Lifetime and Degradation Studies of Poly (Methyl Methacrylate) (Pmma) Via Data-Driven Methods

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Lifetime and Degradation Studies of Poly (Methyl Methacrylate) (Pmma) Via Data-Driven Methods LIFETIME AND DEGRADATION STUDIES OF POLY (METHYL METHACRYLATE) (PMMA) VIA DATA-DRIVEN METHODS by DONGHUI LI Submitted in partial fulfillment of the requirements For the degree of Doctor of Philosophy Department of Materials Science and Engineering CASE WESTERN RESERVE UNIVERSITY May, 2020 Lifetime and Degradation Studies of Poly (Methyl Methacrylate) (PMMA) via Data-driven Methods Case Western Reserve University Case School of Graduate Studies We hereby approve the thesis1 of DONGHUI LI for the degree of Doctor of Philosophy Dr. Roger H. French Committee Chair, Adviser 03/17/2020 Department of Materials Science and Engineering Dr. Laura S. Bruckman Committee Member 03/17/2020 Department of Materials Science and Engineering Dr. Mark R. De Guire Committee Member 03/17/2020 Department of Materials Science and Engineering Dr. Michael J. A. Hore Committee Member 03/17/2020 Department of Macromolecular Science and Engineering 1We certify that written approval has been obtained for any proprietary material contained therein. To my parents, Jinxing Li & Xuemiao Chen, and my sister, Dongjie Li. Without them, none of this would’ve been possible. Table of Contents List of Tables vi List of Figures vii Acknowledgements xvi Abstract xvii Abstract xvii Chapter 1. Introduction1 PMMA: Applications and Degradation1 Lifetime and Degradation Science: Applicability to Polymers2 Thesis Overview3 Chapter 2. Literature Review5 PMMA and Its Applications5 Long-term Durability of Polymers: PMMA6 How to study polymer degradation scientifically 16 Photostabilization of Polymers: PMMA 21 Data-driven Lifetime Study 22 Statistical Learning Methods in Weathering Studies: State of Art Modeling 29 Chapter 3. Experimental 1 38 PMMA formulations 38 Exposures 38 Evaluations 41 Urbach analysis of absorption edges and Lorentzian fitting 42 iv Chapter 4. Results 45 Stabilizers in baseline samples of the 6 grades of PMMA 46 Yellowness Index and Haze 49 Absorbance and Induced Absorbance to Dose 57 Urbach fit results for 6 grades of PMMA 71 Self-organizing map as a tool to explore degradation patterns in 6 grades of PMMA 74 Chapter 5. Discussion 83 Urbach edge analysis 83 The effect of exposure types on degradation rate 85 Comparison of the durability of the 6 grades of PMMA 86 Degradation pathway models of PMMA 87 Chapter 6. Conclusion 90 Appendix A. Preparation of this document 92 Appendix B. Figures 93 Absorbance data for highly stabilized formulations 93 GC-MS data of the 6 grades of PMMA 94 Pairs plots for UVT and FF1 sample exposed in Hot QUV. 98 Appendix. Complete References 100 v List of Tables 2.1 General properties of unfilled PMMA.1 6 3.1 Exposure based on ASTM G154 and ASTM G155 standards 40 3.2 Spectral characteristics 40 4.1 Additives information for PMMA in Hot QUV at 0 hour. The ’-’ stands for that the stabilizer was not detected and the ’?’ stands for the stabilizer should be in formulation based on UV-Vis spectroscopy but was not detected by GC/MS. 46 4.2 Additives information for PMMA in Hot QUV at 0 hour with brand name and label for self-organizing map. The ’-’ stands for that the stabilizer was not detected and the ’?’ stands for the stabilizer should be in formulation based on UV-Vis spectroscopy but was not detected by GC/MS. 75 5.1 Urbach edge fit parameters for PMMA in Hot QUV at 0 hour 84 5.2 Urbach edge fit parameters for UVT PMMA in Hot QUV 84 5.3 Urbach edge fit parameters for FF1 PMMA in Hot QUV 85 vi List of Figures 2.1 Poly(methyl methacrylate) (PMMA) and monomer methyl methacrylate (MMA) structure5 2.2 The cause-and-effect diagram of PMMA degradation: the diagram is like a fish’s skeleton with the problem, the performance loss of PMMA, at the head and the causes for the performance loss feeding into the spine. General performance loss includes discoloration, embrittlement and haze formation.8 2.3 Decomposition of the ester group: ester groups on the side chain of PMMA absorbing light and the degradation of ester group involves three reaction. Reaction (1) is the most important process/2. 10 2.4 Main chain scission: a ¯-scission with formation of tertiary alkyl radical 11 2.5 PMMA:Disproportion reaction by hydrogen abstraction 11 2.6 Mechanisms for the generation of the secondary alkyl radical by the hydrogen abstraction reaction of backbone with methyl formate radical 11 2.7 PMMA main chain degradation: structure (1) and (2) are the results of homolytic main chain scission. The primary radical (2) can abstract hydrogen from the main chain to form a secondary radical (3). 