Martin Jones

The purposes of this experiment are (1) to learn the technique used for semi-microscale boiling point determinations and (2) to use molecular modeling to calculate heat of formation and topological parameters of several molecules, and to see which type of data best correlates with experimental boiling points. You will use the Project Leader feature of CAChe in this experiment, to become acquainted with its features and versatility.

Background

A. Laboratory Method for BP Determination

The method we will use for boiling point determination is discussed in detail in Technique 6, part B of your lab text (pp. 630-636). You will be using the setup illustrated in Fig. 6.10, for semi-microscale bp determination. Recall from last semester (distillation experiment) that boiling point is dependent on atmospheric pressure and that the observed boiling point must be corrected using the nomograph in the lab.

B. Molecular Modeling

In our class, one physical property that is frequently discussed is boiling point (bp). This is an important property for both preparative laboratory work (e.g., the synthesis of 1- and 3-methylcyclohexene via dehydration of 2-methylcyclohexanol is possible because you can distill the final products away from the starting material) and for characterization of unknown substances. You know that the bp’s of organic molecules depend on size, shape, and types of functional groups. Is the bp also dependent on thermodynamic stability? In this experiment you will determine whether bp’s can indeed be correlated to stability, as measured by heats of formation calculated by CAChe.

Molecular connectivity is a topological descriptor of molecular structure (essentially a descriptor of size and shape) based on a count of groupings of skeletal atoms, weighted by degree of skeletal branching. The following equation permits calculation of molecular connectivity:

ub> and d _j represent the differences between the number of valence electrons and the number of hydrogen atoms attached to bonded atoms i and j. A sample calculation is shown below for 2,2-dimethylpentane.

(Numbers represent type of carbon [primary, secondary, etc.] and letters refer to specific bonds)

= 3.0607

(Molecular connectivity was originally developed by Milan Randic in an article entitled "On Characterization of Molecular Branching", published in Journal of the American Chemical Society, 1975, 97, 6609; and further expanded on by the work of Kier and Hall, in their books "Molecular Connectivity in Chemistry and Drug Research", Academic Press: New York, 1977 and "Molecular Connectivity in Structure-Activity Analysis", John Wiley & Sons: New York, 1986.)

You are already familiar with the heat of formation from previous modeling experiments we have done. Recall that the smaller the value of heat of formation, the more stable the molecule.

You will use the following set of compounds for the modeling component of the experiment: pentane; hexane; heptane; octane; 2-methylheptane; 3-methylheptane; 2,2-dimethylhexane; 2,2,4-trimethylpentane; 3-ethylpentane

Procedure:

Part 1 — Laboratory Determination of Boiling Point

Measure today’s atmospheric pressure and record the value on the report sheet.
On the back bench are 4 known compounds — 2-octanol, octane, 2-pentanone, and ethyl acetate. Select one of these compounds and measure out 0.5 mL (using your calibrated Pasteur pipette) into one of your small test tubes. Look up the known bp of your liquid and record it on the report sheet.
Using the small rubber bands, attach the test tube containing your liquid to your high temperature thermometer and place a melting point capillary tube, open end down, into the liquid (see fig 6.10, p 632).
Clamp a Thiele tube filled with mineral oil to a ring stand, then place the thermometer/ test tube assembly into the Thiele tube until the test tube and thermometer bulb are covered by the mineral oil. DO NOT ALLOW THE RUBBER BAND TO COME INTO CONTACT WITH THE MINERAL OIL. Clamp the thermometer in place. (See fig 6.3, p 625).
With a microburner, gently heat the side arm of the Thiele tube. Watch for bubbles coming out of the melting point capillary tube. When the bubbles are streaming out at a very rapid pace, stop the heating. Carefully watch the capillary tube. When the liquid gets sucked back into the tube, record the temperature. That is the boiling point. Record your data on the report sheet. Using the nomograph in the lab, determine the correction factor for your liquid and record it on the report sheet. Calculate the corrected bp for your compound and record it on your report sheet.
Allow the mineral oil in the Thiele tube to cool to at least 50^oC.
Repeat steps 2-5 with an unknown, A-D. The possible unknowns are: 2-propanol (isopropyl alcohol), 2,2,4-trimethylpentane, butyl acetate, and cyclohexanone.

