Package: navicat-mikimo
mikimo: microkinetic modeling and microkinetic volcano plots for homogeneous catalytic reactions☄️ Why use microkinetic modelling? ☄️Elegant way to deal with complex reaction pathway thermodynamics and kineticsAccounts for reaction conditions: temperature effects, concentration effects, reaction time, etc.☄️ What are microkinetic volcano plots? ☄️Volcano plot:  plots the activity (or selectivity) of catalysts against a descriptor variable that uniquely determines a catalyst. Based on linear free energy scaling relationships.microkinetic volcano plot: the activity/selectivity is expressed the final product concentrations, or ratio of concentrations, after a given time.ContentsDependenciesInstallUsagesExamplesKnown LimitationCitationDependencies↑The code runs on pure python with the following dependencies:numpyscipyautogradmatplotlibpandasscipyh5pyfirenavicat_volcanicInstall↑pipinstall.orpythonsetup.pyinstallUsages↑The code requires two essential inputs for the analysis: energy data, reaction network (along with initial concentrations to be incorporated in the reaction network). All these files must be in the same directory.energy data: reaction_data (in csv or xlsx format)reaction network: rxn_network (in csv or xlsx format)(optional) kinetic data: kinetic_data (in csv or xlsx format)The energy data must be named "reaction_data" and share similar format as innavicat_volcanic. In cases involving multiple reaction pathways, the final column of each pathway (including those pathways leading to the resting state) should contain "Prod" (case-insensitive).The reaction network must be provided as a CSV or XLSX file named "rxn_network". Each row in the network represents an elementary step, while the columns represent the chemical species involved in the mechanism, excluding transition states. When filling in the reaction network, it is crucial to ensure that the species names match those in the energy data.For each step (denoted asi) in the reaction network, assign a value of-nto the species on the left side of the equation and+n(or simplyn) to the species on the right side, wherenrepresents the stoichiometric coefficient. If a chemical species is not involved in step i, leave the corresponding cell empty or fill it with 0.The initial concentrations should be specified in the last row of the reaction network file. This row can be named "c0", "initial_conc," or "initial conc."Once all input files are ready andmikimois installed, several run options are available:Call just kinetic solver:python-mnavicat_mikimomkm-d[DIR]Microkinetic modelling for all reaction profiles:python-mnavicat_mikimovp-d[DIR]-nd0To construct microkinetic volcano plot:python-mnavicat_mikimovp-d[DIR]-nd1To construct microkinetic activity/selectivity map:python-mnavicat_mikimovp-d[DIR]-nd2To screen over reaction time and temperature:python-mnavicat_mikimocond-d[DIR]To smooth the volcano plots generated:pythonreplot.py[i]Examples↑Microkinetic modelling for Pd-catalyzed carbocyclization-borylation of enallene in the presence of chiral phosphoric acid at room temperature for 1 min of reaction time:python-mnavicat_mikimomkm-dtest_cases/pd_carbocylic_borylation/-t298.15-Tf60Microkinetic modelling for all profiles of the catalytic competing carboamination and cyclopropanation of N-enoxyphathanalimides with alkenes (353.15 K, 1 d):python-mnavicat_mikimovp-dvolcanic_test/CA_CP_selectivity/-t353.15-nd0Constructing the microkinetic volcano plot for the catalytic competing carboamination and cyclopropanation of N-enoxyphathanalimides with alkenes (353.15 K, 1 d):python-mnavicat_mikimovp-dvolcanic_test/CA_CP_selectivity/-t353.15-nd1-ncore24Constructiong the microkinetic activity/selectivity map for the catalytic competing carboamination and cyclopropanation of N-enoxyphathanalimides with alkenes (353.15 K, 1 d):python-mnavicat_mikimovp-dvolcanic_test/CA_CP_selectivity/-t353.15-nd2-ncore24Constructing the activity/selectivity map with time [2-24 hr] and temperature [273.15-423.15 K] as descriptors:python-mnavicat_mikimocond-dtest_cases/pincer_CO2_jacs/-tt-Tf720086400-t273.15423.15-ncore24Using filtering to smooth the plot:pythonreplot.pyexamples/data/data.h5-p333-w202020You can find examples of reading h5 files and regenerating plots in the "examples" folder.If the kinetic profile is detected in the directory, the code will prompt the user with an option to choose between using the kinetic profile instead of the energy profile. However, it's important to note that selecting the kinetic profile will restrict the user from screening over a range of temperatures or utilizing different temperature settings.Known Limitations↑Overlapping states of different pathways before the reference state (starting point).Bridging states between otherwise separate pathways.Different TSs connecting the same 2 intermediates: just choose the lowest one.To overcome these limitations and offer more flexibility, users have the option to input a kinetic profile named "kinetic_profile" in either CSV or XLSX format, replacing the conventional energy profile. However, this choice comes with the trade-off of disabling the ability to screen over a range of temperatures or use different temperature settings.Citation↑If you use navicat_mikimo in your work, please cite our work and the forthcoming publication.