Wednesday, January 30, 2019

Discovery of conical intersection mediated photochemistry with growing string methods

Cody Aldaz, Joshua A. Kammeraad and Paul M. Zimmerman (2018)
Highlighted by Jan Jensen

Photochemistry is becoming an increasing important synthetic tool but is significantly harder to study computationally than thermal chemistry. Zimmerman and co-workers have developed a new tool that promises to help change that.

The method uses a growing string method (usually used to find TSs) to locate minimum energy conical intersections (MECI), the lowest energy point where the excited state PES intersects the ground state PES. Ground state geometry optimisation starting from the MECI structures are then used to identify the products of the photochemical reaction. Crucially, the method doesn't just find the MECI closest to the reactant structure, but considers several search directions.

One has to define a driving coordinate but this can be automatically determined by generating several possible products, e.g. using Zimmerman's ZStruct method. As far as I know the molecule is not in thermal equilibrium on the excited state PES, so I am not sure one can use the relative energies of the MECIs to predict a product distribution.  Still, an important step forward.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Saturday, January 26, 2019

Exceptionally Long C−C Single Bonds in Diamino-o-carborane as Induced by Negative Hyperconjugation

Li, J.; Pang, R.; Li, Z.; Lai, G.; Xiao, X.-Q.; Müller, T., Angew. Chem. Int. Ed. 2019, 58, 1397-1401
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Chemists are constantly checking the limits of theories, and the limits of bonding is one that has been subject to many tests of late. I have posted on two recent papers (herehere) that probe just how long a C-C bond can be, and now Li, Müller, and co-workers report a structure that pushes that limit even further out.1

They prepared and obtained the x-ray structure of five derivatives of o-carborane, namely compounds 12a3a3b and 4. In all of these, the C-C bond in the carborane is stretched well beyond that of a typical C-C bond (see Table 1). The longest case is in 3b where the C-C bond length is a whopping 1.931 Å (see Figure 1), which obliterates the previous record holder at 1.798 Å.2 B3PW91-D3/cc-pVTZ computations corroborate these structures and the long C-C bond.

Scheme 1: Carboranes with long C-C bonds (highlighted in blue)
Table 1. C-C bond distance (Å)
cmpdr(C-C) exptr(C-C) DFT
Figure 1. B3PW91-D3/cc-pVTZ optimized structure of 3b.

Topological electron density analysis locates a bond path between the two carbons in all five structures. The Wiberg bond index is small, with a value of only 0.34 in 3b. Natural bond orbital (NBO) analysis identifies a negative hyperconjugation interaction between the nitrogen lone pair and the σ*C-C orbital. This rationalizes both the very long C-C bond and the very short C-N bonds, and the trends associated with the variation between 1° amine, 2° amine and imine.


1. Li, J.; Pang, R.; Li, Z.; Lai, G.; Xiao, X.-Q.; Müller, T., “Exceptionally Long C−C Single Bonds in Diamino-o-carborane as Induced by Negative Hyperconjugation.” Angew. Chem. Int. Ed. 201958, 1397-1401, DOI: 10.1002/anie.201812555.
2. Ishigaki, Y.; Shimajiri, T.; Takeda, T.; Katoono, R.; Suzuki, T., “Longest C–C Single Bond among Neutral Hydrocarbons with a Bond Length beyond 1.8 Å.” Chem 20184, 795-806, DOI: 10.1016/j.chempr.2018.01.011.


3b: InChI=1S/C22H28B10N2/c1-13-7-15(3)19(16(4)8-13)11-33-21-22(34-12-20-17(5)9-14(2)10-18(20)6)25(21)23-27(21)24-30(23,25)28(22,25)29(22)26(21,22,27)31(24,27,29)32(24,28,29)30/h7-10,33-34H,11-12H2,1-6H3

This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.

Monday, January 21, 2019

Understanding Combustion of H/O Gases inside Nanobubbles Generated by Water Electrolysis Using Reactive Molecular Dynamic Simulations.

