An Undergraduate Chemistry Lab Exploring Computational Cost and Accuracy: Methane Combustion Energy

Abstract

Over the past half century, computational chemistry has evolved from a niche field to a ubiquitous pillar of modern chemical research. Driven by the increased demand for computational chemistry in research settings, the undergraduate curriculum has evolved alongside to ensure that students are well-equipped for modern research. Toward this end, many excellent computational chemistry exercises have been developed that aim to teach students what kinds of questions computational chemistry can answer and how to properly interpret the results. However, there has been far less attention given to the complexities of determining how reliable computational results are and how constraining computational scaling can be. We present an undergraduate lab exercise that uses ab initio methods to predict the combustion energy of methane. The exercise walks students through the process of benchmarking errors on a small system (methane), estimating the computational cost to perform the same analysis on a larger system (propane), and justifying an affordable yet accurate method for a hypothetical study of the larger system. Furthermore, students are introduced to other cost-saving measures like basis set extrapolation and additive corrections. The entire exercise is intentionally designed to require little technical knowledge of computational chemistry and to be flexibly grafted into a standard undergraduate curriculum. In order to ensure accessibility, the exercise utilizes the free open source software PSI4 (available on any operating system) and provides a detailed installation and use guide for completing this lab. This lab will provide students the understanding of how to properly judge, select, and justify different computational models where cost and accuracy compete, a highly desirable set of skills that generalize to any computational science.

Determination of Energy Content of “Zero-Sugar” Artificial Sweeteners via Bomb Calorimetry and Theoretical Calculations

“…It is recognized that there are inherent limitations of semiempirical calculations that can lead to larger calculation errors, which in turn contribute to larger percent errors. 59,60 This Journal includes examples of activities that employ semiempirical 61 and ab initio 33 calculations and can provide further insights into the benefits and limitations of each in the practice of computational chemistry. Tabulated average bond energies were employed to calculate the theoretical heats of combustion according to method (2) above.…”

“…(For a more detailed explanation of the rationale, see the Artificial Sweeteners Activity Instructor Notes in the Supporting Information.) It is recognized that there are inherent limitations of semiempirical calculations that can lead to larger calculation errors, which in turn contribute to larger percent errors. , This Journal includes examples of activities that employ semiempirical and ab initio calculations and can provide further insights into the benefits and limitations of each in the practice of computational chemistry.…”

“…Bomb calorimetry is a particularly interesting technique to utilize with food-oriented subject matter because of the technique’s prominence in determining a food’s calorie content . Computational modeling methods can be used to determine the energy contents of various chemical substances, including those compounds that are important in food. ,− These two techniques, which apply principles that are typically covered in an upper-level physical chemistry course, are complementary in that bomb calorimetry is utilized to experimentally measure the energy content of a substance upon combustion, while computational methods can be used to calculate the energies of compounds and reactions more theoretically. A search of this Journal found laboratory activities that combine the use and application of bomb calorimetry and computational methods. ,,, However, none of these activities employ food as the central focus.…”

Untitled

“…The stability and reactivity of the molecule can be known by the factors of hardness (ɳ) and chemical softness (ς) [19][20][21][22]. Hence, compound 1(ς =1.11 eV) is the more softness with the lowest hardness.…”

Integrating Computational Data Science in University Curriculum for the New Generation of Scientists

“…Zdanovskaia et al (2018) discussed access to computational chemistry for community colleges via WebMO. Wolf et al (2022) presented an undergraduate lab exercise that used ab initio methods to predict the combustion energy of methane which provided students the understanding of how to properly judge, select and justify different computational models where cost and accuracy compete. Metz et al (2021) looked at using an open-source code to introduce computational chemistry in first-year or introductory-level courses while enhancing understanding of the Aufbau principle, electron configurations and ionization energy.…”