Integrated TGA, FTIR, and Computational Laboratory Experiment

Laboratory Experiment Cite This: J. Chem. Educ. XXXX, XXX, XXX−XXX

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Integrated TGA, FTIR, and Computational Laboratory Experiment Andrew T. Pemberton,† D. Brandon Magers,* and Daniel A. King* Department of Chemistry and Biochemistry, Taylor University, Upland, Indiana 46989, United States

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S Supporting Information *

ABSTRACT: Thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and computational chemistry are used in concert to evaluate the thermal decomposition of calcium acetate monohydrate, Ca(C2H3O2)2·H2O, and to engage students in high-level thinking as they synthesize results from several techniques. Students use TGA to generate and isolate the reaction intermediates and final product. Three common TGA transitions (the loss of water, the generation of a metal carbonate, and the generation of a metal oxide) with very different reaction temperatures are observed with this sample. The resulting four samples (starting material, two intermediates, and final product) are then analyzed by FTIR. Students are able to observe the progress of the reaction through a comparison of the IR spectra, via the change of water, O−H, and C−H signals. The computational analysis of the vibrational frequencies of carbonate is performed to demonstrate the concepts of predicting the number of principal vibrational frequencies, vibrational degeneracy, and IR activity in addition to aiding in the identification of the second decomposition intermediate, CaCO3. This integrated approach also encourages students to appreciate the strengths and weaknesses of various techniques and recognize that often chemical analysis requires the use of multiple tools. KEYWORDS: Upper-Division Undergraduate, Analytical Chemistry, Laboratory Instruction, Computer-Based Learning, Hands-On Learning/Manipulatives, Inquiry-Based/Discovery Learning, Computational Chemistry, Instrumental Methods, IR Spectroscopy, Quantum Chemistry, Thermal Analysis

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INTRODUCTION The traditional undergraduate chemistry curriculum is both broad and deep. The breadth is reflected in the variety of courses from among the principle subdisciplines of inorganic, organic, physical, analytical, and biochemistry. From the mathheavy theories of physical chemistry to the application focused techniques of analytical chemistry, it will typically require four years for students to explore all of these areas. The depth of the chemistry curriculum is reflected in the amount of content within the subdisciplines. The content is so rich that it is common for universities to offer two-semester course sequences in each of the subdisciplines. Consequently, the challenge for undergraduate students is to master the detailed content of the subdisciplines while somehow building horizontal connections among them at the same time.1−6 Instrumental analysis (IA) is typically taught as an advanced course within the Analytical Chemistry subdiscipline and, like the other subdisciplines, is composed of its own jargon and tools. When students are exposed to the most fundamental information regarding chemical instruments, they will be engaging in the first two levels of thinking within Bloom’s Taxonomy: (1) Gathering Knowledge and (2) Comprehending and Confirming.7,8 This factual oriented portion of the course is often reflected in objective test questions and vocabulary. Then, when students are exposed to the uses of the instruments and the interpretation of data, they will be engaging in the next two levels of thinking: (3) Applying and (4) Analyzing. However, it is difficult to engage IA students in the two highest levels of thinking, (5) Synthesizing and (6) © XXXX American Chemical Society and Division of Chemical Education, Inc.

Evaluating, without placing the students into a context where they must either interact with technique and theory at the same time or apply multiple techniques at the same time.9,10 In addition to achieving high-level cognitive involvement, this approach has the advantage of modeling several crucial characteristics of career work within the field of analytical chemistry that might not otherwise find its way into the curriculum: (1) All methods have strengths and weaknesses, uses and limitations. (2) To fully answer your research question multiple methods may be necessary. (3) You may need the interpretation of one method’s data to help you interpret the data from another. Furthermore, the applications of instrumental techniques and the theories behind them can often be strong points of connection with the other subdisciplines. For example, the high-performance liquid chromatography analysis of a biochemical material can considerably fortify knowledge acquired in both the analytical and biochemistry areas if the students are provided time and incentive to engage the context of the application within the structure of the course. Among the common chemical instruments that would comprise the undergraduate IA course curriculum, there are clear Received: July 26, 2018 Revised: November 17, 2018

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DOI: 10.1021/acs.jchemed.8b00607 J. Chem. Educ. XXXX, XXX, XXX−XXX

