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


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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.

TS(1b→2b-syn)

TS(1b→2b-anti)
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.

References

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.

InChIs

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
InChIKey=GBMHAGKZRAVBDO-UHFFFAOYSA-N
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
InChIKey=MXTVFWTUCPRNIW-UHFFFAOYSA-N
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
InChIKey=SUMMGEBJORQMAI-KYJUHHDHSA-N


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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.

Thursday, November 15, 2018

Carbo‐biphenyls and Carbo‐terphenyls: Oligo(phenylene ethynylene) Ring Carbo‐mers

Chongwei, Z.; Albert, P.; Carine, D.; Brice, K.; Alix, S.; Valérie, M.; Remi, C., Angew. Chem. Int. Ed. 2018, 57, 5640-5644
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Interesting 18 π-electron systems involving cyclooctadecanonenetriyne rings have been synthesized and examined by computations.1 The mono-, di- and tri-C18
ring compounds 12, and 3 were prepared and the x-ray structure of 2 was obtained. The B3PW91/6-31G(d,p) optimized geometries of 1-3 and of the tetra ring 4 are shown in Figure 1.


1

2

3

4
Figure 1. B3PW91/6-31G(d,p) optimized geometries of 1-4.

Since the rings are composed of 18 π-electrons in the π-system perpendicular to the nearly planar ring, the natural question is to wonder if the ring is aromatic. The authors computed NICS(0) and NICS(1) values at the center of the C18 rings. For all four compounds, both the NICS(0) and NICS(1) values are negative, ranging from -12.4 to -14.9 ppm, indicating that the rings are aromatic.


References

1) Chongwei, Z.; Albert, P.; Carine, D.; Brice, K.; Alix, S.; Valérie, M.; Remi, C., "Carbo‐biphenyls and Carbo‐terphenyls: Oligo(phenylene ethynylene) Ring Carbo‐mers." Angew. Chem. Int. Ed. 201857, 5640-5644, DOI: 10.1002/anie.201713411.


InChIs

1: InChI=1S/C58H54/c1-3-5-7-9-11-17-27-49-37-41-55(51-29-19-13-20-30-51)45-47-57(53-33-23-15-24-34-53)43-39-50(28-18-12-10-8-6-4-2)40-44-58(54-35-25-16-26-36-54)48-46-56(42-38-49)52-31-21-14-22-32-52/h13-16,19-26,29-36H,3-12,17-18,27-28H2,1-2H3
InChIKey=KWXYBTWOEJBCQD-UHFFFAOYSA-N
2: InChI=1S/C102H74/c1-3-5-7-9-11-21-39-83-59-67-95(87-41-23-13-24-42-87)75-79-99(91-49-31-17-32-50-91)71-63-85(64-72-100(92-51-33-18-34-52-92)80-76-96(68-60-83)88-43-25-14-26-44-88)57-58-86-65-73-101(93-53-35-19-36-54-93)81-77-97(89-45-27-15-28-46-89)69-61-84(40-22-12-10-8-6-4-2)62-70-98(90-47-29-16-30-48-90)78-82-102(74-66-86)94-55-37-20-38-56-94/h13-20,23-38,41-56H,3-12,21-22,39-40H2,1-2H3
InChIKey=HHRPTZGYBIHFOL-UHFFFAOYSA-N
3: InChI=1S/C146H94/c1-3-5-7-9-11-25-51-117-81-93-135(123-53-27-13-28-54-123)105-109-139(127-61-35-17-36-62-127)97-85-119(86-98-140(128-63-37-18-38-64-128)110-106-136(94-82-117)124-55-29-14-30-56-124)77-79-121-89-101-143(131-69-43-21-44-70-131)113-115-145(133-73-47-23-48-74-133)103-91-122(92-104-146(134-75-49-24-50-76-134)116-114-144(102-90-121)132-71-45-22-46-72-132)80-78-120-87-99-141(129-65-39-19-40-66-129)111-107-137(125-57-31-15-32-58-125)95-83-118(52-26-12-10-8-6-4-2)84-96-138(126-59-33-16-34-60-126)108-112-142(100-88-120)130-67-41-20-42-68-130/h13-24,27-50,53-76H,3-12,25-26,51-52H2,1-2H3
InChIKey=WCBXPLIBHKYESX-UHFFFAOYSA-N
4: InChI=1S/C190H114/c1-3-5-7-9-11-29-63-151-103-119-175(159-65-31-13-32-66-159)135-139-179(163-73-39-17-40-74-163)123-107-153(108-124-180(164-75-41-18-42-76-164)140-136-176(120-104-151)160-67-33-14-34-68-160)97-99-155-111-127-183(167-81-47-21-48-82-167)143-147-187(171-89-55-25-56-90-171)131-115-157(116-132-188(172-91-57-26-58-92-172)148-144-184(128-112-155)168-83-49-22-50-84-168)101-102-158-117-133-189(173-93-59-27-60-94-173)149-145-185(169-85-51-23-52-86-169)129-113-156(114-130-186(170-87-53-24-54-88-170)146-150-190(134-118-158)174-95-61-28-62-96-174)100-98-154-109-125-181(165-77-43-19-44-78-165)141-137-177(161-69-35-15-36-70-161)121-105-152(64-30-12-10-8-6-4-2)106-122-178(162-71-37-16-38-72-162)138-142-182(126-110-154)166-79-45-20-46-80-166/h13-28,31-62,65-96H,3-12,29-30,63-64H2,1-2H3
InChIKey=LLVPDVPZEIYJGN-UHFFFAOYSA-N




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

Tuesday, October 30, 2018

Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

Jiaxuan You, Bowen Liu, Rex Ying, Vijay Pande, Jure Leskovec (2018)
Highlighted by Jan Jensen



Ever since Alán Aspuru-Guzik and co-workers published their seminal paper there has been a flurry of activity on generative models, which is not surprising given that they offer a radically new alternative to screening chemical libraries as a way to discover new molecules.