S. Jain and L. Qiao, The Journal of Physical Chemistry A,122, 5261 2018
Highlighted by Tina Mihm, Colleen Lasar, Matthew Emerson

Abstract Image

It was found (by accident) that nanobubbles containing both H2 and O2 gas would form during the electrolysis of water and spontaneously combust. This is surprising because at smaller scales, the surface-to-volume ratio is large enough that heat loss becomes a real factor when trying to create and sustain a combustion reaction. Jain et al. believe this nanobubble combustion reaction is due to the low temperature and high pressure zone that takes place in the bubble. The initial thought with this discovery was that the combustion reaction inside said nanobubbles could be used to produce energy. However, most of the temperature from the reaction was found to be lost to the walls of the bubbles indicating low energy yields.

The reaction mechanism is as follows: 2 H2(g) + O2(g)  →  2 H2O(g). Both experimental and older computational methods have looked into the temperature changes and kinetics of this reaction, however, the mechanism has not been looked into in detail. Jain et al. uses molecular dynamic simulations to explore the mechanism of this phenomenon. They explored the characteristics of H2/O2 reactions at high pressure and low temperature as a function of Hydrogen radical concentration and found that H2O2 was the dominant species produced instead of the expected H2O.

In the simulations, they used a force field designed specifically to investigate the reaction kinetics of H2/O2 system at high pressures and low temperatures. Specifically, the first-principles derived reactive force field ReaxFF was employed, as implemented in the open-source molecular dynamics simulation code LAMMPS.  After thermalizing the system to 300 K with a Nose-Hoover thermostat, production runs  of 100 fs were carried out, using a 0.1 fs time step. The model was then validated using existing more generalized force fields that were not designed for the H2/O2 system. They also found that increasing the concentration of H radical or the system pressure increased reactivity. While this result was initially thought to be able to increase energy output, it was found that most of the energy from the reaction was found to be lost to the walls of the combustion chamber. If this happened in an automobile, the engine would become so hot that the hood would melt off.

In conclusion, it was found that hydrogen and oxygen gas in nano bubbles formed during electrolysis of water and would spontaneously combust. The mechanism for this reaction was investigated using reactions at high pressure and low temperature as a function of Hydrogen radical concentration and found that H2O2 was the dominant species produced instead of the expected H2O. The increase in reactivity due to increased pressure and H radical concentration during simulation was thought to increase energy output, and, therefore, create a source of clean energy. However, further computational simulations found that most of the heat was lost to the walls of the bubbles, greatly decreasing energy output, making a lousy nano-engine.

Thursday, January 17, 2019

SERS, XPS and DFT investigation on palladium surfaces coated with 2,2′-bipyridine monolayers

M. Muniz-Miranda, F. Miranda-Muniz, S. Caporali, N. Calisi, P. Alfonso, Applied Surface Science, 457, 98-103 2018
Highlighted by Michaella Raglione, Sajeewani Kumarage, and Glorianne Dorce

Palladium (II) chloride complexes containing diimine ligands like what is shown in Figure 1 have been widely used as a reaction catalyst. One application of a palladium catalyst is the Heck reaction, which utilizes a Palladium (II) complex intermediate to activate the reaction of an unsaturated halide with an alkene in the presence of a base. Often, palladium is used in a suspension, but it lacks the colloidal stability to maintain a homogeneous mixture, which can lower its efficiency. Furthermore, heterogenous catalysis provides high yield, and facilitates the reusability of catalysts compared to homogeneous catalysis. Thus, Muniz-Miranda et al. recently investigated the use of Palladium coated with 2,2’-bipyridine monolayers for heterogenous catalysis.

Figure 1. Crystal structure of byp-PdCl2 from Table S1 supplementary material.

Their experiments centered around Palladium plate which was wetted with 2,2’-bipyridine (bpy). In order to test their work, Muniz-Miranda et al. utilized the surface plasmon effect of Ag nanoparticles (nps) to enhance their surface enhance Raman signal (SERS). The Ag nps were obtained through laser ablation in the bpy solution without free chloride anions. To determine the resulting complex, DFT calculations were performed using GAUSSIAN 09 software with a B3LYP/6-311++G(d,p) for non-metal atoms, and Lanl2DZ for palladium basis sets. To ensure their experimental methods would work, byp-PdCl2 was collected and the Raman spectra was compared to the calculated spectra.