Journal of Chemical Education

Laboratory Experiment

students perform all runs, details explained later), and the FTIR takes approximately 1 h for all four samples. The three groups will come to lab staggered by 1 h. Each group will complete the exercise in 2 h in lab with approximately 1 h of work to be done outside of lab in completing the post lab report sheet. Performed in this manner, 4 h of instructional time by the instructor is required to guide all three groups through the TGA/FTIR lab session.

applications in all of the subdisciplines, while the theory behind them is often a strong point of connection to physical chemistry. In an effort to create a laboratory experience that would achieve the primary goal of providing students with experience using chemical instruments, and the secondary goal of engaging content at the highest level of thinking, this paper describes an integrated laboratory experiment that requires students to use computational chemistry, thermogravimetric analysis (TGA), and Fourier transform infrared spectroscopy (FTIR) in concert to determine the identities of a compound and its thermal decomposition intermediates and product. Previous reports of such integrated approaches have shown positive learning outcomes, some including TGA and FTIR.11−17 This experiment requires students to have not only a functional understanding of the three techniques, but also an understanding of the techniques’ strengths and uses, and how the set of data might be used together to corroborate one another. The specific incorporation of computational chemistry within this experiment also illustrates to the students the growing and valued role that computational chemistry (traditionally located within the Physical Chemistry subdiscipline) is playing within the field of modern analytical chemistry. Pedagogically, the Computational Chemistry section of this laboratory experiment is particularly chosen to help introduce concepts and principles of infrared spectroscopy. Students should finish this exercise having met certain learning outcomes, including being able to determine the number of expected fundamental vibrational frequencies for a molecule (3N − 6 or 3N − 5 for a linear molecule), understand the concept of degenerate modes, and resolve whether a vibration should be IR active or inactive by observing a change in dipole moment in the vibration. The instrumental portion of this experiment will not only improve students’ comfort level in operating the TGA and FTIR, but also familiarize students with the kind of information that can be gleaned from both techniques. Students should be able to recognize several common transitions within TGA traces of organic compounds and should be able to interpret observed mass losses and compare them to theoretical mass losses. Students should be able to recognize a few key IR peaks and interpret the significance of these functional group indicators in monitoring a multistep process. The background information needed for the students to understand these concepts while performing the experiment is provided to them in the laboratory instructions and prelab discussion by the instructor. Students are required to record their data and their interpretation of results in a lab notebook which would include balanced chemical equations, hazards, and observations. The postlab questions (included in the Supporting Information) require students to specifically demonstrate their mastery of the learning objectives. The instrumental analysis course where this experiment has been performed over the past three years typically has about 10 students, who generally have limited or no exposure to these techniques. So by performing this experiment in groups of 3− 4, three small groups need to be guided through the lab. The computation portion of the experiment takes approximately 30 min and can be done at a separate meeting time. The TGA and FTIR portions of the lab will be performed in one full lab session. The TGA experiment takes only a little more than an hour if the longest run is completed for them (2 h if the

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HAZARDS For the TGA and FTIR portions of this experiment, students should wear eye protection and exam gloves. Although the compound used in this particular experiment is not hazardous, students should learn how to perform such experiments in a safe manner for future experiments when the samples may be more hazardous. Additionally, TGA pans can be very hot, and they should be handled with gloves or tweezers because they can burn your skin and the oils from the skin can affect the performance of the instrument. For the IR analysis, the pellet press which uses many tons of pressure should never be operated without eye protection. Oils from skin on a prepared IR pellet can also affect the performance of this instrument.

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RESULTS AND DISCUSSION

Computational Chemistry

Though the intricacies of computational chemistry are beyond the scope of an undergraduate instrumental analysis course, the use of computational chemistry tools as a black box is well within the expected intellectual grasp. In practice, the computational analysis of the starting material, Ca(C2H3O2)2·H2O, is much too complex, so the carbonate anion was chosen for this experiment because it is relatively simple computationally and it is an important species within the decomposition pathway of most organic compounds. Students computed an optimized geometry and harmonic fundamental frequencies of carbonate using WebMO18 and PSI4,19 a web-based interface and an open-source computational chemistry package, respectively. Default settings were selected, and computations were carried out with the MP2 level of theory20 with a cc-pVTZ basis set.21 See method details in Supporting Information. The computed vibrational frequencies (Table 1) can be evaluated to some degree by the students. Students see that there are six fundamental vibrational frequencies, which follows the 3N − 6 guideline. Most importantly, WebMO can visually display each vibrational mode. Students observed each vibrational mode and predicted which ones would be IR active based on a change in Table 1. Comparison of Computed Harmonic Frequency Values of CO32− and FTIR Vibrational Frequency Values of CaCO3 Frequency, cm−1 Description c

