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Record W4401729257 · doi:10.1021/acs.accounts.4c00329

Examining the Importance of Hydrogen Bonding and Proton Transfer in Iron Porphyrin-Mediated Carbon Dioxide Upconversion

2024· article· en· W4401729257 on OpenAlexafffund
Jeffrey J. Warren

Bibliographic record

VenueAccounts of Chemical Research · 2024
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsSimon Fraser University
FundersSimon Fraser UniversityNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsCarbon dioxidePhoton upconversionChemistryCarbon fibersCarbon dioxide in Earth's atmosphereNanotechnologyComputer scienceMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Conspectus The title should give a sense of the “big picture” of this Account, but what is it really about? An unexpected change in research direction? A series of courageous and creative students? A team taking on challenging problems in chemistry? The answer is a definite “yes” to all of the above. More specifically, the problem in which we are interested is the upconversion or valorization of carbon dioxide. This problem has captured the attention of a great many chemists in earnest following the gas crisis of the 1970s and more recently galvanized due to climate concerns arising from the ongoing release of anthropogenic carbon. Addressing the problem of atmospheric carbon accumulation requires effort in two very broad areas: capture and conversion. Storage is an alternative to conversion, but this eliminates the opportunity to use what might be otherwise a waste product. Our group has investigated a series of modified versions of iron(III)–5,10,15,20-tetraphenylporphyrin (FeTPP) that can convert CO 2 to carbon monoxide, which is a versatile and useful precursor for other syntheses. Following pioneering work from Savéant and his colleagues in the 1990s and thereafter, we started with a simple question: how many pendent ancillary groups that can donate H-bonds or protons are needed to support efficient CO 2 -to-CO conversion? Using a molecule with only one 2-hydroxylphenyl group, we demonstrated that the single prepositioned −OH group gave rise to efficient turnover, but only when experiments were carried out in a weakly H-bond-accepting solvent system. In other words, the ability of a solvent to accept H-bonds can impede CO 2 reduction. We followed up with a deeper investigation of the influence of H-bonding interactions with external acids in FeTPP-mediated CO 2 reduction. Savéant’s framework mechanism appears to be independent of solvent, and rate differences can be approximated by considering H-bonding equilibria. Following that work, we sought to better understand the minimum catalyst design requirements with respect to internal H-bond/proton donors. To that end, we produced all possible isomers of tetraarylpoprhyrins with 2,6-dihydroxyphenyl + phenyl groups. All else being equal, the complexes with a formally trans orientation of the 2,6-dihydroxyphenyl groups performed the best. Most recently, we surveyed the roles of internal and external Brønsted acids with different p K a values. Surprisingly, the best-performing catalysts have more weakly acidic internal groups. Overall, our work has demonstrated that CO 2 reduction mediated by porphyrin catalysts can be improved by considering solvent H-bonding, the orientation of internal H-bonding groups, and the balance of the p K a values of internal and external acids. The future for molecular electrocatalysts is promising as more ideas emerge about how to design molecules and conditions for CO 2 reduction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.323
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2024
Admission routes2
Has abstractyes

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