Undergraduate Physical Chemistry Research Articles

A Computer Laboratory for the Calculation of the Heat Capacity of a Peptide Unfolding Transition

ABSTRACT We present the implementation of a computer simulation laboratory for the calculation of the heat capacity of the folding-unfolding pseudo phase transition of a polyalanine Ala30α-helix, using molecular dynamics simulations. Unlike conventional calorimetry experiments, which provide a macroscopic interpretation of the heat capacity, the computer laboratory additionally offers a molecular perspective of the energy exchange processes that lead to the peak of the heat capacity at the phase transition, as well as the statistical mechanical interpretation of the phase transition. The exercise is targeted toward 1st- or 2nd-year students of biophysics in the context of an undergraduate physical chemistry course. We use a graphical web interface to overcome the steep learning barriers associated with command line interactions in commonly used molecular dynamics protocols. The web interface (VIKING) also handles communication with computing hardware in the background, so that students with limited or no programming experience can launch and analyze the simulations easily. A collaboration between the VIKING support team and responsible teachers is required to set up VIKING. We also present a solution in which simulations can be launched on students’ own computers, if some command line knowledge can be expected. The laboratory can also be repurposed for students of various backgrounds (physics, chemistry, biology, or engineering) and scholastic levels (undergraduate or graduate).

An Inquiry-Based Computational Chemistry Activity for the Undergraduate Physical Chemistry Laboratory

An Inquiry-Based Computational Chemistry Activity for the Undergraduate Physical Chemistry Laboratory

Physical Chemistry Lab for Data Analysis of COVID-19 Spreading Kinetics in Different Countries.

The COVID-19 pandemic has passed. It gives us a real-world example of kinetic data analysis practice for our undergraduate physical chemistry laboratory class. It is a great example to connect this seemingly very different problem to the kinetic theories for chemical reactions that the students have learned in the lecture class. At the beginning of the spring 2023 semester, we obtained COVID-19 kinetic data from the "Our World in Data" database, which summarizes the World Health Organization (WHO) data reported from different countries. We analyzed the effective spreading kinetics based on the susceptible-infectious-recovered-vaccinated (SIR-V) model. We then compared the effective rate constants represented by the real-time reproduction numbers ( ) underlining the reported data for these countries and discussed the results and the limitations of the model with the students.

Experiences with an Inquiry-Based Ionic Liquid Module in an Undergraduate Physical Chemistry Laboratory.

The topic of ionic liquids is typically not taught at the undergraduate level. Many properties, such as conductivity, vapor pressure, and viscosity, of these so-called "green solvents" are unique compared to traditional molecular solvents. Using active learning techniques, we introduced an ionic liquid module in the physical chemistry laboratory where their structures and physical properties, namely, viscosity, conductivity, and vapor pressure, were explored in relation to molecular solvents. Summative and formative assessments show that a majority of the participants were able to grasp the key concepts of ionic liquids. We envision that our methods and strategies can be one of the building blocks of introducing ionic liquids into the undergraduate chemistry curriculum.

Analysis of Large Data Sets in a Physical Chemistry Laboratory NMR Experiment Using Python.

We describe an update to an experiment demonstrating low-field NMR spectroscopy in the undergraduate physical chemistry laboratory. A Python-based data processing and analysis protocol is developed for this experiment. The Python language is used in fillable worksheets in the notebook software JupyterLab, providing an interactive means for students to work with the measured data step by step. The protocol teaches methods for the analysis of large data sets in science or engineering, a topic that is absent from traditional chemistry curricula. Python is among the most widely used modern tools for data analysis. In addition, its open-source nature reduces the barriers for adoption in an educational laboratory.

Feasibility of Using a Multicompartment Electrochemical Cell for Determination of Solubility Product Constants of Silver Salts from Potentiometric Measurements: A Directed Study in the Undergraduate Physical Chemistry Laboratory

Feasibility of Using a Multicompartment Electrochemical Cell for Determination of Solubility Product Constants of Silver Salts from Potentiometric Measurements: A Directed Study in the Undergraduate Physical Chemistry Laboratory

Physical Chemistry in Context: Using Quantum Mechanics to Understand the Greenhouse Effect

The concepts taught in an undergraduate physical chemistry course are directly related to the molecular processes governing climate change, yet the connections between quantum mechanical molecular properties and global warming are rarely made explicit. To improve student knowledge about climate change, we developed a three-part activity that computationally and experimentally explores blackbody radiation, the greenhouse effect, and the relationship between IR absorption properties and global warming potentials for the anthropogenic greenhouse gases defined in the Paris Agreement. The activities addressed the traditional learning objectives of a quantum-focused physical chemistry course by exploring topics such as the quantized nature of energy in Planck’s Law, the selection rules for rovibrational transitions, and discrepancies between theoretical models and observed experimental results. However, our approach was unique in that each concept was addressed within the context of the atmospheric phenomena related to climate change. A previously published climate science survey instrument was administered pre- and postactivity to assess student learning gains. The average percent of correct responses on this survey increased from 44% to 68% as a result of completing the activities.

