skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Machine learning analysis of dynamic‐dependent bond formation in trajectories with consecutive transition states
Abstract Dynamic motion often controls selectivity in reactions featuring two consecutive potential‐energy transition states. Here we report density functional theory (DFT)‐based direct dynamics trajectories and machine learning classification analysis for cyclopentadienone dimerization and a N 2 extrusion reaction leading to semibullvalene. These reactions have consecutive transition states, and there is dynamic selectivity that determines which of two possible C‐C bonds is formed after the first transition state. For cyclopentadienone dimerization with a bispericyclic first transition state, machine learning analysis using transition‐state based features provided >90% trajectory classification accuracy, but only using AdaBoost and random forest algorithms. Many other relatively sophisticated machine learning algorithms showed poor accuracy despite the obvious motion responsible for selectivity. Feature importance analysis confirmed that the sigmatropic rearrangement vibrational motion in the bispericyclic transition state provides prediction of which of the second C‐C bonds is dynamically formed. For the reaction leading to semibullvalene, machine learning analysis provides solid accuracy for classifying trajectories and predicting which C‐C bond is formed and which C‐C bond is broken immediately after N 2 ejection. Like the cyclopentadienone dimerization reaction, machine learning feature importance analysis showed that the sigmatropic rearrangement vibrational motion in the N 2 extrusion transition state determines which C‐C bond is formed and which is broken. Surprisingly, machine learning struggles to predict which trajectories undergo a subsequent [3,3] sigmatropic rearrangement process, which isomerizes equivalent forms of semibullvalene.  more » « less
Award ID(s):
1952420
PAR ID:
10455975
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Journal of Physical Organic Chemistry
Volume:
35
Issue:
11
ISSN:
0894-3230
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; (, Physical Chemistry Chemical Physics)
    null (Ed.)
    Quasiclassical trajectory analysis is now a standard tool to analyze non-minimum energy pathway motion of organic reactions. However, due to the large amount of information associated with trajectories, quantitative analysis of the dynamic origin of reaction selectivity is complex. For the electrocyclic ring opening of cyclopropyl radical, more than 4000 trajectories were run showing that allyl radicals are formed through a mixture of disrotatory intrinsic reaction coordinate (IRC) motion as well as conrotatory non-IRC motion. Geometric, vibrational mode, and atomic velocity transition-state features from these trajectories were used for supervised machine learning analysis with classification algorithms. Accuracy >80% with a random forest model enabled quantitative and qualitative assessment of transition-state trajectory features controlling disrotatory IRC versus conrotatory non-IRC motion. This analysis revealed that there are two key vibrational modes where their directional combination provides prediction of IRC versus non-IRC motion. 
    more » « less
  2. ; ; ; ; ; (, Journal of the American Chemical Society)
    Selectivity in organic chemistry is generally presumed to arise from energy differences between competing selectivity-determining transition states. However, in cases where static density functional theory (DFT) fails to reproduce experimental product distributions, dynamic effects can be examined to understand the behavior of more complex reaction systems. Previously, we reported a method for nitrogen deletion of secondary amines which relies on the formation of isodiazene intermediates that subsequently extrude dinitrogen with concomitant C–C bond formation via a caged diradical. Herein, a detailed mechanistic analysis of the nitrogen deletion of 1-aryl-tetrahydroisoquinolines is presented, suggesting that in this system the previously determined diradical mechanism undergoes dynamically controlled partitioning to both the normal 1,5-coupling product and an unexpected spirocyclic dearomatized intermediate, which converges to the expected indane by an unusually facile 1,3-sigmatropic rearrangement. This mechanism is not reproduced by static DFT but is supported by quasi-classical molecular dynamics calculations and unifies several unusual observations in this system, including partial chirality transfer, nonstatistical isotopic scrambling at the ethylene bridge, the isolation of spirocyclic dearomatized species in a related heterocyclic series, and the observation that introduction of an 8-substituent dramatically improves enantiospecificity. 
    more » « less
  3. (, eference Module in Chemistry, Molecular Sciences and Chemical Engineering - Comprehensive Computational Chemistry)
    We introduce two new tools for the analysis of bond forming/breaking processes taking place during catalytic reactions, the Uni!ed Reaction Valley Approach (URVA) and the Local Mode Analysis (LMA), both being based on vibrational spectroscopy. We discuss how URVA and LMA complement currently used computational approaches and provide valuable insights into catalytic processes, supporting current design efforts aiming at more ef!cient and environmentally friendly catalysts. Three examples are presented; Au- catalyzed [3,3]-sigmatropic rearrangement of allyl acetate, Re-catalyzed CO2 cycloaddition to epoxides, and a-ketoamide inhibitors for SARS-CoV-2 main protease. We hope that URVA and LMA will become routinely applied tools in computational catalysis and also enter the classroom. 
    more » « less
  4. ; ; (, Chemical Science)
    We report a diastereoconvergent synthesis of anti -1,2-amino alcohols bearing N-containing quaternary stereocenters using an intermolecular direct C–H amination of homoallylic alcohol derivatives catalyzed by a phosphine selenide. Destruction of the allylic stereocenter during the selenium-catalyzed process allows selective formation of a single diastereomer of the product starting from any diastereomeric mixture of the starting homoallylic alcohol derivatives, eliminating the need for the often-challenging diastereoselective preparation of starting materials. Mechanistic studies show that the diastereoselectivity is controlled by a stereoelectronic effect (inside alkoxy effect) on the transition state of the final [2,3]-sigmatropic rearrangement, leading to the observed anti selectivity. The power of this protocol is further demonstrated on an extension to the synthesis of syn -1,4-amino alcohols from allylic alcohol derivatives, constituting a rare example of 1,4-stereoinduction. 
    more » « less
  5. ; (, The Chemical Record)
    Abstract The amide bond N−C activation represents a powerful strategy in organic synthesis to functionalize the historically inert amide linkage. This personal account highlights recent remarkable advances in transition‐metal‐free activation of amides by N−C bond cleavage, focusing on both (1) mechanistic aspects of ground‐state‐destabilization of the amide bond enabling formation of tetrahedral intermediates directly from amides with unprecedented selectivity, and (2) synthetic utility of the developed transformations. Direct nucleophilic addition to amides enables a myriad of powerful methods for the formation of C−C, C−N, C−O and C−S bonds, providing a straightforward and more synthetically useful alternative to acyl‐metals. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email