In-plane bend Out-of-plane bend Symmetric C−O stretch Asymmetric C−O stretchc

Computeda

Exptlb

645 898 1025 1446

713 875 1429

a

Computed harmonic CO32− frequencies, performed at the MP2 level of theory with a cc pVTZ basis set. bFTIR CaCO3 vibrational frequencies. cDoubly degenerate mode. B




corresponds to 9.9% of the original sample, students should be able to calculate that the sample is monohydrated. The water loss is in excellent agreement with the theoretical mass loss of 10.2%. Therefore, students should be able to determine that the starting material is Ca(C2H3O2)2·H2O, and the first intermediate ought to be the anhydrous calcium acetate, Ca(C2H3O2)2. Then, knowing that the next to last transition for organics tends to be the formation of the metal carbonate, with a little prodding students ought to be able to predict that the second intermediate is likely to be CaCO3. This can be further supported by comparing the observed mass loss between the starting material and the second intermediate of 42.5% and the theoretical weight loss of 43.2%. Finally, students should predict that the final product will be the metal oxide, calcium oxide in this case. The observed weight loss between the starting material and the final product was 67.9%, which agrees quite nicely with the theoretical mass loss between calcium acetate monohydrate and calcium oxide, 68.2%. Chemical reactions for each decomposition step are shown below.

dipole moment. A sample video of one of the vibrational modes is provided in the Supporting Information. A free anion carbonate will have one IR inactive mode, ν1, corresponding to the all-symmetric stretch of the C−O bonds. Students also noted how multiple vibrations can be degenerate and thus absorb at the same energy. Both ν3 and ν4 are doubly degenerate, at 1025 and 1446 cm−1, respectively. It is worth noting that, at the time of this paper, IR intensities are not available in PSI4 and thus show as zero in the WebMO results page. The students will compare these computational results with the FTIR spectra produced for the thermal decomposition intermediates and products to confirm to presence or absence of carbonate in the samples. Thermogravimetric Analysis

For the sake of time, an initial complete decomposition scan of the calcium acetate monohydrate sample by TGA was performed by the instructor ahead of time and the resulting trace is provided the students upon arrival to the lab. This experiment was carried out on a Q600 dual TGA/DSC (TA Instruments). A representative decomposition trace, the heating of sample from 20 to 800 °C at 20 °C/min, is shown in Figure 1. See method details in Supporting

Ca(C2H3O2 )2 ·H 2O(s) → Ca(C2H3O2 )2 (s) + H 2O(g) Ca(C2H3O2 )2 (s) + 4O2 (g) → CaCO3(s) + 3CO2 (g) + 3H 2O(g) CaCO3(s) → CaO(s) + CO2 (g) Fourier Transform Infrared Spectroscopy

At this point, the students should be pretty confident in the identity of each of the four materials, Ca(C2H3O2)2·H2O, Ca(C2H3O2)2, CaCO3, and CaO. For further corroboration of their findings, the starting material and the three samples isolated from the TGA (two intermediates and the final product) were analyzed by FTIR (Nicolet 6700) at a resolution of 2 cm−1. Samples were prepared as pellets in a 1/10 ratio with KBr. See method details in Supporting Information. Sample spectra are shown in Figure 2. Although the thorough interpretation of an IR spectra can be complicated and particularly so for decomposition intermediates which are not likely to be pure, students are well-equipped to use the IR spectra to help evaluate their determinations made from the TGA data. Therefore, students only need to be able to recognize key IR transitions relevant to the comparison of the four materials. For example, students should recognize the very broad signal characteristic of the OH stretch (3300 cm−1), which is indicative of the presence of water or alcohol in the starting material. To evaluate the first transition, the IR spectrum of the starting material is compared with that of the first intermediate. The characteristic water signal dramatically decreases during the first transition which should confirm to them the loss of water. The rest of the spectrum remains primarily unchanged during this transition. The removal of the water reveals more discrete signals from 3000 to 3600 cm−1 indicative of O−H vibrations from an alcohol or carboxylate as well as CH vibrations that were previously covered up. The presence of a carbonyl signal, CO, at approximately 1600− 1700 cm−1, may help to confirm the presence of the carboxylate. When comparing intermediates 1 and 2, students should notice that there are no more CH or OH signals, or fine fingerprint region signals indicative of organics. Additionally, the CO vibration previously observed in the 1600−1700

Figure 1. Thermogravimetric decomposition trace for calcium acetate monohydrate.

