Evidence map›Paper›PMID 39356829›Full record

ArticleJournal of chemical theory and computation2024

A Strategy for Modeling Nonstatistical Reactivity Effects: Combining Chemical Activation Estimates with a Vibrational Relaxation Model.

Tomislav Rožić, Matthew S Teynor, Nađa Došlić, David M Leitner, Gemma C Solomon

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Tomislav RožićNano-Science Center and Department of Chemistry, University of Copenhagen, DK-2100 Copenhagen, Denmark.ORCID 0000-0001-7591-1624
Matthew S TeynorNano-Science Center and Department of Chemistry, University of Copenhagen, DK-2100 Copenhagen, Denmark.ORCID 0000-0002-6981-4809
Nađa DošlićDepartment of Physical Chemistry, Ruder Bošković Institute, HR-10000 Zagreb, Croatia.ORCID 0000-0001-6535-9020
David M LeitnerDepartment of Chemistry, University of Nevada, Reno, Nevada 89557, United States.ORCID 0000-0002-3105-818X
Gemma C SolomonNano-Science Center and Department of Chemistry, University of Copenhagen, DK-2100 Copenhagen, Denmark.ORCID 0000-0002-2018-1529

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The kinetics of many chemical reactions can be readily explained with a statistical approach, for example, using a form of transition state theory and comparing calculated Gibbs energies along the reaction coordinate(s). However, there are cases where this approach fails, notably when the vibrational relaxation of the molecule to its statistical equilibrium occurs on the same time scale as the reaction dynamics, whether it is caused by slow relaxation, a fast reaction, or both. These nonstatistical phenomena are then often explored computationally using (quasi)classical ab initio molecular dynamics by calculating a large number of trajectories while being prone to issues such as zero-point energy leakage. On the other side of the field, we see resource-intensive quantum dynamics simulations, which significantly limit the size of explorable systems. We find that using a Fermi's golden rule type of model for vibrational relaxation, based on anharmonic coupling constants, we can extract the same qualitative information while giving insights into how to enhance (or destroy) the bottlenecks causing the phenomena. We present this model as a middle ground for exploring complex nonstatistical behavior, capable of treating medium-sized organic molecules or biologically relevant fragments. We also cover the challenges involved, in particular quantifying the excess energy in terms of vibrational modes. Relying on readily available electronic structure methods and providing results in a simple master equation form, this model shows promise as a screening tool for opportunities in mode-selective chemistry without external control.

Identifiers

PMID39356829
PMCPMC11500308

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.