Engaging Students in Physical Chemistry, Volume 2

We have added CURE-like experiences into the undergraduate physical chemistry laboratory to provide opportunities for students to practice experimental design. The remediation of pollutants in wastewater using adsorption was found to be highly engaging to students while also being a very flexible framework for a CURE-like experience. In this project, students carried out a traditional adsorption experiment, then they proposed, designed and performed their own studies in an iterative process. The experience was very open ended, yet highly scaffolded. This scaffolding provided a supportive structure for students and assisted the instructor with class and project management.

A 10-week physical chemistry course was taught using a flipped classroom format. In a flipped classroom, students watch lecture videos at home, and come to class to participate in in-class activities which help them understand and apply the knowledge from the lecture videos. In this chapter, the design of the class and especially the activities used in the class were described, including traditional practice problems, data analysis, role play, escape room, scavenger hunt, and board game. Their effectiveness was shown based on students’ feedback and grades.

Physical chemistry courses pose major challenges for many students since they require significant mathematical knowledge, quantitative reasoning, and problem-solving skills. Several interventions have been identified to bolster mathematical skills for students, however, most of these interventions have been implemented in general chemistry courses. In this chapter, we describe the design of an asynchronous online resource, Math for PChem Foundation Modules, to help students review and apply prerequisite mathematical knowledge and skills in undergraduate physical chemistry courses. Additionally, the online resource enables students to review complex concepts and test their understanding at their own pace, enhancing self-assessment and knowledge retention. Finally, we describe different implementation approaches and present preliminary data on student experiences with the online resource.

Educational research supports the effectiveness of cooperative learning in the college classroom. Cooperative learning uses “structures” which are the building blocks to which instructors add content to form a cooperative learning classroom activity. Here a cooperative learning structure suitable for physical chemistry classes is described. “Equation mapping” was inspired by concept mapping and has been used extensively in the author’s classroom. Examples of student work are shown and logistical details are addressed for using this cooperative learning structure in the physical chemistry classroom.

Physical chemistry courses can be challenging for both students and educators in chemistry. With its difficult course reputation, students can view physical chemistry as a hurdle to graduation and even their scientific identities. Educators can struggle to engage students and balance the chemical and mathematical needs of the course. In this chapter, I discuss that because of these challenges, physical chemistry is uniquely positioned in the chemistry curriculum to promote cohort building and strengthen student and instructor relations in the major. I share my experiences as a physical chemistry educator at a primary undergraduate institution (PUI), having to transform my junior/senior-level physical chemistry courses to overcome teaching barriers and to learn how to leverage physical chemistry to support student growth and belonging. This chapter uses a generalized course syllabus to highlight teaching strategies that experiment with course structure and practices, including team building, peer learning assistants, math-based laboratory modules, and in-class activities in a physical chemistry course.

The course syllabus plays an important role in students’ first impressions of a course. Considering students’ negative perceptions of physical chemistry, it is a potentially invaluable tool for communicating an instructor’s focus on learning and expectations for student success. We conducted a positive deviance analysis of learning-focused syllabi analyzed previously to identify strategies to improve the learning focus of physical chemistry syllabi. Specifically, we 1) present goals and objectives that map on to a wide range of Fink’s categories of significant learning, 2) describe assessments that align with course level goals and objectives, and 3) explain how the tone used in writing syllabus components can affect the learning environment conveyed by the document. We also discuss a reflective tool instructors can use to self-assess their syllabus and identify components that, if modified, could have significant impact on the focus of this document.

Physical chemistry lecture courses pose a unique set of challenges for students and instructors. Specifications grading offers a valuable alternative structure to conventional grading, addressing student anxiety, providing numerous oppor­tunities to demonstrate knowledge, and enabling a strong sense of student agency. In this chapter, we discuss three different implementations of specifications grading across different physical chemistry lecture courses. We describe course structures in detail and share lessons learned about each implementation that other instructors may use to adopt a specifications grading framework into their own physical chemistry lecture courses.

