This is a jmol display of the atomic orbitals from 1s to 4f that can be rotated in space. They are plotted relative to the x, y, and z-axes.
This will depend on the lecture or lab selected.
I learned of this website after attending the Computational Chemistry for Chemistry Educators (CCCE) workshop last summer '11. In this webpage you will find all the workshop lectures intended for audiences who do not have a computational expertise. You will also find lab exercises already written.
The learning goals here will depend on the lecture and lab from the webpage.
I have not used the lectures or the labs in this website in my classes because they are predominantly geared towards general, organic and physical chemistry. But, I still think this is a good resource for people who are interested in incorporating computational work in their classes.
Use of the cards gives a rough "eyeball" evaluation of student learning throughout a lecture. Using the cards, for me at least, also provides a gauge of attendance as well and also if it waxes or wanes during the class period.
For many years I have resisted using clickers, mainly because at our university there is no standard universal clicker. I wanted to keep student costs as low as possible but also desired the type of live feedback during a lecture that clicker questions can provide. In both my general chem. (200-300 students) and upper division courses (50-75 students), I now pass out 4 or 5 colored notecards on the first day of class and make sure everyone has one of each color. I then do clicker style questions and color code the different answer choices in powerpoint and ask them to hold up their choice after 15-60 seconds depending on the question. This has worked well to provide me instant feedback on difficult topics and doesn't end up singling out any particular student, which most students detest in larger lecture courses.
Students are able to provide feedback to the instructor on questions quickly and "anonymously" and allow one to adjust the direction of a lecture on the fly.
I typically use between 4-6 clicker questions during a 50 minute lecture. I'm sure someone could use more/less based on an individual's needs. I think the key is to use clicker style questions from the beginning of the class on a daily basis to remind students to bring the note cards in a book/binder/bag. This is really the only problem I have encountered- students often forget their cards. It is probably a wash though, as I'm sure students can also forget clickers.
I usually have to work individually with students on this, but the payoff is high. Once students see the light, they get really excited about it. I look to make sure they are calculating the total energy of the reaction, have correctly identified the CO stretches and made some attempt to visualize the MOs.
students sometimes try to calcuate the reaction coordinate energy by only using the HOMO energy. Students sometimes have a hard time finding the correct vibrational modes that relate to CO stretching
This is an addendum to the Manganese Carbonyl experiment (linked below). In this part of the experiment, students carry out high level quantum mechanical calculations of reactants, intermediates, and products in order to determine which of two possible structures is correct.
A student will learn modern computational methods as applied to an organometallic complex
a student will apply the results of a computational experiment to a real synthesis
The exercise is written assuming access to a WebMO cluster, but could be readily modified for use on a local Gaussian/Spartan environment. There are two related activities that are not showing up below so I am linking them here:
I have made this a required characterization method for my students who choose to do this experiment in my course. As the theory required to get the "right" answer is high, I provide optimized input files and simply have the students calculate the energies, vibrations, and MOs. This addendum is very strongly appealing for budding computational chemists, and is a good way for me to recruit joint thesis students to work on modeling inorganic systems for my research. It is very helpful to have a computational chemist available to help with running the jobs the first time you do this, but it is not particularly taxing for the software.
I would hope a discussion would ensue where different groups of students present the pros and cons of the various forms of data fitting.
I was taught (many years ago) the common misconception that fitting the linearized form of the Eyring equation overstates the error in the intercept because on a 1/T axis, the intercept is at infinite temperature, and the intercept is far from the real data. While researching various methods of data fitting, I stumbled across this great article from the New Journal of Chemistry (New J. Chem., 2005, 29, 759–760, doi: 10.1039/b501687h) which proves that in fact, the errors in ∆S‡ and ∆H‡ are the same no matter how you fit the data… but… you must be sure to appropriately weight the data in the non-linear fit. The supplemental information for the paper includes the real data so that you can examine it in more detail.
The attached Mathematica file was developed by my student Ryan Brewster (HMC, Chem 104, Spring 2010), and he deserves partial author credit for this learning object. I thank him for working with me and encouraging me to develop this LO.
A student will learn to fit rate data to various forms of the Eyring equation.
A student will be able to explain when weighting of data is necessary.
If done as an in-class activity, computer workstations running Kaleidagraph, Mathematica or other curve-fitting programs would be required. If done as a discussion, the faculty member would need to have access to these programs in order to verify the data presented.
I have only done this as a lecture and problem set (see the related problem set) but I think it would work very well as an in-class activity. I look forward to seeing either comments or other implementations. Make sure to look at the supporting information for the article as it includes a dataset for use in class.
Here is a suggested procedure (and language) for implementing this activity as an in-class exercise. Take a kinetics data set (there is usually one in the chapter on ligand substitution reactions, or you could use the dataset in the article) and divide the class into several groups. Have one group of students fit the linearized data, one group fit to the Eyring equation using non-weighted data, and a third group fit to the equation while weighting the data appropriately.
