Understanding Thermodynamic Control in Covalent Self-Assembly: A

Laboratory Experiment Cite This: J. Chem. Educ. 2019, 96, 1230−1235

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Understanding Thermodynamic Control in Covalent Self-Assembly: A Mixed Synthetic−Computational Experiment for the Undergraduate Organic-Chemistry Laboratory Adam G. L. Schafer, Ellen J. Yezierski, and C. Scott Hartley* Department of Chemistry and Biochemistry, Miami University, Oxford, Ohio 45056, United States

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S Supporting Information *

ABSTRACT: A laboratory experiment was developed that connects the interpretation of computer-generated models to the self-assembly of macrocycles. Students compare the reactions of terephthalaldehyde and isophthalaldehyde by reacting each with (R,R)-(−)-1,2-diaminocyclohexane. These isomeric systems serve as the foundation for a discussion about the impact of entropy and enthalpy on macrocycle formation. This experiment requires students to use multiple data sources to develop evidence-based explanations about the impact of the starting-material geometry on macrocyclization. Results from laboratory implementation indicate that a majority of students were able to successfully demonstrate competency of the learning goals. KEYWORDS: Second-Year Undergraduate, Organic Chemistry, Laboratory Instruction, Molecular Modeling, Synthesis, Thermodynamics, Inquiry-Based/Discovery Learning, Computer-Based Learning, Hands-On Learning/Manipulatives

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dehyde (T) and isophthalaldehyde (I), as shown in Scheme 1.4,5 For each system, the geometry of the dialdehyde starting material leads to differences in the macrocycle produced. The system involving T (Scheme 1a) forms a single 3 + 3 macrocycle product, 3T (i.e., three dialdehydes and three diamines), that is relatively free of strain. Alternatively, the system involving I (Scheme 1b) results in 2 + 2 and 3 + 3 macrocycle products (2I and 3I) because the meta-phenylene subunit is not a particularly good match to either geometry. The concept of strain aligns to the topics essential to the organic-chemistry curriculum cited in the American Chemical Society Exams Institute’s Anchoring Concept Content Map for organic chemistry.9 Students synthesize both sets of macrocycles and then use computer-generated models to explore how strain impacts their formation. Constructing models is a scientific practice that is highly intertwined with other practices, such as analyzing and interpreting data.10 Many studies assert the need to incorporate computer models into the chemistry curriculum.11−14 Computer models offer a unique opportunity to help students visualize the structure of a molecule, while also providing opportunities to connect calculated values, such as stability, to the generated model. As such, computer models open the door to many added learning benefits. However, models can also potentially introduce incorrect ideas, because

INTRODUCTION Self-assembly is broadly defined as a process in which a product naturally forms from its components.1 Because self-assembly allows for the efficient formation of many bonds in one synthetic step, it can be used in the synthesis of large molecules, such as macrocycles.1−3 In recent years, the popularity of using selfassembly for the synthesis of large organic molecules has grown. However, despite popularity in the field and a significant number of real-world applications, such as host−guest chemistry, molecular recognition, and molecular machines, organic synthesis using self-assembly is not commonly addressed in organicchemistry laboratory courses.1−8 Synthesis in organic-chemistry laboratory courses is commonly taught through step-by-step syntheses, despite the ability of self-assembly to reduce the number of synthetic steps required to form certain products. As shown in Figure 1, a dynamic system of bifunctional monomers will give macrocycles of various sizes in equilibrium with polymer. The most thermodynamically stable product or products, which balance the entropic preference for the smallest possible closed structure (maximizing translational entropy) against the penalties associated with introduced strain and conformational rigidification, will be favored at equilibrium. This allows for an “error checking” that reduces or eliminates other thermodynamically unfavorable products,1,2 but high yields depend strongly on the geometries of the subunits. In this experiment, the process of self-assembly is applied to the formation of trianglimine macrocycles from (R,R)-(−)-1,2diaminocyclohexane (1) and benzenedialdehydes terephthalal© 2019 American Chemical Society and Division of Chemical Education, Inc.

Received: December 21, 2018 Revised: April 19, 2019 Published: May 10, 2019 1230

DOI: 10.1021/acs.jchemed.8b01046 J. Chem. Educ. 2019, 96, 1230−1235

Journal of Chemical Education

Laboratory Experiment

Figure 1. Dynamic system of bifunctional monomers giving, in principle, a distribution of macrocycles of various sizes and polymer, with the major product dictated by thermodynamic stability.