Bachelor’s of Science (B.S.) or Bachelor’s of Arts (B.A.) degrees in chemistry differ in requirements for math and laboratory experiences, which may require the same topics to be taught in two different physical chemistry courses, each with different math pre-requisites and laboratory requirements. Here the curriculum requires a year of calculus for the B.S. physical chemistry course or a single survey of calculus for the B.A. I delivered both of these different physical chemistry courses simultaneously by teaching core lectures to both groups of students, with other class sessions separate, while giving the groups different homework assignments and tests tailored to their level of mathematical preparation. The separated sessions for B.S. students were in-person “Math Days” where we worked together to apply more advanced calculus and modeling to selected physical chemistry homework problems. During these times, B.A. students attended asynchronous “Data Talks” of topical lectures from recent literature followed by online Q&A discussion. These “Data Talks” showed data from the literature, summarizing recent research papers that illuminate physical and/or chemical aspects of evolution, in the context of a chemical evolution narrative provided by a popular science book. The narrative provided a qualitative foundation for interdisciplinary connections, including historical connections through assigned readings by Planck and Einstein. Finally, B.A. students completed lab sessions based on biophysical or biochemical research, gaining practical laboratory experience in contrast to the theoretical explorations assigned to the B.S. students. In this way, students learned physical chemistry in different ways so that they could fulfill the requirements of their different degrees in two courses taught during one assigned class period by a single instructor.

The subject of engaging students in physical chemistry, P-Chem, at the point when they encounter P-Chem for the first time is well covered in Volume 1. What we present here in Volume 2 is what happens when the students are proficient in foundational knowledge and skills of P-Chem and decide on a set of courses to complete their undergraduate education, thus finalizing their preparation for professional chemistry work or continuation of study in graduate school. This culmination is an advantageous opportunity for students to strengthen their knowledge of P-Chem as the underlying foundation for understanding phenomena in other branches of chemistry, a necessary development for fundamental mastery of chemical principles. A great deal of educational research is devoted to the students’ transition from the high school level to the college level and the teaching of freshman/sophomore courses. The present chapter deals with a much less studied subject, i.e., the transition from the college level to the professional level and improving the proficiency of chemistry graduates, the latter problem being much more complex than the former one because the latter predominantly deals with the highest levels of cognitive learning in terms of Bloom’s taxonomy. To finalize the education of undergraduate chemistry majors, either capstone undergraduate research (less structured) or courses (more structured) are utilized. Our work details the three-semester sequence of experimental physical chemistry courses developed at Penn State to optimize the capstone experience for chemistry majors interested in pursuing careers in physical chemistry either in graduate school or industry. In addition to the ACS guidelines and decades of teaching, mentoring, research, and development experience, the sequence design is also based on the Department of Labor’s professional expectations and job descriptions and recruiters’ suggestions for curriculum modifications. Additionally, the worldwide experience of numerous colleagues involved in graduate education was used to inform the sequence design. The sequence consists of i. experimental physical chemistry (2 credits), ii. advanced experimental physical chemistry (4 credits), and iii. undergraduate research (2 or 4 credits). The courses’ organization and management as well as the pedagogical grounds for the presented capstone experience are elaborated in detail. Problems such as limited time, insufficient lab skills, lack of problem-solving skills, and related inept professionalism were addressed. Several examples were presented to illustrate the optimal capstone projects’ design. The learning results, progress, and improvements were assessed from the students’ reports, posters, and PowerPoint presentations as well as their post-graduation feedback.

Engaging undergraduate students in physical chemistry requires innovative approaches that connect theoretical concepts to tangible, visual experiences. We describe a strategy for making thermodynamics more accessible to students by prioritizing the geometric properties of the theory in combination with highly interactive capabilities built into the Jupyter Notebook platform. The approach, broadly characterized as Computational Guided Inquiry (CGI), permits instructors to generate scaffolded learning modules that enable students to quickly generate high-quality two- and three-dimensional plots, foster intuition about foundational ideas of thermodynamics, and facilitate meaningful engagement in complex real-world problems that extend beyond the thermodynamics classroom.

This chapter describes an approach to incorporating python coding in an undergraduate physical chemistry course that is accessible for both instructors and students. The students begin to learn to read code in the context of learning or re-learning mathematical content critical to the development of foundational quantum mechanics. The mathematical content stresses basic calculations, symbolic mathematics, interpreting diagrams, and graphing functions. This chapter describes a series of Jupyter notebooks that run within the free Google Colab environment, which are written using principles of guided inquiry.