12 2.8 Main chain radical termination 12 2.9 Degradation of PMMA in the presence of oxygen: the three types of alkyl readicals react rapidly with oxygen to generate peroxyl radicals. vii The CH , secondary and tertiary alkyl radicals react with oxygen to ¢ 3 yield peroxyl radicals3 13 2.10 Termination of peroxyl radical happens when at least one of the peroxyl radical is primary or secondary. The termination undergoes a Russell-type reaction to generate a ketone or aldehyde with an alcohol 14 2.11 Alkoxyl radicals generated by non-terminating reaction of two tertiary peroxyl radicals 14 2.12 The ¯-scission of Alkoxyl radicals 14 2.13 Monomer reactions: 3 pathways to degradation, where I is the free ¤ radical initiator generated from the degradation of the monomer and M and M represent the propagating radical and monomer ¤ respectively. 15 2.14 The monomer residual’s effect on degradation: reaction to generate tertiary alkyl radical 15 2.15 Spectral power distributions (280-4000nm) of The ASTM G173-03 AM 1.5, fluorescent UVA-340 and xenon arc full spectrum light sources 19 2.16 Spectral power distributions (280-400nm) of The ASTM G173-03 AM 1.5, fluorescent UVA-340 and xenon arc full spectrum light sources 20 2.17 Photostabilizations in photooxidative process 21 2.18 Data-driven method to study the durability of polymer materials 22 2.19 FTIR spectra for extruded PMMA sample. 24 2.20 Block diagram for Gas chromatography–mass spectrometry using electron ionization for collection of mass spectrum. 25 viii 2.21 CIE color space, top view 27 2.22 Spectrophotometer for haze measurement. 28 2.23 The Jablonski diagram for fluorescence. 30 2.24 Computational environment for data analysis: several open source software tools and R packages for visualization and spectral analysis. 30 2.25 An artificial network with 3 layers: input layer, hidden layer, and output layer 32 2.26 Training process of a self-organizing map 32 2.27 An example of structural equation model. Boxes contain variables that can be measured in the data. Circles contain variables that cannot be measured. Residuals and variances are drawn as double headed arrows pointing into an object. 36 2.28 An example of path modeling 36 2.29 An example of network modeling for yellowness index prediction with induced absorbance to dose as mechanism variable. 37 3.1 The exposure routes for the degradation study of the 6 grades of PMMA. 41 4.1 Stabilizers in the 6 grades of PMMA detected by GC/MS 48 4.2 The optical absorbance for UV absorbers4. 49 4.3 Yellowness index data for the stablilizer-free PMMA (UVT). 50 4.4 Yellowness index data for the 6 grades of PMMA. 50 4.5 Yellowness index data for the 5 grades of PMMA without UVT. 52 ix 4.6 Haze data for the 6 grades of PMMA. 52 4.7 Haze data for the 6 grades of PMMA exposed in QSUN. 53 4.8 Haze data for the 6 grades of PMMA in Hot QUV and Cyclic QUV. 53 4.9 Surface morphology of UVT samples at 0 hour 55 4.10 Surface morphology of UVT samples at 3200 hours exposure in QSUN. 55 4.11 Surface roughness of irradiated side (front) and non-irradiated side (back) in QSUN 56 4.12 ¢E data for the 6 grades of PMMA. 56 4.13 The panel plots for the baseline sample without any exposure. Each panel has 8 UV-Vis spectral data of samples. At baseline measurement, all the panel plots in one column should have similar results, indicating each grade of PMMA has low samplt-to-sample variation. 58 4.14 The process of quantification of degradation rate by induced absorbance to dose calculation: UVT exposed in Hot QUV as an example. 59 4.15 Abs/cm spectra for UVT under Hot QUV exposure. 60 4.16 Induced absorbance to dose (IAD) spectra for UVT under Hot QUV exposure. 60 4.17 Abs/cm spectra for UVT under Cyclic QUV exposure. 61 4.18 Induced absorbance to dose (IAD) spectra for UVT under Cyclic QUV exposure. 61 4.19 Abs/cm spectra for UVT under QSUN exposure. 62 x 4.20 Induced absorbance to dose (IAD) spectra for UVT under QSUN exposure. 63 4.21 Abs/cm spectra for FF1 under Hot QUV exposure. 65 4.22 Induced absorbance to dose (IAD) spectra for FF1 under Hot QUV exposure. 65 4.23 Abs/cm spectra for FF1 under Cyclic QUV exposure. 66 4.24 Induced absorbance to dose (IAD) spectra for FF1 under Cyclic QUV exposure. 66 4.25 Abs/cm spectra for FF1 under QSUN exposure. 67 4.26 Induced absorbance to dose (IAD) spectra for FF1 under QSUN exposure. 67 4.27 Abs/cm spectra for UVO under Hot QUV exposure. 68 4.28 Induced absorbance to dose (IAD) spectra for UVO under Hot QUV exposure. 68 4.29 Abs/cm spectra for UVO under Cyclic QUV exposure. 69 4.30 Induced absorbance to dose (IAD) spectra for UVO under Cyclic QUV exposure.
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