CCL: bond order calculation method

Dear colleagues,

One of my graduate students is in the process of preparing a YouTube video on the topic of computing bond orders using the method introduced in the following paper:

T. A. Manz, "Introducing DDEC6 atomic population analysis: part 3. Comprehensive method to compute bond orders," RSC Advances, 7 (2017) 45552-45581 (open access) DOI: 10.1039/c7ra07400j

The video will be a less technical presentation, emphasizing chemical concepts with less focus on mathematics.

Were any of the concepts presented in the above paper unclear to you? If so, could you please explain which of those concepts you did not understand? If there is a pattern of some aspects being unclear, then I would like to know so that it can be explained in a more understandable way.

If any of you have not taken the time to carefully read that paper, I believe it would be worth your while to do so. Bond order is a foundational chemical concept that has wide-ranging impacts and numerous applications throughout the chemical sciences. The above paper presents the first comprehensive and computationally efficient method to compute accurate bond orders across an extremely wide range of material types.

This method to compute bond orders enabled the first study of quantum-mechanically computed bond orders for a large number of diatomic molecules:

T. Chen and T. A. Manz, "Bond orders of the diatomic molecules," RSC Advances, 9 (2019) 17072-17092 (open access) DOI: 10.1039/c9ra00974d

In this work, bond orders were quantum-mechanically computed for 288 diatomic molecules and ions, which is >10 times the number of diatomics for which bond orders were quantum-mechanically computed in each prior work.

Because diatomic molecules are the smallest molecules containing a chemical bond, they are natural textbook examples for studying bond order. Therefore, I view the accurate bond orders for diatomic molecules as foundational to chemical theory. Even among the diatomic molecules, there are many interesting effects that you may not be familiar with yet. These can often provide insights that are helpful to understand larger materials with more atoms.

In two recent papers, the above bond order method was applied to identify misbonded atoms in the experimentally-derived crystal structures of metal-organic frameworks:

T. Chen and T. A. Manz, "Identifying misbonded atoms in the 2019 CoRE metal–organic framework database," RSC Advances, 10 (2020) 26944-26951 (open access) DOI: 10.1039/d0ra02498h  

T. Chen and T. A. Manz, "A collection of forcefield precursors for metal-organic frameworks," RSC Advances, 9 (2019) 36492-36507 (open access) DOI: 10.1039/c9ra07327b

For example, carbon atoms in organic compounds often have a sum of bond orders (SBOs) of approximately 4, because they have four electrons to share in covalent bonding. Therefore, in the above two studies, carbon atoms having abnormally low or abnormally high SBOs were flagged as misbonded. (A low carbon SBO might be caused by a missing hydrogen atom that was not reported in the crystal structure.) This kind of screening would have been much harder or perhaps infeasible without the above method to compute bond orders.

Another important application of these bond orders is to understand changes that occur during chemical reactions. For example, several studies reported changes in these bond orders during catalytic reactions.

Finally, last year an interesting paper explored correlations between these bond orders and crystal orbital Hamilton populations (a bond energy projection method):

R.Y. Rohling, I.C. Tranca, E.J.M. Henen, and E.A. Pidko, "Correlations between density-based bond orders and orbital-based bond energies for chemical bonding analysis," J. Phys. Chem. C, 123 (2019) 2843-2854 DOI: 10.1021/acs.jpcc.8b08934

Within the same material class, the bond order between two specific chemical elements was shown to be proportional to the COHP. The bond order is easier to interpret than the COHP.

An encouraging sign is this bond order method is starting to gain some traction in VASP and CP2K calculations (using the Chargemol code for post-processing), which going back >3 years bond order calculations using those codes were nearly unheard of.

I believe the impact could be even much larger, which is why I'm reaching out to try to highlight some of the use cases for this method as well as to give you an opportunity to explain to me what aspects of the method you are having trouble understanding.


Tom Manz