Information. The trace clearly shows an initial mass loss near 4 min (100 °C), with the plateau extending to 15 min (400 °C) when there is a second mass loss. Finally, at approximately 30 min (600 °C) there is another mass loss event. The three transitions correspond to loss of approximately 10%, 30%, and 40% of the initial sample weight, respectively. The final product was removed from the TGA sample pan and set aside for FTIR analysis. Students used this complete decomposition trace to determine the approximate temperatures at which subsequent runs should be stopped in order to generate and isolate the two decomposition intermediates. Students ran the second sample using the same method as before but stopped at approximately 14 min (300 °C) to collect the first intermediate. The product was removed from the pan and set aside for FTIR analysis. Students ran the third sample as before but stopped at approximately 26.5 min (550 °C) to collect the second intermediate. The product was removed from the pan and set aside for FTIR analysis. Knowing only that the original sample was Ca(C2H3O2)2· nH2O, and that what is likely a loss of water near 100 °C C




Figure 2. FTIR spectra of the starting material (solid), first intermediate (small dashes), second intermediate (medium dashes), and final product (large dashes) are shown.

cm−1 range is now gone, leaving a prominent signal at about 1400 cm−1. Students will not likely know that this strong signal at 1400 cm−1 is indicative of carbonates prior to this experiment, but at this point the computational results can be used to complement their identification of the calcium carbonate as the second intermediate. The IR spectra of the final product is rather empty, and its most important characteristic is its decrease in significant IR signals. They should observe that the carbonate signal, if not entirely gone, is now significantly diminished. This should strengthen their confidence in their determinations.

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production of a metal carbonate, and then the production of a metal oxide) with large gaps in reaction temperatures make Ca(C2H3O2)2·H2O an ideal choice for this experiment. While comparing the FTIR spectra of the starting material, two intermediates, and final product, students are encouraged to look for signals that indicate changes in functional groups among the samples. As identifications are proposed, students can compare observed decreases in the weight percent from the TGA to theoretical mass losses to support their theories. The inclusion of the computational analysis of carbonate is a great way to incorporate the vibrational spectroscopy concepts of the number of principle vibrational frequencies, degeneracy, and IR activity, as the specific computational results aid in the interpretation of the FTIR spectrum of the second intermediate, CaCO3.

CONCLUSIONS

This experiment has proven to be an effective method for not only providing students with hands-on experience performing computational, thermogravimetric, and FTIR analyses, but also engaging students in high-level thinking practices of application, analysis, synthesis, and evaluation. Throughout this experiment students must analyze the results from several techniques while synthesizing them into a coherent evaluation of a decomposition reaction. Using the TGA as a means to generate and isolate thermal decomposition intermediates for subsequent analysis by FTIR requires students to be able to interpret a TGA trace and to intentionally alter operational settings to stop their two subsequent runs at the desired temperatures. Common TGA transitions (the loss of water, the

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available on the ACS Publications website at DOI: 10.1021/acs.jchemed.8b00607. Method details (PDF, DOCX) Student instructions (PDF, DOCX) Postlab questions (PDF, DOCX) Video of carbonate vibration (MPG) D



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(16) Björk, E. M. Synthesizing and Characterizing Mesoporous Silica SBA-15: A Hands-On Laboratory Experiment for Undergraduates Using Various Instrumental Techniques. J. Chem. Educ. 2017, 94 (1), 91−94. (17) Jefferson, A.; Phillips, D. N. Teaching Polymer Science to Third-Year Undergraduate Chemistry Students. J. Chem. Educ. 1999, 76 (2), 232−235. (18) Schmidt, J. R.; Polik, W. F. WebMO, 17.0.; WebMO LLC: Holland, MI, 2017. (19) Parrish, R. M.; Burns, L. A.; Smith, D. G. A.; Simmonett, A. C.; DePrince, A. E.; Hohenstein, E. G.; Bozkaya, U.; Sokolov, A. Y.; Di Remigio, R.; Richard, R. M.; et al. Psi4 1.1: An Open-Source Electronic Structure Program Emphasizing Automation, Advanced Libraries, and Interoperability. J. Chem. Theory Comput. 2017, 13, 3185−3197. (20) Møller, C.; Plesset, M. S. Note on an Approximation Treatment for Many-Electron Systems. Phys. Rev. 1934, 46, 618−622. (21) Dunning, T. H. Gaussian Basis Sets for Use in Correlated Molecular Calculations. I. The Atoms Boron through Neon and Hydrogen. J. Chem. Phys. 1989, 90 (2), 1007−1023.