Foregrounding the Code: Computational Chemistry Instructional Activities Using a Highly Readable Fluid Simulation Code

Computational chemistry instructional activities are often based around students running chemical simulations via a graphical user interface (GUI). GUI-based activities offer many advantages, as they enable students to run chemical simulations with a few mouse clicks. Although these activities are excellent for introducing students to the capabilities of chemical simulations, the disadvantage is that the students’ experience is not representative of how professional computational chemists work. Just as it is important that students in an organic chemistry instructional lab gain hands-on experience with equipment commonly used by professional organic chemists, students of computational chemistry must gain hands-on experience with coding, as professional computational chemists do not rely on GUIs; we write code. Motivated by the need for instructional activities that provide hands-on experience with computer code, a pair of activities were created around a free lightweight (runs on standard laptops) open-source Lennard-Jones (LJ) fluid simulation code written in Python, a programming language that prioritizes readability. The first activity, aimed at undergraduate physical chemistry lab courses, involves students writing Python code in a Jupyter Notebook that is used to run LJ simulations and fit a van der Waals gas model to data produced by the LJ fluid simulations. The second is a jigsaw activity, aimed at advanced undergraduate or graduate students, where students are assigned different sections of the LJ fluid simulation code, and must demonstrate the functionality of their section to the class by both giving an oral presentation and sharing a Jupyter Notebook demonstration of their own design.

Coherent Phonons in Antimony: An Undergraduate Physical Chemistry Solid-State Ultrafast Laser Spectroscopy Experiment

Ultrafast laser pump-probe spectroscopy is an important and growing field of physical chemistry that allows the measurement of chemical dynamics on their natural timescales, but undergraduate laboratory courses lack examples of such spectroscopy and the interpretation of the dynamics that occur. Here we develop and implement an ultrafast pump-probe spectroscopy experiment for the undergraduate physical chemistry laboratory course at the University of California Berkeley. The goal of the experiment is to expose students to concepts in solid-state chemistry and ultrafast spectroscopy via classic coherent phonon dynamics principles developed by researchers over multiple decades. The experiment utilizes a modern high-repetition rate 800 nm femtosecond Ti:Sapphire laser, split pulses with a variable time delay, and sensitive detection of transient reflectivity signals. The experiment involves minimal intervention from students and is therefore easy and safe to implement in the laboratory. Students first perform an intensity autocorrelation measurement on the femtosecond laser pulses to obtain their temporal duration. Then, students measure the pump-probe reflectivity of a single-crystal antimony sample to determine the period of coherent phonon oscillations initiated by an ultrafast pulse excitation, which is analyzed by fitting to a sine wave. Due to the disruption of in-person instruction caused by the COVID-19 pandemic, during those semesters students were provided the data they would have obtained during the experiment to analyze at home. Evaluation of student written reports reveals that the learning goals were met, and that students gained an appreciation for the field of ultrafast laser-induced chemistry.

High-Performance Computational Chemistry in Undergraduate Physical Chemistry: Exercises in Homonuclear Diatomic Molecules

High-Performance Computational Chemistry in Undergraduate Physical Chemistry: Exercises in Homonuclear Diatomic Molecules

Teaching undergraduate physical chemistry lab with kinetic analysis of COVID-19 in the United States.

A physical chemistry lab for undergraduate students described in this report is about applying kinetic models to analyze the spread of COVID-19 in the United States and obtain the reproduction numbers. The susceptible-infectious-recovery (SIR) model and the SIR-vaccinated (SIRV) model are explained to the students and are used to analyze the COVID-19 spread data from U.S. Centers for Disease Control and Prevention (CDC). The basic reproduction number R 0 and the real-time reproduction number R t of COVID-19 are extracted by fitting the data with the models, which explains the spreading kinetics and provides a prediction of the spreading trend in a given state. The procedure outlined here shows the differences between the SIR model and the SIRV model. The SIRV model considers the effect of vaccination which helps explain the later stages of the ongoing pandemic. The predictive power of the models is also shown giving the students some certainty in the predictions they made for the following months.