Muniz-Miranda et al.  have made bpy-PdX, and by comparing the resulting calculated Raman active modes to the experimental bpy-PdR (R=O,O2,(OH)2)  revealed that they created bpy-Pd(OH)2.

Due to similar structural and spectroscopic characteristics of the bpy-Pd(OH)2 and bpy-PdCl2, the catalysts are expected to function similarly. The similarities in these catalysts opens the possibility of utilization of the much simpler heterogenous nucleation of the bpy-Pd(OH)2 complex for reaction mechanisms. This suggests that combined benefits of both heterogenous and homogenous nucleation can be achieved: improved yield and reusability as well as selectivity control.

Monday, December 31, 2018

Computationally Augmented Retrosynthesis: Total Synthesis of Paspaline A and Emindole PB

Daria E. Kim, Joshua E. Zweig and Timothy R. Newhouse (2018)
Highlighted by Jan Jensen

Figure 2 from the paper reproduced under the CC-BY-NC-ND licence

This paper presents a rare example of using quantum chemical TS calculations to guide, rather than post-rationalise, organic synthesis. The authors wanted to design a retrosynthetic path that could be used to make two related natural products, paspaline A and emindole PB, that require either a ring closure (paspaline A) or a methyl shift (emindole PB). Three different routes were possible that lead to different functionalities that were relatively distant from the ring closure/methyl shift, which made it hard to predict the best route by chemical intuition.

Instead the authors used mPW1PW91/6-31+G(d,p)//B3LYP/6-31G(d) to find the TSs for both reactions for each of the three routes to predict the best route, which turns out to be "C". Route C did indeed work great in practice, while route A (predicted to be worst route) didn't give the desired results.

My guess is that the key here is that the synthetic question was reduced to a question of relative barrier heights of closely related reactions, i.e. ΔΔΔG = ΔΔG(4→5) - ΔΔG(4→6), which leads to maximum error cancellation. I hope this paper will lead to more use of QM to guide synthetic decisions and more work on making TS calculations even more accessible to synthetic chemists

This work is licensed under a Creative Commons Attribution 4.0 International License.

Friday, December 7, 2018

Electrocyclic reactions of cethrene derivatives

Šolomek, T.; Ravat, P.; Mou, Z.; Kertesz, M.; Juríček, M., "Cethrene: The Chameleon of Woodward–Hoffmann Rules." J. Org. Chem. 2018, 83, 4769-4774
Ravat, P.; Šolomek, T.; Häussinger, D.; Blacque, O.; Juríček, M., "Dimethylcethrene: A Chiroptical Diradicaloid Photoswitch." J. Am. Chem. Soc. 2018, 140, 10839-10847.
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Pericyclic reactions remain a fruitful area of research despite the seminal publication of the Woodward-Hoffmann rules decades ago. Here are two related papers of pericyclic reactions that violate the Woodward-Hoffmann rules.

First, Solomek, Ravat, Mou, Kertesz, and Jurícek reported on the thermal and photochemical electrocyclization reaction of diphenylcetherene 1a.1 Though they were not able to directly detect the intermediate 2, through careful examination of the photochemical reaction, they were able to infer that the thermal cyclization goes via the formally forbidden conrotatory pathway (see Scheme 1).
Scheme 2.
Kinetic studies estimate the activation barrier is 14.1 kcal mol-1. They performed DFT computations of the parent 1b using a variety of functionals with both restricted and unrestricted wavefunctions. The allowed pathway to 2syn is predicted to be greater than 27 kcal mol-1, while the formally forbidden pathway to 2anti is estimated to have a lower barrier of about 23 kcal mol-1. The two transition states for these different pathways are shown in Figure 1, and the sterics that force a helical structure to 1 help make the forbidden pathway more favorable.


Figure 1. (U)B3LYP/6-31G optimized geometries of the transition states taking 1 into 2.

