Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 423

The DOI matches its Crossref record; 503 of the 503 references it cites were found in a registry or an index.

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

Open access
Vogiatzis, Konstantinos D., Polynski, Mikhail V., Kirkland, Justin K., Townsend, Jacob, Hashemi, Ali, Liu, Chong, Pidko, Evgeny A.·2019·Chemical Reviews

Abstract

Computational chemistry provides a versatile toolbox for studying mechanistic details of catalytic reactions and holds promise to deliver practical strategies to enable the rational in silico catalyst design. The versatile reactivity and nontrivial electronic structure effects, common for systems based on 3d transition metals, introduce additional complexity that may represent a particular challenge to the standard computational strategies. In this review, we discuss the challenges and capabilities of modern electronic structure methods for studying the reaction mechanisms promoted by 3d transition metal molecular catalysts. Particular focus will be placed on the ways of addressing the multiconfigurational problem in electronic structure calculations and the role of expert bias in the practical utilization of the available methods. The development of density functionals designed to address transition metals is also discussed. Special emphasis is placed on the methods that account for solvation effects and the multicomponent nature of practical catalytic systems. This is followed by an overview of recent computational studies addressing the mechanistic complexity of catalytic processes by molecular catalysts based on 3d metals. Cases that involve noninnocent ligands, multicomponent reaction systems, metal-ligand and metal-metal cooperativity, as well as modeling complex catalytic systems such as metal-organic frameworks are presented. Conventionally, computational studies on catalytic mechanisms are heavily dependent on the chemical intuition and expert input of the researcher. Recent developments in advanced automated methods for reaction path analysis hold promise for eliminating such human-bias from computational catalysis studies. A brief overview of these approaches is presented in the final section of the review. The paper is closed with general concluding remarks.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acs.chemrev.8b00361

Cites

503 of 503 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

1 retracted

Show all 503 references

Cited by

See all 423

Metadata

Authors
Vogiatzis, K. D., Polynski, M. V., Kirkland, J. K., Townsend, J., Hashemi, A., Liu, C., & Pidko, E. A.
Venue
Chemical Reviews
Published
2018-10-30
Volume
119
Issue
4
Pages
2453-2523
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W2898972408
Cited by
423
References
503
FWCI
2.52
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities. https://app.cochat.ai/papers/10.1021/acs.chemrev.8b00361
The paper
Vogiatzis, K. D., Polynski, M. V., Kirkland, J. K., Townsend, J., Hashemi, A., Liu, C., & Pidko, E. A. (2019). Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.8b00361

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.