Understanding the electrochemical sensors’ figures of merit using a H2O2 sensitive, low-cost ferrite powder first generation electrode

The development of electrochemical sensors capable of quantifying either chemical, biological, or environmental parameters of interest endorses both the increased academic and educational relevance of electrochemistry. As a result, understanding quantitative electrochemical sensing characterization and performance analysis through analytical figures of merit stands as a curricular requirement from both a theoretical and methodological standpoint as it involves the development of several skills which are highly transferable into further electrochemical education and professional practices. On the other hand, due to popular fields of applications such as non-invasive wearable electrochemical sensors for monitoring electrolytes in sweat on high-performance athletes, students are well-aware of its potential, increasing their willingness to partake in electrochemical activities. Addressing the aforementioned, the experience described herein is divided into two main sections. Firstly, a theoretical introduction regarding electrochemical sensors and electrochemical performance validation techniques known as electroanalytical figures of merit are proposed. Secondly, a hands-on experience using a H2O2sensitive ferrite powder working electrode is carried out by performing voltammetric and chronoamperometric techniques so that students develop a basic understanding of the redox processes occurring at the working electrode surface and obtain analytical performance parameters that allow conclusions to be drawn regarding the ferrite powder sensing capabilities towards H2O2 reduction. As for implementation requirements, the proposed four-hour laboratory protocol is suitable for graduate/upper-level undergraduate physical or analytical chemistry courses and, due to its length, is recommended to be conducted in groups of two to three students.

Development of a framework to capture abstraction in physical chemistry problem solving

Productive problem solving, concept construction, and sense making occur through the core process of abstraction. Although the capacity for domain-general abstraction is developed at a young age, the role of abstraction in increasingly complex and disciplinary environments, such as those encountered in undergraduate STEM education, is not well understood. Undergraduate physical chemistry relies particularly heavily on abstraction because it uses many overlapping and imperfect mathematical models to represent and interpret phenomena occurring on multiple scales; however, studying and identifying abstraction in-the-moment in physical chemistry is challenging, because current conceptions of abstraction neglect the domain-specific features. This work uses an approach guided by informed grounded theory to develop a conceptual framework that makes abstraction in physical chemistry problem solving visible. Problem solving teaching interviews with individuals and pairs (n = 18) on thermodynamics and kinetics topics are analyzed using an abductive approach. The resulting Epistemic Actions of Abstraction framework characterizes eight epistemic actions along two dimensions: increasing abstractness relative to the context (concretizing, manipulating, restructuring, and generalizing) and nature of the object the action operates on (conceptual or symbolic). These actions are used to identify two types of abstraction: horizontal and vertical abstraction. We discuss how abstraction in problem solving is contextually dependent and implications this work has for problem solving in physical chemistry, as well as implications for physical chemistry instruction.

Machine Learning for Functional Group Identification in Vibrational Spectroscopy: A Pedagogical Lab for Undergraduate Chemistry Students

Techniques from the branch of artificial intelligence known as machine learning (ML) have been applied to a wide range of problems in chemistry. Nonetheless, there are very few examples of pedagogical activities to introduce ML to chemistry students in the chemistry education literature. Here we report a computational activity that introduces undergraduate physical chemistry students to ML in the context of vibrational spectroscopy. In the first part of the activity, students use ML binary classification algorithms to distinguish between carbonyl-containing and noncarbonyl-containing molecules on the basis of their infrared absorption spectra. In the second part of the activity, students test modifications to this basic analysis including different analysis parameters, different ML algorithms, and different test data sets. In a final extension of the activity, students implement a multiclass classification to predict whether carbonyl-containing molecules contain a ketone, a carboxylic acid, or another carbonyl group. This activity is designed to introduce students both to the basic workflow of a ML classification analysis and to some of the ways in which ML analyses can fail. We provide a comprehensive handout for the activity, including theoretical background and a detailed protocol, as well as data sets and code to implement the exercise in Python or Mathematica. This activity is designed as a standalone exercise for physical chemistry lab classes but can also be integrated with courses or modules on vibrational spectroscopy and computational chemistry. On the basis of student surveys, we conclude that this activity was successful in introducing students to applications of ML in chemistry.

The Briggs–Rauscher Reaction: A Demonstration of Sequential Spatiotemporal Patterns

The Briggs–Rauscher reaction is a popular demonstration to illustrate chemical oscillations in laboratories, classrooms, and public seminars because of its simplicity and visual appeal. Here, we adapt the Briggs–Rauscher reaction to present reaction–diffusion–convection patterns in the undergraduate general or physical chemistry laboratory. By maintaining the ratio between malonic acid and potassium iodate concentrations as 0.2 in an uncovered Petri dish, sequential patterns (transient dendritic patterns and rotating dendritic patterns) can be observed, which are induced by the interaction of reaction, diffusion, and convection. This beautiful demonstration captures students’ attention and inspires reflection and discussion about similar phenomena in nature as well as the wealth of behaviors in systems far from equilibrium.

