Literature DB >> 23676024

Growing string method with interpolation and optimization in internal coordinates: method and examples.

Paul M Zimmerman1.   

Abstract

The growing string method (GSM) has proven especially useful for locating chemical reaction paths at low computational cost. While many string methods use Cartesian coordinates, these methods can be substantially improved by changes in the coordinate system used for interpolation and optimization steps. The quality of the interpolation scheme is especially important because it determines how close the initial path is to the optimized reaction path, and this strongly affects the rate of convergence. In this article, a detailed description of the generation of internal coordinates (ICs) suitable for use in GSM as reactive tangents and in string optimization is given. Convergence of reaction paths is smooth because the IC tangent and orthogonal directions are better representations of chemical bonding compared to Cartesian coordinates. This is not only important quantitatively for reducing computational cost but also allows reaction paths to be described with smoothly varying chemically relevant coordinates. Benchmark computations with challenging reactions are compared to previous versions of GSM and show significant speedups. Finally, a climbing image scheme is included to improve the quality of the transition state approximation, ensuring high reliability of the method.

Year:  2013        PMID: 23676024     DOI: 10.1063/1.4804162

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  22 in total

1.  Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities.

Authors:  Konstantinos D Vogiatzis; Mikhail V Polynski; Justin K Kirkland; Jacob Townsend; Ali Hashemi; Chong Liu; Evgeny A Pidko
Journal:  Chem Rev       Date:  2018-10-30       Impact factor: 60.622

2.  Mechanistic Investigations of the Iron(III)-Catalyzed Carbonyl-Olefin Metathesis Reaction.

Authors:  Jacob R Ludwig; Susan Phan; Christopher C McAtee; Paul M Zimmerman; James J Devery; Corinna S Schindler
Journal:  J Am Chem Soc       Date:  2017-07-28       Impact factor: 15.419

3.  Nickel-Catalyzed Three-Component Cycloadditions of Enoates, Alkynes, and Aldehydes.

Authors:  Aireal D Jenkins; Michael T Robo; Paul M Zimmerman; John Montgomery
Journal:  J Org Chem       Date:  2020-02-14       Impact factor: 4.354

4.  Regiodivergent Glycosylations of 6-Deoxy-erythronolide B and Oleandomycin-Derived Macrolactones Enabled by Chiral Acid Catalysis.

Authors:  Jia-Hui Tay; Alonso J Argüelles; Matthew D DeMars; Paul M Zimmerman; David H Sherman; Pavel Nagorny
Journal:  J Am Chem Soc       Date:  2017-06-19       Impact factor: 15.419

5.  Discovery of conical intersection mediated photochemistry with growing string methods.

Authors:  Cody Aldaz; Joshua A Kammeraad; Paul M Zimmerman
Journal:  Phys Chem Chem Phys       Date:  2018-11-07       Impact factor: 3.676

6.  Quantum Chemical Investigation of Dimerization in the Schlenk Equilibrium of Thiophene Grignard Reagents.

Authors:  Ethan R Curtis; Matthew D Hannigan; Andrew K Vitek; Paul M Zimmerman
Journal:  J Phys Chem A       Date:  2020-02-18       Impact factor: 2.781

7.  Experimental and Computational Studies on Regiodivergent Chiral Phosphoric Acid Catalyzed Cycloisomerization of Mupirocin Methyl Ester.

Authors:  Sibin Wang; Alonso J Arguelles; Jia-Hui Tay; Miyuki Hotta; Paul M Zimmerman; Pavel Nagorny
Journal:  Chemistry       Date:  2020-03-18       Impact factor: 5.236

8.  Combined Theoretical and Experimental Investigation of Lewis Acid-Carbonyl Interactions for Metathesis.

Authors:  Tanmay Malakar; Carly S Hanson; James J Devery; Paul M Zimmerman
Journal:  ACS Catal       Date:  2021-03-25       Impact factor: 13.084

9.  Towards a converged strategy for including microsolvation in reaction mechanism calculations.

Authors:  Rebecca Sure; Moad El Mahdali; Alex Plajer; Peter Deglmann
Journal:  J Comput Aided Mol Des       Date:  2021-01-09       Impact factor: 3.686

10.  Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems.

Authors:  John A Keith; Valentin Vassilev-Galindo; Bingqing Cheng; Stefan Chmiela; Michael Gastegger; Klaus-Robert Müller; Alexandre Tkatchenko
Journal:  Chem Rev       Date:  2021-07-07       Impact factor: 60.622

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