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. ORCID

Andrew T. Pemberton: 0000-0001-9089-5861 D. Brandon Magers: 0000-0001-6002-0183 Daniel A. King: 0000-0002-5993-0814 Present Address †

Department of Chemistry, Washington State University, Pullman, Washington 99164, United States. Notes

The authors declare no competing financial interest.

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REFERENCES

(1) Levy, S. T.; Wilensky, U. Crossing Levels and Representations: The Connected Chemistry (CC1) Curriculum. J. Sci. Educ. Technol. 2009, 18 (3), 224−242. (2) Bruck, L. B.; Towns, M.; Bretz, S. L. Faculty Perspectives of Undergraduate Chemistry Laboratory: Goals and Obstacles to Success. J. Chem. Educ. 2010, 87 (12), 1416−1424. (3) Schaller, C. P.; Graham, K. J.; Johnson, B. J.; Fazal, M. A.; Jones, T. N.; McIntee, E. J.; Jakubowski, H. V. Developing and Implementing a Reorganized Undergraduate Chemistry Curriculum Based on the Foundational Chemistry Topics of Structure, Reactivity, and Quantitation. J. Chem. Educ. 2014, 91 (3), 321−328. (4) Talanquer, V. Chemistry Education: Ten Facets To Shape Us. J. Chem. Educ. 2013, 90 (7), 832−838. (5) Levy, S. T.; Wilensky, U. Students’ Learning with the Connected Chemistry (CC1) Curriculum: Navigating the Complexities of the Particulate World. J. Sci. Educ. Technol. 2009, 18 (3), 243−254. (6) Bretz, S. L.; Fay, M.; Bruck, L. B.; Towns, M. H. What Faculty Interviews Reveal about Meaningful Learning in the Undergraduate Chemistry Laboratory. J. Chem. Educ. 2013, 90 (3), 281−288. (7) Krathwohl, D. R. A Revision of Bloom’s Taxonomy: An Overview. Theory Pract. 2002, 41 (4), 212−218. (8) Seddon, G. M. The Properties of Bloom’s Taxonomy of Educational Objectives for the Cognitive Domain. Rev. Educ. Res. 1978, 48 (2), 303−323. (9) Domin, D. S. A Content Analysis of General Chemistry Laboratory Manuals for Evidence of Higher-Order Cognitive Tasks. J. Chem. Educ. 1999, 76 (1), 109−111. (10) Crowe, A.; Dirks, C.; Wenderoth, M. P. Biology in Bloom: Implementing Bloom’s Taxonomy to Enhance Student Learning in Biology. CBELife Sci. Educ. 2008, 7 (4), 368−381. (11) Williams, K. R. Analysis of Ethylene-Vinyl Acetate Copolymers: A Combined TGA/FTIR Experiment. J. Chem. Educ. 1994, 71 (8), A195−A198. (12) Williams, K. R.; Young, V. Y.; Killian, B. J. Coulometric Titration of Ethylenediaminetetraacetate (EDTA) with Spectrophotometric Endpoint Detection: An Experiment for the Instrumental Analysis Laboratory. J. Chem. Educ. 2011, 88 (3), 315−316. (13) Luna Vera, F.; Guancha Chalapud, M.; Castillo Viveros, I.; Vásquez Medina, E. A. From Eggshells to Quicklime: Using Carbonate Cycle as an Integrating Concept To Introduce Students to Materials Analysis by TGA and FTIR. J. Chem. Educ. 2018, 95 (4), 625−630. (14) Harris, J. D.; Rusch, A. W. Identifying Hydrated Salts Using Simultaneous Thermogravimetric Analysis and Differential Scanning Calorimetry. J. Chem. Educ. 2013, 90 (2), 235−238. (15) Hutchison, A. R.; Krepps, M. K.; Atwood, D. A.; Otieno, T. Synthesis and Spectral and Thermal Properties of Pyrazine-Bridged Coordination Polymers of Copper(II) Nitrate: An Experiment for Advanced Undergraduates. J. Chem. Educ. 2002, 79 (11), 1355−1357. E


Integrated TGA, FTIR, and Computational Laboratory Experiment

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