Physical Property Relationships in

Department of Chemistry, State University of New York at Binghamton, Binghamton, NY 13902-6016. Recently there has been a great deal of interest in in...
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In the Laboratory

Understanding Chemical Structure/Physical Property Relationships in Polymers through Molecular Modeling and Thermal Analysis Techniques A. Kim and J. L. Musfeldt* Department of Chemistry, State University of New York at Binghamton, Binghamton, NY 13902-6016

Recently there has been a great deal of interest in incorporating technology into the classroom setting (1–9). Molecular modeling, in particular, has experienced a renaissance in this regard, moving from a relatively specialized technique for highly trained theoretical chemists to a tool routinely employed throughout our profession (10, 11). In our department and in others, simple modeling exercises in the general and organic chemistry laboratories have been effective interest-building and visualization tools (12–14). Less work has been done, however, to integrate chemical modeling into the upper-divisional curriculum (15, 16). At the same time, the need to couple these new predictive capabilities with modern experimental approaches is equally pressing. Many problems of current interest are multifaceted, requiring several types of experimental analysis combined with a strong theoretical approach. This is especially true in highly interdisciplinary fields such as materials chemistry, environmental chemistry, or biochemistry. Despite the recognized value of a techniques-integrated classroom, incorporation of both theoretical and experimental tools and technology into the upper-division laboratory has been limited. Laboratories are typically “one-week episodes” in which students engage in a series of planned experiments using a single piece of equipment. Little time is spent considering how the technique could be combined with other methods to address real problems. Longer laboratory programs (17) are available to too few undergraduates. To provide a modern topic-oriented classroom and create real-life, hands-on, problem-solving opportunities for our students, we have created a four-week coupled lecture/ laboratory program to study the physical states of polymers. Using molecular modeling (CAChe) and thermal analysis (DSC) techniques, we concentrate on the role of chemical structure in determining the characteristics of the glass transition. Our goal is to mimic an advanced, real-world problem-solving situation where the predictive nature of modeling and the more time-consuming experimental observations are employed in an interactive way to tune materials for specific applications. Methods

Molecular Modeling of the Glassy Transition The glass transition temperature (Tg) of a polymer is the highest temperature relaxation of a macromolecule, associated with the onset of main-chain segmental motion;1 it is the most important thermal transition in an amorphous polymer. While a complete theoretical description of this com*Corresponding author.

plicated process is still out of reach, a variety of semiempirical methods have been put forward as a way to calculate the softening temperature of a polymer (18). In one such method, developed by Biscerano (19), the composition and chemical structure of the repeat unit work to determine Tg. In this model, 12 semiempirical factors describe chain stiffness, symmetry, and the cohesive forces between chains. These parameters are determined by comparison with a large data set; calculations on new materials show reasonable agreement (19). Students are provided with a detailed description of the CAChe modeling software and a copy of the original Biscerano paper (19). As in any calculation, the structure “input decks” are set up using the CAChe Molecular Editor. Once the geometry of the repeat unit is optimized, the atoms involved in the polymerization are designated. Our students run the Biscerano calculation using the Project Manager mode in CAChe. Insertion of the repeat unit structure and selection of the Biscerano calculation of Tg from a pull-down menu makes for a straightforward and rapid determination of the relaxation temperature. We suggest that one class period be devoted to familiarizing the students with the modeling software; an in-class discussion of the Biscerano method can be done at this time as well. At Binghamton, the students work in groups of two or three to begin the assignment and finish the calculations on their own as an extended out-of-class laboratory assignment. We provide five lessons on structure– property relationships in polymer Tg’s, and we ask students to complete three of them.

Experimental Determination of the Glass Transition Temperature The calorimetry experiments are carried out using a Perkin Elmer DSC 7, for which students are given detailed operating instructions. The standard operating range of the instrument is 25–700 °C.2 Approximately 15 mg of each polymer sample3 is encapsulated in a standard aluminum pan. Runs are made over “reasonable” temperature ranges at 20 °C/min, based upon students’ theoretical results.4 The glass transition temperature for each material is calculated using the accompanying Perkin-Elmer software to pinpoint the inflection point in the thermogram. Choice of Sample Materials Sample systems were chosen to illustrate a variety of chemical structure–physical property relationships. The material sets include constitutional isomers in poly(ethylene oxide), a series of poly(methyl methacrylate) (PMMA) derivatives with side chains of varying length and structure, a series of ring-containing high-performance composite polymers