With the advent of the Google Colab, a free, online Jupyter notebook environment, it is now possible for anyone with internet access to use Jupyter notebooks to program in Python without installing any software. In the POGIL-PCL project, Jupyter notebooks have been developed to teach basic notebook use and coding, to analyze data with linear and nonlinear optimization, and to exploit the symbolic math capabilities. A 3-session workshop for instructors to learn Jupyter and its use in teaching Physical Chemistry was developed and run during Spring 2024. In general, the workshop was well-received and sparked discussions about pedagogical uses of programming in chemistry. We will discuss best practices for notebooks in the guided inquiry environment for four main areas: reading code, data analysis and nonlinear optimization, symbolic math manipulation, and writing code.

To keep pace with the growing demand for computational literacy, it is crucial that undergraduate science programs show students how to meaningfully integrate coding into their disciplines of study. Unfortunately, many undergraduates enter college with little to no experience in computer science, and the already demanding undergraduate chemistry curriculum may not seem to leave much room for the additional instruction needed to teach coding-reluctant students how to program. Here, I describe a comprehensive, highly scaffolded approach to incorporating Python into an undergraduate Physical Chemistry course that treats programming as integral. The activities cover the full set of concepts taught in a typical Physical Chemistry (Thermodynamics and Kinetics) course: real and ideal gas laws, the Maxwell-Boltzmann distribution, expansion work, heat capacity and enthalpy, entropy and spontaneity, and chemical kinetics. Students begin with simple, unintimidating plotting exercises in an easy-to-access online coding platform, then progress to larger-scale projects that involve more complex mathematics and direct investigation of higher-level concepts such as nonlinear fitting and model failure. Along the way, students are required to not just use code, but create it, then use the tools they make to deepen their understanding of chemistry. The curriculum particularly emphasizes data fitting, guiding students away from a “black box” understanding of mathematical modeling. Taken as a whole, this set of assignments can be fully integrated into a Physical Chemistry course, helping students to build an entirely transferrable set of skills that may be applied to many future fields of study.

This chapter examines the implementation of programming skills in the physical chemistry laboratory course within the R framework. Skills were introduced to the students through live-coding sessions and application assignments for classic labs in the physical chemistry curriculum, such as bomb calorimetry. Students were required to submit R scripts for the data analysis of each experiment in Physical Chemistry I lab, with grades assigned for accuracy, efficiency, and aesthetic presentation of included figures. The implementation of these assignments is explained here by examining three labs with varying required programming skills. Background theory and programming applications are presented for the three labs with representative student work, including submitted R scripts. The full tutorial referenced in this chapter is available at GitHub.

Physical Chemistry Laboratories (PCLs) often involve simple measurements but challenging data analysis that can negatively impact students’ ability to interpret and communicate their results. Computational softwares, such as Mathematica or Python, can enable students to focus on the chemical concepts and reduce time consuming calculations. While linearization of physical equations for data analysis is a common practice, the “simplifications” introduce additional layers of complexity and shift error distributions of processed data. By directly applying nonlinear fitting capabilities in computational softwares, students in PCLs can focus on interpreting their data and making conceptual connections while avoiding the additional steps and possible mistakes that come with linearization. Furthermore, many nonlinear fitting routines provide access to uncertainties of the fitting parameters which can be used for further error propagation. However, computational software programs have their own learning barriers that must be overcome to effectively leverage them. To address these challenges, we incor­porated a series of interconnected computational-based assignments, in-class activities, and data analysis templates into our PCL with the goal of streamlining complex data analysis to improve student understanding of chemical concepts. Important software concepts and syntax are introduced early in the semester and are revisited throughout the remainder of the course. This chapter will provide explanations and examples of how to incorporate computational software into PCLs through the use of data analysis templates and in-class activities. Empirical evidence of student success is limited, but promising. These changes have resulted in improved discussions and interpretation of results for students and a reduction in grading time for instructors.