Nonetheless, all of the DFT computations significantly overestimate the activation barrier. The authors make the case that a low-lying singlet excited state results in an early conical intersection that reduces the symmetry from C2 to C1. In this lower symmetry pathway, all of the states can mix, leading to a lower barrier. However, since DFT is intrinsically a single Slater configuration, the mixing of the other states is not accounted for, leading to the overestimated barrier height.

In a follow up study, this group examined the thermal and photo cyclization of 13,14-dimethylcethrene 4.2 The added methyl groups make the centhrene backbone more helical, and this precludes the formal allowed disrotatory process. The methyl groups also prohibit the oxidation that occurs with 1, driven by aromatization, allowing for the isolation of the direct product of the cyclization 5. This antistereochemistry is confirmed by NMR and x-ray crystallography. The interconversion between 4 and 5 can be controlled by heat and light, making the system an interesting photoswitch.
Also of interest is the singlet-triplet gap of 1 and 4. The DFT computed ΔEST is about 10 kcal mol-1 for 4, larger than the computed value of 6 kcal mol-1 for 1b. The EPR of 1b does show a signal while that of 4has no signal. To assess the role of the methyl group, they computed the singlet triplet gaps for 1b and 4at two different geometries: where the distance between the carbons bearing the methyl groups is that in 1b (3.03 Å) and in 4 (3.37 Å). The lengthening of this distance by the methyl substituents is due to increased helical twist in 4 than in 1b. For 1b, the gap increases with twisting, from 7.1 to 8.3 kcal mol-1, while for 4 the gap increases by 1.8 kcal mol-1 with the increased twisting. This change is less than the effect of methyl substitution, which increases the gap by 2.2 kcal mol-1 at the shorter distance and 2.8 kcal mol-1 at the longer distance. Thus, the electronic (orbital) effect of methyl substitution affects the singlet-triplet gap more than the geometric twisting.


1) Šolomek, T.; Ravat, P.; Mou, Z.; Kertesz, M.; Juríček, M., "Cethrene: The Chameleon of Woodward–Hoffmann Rules." J. Org. Chem. 201883, 4769-4774, DOI: 10.1021/acs.joc.8b00656.
2) Ravat, P.; Šolomek, T.; Häussinger, D.; Blacque, O.; Juríček, M., "Dimethylcethrene: A Chiroptical Diradicaloid Photoswitch." J. Am. Chem. Soc. 2018140, 10839-10847, DOI: 10.1021/jacs.8b05465.


1b: InChI=1S/C28H16/c1-5-17-7-3-11-23-25(17)19(9-1)15-21-13-14-22-16-20-10-2-6-18-8-4-12-24(26(18)20)28(22)27(21)23/h1-16H
4: InChI=1S/C30H20/c1-17-9-11-19-5-3-7-21-15-23-13-14-24-16-22-8-4-6-20-12-10-18(2)26(28(20)22)30(24)29(23)25(17)27(19)21/h3-16H,1-2H3
5: nChI=1S/C30H20/c1-29-13-11-17-5-3-7-19-15-21-9-10-22-16-20-8-4-6-18-12-14-30(29,2)28(24(18)20)26(22)25(21)27(29)23(17)19/h3-16H,1-2H3/t29-,30-/m0/s1

This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.

Friday, November 30, 2018

Evolving and nano data enabled machine intelligence for chemical reaction optimization

Daniel Reker, Gonçalo J. L. Bernardes, Tiago Rodrigues (2018)
Highlighted by Jan Jensen

This paper is probably on the edge of what most people would call computational chemistry in the sense that is doesn't deal with structure-based predictions. 

The paper uses a random forest algorithm to optimise reaction conditions. What is especially interesting is the small amount of data needed to train the model compared to other machine learning algorithms. The method starts with only 10 randomly chosen reaction conditions as input and goes on to find an optimum set of conditions in only 20 additional steps. This approach is tested against expert synthetic chemists and found to be just as good or better.

It is possible that this method could be adapted to molecular design (e.g. choosing the best combination of ligands) of properties that are expensive to compute or costly to measure experimentally.