Scheme 1. Terephthalaldehyde Reacting with 1,2-Diaminocyclohexane to Self-Assemble into a Single Macrocycle Product (a) and Isophthalaldehyde Reacting with 1,2-Diaminocyclohexane to Self-Assemble into Two Macrocycle Products (b)

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students often do not interpret models with consideration to their applications and limitations.15−17 In this experiment, a novel approach to model generation and modification allows for a more meaningful application of the key chemistry skills used in the experiment, such as analyzing and interpreting data from multiple sources to draw conclusions. Students are prompted to consider the limitations and applications of their models to help them avoid potential incorrect ideas. Students encounter a structured obstacle, commensurate with organic chemists conducting research. The experiment promotes a more meaningful laboratory experiment by incorporating a real-world obstacle that requires students to generate potential solutions.18

EXPERIMENTAL OVERVIEW

Before coming to lab, students complete a prelab module. The module has two main objectives: (1) to elicit students’ prior knowledge about entropy and enthalpy and situate these concepts in the context of macrocyclization and (2) to introduce students to the molecular-modeling application to make later model generation in the experiment more efficient. In the laboratory, students synthesize macrocycles by setting up the two systems (T or I with 1, Scheme 1) to react simultaneously. These syntheses lay the foundation for the rest of the experiment. Once completed, students collect NMR and IR spectra for the products. The IR, NMR, and TLC observations serve to inform the students about the composition of their product mixtures. 1231




After students finish the syntheses, they generate 3D models of all possible macrocycle products from the reactions. Students calculate the strain energy for each of the models they generate. The strain energy estimates calculated from the computergenerated models serve as evidence for why the products formed over other possible products. The computer-generated models also facilitate a discussion about the applications and limitations of the macrocycle models generated. The experiment was developed using WebMO as the molecular-modeling application.19 Other packages that carry out molecular-mechanics calculations, such as Avogadro and Spartan, could also be used.20,21 Finally, students complete a postlab module requiring them to explain why certain macrocycles were produced for each reaction they conducted. Students justify the likelihood of forming one macrocycle product over another using data from multiple sources, including (1) estimates of strain from computer-generated models, (2) relative entropies from stoichiometry, (3) macroscopic observations from bench experimentation, and (4) NMR and IR spectra of the products obtained.

gradually build from simple, straightforward models to the generation of a complex macrocycle. A brief how-to guide is provided for the students, as well as several experiment-specific online tutorial videos to help them develop competency working with the molecular-modeling application (provided in pp S7− S12 of the Supporting Information). Students generate the macrocycles using the molecular-modeling application and estimate the strain energy for the generated molecules. The strain energy is used as a means to compare the relative enthalpy between molecules. In-Lab Bench Experiment

During the bench experiment, students monitor the two reactions via TLC and collect IR and NMR spectra of the products. In one reaction, modified from Gawronski et al., T and 1 are combined (Scheme 1a).4 In the other reaction, modified from Nour et al., I and 1 are combined (Scheme 1b).5 Minor modifications were made to the procedures (e.g., concentrations) so that both reactions were completed within about 1 h; however, each reaction is fairly simple. Both reactions use basic laboratory techniques and are conducted in open air at room temperature. Students are provided with the structural equation for each reaction with reaction schemes stating several possible products. However, they are not told the specific products. The simplicity of the in-lab bench experiment allows for greater emphasis to be placed on fundamental concepts underlying self-assembly, scientific practices (such as using evidence from IR and NMR spectroscopy), and computer modeling to justify observations made at the bench. During TLC monitoring, students observe a single product spot (3T) for the T system and multiple spots (2I and 3I) for the I system (Scheme 1). To justify the observed TLC spots, they are guided to incorporate key signals from the NMR and IR spectra (see pp S36−S40 of the Supporting Information).

