Recommended method: fit k> values at one temperature, fit Ea> values at all other temperatures, then fit k> and Ea> values to all data.

1. Set up the reactions in Excel with initial guesses for the k> rate constant values at Tref. Set Ea> values to be 60 kJ/mol.
2. Manually fit k> values in Simulator to experiments run at Tref. Update the model and open in Fitting.
3. Fit k> values at the reference temperature, Tref. View the Data vs Model plot as a visual check on the fit.
4. Fit Ea> values to the other Scenarios (i.e. to experimental data at different temperatures to Tref).
5. Fit k> values and Ea> values to all data.
6. Update the model and run all Scenarios in Simulator.
7. Update the k> values and Ea> values back to the Excel model.

Recommended method: fit k> and Keq values at one temperature, fit Ea> and Ea< values at other temperatures, then fit all parameters to all data.

1. Set up the reactions in Excel with initial guesses for the k> rate constants and Keq equilibrium constants at Tref. Set Ea> and Ea< values to be 60 kJ/mol.
2. Manually fit k> and Keq values in Simulator to experiments run at Tref. Update the model and open in Fitting.
3. Fit k> and Keq values at the reference temperature, Tref. View the Data vs Model plot as a visual check on the fit.
4. Fit Ea values to the other Scenarios at different temperatures to Tref.
5. Fit k>, Keq and Ea values to all data.
6. Update the model and run all Scenarios in Simulator.
7. Update the k>, Keq and Ea values back to the Excel model.

Note: If your reversible reactions are fast (always at equilibrium) then there are fewer parameters to fit. In this case, you do not need to fit the k>, simply give it a large value (exactly how large depends on the model, but you should be able to increase this in Simulator until it has no effect). With k> set to an arbitrarily high value you only need to fit the equilibrium constant Keq and Ea<.

Often a reasonable approximation is to express the reaction heat as the difference between the forward and reverse activation energies. This allows the activation energy of the reverse reaction (Ea<) to be calculated directly from the forward reaction activation energy (Ea>) and the reaction heat (dHr), i.e. Ea< = Ea> - dHr. This relationship can be set up in a Calculate statement and reduces the number of parameters to fit. An example of how to implement this is given in statements.xls.

You only have to update the model once at the end of a set of exercises to save the values from all of the Scenarios you have fitted to.

Example workflow:

1. Select Scenario1 and its data, data1. Select the parameter to be fitted. Run Fitting. Fitting gives a parameter value = 10.
2. Deselect Scenario1 and select Scenario2 and data2. Run Fitting. Fitted parameter has value = 20.
3. Deselect Scenario2 and select Scenario3 and data3. Run Fitting. Fitted parameter has value = 30.
4. Update the Master model.
5. Right-click on the model icon and View Log. You will see that the values 10, 20 and 30 have been logged as modifications to the three Scenarios.
6. Update your Excel model with the new Scenario values.