Group 1: The following data (provided by the instructor) is a series of rate constants at different temperatures for a chemical reaction. Linearize the data by taking the natural log of each rate constant and plot it vs 1/T (Kelvin temperature!). Fit the linear data to the linearized form of the Eyring equation and extract the activation paramaters from the fit. Report your paramaters on the chalkboard and indicate your group number and how long it took you.
Group 2: The following data (provided by the instructor) is a series of rate constants at different temperatures for a chemical reaction. Fit the data to the Eyring equation and extract the activation paramaters from the fit. Do not weight the data. Report your paramaters on the chalkboard and indicate your group number and how long it took you.
Group 3: The following data (provided by the instructor) is a series of rate constants at different temperatures for a chemical reaction. Fit the data to the Eyring equation and extract the activation paramaters from the fit. Weight the data using the standard weighting scheme in Kaleidagraph (1/k2). Report your paramaters on the chalkboard and indicate your group number and how long it took you.
All groups: After you fit your data, be prepared to discuss the pros and cons of your approach. How easy was it to fit your data? How easy was it to extract the activation paramaters? Do your values match those from the other groups?
Upon completion of the assignment, each group of students gives a short PowerPoint presentation (10-15 minutes) describing their assigned computational project. Their results are described, reporting computed energetic and spectroscopic differences, and using calculated molecular orbital diagrams to explain key intrinsic differences between their computed compounds.
Groups of 2-4 students (depending on class size) are each assigned a different collaborative project that involves using DFT calculations to evaluate some of the principles of inorganic structure and bonding developed in lectures throughout the semester. Each “project” involves comparing the computed properties (spectroscopic (IR), geometric,or relative energies) of a series of molecules and drawing conclusions about the observed differences using concepts developed in class. For each project, a handout is provided, describing the assigned task and providing insightful questions to guide their group discussions. Examples of assignments and the corresponding handouts are attached below.
Molecules are constructed and Gaussian 09 calculations are set up using the user-friendly Gaussview interface. Each group project involves 4-8 calculations,enough that each student gets practice setting up a calculation. Upon completion of their DFT calculations,each group of students collects their data and together they explain the IR results using concepts they learned in class.
Upon completion of this assignment, students will be familiar with:
- the computational methods typically utilized in inorganic chemistry
- the types of information that can (and cannot) be extracted from computational outputs.
Students will also be:
- able to understand and interpret the computational results presented in papers in the current literature
- familiar with procedures for setting up, running, and interpreting computational results using density functional theory (DFT) implemented by Gaussian 09.
Assignment is written with Gaussian 09 in mind, but it is certainly adaptable to Spartan or WebMO.
Students turned in the lab reports for grading. Nearly all students completed the lab report - a few needed extra time after the lab period to finish up calculations.
We also asked students their opinion of the usefulness of the MO exercise on the lab evaluation form. I comment on these more in the next section.
Of the five lab exercises done during the semester (some were multi-week) the MO exercise received the lowest marks from students on the lab evaluation form. A significant fraction of students in the class (15 out of 45) included comments about this lab that indicated that many of the students did not understand the point of the calculations or how it related to what we were discussing in the course. As a result of these comments I will be implementing this exercise in the Fall 2011 offering of Chem 111 as part of the regular course meetings rather than the lab so it can be closely integrated with the class sessions on molecular orbitals.
In Haverford College's course Chem 111:Structure and Bonding, we have included a workshop exercise that guides students through their first experience using electronic structure calculations. We use the WebMO interface along with Gaussian03, but the exercise could be adapted for other electronic structure programs. The general structure of the exercise is as follows:
- Each student in the class performs an MO energy calculation on an H2 molecule with a different H-H distance in the range of 0.5 to 2.0 Å. The class data is used to construct an E vs. r graph for the H-H bond. The students then verify that the "optimize geometry" calculation will find the minimum energy configuration of the H2 molecule.
- The students perform similar calculations for O2 and discover that the triplet state is lower than the singlet state (in addition to learning what "singlet" and "triplet" mean). Then using the O2 molecule they learn to visuallize the molecular orbitals and learn how the "isovalue" affects the appearance of the MOs.
- The students each take a different HX molecule with X from 2nd or 3rd row and calculate dipole moments, atomic (Mulliken) charges, and bond distances. Then as a class the students use their data to construct an electronegativity scale and see how their scale compares with the Pauling scale. They also use the bond lengths to construct a table of atomic covalent radii, and discuss the periodic trends.
- The students are given some suggestions for further topics to explore using electronic structure calculations. Suggestions include (1) Calculating the shapes and bond angles in various XYn molecules and comparing them to VSEPR predictions. (2) Discovering inductive effects on the partial charge on atoms depending on electronegativity of atoms several bonds away. (3) Shapes of MOs in CO (vs. those in O2). (4) Shapes and energies of MOs in benzene.
In the Fall of 2010 these activities all were part of a 3 hour laboratory period devoted to computational chemistry. The report form for this activity is included as an attachment. I've also attached a slightly modified version of the description of the exercise from the Fall 2010 lab manual for the course. My plan for next semester is to implement this as a 1 hour recitation exercise followed by a series of homework activities. Stay tuned.