Learning Goals

After completing the experiment, students are expected to demonstrate competency in each of the following learning goals: (1) Use strain, predicted by molecular modeling, to justify claims about the enthalpic favorability of forming one product over a structurally comparable alternative. (2) Use stoichiometry to justify claims about the entropic favorability of one product compared against that of another in a dynamic system. (3) Interpret evidence of the formation of products and the disappearance of reactants from TLC observations. (4) Use characteristic features observed in collected spectra (IR and NMR) to justify claims regarding the formation of the provided macrocycles. This experiment was implemented at the end of a secondsemester, second-year organic-chemistry laboratory course. Students were assumed to have prior knowledge from organic chemistry regarding carbonyl chemistry and the chemistry of amines, as well as a basic understanding of the interpretation of NMR and IR spectra. Other prior knowledge included introductory-level knowledge of enthalpy; entropy; and structural features of organic molecules, such as bond length and bond angles. Institutional Review Board (IRB) approval was obtained to evaluate the efficacy of the experiment’s design and evaluation of the extent to which students met the learning goals.

In-Lab Modeling and Discussion

Once the student groups complete the in-lab bench experiment, they transition to using the modeling application to construct models of the possible products provided for each reaction. Students are asked to bring their laptops to lab, so they may use them to construct the models. After generating a model of the possible macrocycle product, each group estimates the strain energy for their model and reports the strain-energy values to the rest of the class. Inevitably, nearly all groups end up with strainenergy values that vary significantly; this is intentional and results from the conformational degrees of freedom of the imine linker between aryl and cyclohexyl subunit components. At this point, students are directly confronted with the limitations of their model. The challenge to synthesize an accurate model is quickly recognized by the students as the result of a minor limitation of the modeling strategy. The students then form groups of four to discuss the applicability and limitations of the models they used. During this discussion, they engage in discourse about the positive qualities of the representations and potential improvements with respect to molecular structure and energy estimates. From their discussions, nearly all groups mention the need for consistent models and propose ways to make more consistent representations of the macrocycles. Once students recognize that models need to be reliable to be applied to their intended purpose, they are provided with the postlab module.

Prelab Module

The prelab module is self-paced and completed before coming to lab. The module begins by asking students to consider the characteristics of a system and the synthetic routes available for organic chemists wishing to generate macrocycles. Students are guided toward synthetic routes incorporating self-assembly. Guiding questions and supporting text prompt students to use the concepts of entropy and enthalpy to think about processes that could result in the self-assembly of macrocycles from bifunctional starting materials (as opposed to polymers). Throughout the prelab, students are expected to use a molecular-modeling application to construct models.19 This is possibly the first time students use this molecular-modeling application to generate molecules, so the prelab is designed to 1232




Postlab Module

freedom in the proxy molecules, as compared with those of the macrocycles produced in the lab, but still capture the essential effects of geometry on strain. That is, they can only be constructed one way because of the structural simplicity of the alkynes and serve as a more reliable model of the products in this experiment. Similar to the in-lab modeling, students estimate the strain energy associated with each macrocycle and use the values to compare structural features of the macrocycles. At the conclusion of the postlab module, students use multiple data sources from the experience to generate an explanation of “how the geometry of the dialdehyde starting material affected the products obtained in the TLC monitoring trials.” In their responses, students are prompted to use the calculated values for strain energy per subunit for the proxy macrocycles, the relative entropy change for each system, TLC observations from the inlab bench experiment, and data from the collected spectra as justification for their explanations.

The postlab module begins by asking students to generate proxy macrocycles with rigid alkyne linkers between subunits, as shown in Tables 1 and 2. The alkyne linkers limit the degrees of Table 1. Terephthalaldehyde Proxy Macrocyclesa

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HAZARDS

Proper laboratory safety procedures should be followed, including the appropriate use of personal protective equipment such as goggles and gloves. All syntheses should be performed in a well-ventilated area. Terephthalaldehyde (T), isophthalaldehyde (I), hexanes, triethylamine, and deuterated chloroform can cause minor irritation if they come into contact with the skin, eyes, or throat. Dichloromethane (DCM) and hexanes are toxic if inhaled or ingested. (R,R)-(−)-1,2-Diaminocyclohexane and ethyl acetate can cause severe eye and skin burns. The imine products can likely cause minor irritation or burns if they come into contact with eyes or skin.

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a

Possible terephthalaldehyde macrocycle products provided along with structurally similar proxy macrocycles.

