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In this approach, an integrated neural network (NN /thermogravimetric analyser (TGA) is designed to filter a noisy signal from TGA equipment.
Thermogravimetric analysis (TGA) was used to study thermal rearrangement at temperatures between 350 and 450 °C, and evolved gases from TGA were analyzed via mass spectrometry to characterize the byproducts of thermal rearrangement and thermal degradation.
The results from TGA studies supported these findings.
The char oxidation kinetics from TGA experiments is embedded in an integral model.
Physical properties include thermal, surface morphology of the materials were explained from TGA, DSC and SEM analysis.
These observations were similar to the weight loss results obtained from TGA studies reported in this study.
Taking into consideration from TGA this form is found to be a methanol solvate with 1: 1 stoichiometry.
Finally, another model was formulated from TGA results which represented a %weight loss at 400 °C with grafting percentage.
The thermal stability of SR composites obtained from TGA apparently improved by the addition of OM-POSS.
Solid residues produced at 300 °C and 800 °C from TGA were also analysed to determine the ultimate composition of chars.
The mass loss and mass loss rate with time derived from macro-TGA looks similar to TG curve and differential thermogravimetric (DTG) curve from TGA.
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