The stability to high temperature is one of the important indicators of the stability of fiber materials. Alfa Chemistry provides analytical testing services for heat resistance and thermal stability of fiber materials. Our fiber analysis laboratory has a strong technical infrastructure and a team of well-trained and experienced experts.
Heat resistance: It characterizes the change in the mechanical properties of the fiber measured at elevated temperature. This change can often be recovered when returning to normal temperature (belonging to a reproducible change), so it is also called physical heat resistance.
Thermal stability: It characterizes irreversible changes in mechanical properties of fibers after they are heated. This change is measured after heating the fiber and cooling to normal temperature, which is caused by the degradation or chemical change of the polymer, so it is also called chemical heat resistance.
Characterizing the heat resistance and thermal stability of fiber materials is a very important step because fibers may involve high temperature environments in specific applications.
Combining rich analysis experience and advanced technology, our team provides comprehensive and accurate heat resistance and thermal stability analysis services for fiber materials, as well as detailed analysis results and reports. Analysis items for fiber thermal properties include but are not limited to the following:
Alfa Chemistry has been focusing on the research and development of analytical technology in the fiber materials industry, and is committed to continuously improving our fiber analysis technology. It has been reported that the fast boundary element method is applied to the three-dimensional large-scale thermal analysis of fiber-reinforced composites based on the line inclusion model. For example, H.T. Wang et al. used the line inclusion model of the fast boundary element method for large-scale thermal analysis of fiber composites. In this work, the researchers calculated temperature distributions for 200 fibers using conventional and line inclusion modeling. The results show that the relative error is within 0.4% in all cases, and the line inclusion model significantly reduces the problem size. [1]
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