RESULTS AND DISCUSSION Following a pilot study with 2 undergraduates and 5 graduate students, the experiment was conducted by a total of 69 students during the spring of 2018. Students came from three laboratory sections of a second-semester, second-year undergraduate organic-chemistry laboratory course that met for 4 h weekly. Students worked in pairs for the in-lab experiment, groups of four for the in-lab discussion, and individually for the pre- and postlab modules. Students were able to complete the prelab module prior to class. Most students had little trouble learning the basics of the molecular-modeling application, as is shown by the sampled student quotation, “That’s a cool program though... Once you get the hang of it, it’s really not that bad.” During implementation, all students were able to complete the in-lab experiment and the in-lab modeling and discussion within a single laboratory period. Although students at this institution had 4 h to complete the experiment, students generally completed the in-lab portion within 3 h. Student responses to laboratory modules and recorded in-lab observations were qualitatively analyzed to determine which learning goals were met by the students. All students obtained useable results; however, students who met or exceeded learning goals were able to make accurate claims and justify them with experimental data. Example student TLC and spectra are available in pp S36−S40 of the Supporting Information. The experiment could be modified for two laboratory periods by conducting the in-lab bench experiment and in-lab modeling with discussion in separate laboratory periods. Considerations for implementing the experiment are discussed in pp S2−S6 of the Supporting Information.

Table 2. Isophthalaldehyde Proxy Macrocyclesa

a

Possible isophthalaldehyde macrocycle products provided along with structurally similar proxy macrocycles.

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Table 3. Comparative Achievement of Learning Goals Graded Resultsa,b (%, N = 69) Does Not Meet

Learning Goal 1. Use molecular modeling to justify claims about the enthalpic favorability of forming one molecule over a structurally comparable molecule in the provided system. 2. Use stoichiometry to justify claims about the entropic favorability of one molecule compared with that of another molecule in a dynamic system. 3. Interpret evidence of the formation of products and the disappearance of reactants from TLC observations. 4. Use characteristic features observed in collected spectra (IR and NMR) to justify claims regarding the formation of the macrocycles.

Meets Exceeds

25

48

27

31

63

6

46 11

43 58

12 31

a

Student responses to questions in the laboratory modules were analyzed holistically for evidence of achieving learning goals. bPercentage values may exceed 100 because of rounding.

Achievement of Learning Goals

Alternatively, 89% of students met or exceeded expectations when using evidence from spectra (Learning Goal 4, Table 3). Student answers for questions aligned with this learning goal often identified all signals required for identification of the macrocycle products formed, with 31% of the students identifying additional signals that indicated structural features of the macrocycles. A student’s interpretation of their 1H NMR spectrum of the product in the terephthalaldehyde reaction (Scheme 1a) shows an example of exceeding learning goal requirements: The peak at 8.18 ppm corresponds to the imine structure in which it is only attached to 1 hydrogen which corresponds to the integration of the peak which is one. The integrations added together yield 1 hydrogens which is the number of hydrogens on one subunit. The peaks between 1 ppm − 2 ppm are the aliphatic hydrogens which there are 10 per subunit and that corresponds to the addition of the integration. The peaks between 7−8 represent the aromatic hydrogens present on the molecule. The integrations add up to 4 hydrogens, which is the number of aromatic hydrogens per subunit. In their response, the student identified the required peaks for identifying the substance but also interpreted the meaning of the integrations. Interpreting IR and 1H NMR spectra is a consistent practice for the students, leading to more students meeting or exceeding the learning goal. Items about enthalpy and entropy seemed to provide similar challenges to students, although a majority of students were able to meet or exceed expectations (Learning Goals 1 and 2, Table 3). Many of the students who did not meet expectations either just provided uninterpreted values as justification for product formation or conflated the ideas of enthalpy and entropy. For example, a student’s response to the final question, which asked them to use relative entropies as evidence to justify a claim about the impact of the starting materials on macrocycle formation, wrote, “Larger ΔS, larger strain e. → entropically favored → form bigger macrocycle.” This student is using the calculated strain energy as a measure of entropy for their justification. Often, students would simply state that one product had “more disorder” and thus was favored over the other; however, this response does not provide sufficient evidence as to how entropy contributed to macrocycle formation. Students who were able to meet or exceed expectations for questions about enthalpy and entropy provided evidence and explained how that evidence resulted in macrocycle formation. In response to the final question asking students to use strain energy per subunit to justify a claim about the impact of the starting material on macrocycle formation, one student who met the learning goal wrote, “The strain energies per subunit were 14.694 kcal/mol and 6.397 kcal/mol for the small and big macrocycle,