- Students will learn how to carry out and interpret electronic structure calculations for real and hypothetical small molecules
- Students will learn how to visualize molecular orbitals and electronic potential surfaces derived from electronic structure calculations
- Students will relate results from electronic structure calculations to properties such as atomic radius and electronegativity
- Student's prior learning about periodic trends in atomic radius and electronegativity will be reinforced
Students can use their own laptops or institution-owned computers. Institution supplies computer cluster operating WebMO and Gaussian software.
The attached lecture provides a brief overview to computational methods and introduces their application to inorganic systems. Two specific literature examples are included. I have given this lecture in a senior level advanced inorganic chemistry class for the past 3 years.
At the end of this lecture, students should have an understanding of the principle computational methods and an appreciation for their implementation to inorganic comounds.
Please see attached notes.
A student will be able to hybridize orbitals of appropriate symmetry to help form MO diagrams.
A student will be able to draw pictures of hybrid orbitals.
Upon completion of the experiment the student pairs submit a brief summary of their results and plans to developing a formal report. A draft report is then written in the style and format of an American Chemical Society journal article; the draft must be thoroughly referenced. The instructor reads the draft and returns it to the students with suggestions for revisions. The final version of the report is evaluated in accord with criteria presented in the policy section of the laboratory manual.
Given the integrated nature of this exercise, the laboratory reports indicate whether or not the students have mastered the essential ideas of coordination chemistry. The reports reveal skill in laboratory technique through the percent yield and quality of the products and recording infrared and electronic absorption spectra and in interpretation of the spectra. Although reports are often of high quality and reflect considerable insight, some students seem not to grasp the distinction between molecular and electronic structure. A somewhat larger number have difficulty synthesizing the reaction observations and the measurements, computation, and database results into a comprehensive narrative. That requires further discussion with the instructor. Many students need to learn when to reference statements appropriately.
This experiment, intended for an upper-level inorganic chemistry course, involves classical transition-metal coordination compounds. The purpose of the exercise is to compare the physical and chemical properties of coordination complexes containing copper(II) and silver(II) ions bound to the anion of pyridine–2–carboxylic acid, also known as picolinic acid, picH. The metallic elements copper and silver are in the same family in the periodic table, but their chemical properties are quite different. Although Cu(II) is the stable oxidation state in aqueous solution, Ag(II) is powerfully oxidizing in water. The conjugate base of picH, pyridine–2–carboxylate or picolinate ion, acts as a ligand toward these metal ions, binding to them in chelating mode through the pyridine ring nitrogen atom and one of the carboxylate oxygen atoms. The compounds are synthesized in water at room temperature. In both cases picolinic acid is deprotonated to give picolinate ion, which then binds to Cu2+ and Ag2+, yielding products formulated as M(pic)2. For silver, Ag+ must be oxidized to Ag2+. Molecular and electronic structural characterization is accomplished through infrared, electronic absorption, and electron spin resonance spectroscopy and density functional calculation. Available crystal and molecular structure information is surveyed using the Cambridge Structure Database.
• Students will discover that two structurally similar transition metal compounds can be synthesized cleanly from water solutions.
• Students will engage in the molecular and electronic structural characterization of both compounds. They should appreciate the need to employ a variety of physical measurements to develop a comprehensive structural understanding of a molecule.
• Students will develop an appreciation of differences arising from position in the first vs. second vs. third transition series (the gold(II) compound does not exist).
• Students will learn to do an electronic structure calculation on a transition metal compound and to explore a crystallographic database.
• Pyridine-2-carboxylic acid (picolinic acid), copper(II) acetate hydrate, silver(I) nitrate, ammonium peroxodisulfate, sodium carbonate, deionized water
• Beakers, magnetic stirrers, magnetic stirring bars, filtering funnels, filtering, vacuum drying capability, vials
• FTIR spectrometer (mineral-oil/NaCl or KBr disks or KBr and press for pellet making), UV/Visible spectrometer (quartz cell, water), ESR spectrometer (quartz tubes)
• Access to density functional theory computation software (Spartan, for example) and to Cambridge Structure Database
Students do this experiment in pairs. The synthetic reactions are easily accomplished. The copper reaction gives either the anhydrous material or the monohydrate. The reaction filtrate will yield large crystals, but this requires several weeks at room temperature. The silver compound that does not precipitate from the initial reaction will decompose in solution within a few days at ambient temperature. We store the silver compound in a refrigerator and allow the storage vial to warm to room temperature before removing a sample for physical measurements. The IR measurements are straightforward. We record both solid-state and solution electronic absorption spectra for comparison with the IR spectra (solid state) and to obtain molar absorptivity values. Both compounds give strong ESR spectra for solid-state samples, and a procedure for data analysis is provided. The density functional calculation for the copper compound works well using low-level Spartan software; for silver the number of electrons is too large for successful calculation. Students should understand that generally the simple Spartan DF computation applies to the molecules in the gas phase.