That’s So Cool. Using a Flame to Freeze Water. The Vapor-Absorption Refrigerator and How It Works

The design and operation of the vapor-absorption refrigerator (VAR) are described using the principles and tools typically covered in upper-division undergraduate physical chemistry courses. The objective is to enable students to understand in detail how this device works and how it compares with more typical vapor-compression refrigerators. Calculations of the thermodynamics and heat flow relating to the refrigeration cycles are presented, leading to the calculation of the coefficient of performance. Two types of VARs are examined, one using LiBr/water solution as the absorbing medium and water as the refrigerant, which relies on the hygroscopic nature of aqueous solutions of LiBr. The second uses water as the absorber and ammonia as the refrigerant. The device described, the Crosley IcyBall, was a popular and inexpensive home refrigerator requiring no electricity. It is an example of a VAR operating in a single-cycle mode.

BASIC CONCEPTS OF SELF-ORGANIZED PHENOMENA IN CHEMICAL SYSTEMS

We present the main concepts of nonlinear dynamics and thermodynamics of irreversible processes to introduce chemistry students to the topic of self-organized phenomena. This task is performed by theoretically describing the emergence of self-sustained oscillations, waves, and stationary patterns/Turing patterns in the Belousov-Zhabotinsky (BZ) reaction, through the Oregonator model. We carefully developed such a description, which resulted in long algebraic deductions and rich supplementary material. Considering that, we encourage the use of this material in undergraduate and graduate advanced physical chemistry classes.

Teaching Entropy from Phase Space Perspective: Connecting the Statistical and Thermodynamic Views Using a Simple One-Dimensional Model

Connecting the thermodynamic definition of entropy, dS = dQ/T (Clausius’s equation), with the statistical definition, S = kB ln Ω (Boltzmann’s equation), has been a persistent challenge in chemical education at the undergraduate level. Not meeting this challenge results in students taking away the meaning of entropy in a vague and subjective way as a measure of “disorder” or increase in number of configurations without any meaningful way of connecting it to heat. To address this challenge, we present a simple model that connects these two definitions. This approach relies centrally on emphasizing that the number of configurations, Ω, includes configurations in both real space and momentum space, collectively known as the phase space. Without including momentum configurations (i.e., how fast the particles move), connecting heat to entropy change is not possible. We construct the phase space for an ensemble of simple one-dimensional systems at equilibrium and show that delivery of heat dQ to the system results in an increase in the number of momentum configurations and consequently an expansion of the phase space area by dΩ. Relating dQ to dΩ is the linchpin between the two views and, when integrated, leads to Boltzmann’s equation. We further show that understanding entropy in terms of volume of phase space removes common ambiguities in teaching the subject. Among other examples, we show that understanding adiabatic compression, if treated using the usual approach, results in contradictions that are resolved if a phase space view is adopted. We propose this approach at the undergraduate physical chemistry and physics level.

Reverse Micelles as Templates for the Fabrication of Size-Controlled Nanoparticles: A Physical Chemistry Experiment

Synthesis and characterization of nanomaterials yields opportunities for instruction of related topics in solution chemistry and materials science, as well as spectroscopy connecting to band theory, the particle in a box quantum mechanical model, and thermodynamics. In collaboration with an undergraduate research assistant, we have developed a synthesis experiment that investigates the use of reverse micelles as reaction templates for the preparation of size-controlled nanomaterials through simple, controlled precipitation reactions. This experiment is designed for an undergraduate physical or inorganic chemistry laboratory course. The proposed method boasts several advantageous features, including simplicity, functionality both at low temperature and in the presence of oxygen, applicability to a wide variety of compounds including semiconductors and colloidal metals, and precise control of particle size. To demonstrate our method, we chose CdSe as a model system due to its readily observable size-dependent optical effects. The particles produced are well-controlled and show high optical quality. Additionally, the use of reverse micelles allows us to further broaden the scope of this assessment, incorporating other key topics including ligand–metal chelation, nucleation/growth kinetics, thermodynamics, surfactant chemistry, and hydrodynamics.

On Teaching Molecular Term Symbols: From the Atomic Term Symbols in a Two-Dimensional World to the Molecular Term Symbols in a Three-Dimensional World

In the article “A Systematic Method for Determining Molecular Term Symbols for Diatomic Molecules Using Uncoupled-States Orbital Diagrams” in this Journal, Campbell introduced a systematic method to determine the molecular term symbols for diatomic molecules. This method is introduced in various undergraduate Physical Chemistry textbooks because of its practicality. However, there remains one question that may baffle some students: Why is |ML| = Λ used when determining the molecular term symbols whereas it is |ML| ≤ L for atomic term symbols? This letter aims to provide a more comprehensive yet clear answer to this question, which, I hope, will help students better understand molecular term symbols and polish their creative problem-solving skills.