While teaching students to code is a valuable skill, we need to consider the equity implications of such instruction. Computer programming is a highly stereotyped activity, and as such can negatively impact a student’s sense of chemistry identity. This is likely to be especially acute for students from historically excluded groups. Recommendations for coding instruction that will support a student’s sense of chemistry identity are given. These include using pedagogies that encourage student interaction (Live Coding, spending class time for introductory instruction), differentiating by prior knowledge, and knowing how computer scientists talk about coding. By using pedagogies that increase student’s chemistry identity during programming instruction, we can help all of our students see that they belong in our field.

The particle-in-a-box (PIB) model is a quintessential yet abstract concept for Physical Chemistry. Students often find the model hard to understand due to the mathematical complexity of the model and the limited perceived relevance. Traditionally, students probe the PIB model by measuring the UV-vis absorption of conjugated carbocyanine dyes. This experiment links chain length to π-π* transition energies via an analytical formula in comparison to experimental spectra. To deepen engagement and conceptual understanding, an updated version of the experiment integrates computational chemistry with classic laboratory techniques. In this new version of the PIB experiment, students collect data through three routes: 1) compute the UV-vis absorption spectra using time-dependent density functional theory (TDDFT), 2) collect experimental UV-vis spectra using a spectrophotometer, and 3) solve the PIB model in an infinite and finite well with Python scripts to predict theoretical absorption peaks. Students can connect molecular orbital theory to the restriction of electron motion to discrete energy levels by comparing the computationally determined λ_max to the experimentally collected spectra. Additionally, the use of Python introduces valuable skills in coding, data analysis, and visualization. Together, these elements create a multifaceted learning experience that reinforces core physical chemistry concepts through modern computational tools and showcases how students are engaged with Physical Chemistry via an appreciation of computational chemistry and modeling.

Analysis of the rotational fine structure of the fundamental infrared band of HCl has been a standard experiment in the physical chemistry laboratory curriculum since the early 1960s. Polynomial fitting to a model function yields spectroscopic constants in very good agreement with literature data. However, acquisition and analysis of a single spectrum is not sufficient to illustrate the meanings of the spectroscopic constants, or the deep relationship between the structure of the spectrum and the potential energy surface of the molecule. In this work, a number of extensions of the spectroscopy of the hydrogen halides beyond the standard curriculum are described, including use of the research tool PGOPHER to facilitate data analysis, use of high-resolution linelist data from the HITRAN database to investigate overtones and hot bands, the estimation of bond dissociation energies from HITRAN data using Birge-Sponer extrapolation, and simulation of rovibrational bands based on high-level calculations of the ground state potential energy curve. This article also provides historical and environmental context helpful in enhancing student motivation.

In this chapter, I describe the development of an undergraduate physical chemistry guided inquiry laboratory activity focused on symmetry and spectroscopy. This lab activity was developed through the POGIL-PCL (Process Oriented Guided Inquiry Learning - Physical Chemistry Lab) framework. I describe the student learning outcomes, the development philosophy, the development process, safety aspects, the available instructor material, and facilitation options available for instructors wishing to implement this lab activity. There is significant flexibility for instructors, especially with respect to how much formal symmetry analysis to include. The lab activity consists of multiple modules, and examples of questions students answer and/or tasks they carry out are given for each module. The lab activity focuses on experimental and computational analysis of two isomers of dichloroethene. If the instructor wishes, this lab activity can be used to introduce Raman spectroscopy in the undergraduate physical chemistry curriculum. Instructor materials include Raman data, and this part of the lab activity can be carried out as a dry lab in the case that a Raman spectrometer is not available. Other ideas students develop in this lab activity include scattering of radiation; complementarity of infrared and Raman spectroscopies; selection rules; the use of symmetry to identify and predict spectra and molecular structure; Mulliken symbols and irreducible representations; use of character tables in IR and Raman spectroscopies; and basic pictorial normal mode analysis. Overall, in this chapter I present an engaging guided inquiry laboratory activity that instructors may wish to adopt in their undergraduate physical chemistry lab.

