and Crystallization of High-Calcium, CMAS Glass Ceramics Synthesized with a High Content of Slag

In this work, more than 70 wt % of ferromanganese slag (containing 40 wt % CaO) was used to synthesize high-calcium, CaO-MgO-Al2O3-SiO2 (CMAS) glass ceramics. The effect of SiO2/CaO on the structure, crystallization behavior and microstructure of high-calcium, CMAS, slag glass ceramics was studied by IR, NMR, DSC, XRD and SEM. The results showed that in the high-calcium, CMAS glass ceramics, the main existing forms of silicon–oxygen tetrahedra (Qn) were Q0 and Q1. With the increase in the SiO2/CaO, Qn changed from Q0 and Q1 (main units) to Q1 (main units) and Q2, and then to Q1 and Q2 (main units). The polymerization degree of Qn changed from low to high, making the glass more stable, which led to the increase in crystallization temperature and the decrease in crystallization kinetic constant (k) and frequency factor (υ). At the same time, the change in the Qn structure resulted in a gradual change to the main crystal, from akermanite to diopside–wollastonite.

Effects of Chemical Properties and Inherent Mineral Matters on Pyrolysis Kinetics of Low-Rank Coals

The kinetics during the pyrolysis process depend on both chemical structure and inherent mineral matters in coal, but normally, only one of these components is investigated in literature. In the present work, four low-rank coals were pyrolyzed in a thermogravimetric analyzer at a heating rate of 10 K/min in a constant nitrogen stream at a temperature up to 900 °C to study the pyrolysis behavior and kinetics. Two of the samples were raw coal (R-YL) and clean coal (C-YL) obtained through the washing process. The results showed that the coal-washing process mainly affected the inorganic part (mineral matters) and structure in coal, which did not largely change the chemical properties. The pyrolysis behavior in primary stage (before 550 °C) was mainly affected by the chemical properties of coal, while the pyrolysis behavior in higher temperature also depended on inherent mineral matters. The kinetics of four coals were obtained using the Coats–Redfern (CR) method with five theoretical models. The difference of E value was almost negligible for R-YL and C-YL, also showing that the coal-washing process did not largely change the chemical properties. The higher frequency factor A for clean coal C-YL showed a more porous structure due to the coal-washing process. The apparent activation energy E in the third stage was affected by the thermodynamic property of inherent minerals.

Coal Pyrolysis Distribution

<p>Coal pyrolysis is a complex process involving a large number of chemical reactions. The most accurate and up to date approach to modeling coal pyrolysis is to adopt the Distributed Activation Energy Model (DAEM) in which the reactions are assumed to consist of a set of irreversible first-order reactions that have different activation energies and a constant frequency factor. The differences in the activation energies have usually been represented by a Gaussian distribution. This thesis firstly compares the Simple First Order Reaction Model (SFOR) with the Distributed Activation Energy Model (DAEM), to explore why the DAEM may be a more appropriate approach to modeling coal pyrolysis. The second part of the thesis uses the inverse problem approach together with the smoothing function (iterative method) to provide an improved estimate of the underlying distribution in the wide distribution case of the DAEM. The present method significantly minimizes the error due to differencing and smoothes the chopped off parts on the underlying distribution curve.</p>

Coal Pyrolysis Distribution

<p>Coal pyrolysis is a complex process involving a large number of chemical reactions. The most accurate and up to date approach to modeling coal pyrolysis is to adopt the Distributed Activation Energy Model (DAEM) in which the reactions are assumed to consist of a set of irreversible first-order reactions that have different activation energies and a constant frequency factor. The differences in the activation energies have usually been represented by a Gaussian distribution. This thesis firstly compares the Simple First Order Reaction Model (SFOR) with the Distributed Activation Energy Model (DAEM), to explore why the DAEM may be a more appropriate approach to modeling coal pyrolysis. The second part of the thesis uses the inverse problem approach together with the smoothing function (iterative method) to provide an improved estimate of the underlying distribution in the wide distribution case of the DAEM. The present method significantly minimizes the error due to differencing and smoothes the chopped off parts on the underlying distribution curve.</p>

Analysis of the thermoluminescent of borate glass by computerized glow curve deconvolution in kinetic formalism

Borate based phosphor is a suitable material for thermoluminescence dosimetry. Glow curves of β-irradiated pure borate glass has been analyzed by restoring to Computerized Glow Curve Deconvolution (CGCD) technique and evaluate the trapping parameters namely activation energy (E), frequency factor (s) and order of kinetics (b). It is observed that there are stable peaks in the range 110° to 150°C even to various extent of thermal cleaned ones also. The activation energies of the phosphor are in the range 0.898 to 1.325 eV and frequency factors are in the order of 1011 to 1013 s−1.

The effects of complications, frequency of control and education level on quality of life of type 2 diabetes mellitus patients

Background: Diabetes mellitus (DM) is a chronic disease with multiple aetiologies characterized by an increase in blood glucose levels exceeding normal limits. The world health organization predicts an increase in people with DM2 in Indonesia from 8.4 million to 21.3 million in 2030. Diabetes mellitus is one of the ninth main causes of decreased life expectancy, so it will greatly affect the quality of life of a person suffering from DM. Several factors that affect the quality of life of DM patients include age, gender, length of suffering, complications, education, marital status, level of compliance and occupation.Methods: This type of research is descriptive research with total sampling and obtained a sample of 26 respondents. Measurement of quality of life using the SF-36 instrument then the results were analysed using the chi square test to see the relationship between the factors that affect the quality of life.Results: The results obtained statistically that the complication factor (p=0.189) and the control frequency factor (p=0.596) did not significantly affect the quality of life. While the level of education statistically (p=0.006) affects the quality of life of DM patients.Conclusions: The results of the statistical study between complication factors and the frequency of control on the quality of life of DM patients showed no significant relationship. Meanwhile, the education level factor, both statistically and clinically, showed that there was a significant relationship with the quality of life of DM patients.