More Like this

1. High-yield gram-scale organic synthesis using accelerated microdroplet/thin film reactions with solvent recycling

   https://doi.org/10.1039/C9SC06265C  

   Nie, Honggang; Wei, Zhenwei; Qiu, Lingqi; Chen, Xingshuo; Holden, Dylan T.; Cooks, R. Graham (March 2020, Chemical Science)

   A closed system has been designed to perform microdroplet/thin film reactions with solvent recycling capabilities for gram-scale chemical synthesis. Claisen–Schmidt, Schiff base, Katritzky and Suzuki coupling reactions show acceleration factors relative to bulk of 15 to 7700 times in this droplet spray system. These values are much larger than those reported previously for the same reactions in microdroplet/thin film reaction systems. The solvent recycling mode of the new system significantly improves the reaction yield, especially for reactions with smaller reaction acceleration factors. The microdroplet/thin film reaction yield improved on recycling from 33% to 86% and from 32% to 72% for the Katritzky and Suzuki coupling reactions, respectively. The Claisen–Schmidt reaction was chosen to test the capability of this system in gram scale syntheses and rates of 3.18 g per h and an isolated yield of 87% were achieved. 

   more » « less
2. Highly diastereo- and branched-selective rearrangement of substituted N -alloc- N -allyl ynamides

   https://doi.org/10.1039/d2cc03399b  

   Jackson, Oliver D.; Stankevich, Ksenia S.; Cook, Matthew J. (October 2022, Chemical Communications)

   An auto-tandem catalytic, branched-selective rearrangement of substituted N-alloc-N-allyl ynamides was developed. This reaction provides ready access to complex quaternary nitrile products with vinylogous stereocentres in excellent diastereoselectivity, including contiguous all-carbon quaternary centres. The stereochemical outcome is determined via a Pd(0) catalysed dipolar ketenimine aza-Claisen rearrangement and computational studies exemplify the key role ligand geometry plays. 

   more » « less
3. The aromatic Claisen rearrangement of a 1,2-azaborine

   https://doi.org/10.1039/d2ob02186b  

   Robichaud, Hannah M.; Ishibashi, Jacob S.; Ozaki, Tomoya; Lamine, Walid; Miqueu, Karinne; Liu, Shih-Yuan (May 2023, Organic & Biomolecular Chemistry)

   The first aromatic Claisen rearrangement of a 1,2-azaborine is described along with a quantitative kinetic comparison of the reaction of the azaborine with its direct all-carbon analogue. The azaborine A rearranged in a clean, regioselective fashion and reacted faster than the all-carbon substrate B at all temperatures from 140–180 °C. Activation free energies were extracted from observed first-order rate constants (A: Δ G ‡298K = 32.7 kcal mol −1 ; B: Δ G ‡298K = 34.8 kcal mol −1 ) corresponding to a twenty fold faster rate for A at observed reaction temperatures. DFT calculations show that the rearrangement proceeds via a concerted six-membered transition state and that the electronic structure of the BN and CC rings is mostly responsible for the observed regioselectivity and relative reactivity. 

   more » « less
4. Tris-(2-pyridylmethyl)amine-ligated Cu( ii ) 1,3-diketonate complexes: anaerobic retro-Claisen and dehalogenation reactivity of 2-chloro-1,3-diketonate derivatives

   https://doi.org/10.1039/d0dt04074f  

   Elsberg, Josiah G.; Anderson, Stephen N.; Tierney, David L.; Reinheimer, Eric W.; Berreau, Lisa M. (February 2021, Dalton Transactions)

   null (Ed.)

   We report synthetic, structural and reactivity investigations of tris-(2-pyridylmethyl)amine (TPA)-ligated Cu( ii ) 1,3-diketonate complexes. These complexes exhibit anaerobic retro-Claisen type C–C bond cleavage reactivity which exceeds that found in analogs supported by chelate ligands with fewer and/or weaker pyridyl interactions. 

   more » « less
5. Training machine learning potentials for reactive systems: A Colab tutorial on basic models

   https://doi.org/10.1002/jcc.27269  

   Pan, Xiaoliang; Snyder, Ryan; Wang, Jia‐Ning; Lander, Chance; Wickizer, Carly; Van, Richard; Chesney, Andrew; Xue, Yuanfei; Mao, Yuezhi; Mei, Ye; et al (April 2024, Journal of Computational Chemistry)

   Abstract In the last several years, there has been a surge in the development of machine learning potential (MLP) models for describing molecular systems. We are interested in a particular area of this field — the training of system‐specific MLPs for reactive systems — with the goal of using these MLPs to accelerate free energy simulations of chemical and enzyme reactions. To help new members in our labs become familiar with the basic techniques, we have put together a self‐guided Colab tutorial (https://cc-ats.github.io/mlp_tutorial/), which we expect to be also useful to other young researchers in the community. Our tutorial begins with the introduction of simple feedforward neural network (FNN) and kernel‐based (using Gaussian process regression, GPR) models by fitting the two‐dimensional Müller‐Brown potential. Subsequently, two simple descriptors are presented for extracting features of molecular systems: symmetry functions (including the ANI variant) and embedding neural networks (such as DeepPot‐SE). Lastly, these features will be fed into FNN and GPR models to reproduce the energies and forces for the molecular configurations in a Claisen rearrangement reaction. 

   more » « less