This laboratory experiment explores nanosecond transient absorption spectroscopy, a powerful technique to study the ultrafast dynamics of excited-state species in various materials. Transient absorption (TA) provides insight into the time-resolved behavior of excited states, including processes such as charge transfer, energy relaxation, and chemical reactions. In this laboratory experiment, students measure TA signals in zinc-tetraphenylporphyrin (ZnTPP) to study excited state population dynamics. Students also investigate the influence of a fullerene on the excited state decay time. In addition to performing the experiments, students analyze data using Python. These laboratory activities provide undergraduate students with a hands-on experience using modern optical and spectroscopic methods.

The availability of inexpensive quantum chemical calculation packages for personal computers makes it possible to integrate these calculations into the chemistry curriculum. This allows students to investigate concepts that cannot be investigated experimentally in the lab due to safety concerns, the cost of doing the experiment, or the lack of the necessary instrumentation needed for the investigation. This chapter presents some examples of the ways quantum calculations have been integrated into the physical chemistry laboratories at James Madison University (JMU) either as stand-alone exercises that only use quantum calculations or as blended projects that couple quantum calculations with experimental measurements. The investigation of the ground state electron configurations of the first ten atoms in the periodic table and the potential curves of H₂ ⁺ and H₂ are examples of stand-alone exercises where the results of the calculations provide all the data. The investigation of the infrared spectrum of HCl/ DCl, the structure of benzene using multiple measurements, and the exploration of the hydrogen bonding in methanol are examples of blended exercises that combine instrumental measurements with quantum calculations. The calculations provide insight and add data to supplement the physical measurements. The results obtained for DFT-B3LYP for each system are presented to show the types of information that can be obtained. Examples are given to show where the method gives good results and where it does not. The results from other methods are presented that can be used when DFT fails.

Chemical equilibrium, and in particular the protonation equilibria of polyprotic species, integrates a complex set of concepts that are frequently difficult for undergraduate students to grasp. Here, we present a Python-based tool that allows the user to graphically portray relative concentrations of protonation states for molecules across a range of pH values. To address the tool’s utility for applied problems, we accompany the code with two worked examples that rely on an understanding of protonation states: a step in a biochemical pathway at physiological pH and the fate of an herbicide in acidic conditions. Mathematical derivations, line-by-line code annotations, and deployment instructions are included.

Computational chemistry is the most rapidly growing subdiscipline in chemistry. For small molecules calculations are now as good as experiment and readily accessible in undergraduate courses. These calculations are made available at the undergraduate level because of advances in computer power, availability of computational chemistry programs, and excellent graphical interfaces. In this chapter examples are provided on how computational chemistry exercises that illustrate physical chemistry concepts can be incorporated into general and physical chemistry courses using modern programs with a web-based user-interface, WebMO. As computations become a practical tool used by almost every chemist to enhance chemical understanding and make chemical predictions, providing undergraduate chemistry students hands-on experience with computational chemistry is an essential part of a modern chemistry education.

This chapter presents the motivation for implementing orbital coupling diagrams in Physical Chemistry courses and then summarizes what this involves in one of the two courses I teach at the University of Illinois that utilizes the material. While the approach is based on a rigorous quantum chemical foundation, it is inherently graphical. It combines static and animated depictions of orbitals with the potential energy curves associated with bond formation and chemical transformations. The material introduces a family of glyphs for representing atoms and the couplings they undergo in forming molecules, including radicals and charged species. Bonding is treated as a process with a beginning and an end that is visualized with orbitals that are able to reflect both endpoints. Molecules are constructed atom-by-atom, an inquiry-based approach that enhances and encourages the exploration of the nearly endless possibilities for chemical change. The glyph-based iconography represents atoms and the couplings between them in molecules, conveying their underlying orbital scaffolding. The chapter describes the course narrative of the new material as well as student molecule projects that use coupling diagrams. A variety of associated material is available for download: lecture notes, examples of homework and exam problems with solutions, and resources for the molecule project.

Physical Chemistry Laboratory courses are intended to make the subject tangible and approachable for students. Outdated experiments can contribute to student perception that the subject is stale or unrelatable. Unfortunately, modernizing a physical chemistry laboratory course can be difficult, especially on a tight budget. The poster project presented here is designed to complement classic wet chemistry experiments by extending connections to modern research. The project further benefits undergraduate students by supporting ACS core competencies related to the chemical literature and professional communication.

