Developing an Augmented Reality Application in an Undergraduate DNA Precipitation Experiment to Link Macroscopic and Submicroscopic Levels of Chemistry

Ovens, Michael; Ellyard, Megan; Hawkins, Jacob; Spagnoli, Dino

doi:10.1021/acs.jchemed.0c00481

Cited by 21 publications

(17 citation statements)

References 16 publications

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“…A new emerging visualization technology that is widely used in other areas is augmented reality (AR). AR offers a seamless interface combining real and virtual worlds and has been employed as a teaching medium in the science field , and used in the visualization of 3D molecular structures . In the present study, we use AR to not only visualize MOF structures but, more importantly, for the detection of favorable adsorption sites for gas molecules enabling experimental and computational MOF scientists to better understand the pore environment.…”

Section: Resultsmentioning

confidence: 99%

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications

Oktavian

Schireman

Glasby

et al. 2022

ACS Appl. Mater. Interfaces

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Zr-oxide secondary building units construct metal–organic framework (MOF) materials with excellent gas adsorption properties and high mechanical, thermal, and chemical stability. These attributes have led Zr-oxide MOFs to be well-recognized for a wide range of applications, including gas storage and separation, catalysis, as well as healthcare domain. Here, we report structure search methods within the Cambridge Structural Database (CSD) to create a curated subset of 102 Zr-oxide MOFs synthesized to date, bringing a unique record for all researchers working in this area. For the identified structures, we manually corrected the proton topology of hydroxyl and water molecules on the Zr-oxide nodes and characterized their textural properties, Brunauer–Emmett–Teller (BET) area, and topology. Importantly, we performed systematic periodic density functional theory (DFT) calculations comparing 25 different combinations of basis sets and functionals to calculate framework partial atomic charges for use in gas adsorption simulations. Through experimental verification of CO2 adsorption in selected Zr-oxide MOFs, we demonstrate the sensitivity of CO2 adsorption predictions at the Henry’s regime to the choice of the DFT method for partial charge calculations. We characterized Zr-MOFs for their CO2 adsorption performance via high-throughput grand canonical Monte Carlo (GCMC) simulations and revealed how the chemistry of the Zr-oxide node could have a significant impact on CO2 uptake predictions. We found that the maximum CO2 uptake is obtained for structures with the heat of adsorption values >25 kJ/mol and the largest cavity diameters of ca. 6–7 Å. Finally, we introduced augmented reality (AR) visualizations as a means to bring adsorption phenomena alive in porous adsorbents and to dynamically explore gas adsorption sites in MOFs.

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Section: Resultsmentioning

confidence: 99%

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications

Oktavian

Schireman

Glasby

et al. 2022

ACS Appl. Mater. Interfaces

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“…PedChemSense may consequently be so tailored to the VCI that theoretical adjustments are likely necessary to enable better fit for other teacher learning contexts. However, we note that the use of particulate animations, modelling practices, and Johnstone's triangle are still popular endeavors for chemistry education research (e.g., Ovens et al, 2020;Long et al, 2021). PedChem-Sense also has useful applications for other PD programs that heavily feature molecular visualizations.…”

Section: Limitationsmentioning

confidence: 99%

Pedagogical chemistry sensemaking: a novel conceptual framework to facilitate pedagogical sensemaking in model-based lesson planning

Yezierski

2022

Chem. Educ. Res. Pract.

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Researchers have typically identified and characterized teachers’ knowledge bases (e.g., pedagogical content knowledge and subject matter knowledge) in an effort to improve enacted instructional strategies. As shown by the Refined Consensus Model (RCM), understanding teacher learning, beliefs, and practices is predicated on the interconnections of such knowledge bases. However, lesson planning (defined as the transformation of subject matter knowledge to enacted pedagogical content knowledge) remains underexplored despite its central position in the RCM. We aim to address this gap by developing a conceptual framework known as Pedagogical Chemistry Sensemaking (PedChemSense). PedChemSense theoretically expands upon the RCM that generates actionable guidelines to support chemsistry teachers’ lesson planning. We incorporate the constructs of sensemaking, Johnstone's triangle, and the models for perspective to provide a lesson-planning mechanism that is specific, accessible, and practical, respectively. Lesson examples from our own professional development contexts, the VisChem Institute, demonstrate the efficacy of PedChemSense. By leveraging teachers’ sensemaking of the limitations and utility of models, PedChemSense facilitates teachers’ designing for opportunities to advance their students’ chemistry conceptual understanding. Implications and recommendations for chemistry instruction and research at secondary and undergraduate levels are discussed.

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“…Various studies have been carried out regarding the use of AR technology in chemistry learning, including the use of AR in elemental chemistry practicum (Chen et al, 2019), DNA deposition practicum (Ovens et al, 2020), and stereochemistry learning (Habig, 2020). In addition, research conducted by Candra et al (2020) on the manufacture of interactive modules with AR technology on thermochemical materials is also able to provide 3D visualization so that students' interest and interest in the learning process can increase.…”

Section: Introductionmentioning

confidence: 99%

Augmented Reality Media Validity based on Tetrahedral Chemical Representation with Aiken Validation Index

Sari

Yamtinah

Ariani

et al. 2022

jppipa, pendidikan ipa, fisika, biologi, kimia

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The development of science and technology has brought significant changes to the world of education, especially in the teaching and learning process. In the learning process, there is an interaction between teachers and students to transform their knowledge in the learning environment. To convey this knowledge, a supporting factor in learning is needed, namely learning media. This study aims to determine the feasibility of chemistry learning media in the form of augmented reality (AR) media based on chemical tetrahedral representations on thermochemical materials. This study uses quantitative research methods, with data processing and analysis using the Aiken model. The instrument used is a validation questionnaire sheet to determine the feasibility of the media. The feasibility test itself is carried out by testing 1 chemist, 1 learning media expert, 1 learning technology expert, and 6 education practitioners. The results of the validation test of the feasibility of augmented reality media get the results of Aiken's V 0.9899, which means that the media is feasible to use. However, improvements still need to be made according to suggestions from the validator so that the finalized product can be used as a measuring tool that meets the criteria.

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Developing an Augmented Reality Application in an Undergraduate DNA Precipitation Experiment to Link Macroscopic and Submicroscopic Levels of Chemistry

Cited by 21 publications

References 16 publications

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications

Pedagogical chemistry sensemaking: a novel conceptual framework to facilitate pedagogical sensemaking in model-based lesson planning

Augmented Reality Media Validity based on Tetrahedral Chemical Representation with Aiken Validation Index

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