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such as poly(ether ether ketone) (PEEK), hybrid organic/ inorganic composite polymers, and fire-retardant polymers (with emphasis on the chemical structure that promotes high thermal stability). Specific examples are given below.5 Naturally, theoretical estimates of Tg can be obtained on all polymers in our test set. Experimental determinations of Tg were conducted on a subset of those examined theoretically, the experimental samples representing a compromise between cost and availability. For example, the poly(ethylene oxide) derivative materials and most of the methacrylatebased polymers are available at reasonable cost from Aldrich or PolySciences, Inc. Unfortunately, we were not able to find a commercial source for poly(propyl methacrylate) (PPMA). We obtained samples of various fire-retardant polymers through the generous donation of fire-fighting gear from the local fire department.6

The Classroom Situation This is intended to be a fairly open-ended and researchlike laboratory experience, appropriate for an advanced class in polymer science. The need for such open-ended undergraduate laboratories is well documented (20). Students report that they enjoy the responsibility of this work and they seem to like the synergy between theory and experiment. Below, we discuss some aspects of data interpretation, which we look for in the lab write-up.

Figure 1. Chemical structure of methacrylate-based polymer derivatives.

Results And Discussion

PMMA-Based Polymers The exercise to understand the effect of chemical structure on Tg’s in a series of PMMA derivatives is one of the most interesting, as it is possible to consider both the length and the linearity of the hydrocarbon side-chain. The chemical structures of these derivatives are displayed in Figure 1. Both theoretical and experimental Tg’s of the various PMMA-based polymers are shown in Figure 2 as a function of the number of carbons in the side chain.7 Linear and branched chains are shown separately in this plot. As expected based upon configurational entropy considerations (Table 1), Tg decreases with the length and disorder of the linear side chain.8 This is an “internal plasticization” effect. As the length of the side chain increases, the number of available conformations increases owing to rotations around the C–C bonds; since Sconfig ↑, Tg ↓. A comparison of linear and branched side-chain polymers (for instance, PiPMA vs PMMA or PiBMA vs PBMA) shows that two competing factors are at work. First, increased branching results in a larger number of chain ends, which might work to increase the entropy and reduce Tg . On the other hand, the branching also results in fewer available conformations for the sterically hindered side chain, which can work to decrease the entropy of the side chain and increase Tg . The second factor is clearly more important here, as both the predicted and experimental transition temperatures increase on going to the corresponding branched derivative. Comparing the branched derivatives themselves (PiPMA and PiBMA), there is a major discrepancy between prediction and experiment. The Biscerano method predicts that upon going from the isopropyl to the isobutyl polymer, Tg should increase, perhaps owing to fewer conformations of the sidechain group. However, according to the experimental result, Tg actually decreases. 9 The competing factor is the number of branches on the side chain, and the number of defect structures present. Apparently, the CAChe modeling system

Figure 2. Glass transition temperature vs length of side chain in linear-chain methacrylate-based polymer derivatives. Inset: Glass transition temperature vs size of side chain for the branched-chain methacrylate derivatives. 䉭 : theoretical T g values, calculated using the Biscerano method; 䊊: experimental Tg values, measured with the DSC. Error bars are based upon multiple experimental runs for each material.

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In the Laboratory

favors the argument related to the number of conformations, whereas experimentally, the more important factor in comparing the two branched derivatives is the number of chain ends. From the series of Tg calculations for the PMMA derivatives, students find that the theoretically predicted trend is reasonable for the linear side-chain derivatives. This result suggests that the Biscerano technique can be useful for understanding the general trend of chemical structure–physical property relationships in hydrocarbon side-chain systems. In fact, such a conclusion is fairly general, applying to most of the polymer sets we examined. However, students also discover that, while the trends are correct, the absolute values of the various Tg’s are less reliable. Interestingly, there is a major discrepancy between the Biscerano prediction and the experiment for branched-chain methacrylate-based materials. Thus, students discover that while modeling is helpful as a predictive tool, experiments are necessary for accurate thermal characterization of a polymer. A straightforward extension of this project is to include a literature search of how these same chemical structure relationships affect the dynamic mechanical properties of the polymers in the series (21).

