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Journal Articles: 36 results
Forecasting Periodic Trends: A Semester-Long Team Exercise for Nonscience Majors  John Tierney
Teams of students in a course for nonscience majors identify trends among the properties of elements in the periodic table, use Excel to plot and produce best-fit equations to describe relationships among those properties, and apply the resulting formulas to predict and justify the properties of missing elements.
Tierney, John. J. Chem. Educ. 2008, 85, 1215.
Atomic Properties / Structure |
Computational Chemistry |
Main-Group Elements |
Nonmetals |
Periodicity / Periodic Table |
Metals |
Student-Centered Learning
Using Molecular Dynamics Simulation To Reinforce Student Understanding of Intermolecular Forces  Phillip R. Burkholder, Gordon H. Purser, and Renee S. Cole
This article presents a series of experiments incorporating molecular dynamics simulations which predict the motion of chemical species based on the application of empirical rules and a physical analysis of the forces that act between the species. These motions can then be shown in vivid graphical form.
Burkholder, Phillip R.; Purser, Gordon H.; Cole, Renee S. J. Chem. Educ. 2008, 85, 1071.
Computational Chemistry |
Hydrogen Bonding |
Molecular Mechanics / Dynamics |
Physical Properties |
Solutions / Solvents
Data-Driven Exercises for Chemistry: A New Digital Collection  W. Tandy Grubbs
The JCE Data-Driven Exercises collection is devoted to the accumulation, distribution, and curricular use of guided-inquiry, data-centered exercises. Each exercise is based upon real data and can be downloaded from the collection and assigned in or out of class.
Grubbs, W. Tandy. J. Chem. Educ. 2007, 84, 1391.
Computational Chemistry
Lewis Structure Representation of Free Radicals Similar to ClO  Warren Hirsch and Mark Kobrak
An unconventional Lewis structure is proposed to explain the properties of the free radical ClO and a series of its isoelectronic analogues, particularly trends in the spin density of these species.
Hirsch, Warren; Kobrak, Mark. J. Chem. Educ. 2007, 84, 1360.
Atmospheric Chemistry |
Computational Chemistry |
Covalent Bonding |
Free Radicals |
Lewis Structures |
Molecular Modeling |
MO Theory |
Valence Bond Theory
Introducing the Practical Aspects of Computational Chemistry to Undergraduate Chemistry Students  Jason K. Pearson
Presents a laboratory exercise in which students use traditional second-year concepts such as the rigid rotor and harmonic oscillator approximations in conjunction with Gaussian 03 to reinforce practical aspects of computational chemistry.
Pearson, Jason K. J. Chem. Educ. 2007, 84, 1323.
Computational Chemistry |
MO Theory |
Quantum Chemistry |
Theoretical Chemistry
Teaching Mathematics to Chemistry Students with Symbolic Computation  J. F. Ogilvie and M. B. Monagan
The authors explain how the use of mathematical software improves the teaching and understanding of mathematics to and by chemistry students while greatly expanding their abilities to solve realistic chemical problems.
Ogilvie, J. F.; Monagan, M. B. J. Chem. Educ. 2007, 84, 889.
Chemometrics |
Computational Chemistry |
Fourier Transform Techniques |
Mathematics / Symbolic Mathematics |
Nomenclature / Units / Symbols
On the Role of d Orbital Hybridization in the Chemistry Curriculum  John Morrison Galbraith
The use of d-orbital hybridization to describe hypervalent molecules should be removed from the general chemistry curriculum. The case of bonding in sulfur hexaflouride can illustrate that no theory provides all the right answers all the time.
Galbraith, John Morrison. J. Chem. Educ. 2007, 84, 783.
Computational Chemistry |
MO Theory |
Valence Bond Theory
Predicting the Stability of Hypervalent Molecules  Tracy A. Mitchell, Debbie Finocchio, and Jeremy Kua
In this exercise, students use concepts in thermochemistry such as bond energy, ionization potentials, and electron affinities to predict the relative stability of two hypervalent molecules (PF5 and PH5) relative to their respective non-hypervalent counterparts.
Mitchell, Tracy A.; Finocchio, Debbie; Kua, Jeremy. J. Chem. Educ. 2007, 84, 629.
Computational Chemistry |
Covalent Bonding |
Ionic Bonding |
Lewis Structures |
Molecular Modeling |
Calorimetry / Thermochemistry |
Molecular Properties / Structure
Characterization of High Explosives and Other Energetic Compounds by Computational Chemistry and Molecular Modeling  John A. Bumpus, Anne Lewis, Corey Stotts, and Christopher J. Cramer
Four experiments suitable for use in the undergraduate instructional laboratory demonstrate the use of computational chemistry and molecular-modeling procedures to calculate selected physical and chemical properties of several high explosives and other energetic compounds.
