An Introduction to Coding with Matlab: Simulation of X-ray Photoelectron Spectroscopy by Employing Slater’s Rules

Fisher, Aidan A. E.

doi:10.1021/acs.jchemed.9b00236

Cited by 20 publications

(16 citation statements)

References 21 publications

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“…This learning method applied computers for chemical problems such as solving complex chemical equilibria, 58 nuclear magnetic resonance (NMR) spectroscopy simulations, 59 reaction mechanism determination, 60 kinetics calculations, 61 and quantum mechanical problems. 62 Today, chemistry courses still utilize computer-based learning; however, the definition has progressed to include simulations, 63 software for data capture and analysis, 64 programming-based tutorials, 65 and coding and computational chemistry 66 , 67 (see Table 1 , VL-6, -10–14). Coding and modeling, for example, have also been used to showcase active-learning techniques in a computer-based undergraduate lab (University of Central Lancashire, UK).…”

Section: Virtual Learning Paradigmmentioning

confidence: 99%

Reassessing Undergraduate Polymer Chemistry Laboratory Experiments for Virtual Learning Environments

et al. 2022

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Chemistry laboratory experiments are invaluable to students’ acquisition of necessary synthetic, analytical, and instrumental skills during their undergraduate studies. However, the COVID-19 pandemic rendered face-to-face (f2f), in-person teaching laboratory experiences impossible from late 2019–2020 and forced educators to rapidly develop new solutions to deliver chemistry laboratory education remotely. Unfortunately, achieving learning and teaching objectives to the same caliber of in-person experiments is very difficult through distance learning. To overcome these hurdles, educators have generated many virtual and remote learning options for not only foundational chemistry courses but also laboratory experiments. Although the pandemic challenged high-level chemistry education, it has also created an opportunity for both students and educators to be more cognizant of virtual learning opportunities and their potential benefits within chemistry curriculum. Irrespective of COVID-19, virtual learning techniques, especially virtual lab experiments, can complement f2f laboratories and offer a cost-efficient, safe, and environmentally sustainable alternative to their in-person counterparts. Implementation of virtual and distance learning techniques—including kitchen chemistry and at-home laboratories, prerecorded videos, live-stream video conferencing, digital lab environment, virtual and augmented reality, and others—can provide a wide-ranging venue to teach chemistry laboratories effectively and encourage diversity and inclusivity in the field. Despite their relevance to real-world applications and potential to expand upon fundamental chemical principles, polymer lab experiments are underrepresented in the virtual platform. Polymer chemistry education can help prepare students for industrial and academic positions. The impacts of polymers in our daily life can also promote students’ interests in science and scientific research. Hence, the translation of polymer lab experiments into virtual settings improves the accessibility of polymer chemistry education. Herein, we assess polymer experiments in the emergence of virtual learning environments and provide suggestions for further incorporation of effective polymer teaching and learning techniques into virtual settings.

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Section: Virtual Learning Paradigmmentioning

confidence: 99%

Reassessing Undergraduate Polymer Chemistry Laboratory Experiments for Virtual Learning Environments

et al. 2022

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“…16 This lab session was used with a chemistry undergraduate class with some limited experience of the MATLAB syntax from a previous MATLAB module. 17 Students worked individually with a lab script detailing the key points in the code with a laboratory demonstrator on hand to ensure that the students remain focused and do not become discouraged. The lab handout provided to the students is included in the Supporting Information.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

Developing the Chemist’s Inner Coder: A MATLAB Tutorial on the Stochastic Simulation of a Pseudo-First-Order Reaction

Fisher

2020

J. Chem. Educ.

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The drive in computational methods and more intuitive software has seen a rise in the number of publications in this area in recent years. Computational simulations can be found in many areas of science from computational biology and chemistry to fundamental physics. These may help synthetic chemists in their drug discovery endeavors and cosmologists predicting astronomical events. This paper is designed to equip chemists with a basic understanding of how loops and conditional statements can be used within both the MATLAB syntax and Excel spreadsheets to simulate dynamic processes. Many commercial software packages require little to no programming and often do not explicitly display the underlying calculations. While these programs are often very efficient for solving a specific problem, they are somewhat limited. Principally, this practical uses a stochastic simulation algorithm to generate the kinetic data of a reversible association reaction. The kinetic data is analyzed using the standard rate laws to highlight to students the effectiveness of this method. Ultimately, the skills developed in this practical will help students in future computational projects, where bespoke coding is necessary.

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“…In one example, coding in Matlab was introduced through a hands-on activity in which students simulate X-ray photoelectron spectra, developing understanding of quantum chemistry, spectroscopy, and coding. 1 Other activities centered on coding in Matlab have been reported. language, typically implemented using Jupyter notebooks, have been reported, 6−12 with applications ranging from colorimetric monitoring of titration end points 13 to visualizing NMR concepts.…”

Section: Introduction Background and Problem Identificationmentioning

confidence: 99%

Activity: Teaching Coding in R through Discipline-Focused Problem-Solving in an Analytical Chemistry Course

2022

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Students completing undergraduate majors in chemistry are not typically required to undergo formal training in computer programming or coding. As a result, many chemistry students are graduating without skills in understanding, writing, or manipulating computer code. This skills gap places students at a disadvantage, considering the widespread and ever-increasing use of computers to acquire, analyze, and present data in chemical industry and research. We hypothesized the following: (1) we could introduce coding to the analytical chemistry curriculum in an accessible and discipline-focused manner and (2) tasks based on adapting existing code would be accessible even to novice coders. Presented here is an activity that teaches students to use R, a widely used programming language designed for data analysis and statistics, within the user-friendly RStudio integrated development environment. The activity uses peptide charge as a motivating bioanalytical chemistry topic. The origin and importance of peptide charge are discussed in the four modules that comprise the activity. Applications relevant to chromatography and mass spectrometry are discussed. Students complete tasks of increasing difficulty, with earlier modules supporting later ones. The activity has been taught to advanced undergraduate and first-semester graduate students. In all iterations, anonymous survey data collected using a Likert-scale questionnaire reflected that most students were not familiar with R or coding generally before completing the activity. Students reported finding the activity enjoyable, efficient, effective, and easy to use. The majority reported that they would use R/ RStudio as a scientific tool in both chemistry and nonchemistry projects in the future. The activity is freely available at https:// weaversd.github.io/R_with_peptides_Project/index.html.

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An Introduction to Coding with Matlab: Simulation of X-ray Photoelectron Spectroscopy by Employing Slater’s Rules

Cited by 20 publications

References 21 publications

Reassessing Undergraduate Polymer Chemistry Laboratory Experiments for Virtual Learning Environments

Reassessing Undergraduate Polymer Chemistry Laboratory Experiments for Virtual Learning Environments

Developing the Chemist’s Inner Coder: A MATLAB Tutorial on the Stochastic Simulation of a Pseudo-First-Order Reaction

Activity: Teaching Coding in R through Discipline-Focused Problem-Solving in an Analytical Chemistry Course

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