Poly(Ethylene Oxide) Constitutional Isomers A second interesting system that we ask students to explore comprises the polyethylene oxide constitutional isomers: polymers with the same chemical makeup but different bonding arrangements within the repeat unit (Fig. 3). Within the oxygen-containing series, the central issue is how the chemical structure of the isomer affects chain flexibility. For instance, when the oxygen is in the main-chain backbone, Tg is reduced (Table 1). Intermolecular hydrogen bonding possibilities are also important here. Isoelectronic substitution of sulfur (for oxygen) works to decrease chain rigidity and intermolecular electrostatic interaction, so Tg of each respective isomer is lowered. This trend is again supported by values obtained from CAChe, and a calculation of bond lengths in the sulfur-containing (vs oxygen-containing) polymers is helpful to illustrate the difference in rotational barriers, as the longer bonds are clearly more flexible. This project can be extended to include crystallization kinetics and spherulite formation in poly(ethylene oxide), as described by Marentette and Brown (22).

High-Performance and Organometallic Polymers As mentioned in the previous section, we have developed three other sets of materials for our molecular modeling/ thermal analysis laboratory. The first examines a set of ringcontaining high-performance polymers such as PEEK. In this exercise, students study the effect on Tg of replacing carbonyl groups with ester or ether linkages. Related liquid-crystalline materials are added to the mix to demonstrate the limitations of the modeling technique: the Biscerano method will compute a Tg for every repeat unit, even if it doesn’t correspond to physical reality. A second set of high-performance materials we study is a group of fire-retardant polymers. These include Nomex, Kevlar, and PBI, which are trade names of thermally resistant materials sold by Hoechst-Celanese and General Electric. Students compare the chemical structures of these polymers with other materials to identify structural characteristics that are responsible for the high thermal stability. Here, it is the aromatic nature of the repeat-unit structure that imparts the high thermal stability. This series also allows an assessment of effects of ortho, meta, and para ring linkages on thermal stability. Experimentally, samples of Nomex, Kevlar, and PBI (obtained from a donation of protective fire-fighting gear) display multiple thermal signatures on first heating (likely due to the blend nature of these fabrics) and a featureless and rising thermal response on multiple heating runs. This behavior indicates the degradation of the fire fighter’s “protective envelope” with thermal exposure. The third set of polymers is designed to highlight chemical/structural relationships in a series of organic– organometallic composites (23, 24). Here, students calculate the Tg’s of –(CH2CH2)–, –(CH2SiH2)–, and –(SiH 2SiH 2)–, which decrease going from polyethylene to polysilane. For these derivatives, it is helpful to calculate and compare the bond lengths of the organic, hybrid, and inorganic analogs to better understand the entropy effects and rotational barrier modifications. Extension of These Laboratory Exercises Clearly, there is wide latitude in which to explore various chemical structure–physical property relationships in polymeric systems, and we plan to develop additional laboratory problems in the future, focusing on modern materials such as adhesives for electronic packaging applications or lightemitting diodes. In these next labs, we want to make the prob-

Figure 3. Chemical structure of three constitutional isomers of poly(ethylene oxide). Poly(ethylene sulfide) derivatives are obtained by replacing the oxygen with sulfur.

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lems more open-ended. However, it is our experience that even with the current lessons, students work quickly to expand the chemical substitution options with those that they invent themselves. Finally, it should be noted that this laboratory program is designed to be coupled with an extended classroom discussion of the well-known configurational entropy theory and the WLF equation (25 ). The general trends, shown in Table 1, are a direct consequence of this analysis. However, without the proper theoretical underpinnings, the summarized results of Table 1 will not be very meaningful. A strong discussion of these concepts in a laboratory manual would probably be workable as well. Conclusion We report the development of a new set of laboratory experiments for our Polymer Science class. These exercises combine the predictive aspects of molecular modeling with experimental measurement of Tg via thermal analysis in order to determine and understand trends in polymer glass transition temperatures. Several case studies are presented as interesting systems with which to study chemical structure/ physical property relationships. In our course, this lab program is coupled with a classroom discussion of configurational entropy theory and the WLF equation. Acknowledgments Financial support from the Instrumentation and Laboratory Improvement Program (DUE-9650197 and DUE9452023) and the Career Development Program (DMR9623221), provided through the National Science Foundation, is gratefully acknowledged. This work benefited from conversations with L. V. Interrante, W. E. Jones, and F. H. Long. We are grateful to Dale Wade for donating the firefighter’s hoods. We thank G. Li for technical assistance. Notes 1. For amorphous polymers, the main thermal transition is the glass transition. Lower temperature relaxations may be present as well. Semicrystalline polymers display crystallization and melting transitions due to the chain-folded crystalline regimes, in addition to the thermal signatures due to the glassy component. Both amorphous and semicrystalline polymers decompose at high temperature. 2. Thermal sweeps are generally started 70 °C below the calculated Tg and continue to ≈70 °C above Tg. Use of a cooling block and a “homemade” Styrofoam Dewar flask filled with liquid nitrogen will allow an ambient-temperature DSC to reach lower temperature. 3. Both powder and compression-molded films were tested. After the first temperature sweep, the thermograms were the same because the processing-induced thermal history had been erased.