Bumpus, John A.; Lewis, Anne; Stotts, Corey; Cramer, Christopher J. J. Chem. Educ. 2007, 84, 329.
Computational Chemistry |
Gases |
Physical Properties |
Molecular Modeling |
Molecular Properties / Structure
Looking behind the Spreadsheet Trendline  William F. Coleman and Edward W. Fedosky
Presents a visual approach to linear least-squares curve fitting that drives home the idea of minimizing the sum of the squares of the deviations in order to find the best fit to a set of data that are being described by a linear relationship.
Coleman, William F.; Fedosky, Edward W. J. Chem. Educ. 2006, 83, 1884.
Computational Chemistry |
Mathematics / Symbolic Mathematics
Looking behind the Spreadsheet Trendline  William F. Coleman and Edward W. Fedosky
Presents a visual approach to linear least-squares curve fitting that drives home the idea of minimizing the sum of the squares of the deviations in order to find the best fit to a set of data that are being described by a linear relationship.
Coleman, William F.; Fedosky, Edward W. J. Chem. Educ. 2006, 83, 1884.
Computational Chemistry |
Mathematics / Symbolic Mathematics
Introducing the Core Concepts of Nanoscience and Nanotechnology: Two Vignettes  Karl Sohlberg
Presents two theoretical calculations that are relatively simple to implement using standard spreadsheet software, are suitable for discussion at the undergraduate level, and directly demonstrate the core concepts of nanoscience and nanotechnology.
Sohlberg, Karl. J. Chem. Educ. 2006, 83, 1516.
Computational Chemistry |
Nanotechnology |
Theoretical Chemistry
A Sequence of Linked Experiments, Suitable for Practical Courses of Inorganic, Organic, Computational Chemistry, and NMR Spectroscopy  Grigoriy A. Sereda
A sequence of investigations associated with the iodochlorination of styrene and 1-hexene is described. The sequence is flexible enough to be used in inorganic, organic, computational, and instrumental courses.
Sereda, Grigoriy A. J. Chem. Educ. 2006, 83, 931.
Alkenes |
Computational Chemistry |
Constitutional Isomers |
MO Theory |
NMR Spectroscopy |
Synthesis
(Strept)Avidin–Biotin: Two Interrelated Experiments for the Introductory Chemistry Laboratory  David E. Hansen, Dengda Tang, Jon A. Sanborn, and Mark D. Marshall
Describes a two-experiment sequence focusing on the noncovalent complex between the egg white protein avidin (or the similar protein streptavidin, which is expressed by the bacterium Streptomyces avidinii) and the essential cofactor biotin. The equilibrium constant for the binding of HABA to avidin is calculated from the data collected.
Hansen, David E.; Tang, Dengda; Sanborn, Jon A.; Marshall, Mark D. J. Chem. Educ. 2006, 83, 777.
Bioorganic Chemistry |
Computational Chemistry |
Equilibrium |
Titration / Volumetric Analysis
Modeling Dynamic Equilibrium with Coins  Martin Bartholow
Students explore the concept of equilibrium by moving small objects between two piles.
Bartholow, Martin. J. Chem. Educ. 2006, 83, 48A.
Computational Chemistry |
Equilibrium |
Rate Law
Mechanisms That Interchange Axial and Equatorial Atoms in Fluxional Processes: Illustration of the Berry Pseudorotation, the Turnstile, and the Lever Mechanisms via Animation of Transition State Normal Vibrational Modes  Marion E. Cass, King Kuok Hii, and Henry S. Rzepa
Teaching the Berry pseudorotation mechanism presents particular pedagogic problems due to both its dynamic and three dimensional character. The approach described here illustrates these processes using interactive animations embedded in a Web page.
Cass, Marion E.; Hii, King Kuok; Rzepa, Henry S. J. Chem. Educ. 2006, 83, 336.
Computational Chemistry |
Enantiomers |
Molecular Mechanics / Dynamics |
Molecular Properties / Structure |
Mechanisms of Reactions |
NMR Spectroscopy |
Nonmetals
Using Jmol To Help Students Better Understand Fluxional Processes   William F. Coleman and Edward W. Fedosky
This new WebWare neatly combines instructional text and Jmol interactive, animated illustrations to teach mechanisms that need to be clearly visualized in order to be well understood.
Coleman, William F.; Fedosky, Edward W. J. Chem. Educ. 2006, 83, 336.
Computational Chemistry |
Enantiomers |
Mechanisms of Reactions |
Molecular Mechanics / Dynamics |
Molecular Properties / Structure |
NMR Spectroscopy |
Nonmetals
Computer Simulations of Salt Solubility  Victor M. S. Gil and João C. M. Paiva
Computer Simulations of Salt Solubility provides an animated, visual interpretation of the different solubilities of related salts based on simple entropy changes associated with dissolution: configurational disorder and thermal disorder.
