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Record W7081925774 · doi:10.1016/j.nanoms.2025.07.009

Electrocatalytic synthesis of hydrogen peroxide: insights from mechanism to material design

2025· article· en· W7081925774 on OpenAlexaff

Bibliographic record

VenueNano Materials Science · 2025
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
FundersJiaxing UniversityNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsHydrogenMaterial DesignMechanism (biology)Hydrogen productionElectrocatalyst

Abstract

fetched live from OpenAlex

Hydrogen peroxide (H 2 O 2 ) represents an important inorganic chemical product. It finds extensive applications across diverse sectors such as textiles, papermaking, chemical industry and water treatment. For industrial production of H 2 O 2 , the anthraquinone-based process, being extremely energy-consuming, fails to meet the requirements of sustainability imposed by huge market demands. The electrochemical synthesis approaches, two-electron Oxygen Reduction Reaction (2e-ORR) and two-electron Water Oxidation Reaction (2e-WOR), are capable to produce H 2 O 2 on-site. Notably, in the whole process, the reactants are merely oxygen, water, and electric energy. These electrochemical processes have emerged as a focal point in research, prompting substantial efforts to be directed towards the development of highly efficient and stable electrocatalysts. This review centered on the latest research progress regarding 2e-ORR/WOR from the perspective of theoretical calculations along with corresponding experimental results. The details of basic principles, impact factors (e.g. pH and electrolyte ions) and catalyst developments of the electrochemical H 2 O 2 production as well as the advanced characterization techniques are summarized and discussed. We emphasized the relationships between the electronic structure of catalysts and key adsorption intermediates (e.g. ∗OOH for 2e-ORR and ∗OH for 2e-WOR) by using computational methods. The design principles, challenges, and future work for the electrochemical H 2 O 2 production are also proposed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.221
Teacher spread0.213 · 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.

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

Citations3
Published2025
Admission routes1
Has abstractyes

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