Solvent Coordination: Example Case Study (LiTMP/THF)

This case study demonstrates how to use SPECI for exploring the speciation and coordination of lithium tetramethylpiperidide (LiTMP) with tetrahydrofuran (THF) solvent. The files in CASE1_LiTMP-THF showcase the input setup, structure enumeration, and energy output typical for solvent coordination chemistry problems.

Directory Overview

The CASE1_LiTMP-THF example includes:

  • components-data.csv — Describes all system fragments, including lithium, TMP ligand, and THF as a coordinating solvent.

  • ct/ — Contains ChemDraw .ct structure files for each fragment.

  • PM7Gibbs_Energies.csv — Output file summarizing PM7 Gibbs energies for all enumerated species.

  • logfile.rtf — Execution log for the run.

  • Additional folders (e.g., xyz/, com/) for 3D structure files and quantum chemistry input files if generated.

Input Preparation

1. Edit the `components-data.csv` file:

This CSV specifies the building blocks for SPECI. For LiTMP/THF, it might look like:

components,charge,connectivity allowed,donor atom,type
TMP,-1,"0, 1, 2",N,ligand
Li,1,"0, 1, 2, 3, 4",Li,metal
DonorTHFO1,0,"0, 1",O,ligand
DonorTHFO1,0,"0, 1",O,ligand

  • TMP is the tetramethylpiperidide anion.

  • Li is the metal center.

  • DonorTHFO1 represents THF molecules acting as monodentate donor ligands.

  • The number and identity of fragments control the degree of coordination and aggregation SPECI will explore.

2. Place ChemDraw `.ct` files Ensure that for each component in the CSV, a matching .ct file exists in the ct/ directory (e.g., TMP.ct, Li.ct, THF.ct).

Running the Workflow

3. Run the SPECI workflow: - Launch the Jupyter notebook or run your Python workflow script. - Adjust any relevant advanced settings (see documentation for parameters such as charge_specified, monomers, or num_cores).

4. Structure Generation: - SPECI will enumerate all unique species formed by different possible combinations and connectivities of Li, TMP, and THF. - 3D coordinates (if generated) will be saved as .xyz files in the xyz/ directory. - Quantum chemical input files (e.g., for PM7, UFF, or DFT) may be generated in the com/ directory.

Analyzing Output

5. Reviewing Energies: - After the calculation, the main result is the PM7Gibbs_Energies.csv file, which contains Gibbs free energies for each enumerated structure.

Example excerpt:

13_index,13_energy,29_index,29_energy,...
THF,0.002637,105.0,0.156997,...

  • Each pair of columns (_index, _energy) refers to a particular structure and its calculated energy.

  • Use these energies to identify the most stable species and to compare relative stability of different coordination motifs.

6. Interpreting Results: - Lower energy structures are more likely to dominate in solution. - Differences in THF coordination number, TMP aggregation state, or Li–ligand connectivity will be reflected in the list of enumerated species and their energies.

Tips & Best Practices

  • Fragment definition: The level of detail (e.g., how you split THF or TMP into donors/fragments) affects the range of structures generated.

  • Solvent effects: THF can be included as an explicit ligand or as part of the environment, depending on your modeling goal.

  • Post-processing: The energies from PM7 or DFT can be used for further thermodynamic or kinetic modeling (see the MKM folder for microkinetic modeling examples, if provided).

References & Further Reading

  • See [General Input Files](general_input_files.html) and [General Output Files](general_ouput_files.html) for more information about input and output formats.

  • For advanced use, consult the [README](https://github.com/Manting-Mu/OLIGO) and example Jupyter notebooks.