Gil, Victor M. S.; Paiva, João C. M. J. Chem. Educ. 2006, 83, 173.
Thermodynamics |
Equilibrium |
Solutions / Solvents |
Precipitation / Solubility |
Computational Chemistry
A New Java Animation in Peer-Reviewed JCE WebWare  William F. Coleman and Edward W. Fedosky
Just added to JCE WebWare, Computer Simulations of Salt Solubility uses a Java applet and Web browser to present an animated illustration of differences in the solubility of salts due to differences in the entropy of solvation.
Coleman, William F.; Fedosky, Edward W. J. Chem. Educ. 2006, 83, 173.
Computational Chemistry |
Equilibrium |
Thermodynamics |
Solutions / Solvents |
Precipitation / Solubility
Using Computer Simulations To Teach Salt Solubility. The Role of Entropy in Solubility Equilibrium  Victor M. S. Gil and João C. M. Paiva
Pairs of salts are discussed to illustrate the interpretation of their different behavior in water in terms of the fundamental concept of entropy. The ability of computer simulations to help improve students' understanding of these chemistry concepts is also examined.
Gil, Victor M. S.; Paiva, João C. M. J. Chem. Educ. 2006, 83, 170.
Computational Chemistry |
Equilibrium |
Thermodynamics |
Solutions / Solvents |
Precipitation / Solubility
Teaching Molecular Symmetry with JCE WebWare  William F. Coleman and Edward W. Fedosky
Presents two tools, 3D Molecular Symmetry Shockwave and An Animated Interactive Overview of Molecular Symmetry, that illustrate and help teach molecular symmetry.
Coleman, William F.; Fedosky, Edward W. J. Chem. Educ. 2005, 82, 1741.
Computational Chemistry |
Molecular Properties / Structure |
Group Theory / Symmetry
Demonstrating and Measuring Relative Molar Magnetic Susceptibility Using a Neodymium Magnet  Charles J. Malerich and Patrica K. Ruff
A method for demonstrating and measuring the magnetic attraction between a paramagnetic substance and a neodymium magnet is described and evaluated. The experiment measures the maximum angle that the magnet can deflect a paramagnetic compound from the vertical. The apparatus to make this measurement is easy to set up and is low-cost.
Malerich, Charles J.; Ruff, Patrica K. J. Chem. Educ. 2004, 81, 1155.
Magnetic Properties |
Metals |
Transition Elements |
Computational Chemistry
Solution of Cubic Equations by Iteration Methods on a Pocket Calculator  Farzad Bamdad
Methods for solving cubic equations by inexpensive pocket-size programmable calculators are presented.
Bamdad, Farzad. J. Chem. Educ. 2004, 81, 758.
Aqueous Solution Chemistry |
Learning Theories |
Computational Chemistry
A Program of Computational Chemistry Exercises for the First-Semester General Chemistry Course  Scott E. Feller, Richard F. Dallinger, and Paul Caylor McKinney
A series of 13 molecular modeling exercises designed for the first-semester general chemistry course is described. The modeling exercises, which are used as both prelecture explorations and postlecture problems, increase in difficulty and in student independence.
Feller, Scott E.; Dallinger, Richard F.; McKinney, Paul Caylor. J. Chem. Educ. 2004, 81, 283.
Atomic Properties / Structure |
Computational Chemistry |
Molecular Modeling |
Molecular Properties / Structure
Simple HTML Templates for Creating Science Oriented Jeopardy! Games for Active Learning  Joseph J. Grabowski and Michelle L. Price
Simple HTML Templates for Creating Science Oriented Jeopardy! Games for Active Learning and A Graphical User Interface for PC GAMESS
Grabowski, Joseph J.; Price, Michelle L. J. Chem. Educ. 2003, 80, 967.
Computational Chemistry |
Undergraduate Research
Laboratory Sequence in Computational Methods for Introductory Chemistry  Jason A. Cody and Dawn C. Wiser
Description of a four-week laboratory sequence that exposes students to instrumentation (FT-NMR, GC) and computational chemistry.
Cody, Jason A.; Wiser, Dawn C. J. Chem. Educ. 2003, 80, 793.
Chromatography |
Computational Chemistry |
Noncovalent Interactions |
MO Theory |
Molecular Modeling |
Molecular Mechanics / Dynamics |
Molecular Properties / Structure |
NMR Spectroscopy |
Gas Chromatography
ORBITAL  Robert M. Hanson
Software that produces probability-based three-dimensional representations of the hydrogen atom and other single-electron systems.