Part 2 — Molecular Modeling

Open a new workspace in CAChe.
Construct a model of each molecule in the set and optimize the geometry using Beautify | Comprehensive.
Save each molecule of the set in a separate file in your folder.
After you have constructed each of the molecules for a given set, close the CAChe workspace. Select Start | Programs | CAChe | Project Leader.
The Project Leader window should appear. This window will contain a table of cells (not unlike a spreadsheet).
To get started, you need to add chemical sample files to the table. Double-click on an empty cell in the Chemical Sample column to display the Choose Chemical Sample dialog box.
Select a chemical sample file (from your folder) by clicking on it in the scrolling list.
Select Open. A small version of the structure will appear in the cell.
Repeat steps 6-8 for the remaining files you need from this experiment.
You now need to add a property to the table. Double-click on an empty column title cell to display the Enter property dialog box.
Select the Property of chemical sample radio button and select Next.
Select heat of formation from the Kind of property scrolling list and select Next.
Select standard procedure from the Kind of procedure scrolling list and select OK.
Double-click on an empty column title cell to display the Enter property dialog box.
Select the Property of chemical sample radio button and select Next.
Select connectivity index 0 from the Kind of property scrolling list and select Next.
Select standard procedure from the Kind of procedure scrolling list and select OK.
Repeat steps 14-17, but select connectivity index 1, then subsequently connectivity index 2. These are different levels of connectivity calculations, focusing on atoms (0), bonds (1), and path (2).
Select the Property of chemical sample radio button and select Next.
Select experimental boiling point from the Kind of property scrolling list and select Next.
Select manual entry from the Kind of procedure scrolling list and select OK.
Enter the appropriate boiling points for your compounds, using the data given at the end of this experiment. To do this, double-click in the cell you wish to edit. When the interior of the cell is white and has a flashing cursor, you may use the keyboard to enter the data. Use the enter key to move to the next cell.
From the top menu bar, select Evaluate | Select server. Select cache@localhost. Then select OK.
Select the cells you wish to have evaluated by dragging the mouse over the cells of interest. These will be the cells in the columns labeled heat of formation and connectivity indices. The cells will be black when they are selected.
To evaluate the selected cells, select Evaluate | Cells from the top menu bar in the Project Leader window.
When the calculations are complete, there should be numbers in each of the cells.
To determine if there is any correlation between heat of formation and boiling point, double-click on an empty column title cell to display the Enter property dialog box.
Now select the Analysis radio button and click Next.
Select Multiple Linear Regression and click Next.
From the Enter Property dialog box, select Predict: experimental boiling point and Using: heat of formation. Then click OK. A formula for the regression analysis will appear in the column title cell.
Repeat steps 27-30, selecting Using: connectivity index 0.
Repeat these steps for connectivity index 1, then for connectivity index 2.
Select all cells that have regression analysis formulas in the column title cell, then select Evaluate | Cells from the top menu bar.
The cells will fill with predicted boiling points. A measure of how close the predicted boiling points are to the actual boiling points is given by the rCV^2 value - the closer it is to 1, the better the correlation.
Look at your data - which is the best predictor of boiling point?
Print this table and attach it to your report sheet. Select File | Page Setup, then click in the Landscape radio button. Click OK, then select File | Print.
To see scatter graphs of the various correlations, click on any heading to highlight the entire column.
Select View | Scatter Plot from the top menu bar.
In the window that comes up, select heat of formation for the horizontal axis column and experimental boiling point for the vertical axis column. Then click on OK.
A plot of the data will appear. If you wish to have a printout of this plot, please follow this procedure: Double click on the graph title and change the title to best fit the plot (e.g., Correlation of boiling point with heat of formation). While the plot is the active window, select Edit | Copy from the main menu bar. Open Microsoft Word, then paste the plot in the new Word document. Double click on the plot, then select Fill color from the bottom menu (the little bucket with paint spilling out of it). Click on the white box for the fill color. If not all the blue background has disappeared, repeat the previous steps until no blue background color is left. Then print the plot.
Repeat steps 37-39 for each of the connectivity indices (instead of heat of formation).
Record appropriate data on the report sheet and answer the questions.

Extensions: You could select other parameters for evaluation - HOMO energies, shape, valence connectivity, dipole moment, dielectric constant, etc. - to see if these have any correlation with boiling point.

Compound	Boiling Point (^oC)
Table of Experimental Boiling Points for Modeling Component of Experiment
Pentane	36.1
Hexane	69
Heptane	98.4
Octane	125.7
2-Methylheptane	117.7
3-Methylheptane	119
2,2-Dimethylhexane	106.8
3-Ethylpentane	93.5
2,2,4-Trimethylpentane	99.2

REPORT SHEET FOR BOILING POINT EXPERIMENT

Name___________________________

Laboratory Data:

Atmospheric Pressure:____________

Known Compound selected_____________________________

Unknown Compound selected (letter code)________

Modeling Data:

Staple your Project Leader table to this report sheet.

Correlation coefficients (rCV^2):
Heat of formation___________
Connectivity 0______________
Connectivity 1______________
Connectivity 2______________

Questions:

How closely did your corrected boiling point agree with the literature boiling point for the known compound? What are some possible errors in this experiment?
Which parameter gave the best correlation with experimental boiling point in the modeling experiment?
Based on your modeling results, is boiling point dependent on thermodynamic stability?
For your particular set of compounds, what conclusions can you draw about how structural features affect boiling point? (Consider such things as length of chain, branching, surface area, etc.)

BOILING POINT

Laboratory and Molecular Modeling Experiment