Percentages of students who did not meet, met, or exceeded learning goals are provided in Table 3. Student responses marked as not meeting the learning goal occurred when the student either provided an incorrect answer or left the answer blank. Student responses that included the correct answer without additional information were marked as meeting the learning goal. Student responses that provided the correct answer as well as significant additional detail or evidence were marked as exceeding the learning goal. Example student responses marked as meeting the learning goal are provided in pp S28−S29 of the Supporting Information. An answer key and grading rubric (available in pp S13−S27 of the Supporting Information) were used to determine whether a student response qualified as not meeting, meeting, or exceeding for each question. Because each learning goal was assessed using multiple questions, a count of student achievement for each learning goal was conducted and translated into a percentage. The majority of students either met or exceeded every learning goal, leading to positive implications about their ability to apply concepts, such as entropy and enthalpy, to novel systems as a result of their laboratory experience. However, questions associated with the interpretation of evidence from TLC (Learning Goal 3, Table 3) seemed to be the most challenging for students, and it is fair to say that this learning objective was not met. To qualify for meeting or exceeding this learning goal, students needed to interpret their TLC plates for the emergence of products and disappearance of reactants. Student answers marked as not meeting the learning goal often included descriptions or drawings of the plates without interpretation of the observations. For example, a student wrote, “The TLC plate had a long, streaked spot near the bottom + then 2 distinct, separated spots above the long spot.” Student answers marked as meeting the learning goal used observations from the plate appearance to describe the emergence of product and the disappearance of reactants without in-depth interpretation of the identity of the spot. For example, a student wrote, “There was 1 dot present for the product, indicating 1 product. This product [2I] was less polar than the iso product [3I], shown by the larger distance traveled on the plate. The tere product [3T] did not travel as far as its reactants, indicating lower polarity.” Interpreting the TLC observations was likely difficult for students because they had not been required to conduct TLC since the very beginning of the course, whereas this experiment was implemented in the final week. Recognizing this potential challenge for students, a brief review of TLC setup and interpretation has been included in pp S2−S6 of the Supporting Information. 1234




(4) Gawronski, J.; Kolbon, H.; Kwit, M.; Katrusiak, A. Designing Large Triangular Chiral Macrocycles: Efficient [3 + 3] DiamineDialdehyde Condensations Based on Conformational Bias. J. Org. Chem. 2000, 65 (18), 5768−5773. (5) Nour, H. F.; Lopez-Periago, A. M.; Kuhnert, N. Probing the Mechanism and Dynamic Reversibility of Trianglimine Formation Using Real-Time Electrospray Ionization Time-of-Flight Mass Spectrometry. Rapid Commun. Mass Spectrom. 2012, 26 (9), 1070− 1080. (6) Debbert, S. L.; Hoh, B. D.; Dulak, D. J. Synthesis and Characterization of Calixarene Tetraethers: An Exercise in Supramolecular Chemistry for the Undergraduate Organic Laboratory. J. Chem. Educ. 2016, 93 (2), 372−375. (7) Kuhnert, N.; Burzlaff, N.; Patel, C.; Lopez-Periago, A. Tuning the Size of Macrocyclic Cavities in Trianglimine Macrocycles. Org. Biomol. Chem. 2005, 3 (10), 1911−1921. (8) Bennett, J.; Meldi, K.; Kimmell, C., II Synthesis and Analysis of a Versatile Imine for the Undergraduate Organic Chemistry Laboratory. J. Chem. Educ. 2006, 83 (8), 1221−1224. (9) Holme, T. A.; Reed, J. J.; Raker, J. R.; Murphy, K. L. The ACS Exams Institute Undergraduate Chemistry Anchoring Concepts Content Map IV: Physical Chemistry. J. Chem. Educ. 2018, 95 (2), 238−241. (10) National Research Council. Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering; Singer, S. R., Nielsen, N. R., Schweingruber, H. A., Eds.; The National Academies Press: Washington, DC, 2012. (11) Springer, M. T. Improving Students’ Understanding of Molecular Structure through Broad-Based Use of Computer Models in the Undergraduate Organic Chemistry Lecture. J. Chem. Educ. 2014, 91 (8), 1162−1168. (12) Dori, Y. J.; Barak, M. Virtual and Physical Molecular Modeling: Fostering Model Perception and Spatial Understanding. Educ. Technol. Soc. 2001, 4 (1), 61−74. (13) Abraham, M.; Varghese, V.; Tang, H. Using Molecular Representations to Aid Student Understanding of Stereochemical Concepts. J. Chem. Educ. 2010, 87 (12), 1425−1429. (14) Wu, H.-K.; Krajcik, J. S.; Soloway, E. Promoting Understanding of Chemical Representations: Students’ Use of a Visualization Tool in the Classroom. J. Res. Sci. Teach. 2001, 38 (7), 821−842. (15) Treagust, D. F.; Chittleborough, G.; Mamiala, T. L. Students’ Understanding of the Role of Scientific Models in Learning Science. Int. J. Sci. Educ. 2002, 24 (4), 357−368. (16) Grosslight, L.; Unger, C.; Jay, E.; Smith, C. L. Understanding Models and Their Use in Science: Conceptions of Middle and High School Students and Experts. J. Res. Sci. Teach. 1991, 28 (9), 799−822. (17) Harrison, A. G.; Treagust, D. F. Secondary Students’ Mental Models of Atoms and Molecules: Implications for Teaching Chemistry. Sci. Educ. 1996, 80 (5), 509−534. (18) Alaimo, P. J.; Langenhan, J. M.; Suydam, I. T. Aligning the Undergraduate Organic Laboratory Experience with Professional Work: The Centrality of Reliable and Meaningful Data. J. Chem. Educ. 2014, 91 (12), 2093−2098. (19) Schmidt, J. R.; Polik, W. F. WebMO Enterprise; WebMO, LLC: Holland, MI, 2013. (20) Deppmeier, B.; Driessen, A.; Hehre, T.; Hehre, W.; Klunzinger, P.; Ohlinger, S.; Schnitker, J. Spartan; Wavefunction, Inc.: Irvine, CA, 2018. (21) Hanwell, M. D.; Curtis, D. E.; Lonie, D. C.; Vandermeersch, T.; Zurek, E.; Hutchison, G. R. Avogadro: An Advanced Semantic Chemical Editor, Visualization, and Analysis Platform. J. Cheminf. 2012, 4, 17.