Almost all the new efforts on generative models have been based on adapting machine learning techniques used for natural language processing to text-based representation of molecules, i.e. SMILES strings. While very promising the SMILES syntax has some quirks which makes them hard to predicts efficiently. One solution is to change the syntax to be more ML-friendly, but this has yet to be tested for generative models.

Another option is to work with a graph (i.e. atoms and bonds) representation of the molecule and this paper is the first I've seen that does that for an ML-based generative model. In this case the ML method is reinforcement learning where the addition of each atom is treated as an action which can be trained to towards a particular outcome, here molecules with certain properties. This approach seems to outperform the SMILES based approaches for the prediction of some properties.

The code is available here.


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

Friday, October 12, 2018

Teaching an old carbocation new tricks: Intermolecular C–H insertion reactions of vinyl cations

Popov, S.; Shao, B.; Bagdasarian, A. L.; Benton, T. R.; Zou, L.; Yang, Z.; Houk, K. N.; Nelson, H. M., Science 2018, 361, 381
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

A recent paper by Papov, Shao, Bagdasarian, Benton, Zou, Yang, Houk, and Nelson uncovers a vinyl cation insertion reaction that once again involves dynamic effects.1

They find that vinyl triflates and cyclic vinyl triflates will react with [Ph3C]+[HCB11Cl11] and triethylsilane to generate vinyl cations that can then be trapped through a C-H insertion reaction. For example, cyclohexenyl triflate 1 reacts in a cyclohexane solvent to give the insertion product 2.


The reactions of isomers 3 and 4 give different ratios of the two products 5 and 6. In both cases, the cyclohexyl is trapped predominantly at the site of the triflate substituent. This means that the mechanism cannot involve a cyclohexene intermediate, since then the two ratios should be identical.


They performed molecular dynamic trajectory analysis at the M062X/6-311+G(d,p) level, starting with the two transition states leading from 3 (TS3) and 4 (TS4), the only transition states located for the insertion reaction. The structures of these TSs are shown in Figure 1.


TS3

TS4
Figure 1. M062X/6-311+G(d,p) optimized geometries of TS3 and TS4.

The trajectories end up in two product basins associated with 5 and 6 starting with either TS3 or TS4. Thus, these transition states are ambimodal, and typical of reactions where dynamic effects dominate. For the reaction of 3, the majority of the trajectories starting at TS3 end up as 5, consistent with the experiments. Similarly, for the trajectories that start at TS4, the majority end up as 6, consistent with experiments.

Once again, we see that relatively simple organic reactions do not follow simple reaction mechanisms, that a single transition state leads to two different products and the product distributions are dependent on reaction dynamics. This may not be too surprising for the vinyl cation insertions given the many examples provide by the Tantillo group of cation rearrangements that are controlled by reaction dynamics (see for examples, this post and this post).


References

1. Popov, S.; Shao, B.; Bagdasarian, A. L.; Benton, T. R.; Zou, L.; Yang, Z.; Houk, K. N.; Nelson, H. M., "Teaching an old carbocation new tricks: Intermolecular C–H insertion reactions of vinyl cations." Science2018361, 381-387, DOI: 10.1126/science.aat5440.


InChIs

1: InChI=1S/C7H10F3O3S/c8-7(9,10)14(11,12,13)6-4-2-1-3-5-6/h4H,1-3,5H2,(H,11,12,13)
InChIKey=CMPVYBNXADJVOM-UHFFFAOYSA-N
2: InChI<=1S/C12H22/c1-3-7-11(8-4-1)12-9-5-2-6-10-12/h11-12H,1-10H2
InChIKey=WVIIMZNLDWSIRH-UHFFFAOYSA-N
3: InChI=1S/C9H14F3O3S/c1-8(2)5-3-7(4-6-8)16(13,14,15)9(10,11)12/h3H,4-6H2,1-2H3,(H,13,14,15)
InChIKey=XDWBLRRAHKBZJR-UHFFFAOYSA-N
4: InChI=1S/C9H14F3O3S/c1-8(2)5-3-4-7(6-8)16(13,14,15)9(10,11)12/h4H,3,5-6H2,1-2H3,(H,13,14,15)
InChIKey=YHVCPSRICQJFDT-UHFFFAOYSA-N
5: InChI=1S/C14H26/c1-14(2)10-8-13(9-11-14)12-6-4-3-5-7-12/h12-13H,3-11H2,1-2H3
InChIKey=BZQBWUOXOYWYJC-UHFFFAOYSA-N
6: InChI=1S/C14H26/c1-14(2)10-6-9-13(11-14)12-7-4-3-5-8-12/h12-13H,3-11H2,1-2H3
InChIKey=AENMAOBTECURBO-UHFFFAOYSA-N


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