The Bürgi–Dunitz angle revisited.

I came across the blog post by Prof. Rzepa on the Bürgi–Dunitz angle the other day. This is a topic close to my heart. Embarrassingly, I did not know this concept until the mid-way of my PhD study at ETH, where I actually had regular interactions with Prof. Dunitz. The discovery of the Bürgi–Dunitz angle marked one of the key moments in crystallography, organic and supramolecular chemistry, and molecular orbital analysis. I was very impressed by the beauty and the neat idea behind this study, and have since used it as an example to show students the vast information one can get from structural analysis. It was truly insightful that Bürgi and Dunitz were able to distill the preferred reaction trajectory starting from simply 6 (!) crystal structures.

Nearly 50 years later, now that we have more than 1 million structures in the CCDC database, we should be better equipped to perform the structural analysis to re-validate the theory behind the Bürgi–Dunitz angle. However, if you try to look at the angle of any nucleophilic atom (N, O, S, etc.) approaching carbonyl functionalities, the most commonly found angles are actually about 90º but not near 105º, as clearly demonstrated by Prof. Rzepa in the blog post. So, were Bürgi and Dunitz wrong?

After a close examination of the structure hits, I found that the primary source of the discrepancy comes from the overwhelming number of structures featuring antiparallel C=O interactions. In those cases, the O of one moiety sits on the C of the other, resulting in O…C=O angle at ~90º. This is quite interesting; starting from the analysis of nucleophilic addition to a carbonyl group, we ended up with one of the most prevalent non-covalent interactions in proteins.

I’ve added my comment below Prof. Rzepa’s post. Part of the reason that I want to write about it again here is to point out that, really, in the age of machine learning, we can easily obtain a huge amount of data. Yet, it is extremely to keep an eye on the actual information in those data. After all, as ML people often say: your model will be only as good (or as bad) as the data you have.

Goodbye Northwestern, it has been a wonderful time.


After a long period of job searching, I am delighted to take the post at Cardiff University starting from January 2019.  I am deeply indebted to all my mentors, colleagues, friends, and family for their help and support during this process.  Working on photo energy researches during the past 6 and a half years in Northwestern has been a wonderful experience.  It is a true privilege to collaborate the brightest minds (you know I am talking about you!) on the daily basis and be able to access to the cutting-edge technologies.  My views to science and its interplay with education and society got to grow and mature, and they are the best gift that I will bring with across the Atlantic Ocean and pass them onto my future coworkers.

Judging at Intel ISEF 2017


“Science’s rightful place is in service of society” (D. Sarewitz, 2013) is always a big part of my belief.  This summer, I was very fortunate to participate as a Chemistry Grand awards judge in the International Science and Engineering Fair (ISEF), the biggest science fair in the world.

Although science fair was a huge thing in my high school, I wasn’t doing so well as many of my high school classmates, and ISEF 2017 is the first time for me to see such a high-level competition.  I was very impressed by one high schooler’s perseverance with identifying an undocumented ferric sulfate compound from the reaction of sulfuric acid and gold ore, which he obtained from hiking; by the applicability of the algorithm that another student developed to filter and assign signals in high-dimensional protein NMR spectroscopy to accelerate drug discovery (and by his smartness, too); and by the usefulness of silk fibers as moisture-activated torsional actuators discovered by the other student, and by many other projects.

The judges caucus is another special experience.  We are composed of industrial scientists, university professors, researchers, postdocs, and PhD students.  Some had participated more science fairs than the others; we discussed all(!) the projects and tried to persuade(!) our colleagues why one project is better/worse.  The voting/discussion cycle repeated again and again until all the prizes were decided.  (Awarded students, you should really thank the eloquent and passionate judges who lobby for your project!)

Judging ISEF was overall a great experience, especially seeing/feeling the pure enthusiasm for the science of all the students, and I am very glad I could contribute and help.  Thanks to my grad school friend Grace for the invitation!

Ethylhexyl in real life.

As a “purist”, I never really like to see any 2-ethylhexyl substituent in my molecules, as it usually has an undefined stereogenic center at the 2 position.  Materials incorporating such a functionality thus are random mixtures(!) of (R)- and (S)- stereoisomers, not to mention molecules possessing multiple 2-ethylhexyl substituents.

Materials scientists, especially aromatic polymer chemists, use 2-ethylhexyl to enhance the solubility, as such a bulky subsituent disrupts pi-stacking/aggregation.  Outside of the research labs, as it turns out, molecules with 2-ethylhexyl are actually ubiquitous in our daily life; I wonder if those 2-ethylhexyls were implemented also for modulating the aggregation properties.

Just to name a few, 2-ethylhexyl nitrate (2-EHN) is a cetane improver added to diesel fuels, bis(2-ethylhexyl) phthalate, which is produced approx. 3 billion kg/year, is a plasticizer for PVC, and octocrylene and octyl methoxylcinnamate are ingredients in sunscreen products that absorb UVB and UVA.  Without a doubt, I should have given ethylhexyl much more credits!

We know so little, so little indeed, about solubility.

PDI is a notoriously insoluble dye, and it is well known that linear aliphatic N-substituents won’t make it much more soluble.  However, the Grozema group published a mind-blowing work back in 2014 (DOI: 10.1039/c4cc00330f) and totally turn down this common believe (along with other important findings, of course).  See the picture!  I knew this work for quite a while (thanks Pat for showing me this paper), and still couldn’t make sense out of it.  This just shows how little we know about intermolecular interaction; there is more to learn!


Alkyl groups modulate π-stacking interactions: size is not the only thing that matters.

The group of Ken Shimizu at the University of South Carolina reported a very interesting finding: the strength of repulsive and/or attractive interactions between π-stacked aromatics can be non-trivially influenced by the alkyl substituents.  Should the interacting area (surface contact area) between aromatics be large enough, even those bearing tBu substituents can display stronger attraction than those bearing Me one!   

Does methanol dissolve silica?  Maybe not, suggested by Biotage.

This is an age-old question for people using MeOH in their flash chromatography.  I guess the answer/result might have something to do with the pore size of the frit of your column.  Anyhow, have a look at an interesting analysis conducted in Biotage.