Having to take a Physical Chemistry course is dreaded and feared by most students. As a field, integration of chemistry, physics, and the use of mathematics are all required to succeed in the course. One thing that makes learning physical chemistry so difficult for novices is that they are asked to think differently about abstract chemical systems and phenomena. Originally, physical chemistry, as a field, was a way to mathematically model chemical systems to predict how to optimize desired processes (e.g., steam engines) or maximize a desired product. The typical way physical chemistry courses are taught is as a mathematics course (think of all the derivations you did) and connections to the systems and processes they are modeling are lost. Earning a passing grade, however, does not guarantee understanding of any of the content. Inclusion of appropriate “every day” phenomena as context helps learners understand why specific topics are included and how the models within the field help explain how the world around us works.

Physical chemistry builds students’ understanding of the fundamental science behind general chemistry, and due to its complexity presents both challenges and opportunities to instructor and student. Writing is an essential skill for scientists and needs more emphasis in our curriculum. By using Writing Across the Curriculum strategies we can incorporate well-designed writing assignments into our courses to teach discipline-specific writing skills, support student understanding of complex topics, increase engagement with class content, and promote critical thinking. Writing assignments can be used to supplement or replace traditional labs or assignments. I describe two writing assignments appropriate for use in physical chemistry courses. One activity was learning to write standard operating procedures (SOPs) for a familiar lab technique. In the second activity, students practiced reading primary source literature and practiced formal journal-style writing, while learning about a historic experiment in quantum chemistry.

Communicating both written and oral arguments is among the most important skills necessary to succeed in industry and graduate school. Chemistry majors practice and develop the vast majority of their writing through laboratory courses aligned with lecture courses. Unfortunately, many students complete these laboratory courses with inadequate gains in scientific writing skills and lack the ability to create manuscripts and scientific reports to the quality level expected by journals, graduate schools, and industry. In response to this concern, we developed a novel, programmatic, and stepwise curriculum to improve technical writing skills through active learning and guided inquiry pedagogies. Over the duration of one semester, students work through a multi-step learning cycle, known as Commence-Act-Review-Reply-Revise (CAR³), where each cycle focuses on a specific aspect of writing a scientific manuscript. Each cycle commences with students composing a rough draft of specific attributes for the manuscript section and writing skills integral to creating an appropriate and quality report. Students then attend a writing workshop during regular class time, which interactively engages them through guided inquiry-based activities focused on the specific writing aspects addressed in the submitted rough drafts. After each workshop, students complete peer reviews on the rough drafts. Finally, students complete a final draft of the report, utilizing the knowledge gained from the workshop and incorporating the peer reviewer’s input. The CAR³ writing cycle has been implemented in a physical chemistry laboratory course. The effectiveness of our novel CAR³ writing cycle was assessed through writing efficacy assessments that were compared to writing samples from previous semesters. Each of the four CAR³ writing cycles implemented in a semester combines to sequentially prepare students to construct a quality journal-style manuscript by the end of the semester.

The Physical Chemistry Laboratory course is one of the most challenging laboratory courses for undergraduate students due to the complexity of concepts as well as unfamiliar instrumentations used in modern physical chemistry laboratory courses such as fluorescence lifetime measurements, atomic force microscopy, measuring optical properties of quantum dots and polarizability of nanostructures, and python programming. The challenge is elevated when those experiments run asynchronously from physical chemistry lecture content. To lower the learning barrier and enhance student learning, a series of video modules were created for the experiments in Physical Chemistry Laboratory courses. Each video module is customized with conceptual lessons and demonstrations of experimental procedures. The final video modules were distributed on easy-to-access online platforms and provided as pre-lab and post-lab resources. In this chapter, technical details are also suggested for the improvement of audio and video qualities. According to students’ responses to survey questions, utilizing customized video content for Physical Chemistry Laboratory courses enhanced their confidence of understanding course materials. Overall, the videos were reported to be helpful on their learning experience. This chapter will provide resources and insights for creating customized videos for upper-level undergraduate laboratory courses which will lower the barrier for learning physical chemistry concepts and technical training.