A backsheet is a polymeric cover of photovoltaic (PV) module and is designed to protect the inner components of module. Typical backsheets consist of three layers of polymers to prohibit diffusion of water and oxygen, as well as to protect human beings from electrical shock. It is critical that your solar panel has a backsheet that is of high quality and can withstand various environmental elements for 25 long years. Polyethylene terephthalate (PET) is an important material, and it mainly used as core and outer layer of backsheets and provide mechanical stability and electrical isolation. However, PET based Backsheets are highly susceptible to moisture and ultraviolet (UV) irradiance. Degradation of backsheets will causes severe economic loss and safty issue. Indoor accelerated exposures are used to study backsheets degradation within short time and predict the performance of backsheets exposed to the real world.
The backsheet degradation can be characterized with yellowness index (YI), which represents the color change of polymer and is associated with chemical change due to irradiance, high temperature and other process. The YI value of a PV backsheet also relates to the module efficiency. In addition, the Fourier-transform infrared spectroscopy (FTIR) is a effective method to study the chemical change of polymers. This non-destructive measurement enable people to obtain qualitative information of polymer functional groups and the relative amount of each group in the sample.
In this example, a dataset containing the YI of PET based backsheets (PET/PET/EVA) exposed to 1,500 hours of Damp Heat with no irradiance and an relative humidity of 85% and a chamber temperature of 85\(^\circ\)C. The PET samples were pull out from exposure chamber every 500 hours and the YI measurement was conducted at every step. The stress variable is exposure time with unit of hour. Mechanistic variables from FTIR are included to track chemical changes in the materials related to polymer chain scission due to hydrolysis, crystallinity change and oxidation.
## Load the backsheet data set
data(backsheet)
## Run netSEM
ans <- netSEMm(backsheet)
## Subset dataset with three cutoff
res <- subsetData(ans,cutoff=c(0.3,0.8,0.9))
## Plot the network model
plot(ans,res)
“Hours” is the endogenous and all other variables are considered as exagenous. Based on the plot, the “oxidation”, which represents the formation of conjugation structure due to oxidation, has the highest correlation with PET yellowing. The reason for this is that the conjugated structure decreases the band gap energy of PET, and the light absorbed by PET converts from UV light to blue light, and then PET starts to show yellow color. The strong relationships between all mechanism variables are also observed, which illustrates that these degradation mechanisms are connected with each other.
However, the models that mechianism variables as function of the endogenous variable of “Hours” have relative low adjusted \(R^2\). It may indicate the complexity of each degradation mechanism and other types of mechanism variables are needed to explain the variance of data.
Edge, M., R. Wiles, N. S. Allen, W. A. McDonald, and S. V. Mortlock. “Characterisation of the Species Responsible for Yellowing in Melt Degraded Aromatic Polyesters-I: Yellowing of Poly(Ethylene Terephthalate).” Polymer Degradation and Stability 53, no. 2 (August 1, 1996): 141-51. https://doi.org/10.1016/0141-3910(96)00081-X.
Gok, Abdulkerim, David K. Ngendahimana, Cara L. Fagerholm, Roger H. French, Jiayang Sun, and Laura S. Bruckman. “Predictive Models of Poly(Ethylene-Terephthalate) Film Degradation under Multi-Factor Accelerated Weathering Exposures.” PLOS ONE 12, no. 5 (May 12, 2017): e0177614. https://doi.org/10.1371/journal.pone.0177614.
This material is based upon work supported by the Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), under Award Number DE-EE-007143.