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4. We recommend that students do at least three temperaturesweep runs to assure good reproducibility. 5. Copies of the lab manual are available from the authors and also at http://chemiris.chem.binghamton.edu:8080/MUSFEDLT/ musfeldt.html. 6. The PBI and Kevlar in the donated fire-fighting gear are not pure; they probably contain plasticizers and other blend materials. However, this is a reasonable exchange, considering the cost savings. 7. Both powder and compression molded samples displayed similar trends after multiple runs (see Note 3). 8. If the side chain becomes very long, the material will display two Tg’s, as expected for a graft copolymer. 9. Our experimental transition temperatures for the branched PMMA-based derivatives are in good agreement with literature values.

Literature Cited 1. Whitnell, R. M.; Fernandes, E. A.; Almassizadeh, F.; Love, J. J. C.; Dugan, B. M.; Sawrey, B. A.; Wilson, K. R. J. Chem. Educ. 1994, 71, 721. 2. Tissue, B. M. J. Chem. Educ. 1996, 73, 65. 3. Krieger, J. H. Chem. Eng. News 1995, 73(46), 35. 4. Borman, S. Chem. Eng. News 1996, 74(38), 38. 5. Casanova, J.; Casanova, S. L. EDCOM Rev. 1991, 26(1), 31. 6. Dix, J. A.; Allendoerfer, R. D.; Jones, W. E., Jr.; Lacey, R. A.; Laurenzi, B. J. J. Educ. Technol. Sys. 1995, 24, 151. 7. Greenbowe, T. J.; Burke, K. A. TechTrends 1995, 23. 8. Krieger, J. Chem. Eng. News 1996, 74(11), 37. 9. Bragin, V. M. J. Chem. Educ. 1996, 73, 747. 10. Krieger, J. H. Chem. Eng. News 1995, 73(36), 30. 11. Krieger, J. H. Chem. Eng. News 1995, 73(18), 36. 12. Buss, D. C.; Fountain, K. R. J. Chem. Educ. 1993, 70, 295. 13. Casanova, J. J. Chem. Educ. 1993, 70, 904. 14. Delaware, D. L.; Fountain, K. R. J. Chem. Educ. 1996, 73, 116. 15. Lipkowitz, K. B.; Pearl, G. M.; Robertson, D. H.; Schultz, F. A. J. Chem. Educ. 1996, 73, 105. 16. Bakalbassis, E. G.; Stiakaki, M.-A. D.; Tsipis, A. C.; Tsipis, C. A. J. Chem. Educ. 1996, 73, 111. 17. Maier, M. L. J. Chem. Educ. 1996, 73, 643. 18. Lee, C. J. J. Macromol. Sci., Rev. Macromol. Chem. Phys. 1989, c29, 431. 19. Biscerano, J. Prediction of Polymer Properties; Dekker: New York, 1993; Chapter 6. 20. Wright, J. C. J. Chem. Educ. 1996, 73, 827. 21. Heijboer, H. The Physics of Non-Crystalline Solids; North-Holland: Amsterdam, 1965. 22. Marentette, J. M.; Brown, G. R. J. Chem. Educ. 1993, 70, 539. 23. Rushkin, I. L.; Interrante, L. V. Macromolecules 1996, 29, 3123. 24. Interrante, L. V.; Lui, Q.; Rushkin, I.; Shen, Q. J. Organomet. Chem. 1996, 521, 1. 25. Hiemenz, C. In Polymer Chemistry—the Basic Concepts; Dekker: New York, 1984; Chapter 4, p 260.

Journal of Chemical Education • Vol. 75 No. 7 July 1998 • JChemEd.chem.wisc.edu