Hanson, Robert M. J. Chem. Educ. 2003, 80, 710.
Atomic Properties / Structure |
Atomic Spectroscopy |
Computational Chemistry |
Enrichment / Review Materials
ORBITAL  Robert M. Hanson
Software for producing probability-based three-dimensional representations of atomic orbitals of the hydrogen atom and other single-electron systems; found on the Advanced Chemistry Collection CD-ROM, 3rd Edition.
Hanson, Robert M. J. Chem. Educ. 2003, 80, 109.
Atomic Properties / Structure |
Atomic Spectroscopy |
Computational Chemistry
Molecular Modeling and Computational Chemistry at Humboldt State University  Richard A. Paselk and Robert W. Zoellner
Project to integrate molecular modeling and computational chemistry throughout the chemistry curriculum; includes consideration of facilities, hardware, software, courses, and listing of undergraduate, computational research projects.
Paselk, Richard A.; Zoellner, Robert W. J. Chem. Educ. 2002, 79, 1192.
Computational Chemistry |
Molecular Modeling |
Undergraduate Research
Lewis Structures in General Chemistry: Agreement between Electron Density Calculations and Lewis Structures  Gordon H. Purser
The internuclear electron densities of a series of X-O bonds (where X = P, S, or Cl) are calculated using quantum mechanics and compared to Lewis structures for which the formal charges have been minimized; a direct relationship is found between the internuclear electron density and the bond order predicted from Lewis structures in which formal charges are minimized.
Purser, Gordon H. J. Chem. Educ. 2001, 78, 981.
Covalent Bonding |
Computational Chemistry |
Molecular Properties / Structure |
Lewis Structures |
Quantum Chemistry
Have Orbitals Really Been Observed? (re J. Chem. Educ. 2000, 77, 1492-1494)  John C. H. Spence, M. O'Keefe, and J. M. Zuo
Clarification of work described in a previous article.
Spence, John C. H.; O'Keefe, M.; Zuo, J. M. J. Chem. Educ. 2001, 78, 877.
Computational Chemistry |
MO Theory |
Quantum Chemistry |
Theoretical Chemistry
Have Orbitals Really Been Observed?  Eric R. Scerri
Recent reports claiming to have observed textbook d orbitals are analyzed and it is argued that what was observed indirectly, and not for the first time, was actually electron density. It is also suggested that the tendency to use the terms electron density and orbital to mean the same thing will give rise to confusion in chemical education.
Scerri, Eric R. J. Chem. Educ. 2000, 77, 1492.
Computational Chemistry |
MO Theory |
Quantum Chemistry |
Theoretical Chemistry
Lewis Structures Are Models for Predicting Molecular Structure, Not Electronic Structure  Gordon H. Purser
This article argues against a close relationship between Lewis dot structures and electron structure obtained from quantum mechanical calculations. Lewis structures are a powerful tool for structure prediction, though they are classical models of bonding and do not predict electronic structure.
Purser, Gordon H. J. Chem. Educ. 1999, 76, 1013.
Molecular Properties / Structure |
Covalent Bonding |
Computational Chemistry |
Quantum Chemistry |
MO Theory |
Learning Theories |
Lewis Structures |
Molecular Modeling
Teaching Chemistry with Electron Density Models  Gwendolyn P. Shusterman and Alan J. Shusterman
This article describes a powerful new method for teaching students about electronic structure and its relevance to chemical phenomena. This method, developed and used for several years in general chemistry and organic chemistry courses, relies on computer-generated three-dimensional models of electron density distributions.
Shusterman, Gwendolyn P.; Shusterman, Alan J. J. Chem. Educ. 1997, 74, 771.
Learning Theories |
Computational Chemistry |
Molecular Modeling |
Quantum Chemistry |
Atomic Properties / Structure |
Covalent Bonding |
Ionic Bonding |
Noncovalent Interactions
Stoogiometry: A Cognitive Approach to Teaching Stoichiometry  Carla R. Krieger
Moe's Mall is a locational device designed to be used by learners as a simple algorithm for solving mole-based exercises efficiently and accurately. The mall functions as a map for setting up solutions to mole-based exercises using dimensional analysis. It clears the cognitive decks of students' easily overburdened short-term memory space, allowing them to focus on the versatility of the mole, rather than stepwise solutions to meaningless exercises.
Krieger, Carla R. J. Chem. Educ. 1997, 74, 306.
Learning Theories |
Computational Chemistry |
Stoichiometry
In This Issue  
Over the past decade computational chemistry has changed from the arcane pursuit of a few advanced university researchers in the area of physical chemistry to a familiar tool used by a wide range of chemists.
J. Chem. Educ. 1996, 73, 104.
Computational Chemistry