respectively. It makes sense only the big macrocycle would form, because it has much less strain and therefore is favored over the small macrocycle.”

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SUMMARY AND CONCLUSIONS This experiment was designed and successfully implemented in an undergraduate organic chemistry laboratory course. Evidence provided shows students can demonstrate competency of the learning goals while synthesizing macrocycles, generating models using a computer molecular-modeling application, and interpreting both 1H NMR and IR spectra. At the conclusion of the postlab module, students demonstrated competency using data from each of the available resources to justify the products they observed during the in-lab bench experiment. All the required resources for the implementation of this experiment are contained in the Supporting Information.

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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.8b01046. Notes for instructors, instructional resources, answers to laboratory questions, rubric, example student responses that qualify as “meets expectations”, example instructorgenerated TLC and spectra with characterization of significant signals, example student-generated TLC and spectra, materials guide, and sample exam questions (PDF, DOCX) Prelab and in-lab modules (PDF, DOCX) Postlab module (PDF, DOCX) Sample macrocycle files (ZIP)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Adam G. L. Schafer: 0000-0002-7411-0208 Ellen J. Yezierski: 0000-0002-7067-7944 C. Scott Hartley: 0000-0002-5997-6169 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank the students and teaching assistants of the CHM 255 Organic Chemistry Lab course; B. McLean; and the instructor of the course, B. Gung. We thank the Yezierski, Hartley, and Bretz research groups for their assistance with lab development and participation in the pilot study. We thank the National Science Foundation (award CHE-1608213) for financial support.

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REFERENCES

(1) Lindoy, L. F.; Atkinson, I. M. Self-Assembly: What Does It Mean? In Self-Assembly in Supramolecular Systems; Stoddart, J. F., Ed.; The Royal Society of Chemistry: Cambridge, U.K., 2000; pp 1−6. (2) Rowan, S. J.; Cantrill, S. J.; Cousins, G. R. L.; Sanders, J. K. M.; Stoddart, J. F. Dynamic Covalent Chemistry. Angew. Chem., Int. Ed. 2002, 41 (6), 898−952. (3) Wilson, A.; Gasparini, G.; Matile, S. Functional Systems with Orthogonal Dynamic Covalent Bonds. Chem. Soc. Rev. 2014, 43 (6), 1948−1962. 1235


Understanding Thermodynamic Control in Covalent Self-Assembly: A

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