Publication | Open Access
Multivariate process trajectories for molecular description of <scp>MF</scp> thermal curing and correlation with hydrolytic stability
13
Citations
21
References
2021
Year
EngineeringDifferential Scanning CalorimetryComputational ChemistryChemistryMolecular DynamicsDerivative ThermogravimetryPolymer ProcessingAnalytical ChemistryMolecular SimulationThermodynamicsPrincipal Component AnalysisMolecular KineticsPolymer ChemistryBiophysicsThermoanalytical MethodMaterials ScienceFtir/pcr ModelHydrolytic StabilityPrincipal Component RegressionPolymer AnalysisMultivariate Process TrajectoriesPolymer ScienceMaterials CharacterizationMolecular DescriptionPolymer CharacterizationChemical KineticsThermophysical Property
Abstract During curing of thermosetting resins the technologically relevant properties of binders and coatings develop. However, curing is difficult to monitor due to the multitude of chemical and physical processes taking place. Precise prediction of specific technological properties based on molecular properties is very difficult. In this study, the potential of principal component analysis (PCA) and principal component regression (PCR) in the analysis of Fourier transform infrared (FTIR) spectra is demonstrated using the example of melamine‐formaldehyde (MF) resin curing in solid state. FTIR/PCA‐based reaction trajectories are used to visualize the influence of temperature on isothermal cure. An FTIR/PCR model for predicting the hydrolysis resistance of cured MF resin from their spectral fingerprints is presented which illustrates the advantages of FTIR/PCR compared to the combination differential scanning calorimetry/isoconversional kinetic analysis. The presented methodology is transferable to the curing reactions of any thermosetting resin and can be applied to model other technologically relevant final properties as well.
| Year | Citations | |
|---|---|---|
Page 1
Page 1