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Record W4417292086 · doi:10.1002/advs.202522273

Modulation of Electronic Structure in Kraft Lignin‐Derived Mo Single‐Atom Catalysts for Optimized Electrochemical Oxygen Reduction

2025· article· en· W4417292086 on OpenAlexaff
Junbeom Park, Jae Min Park, Jun Ho Seok, Jeong Hwan Byun, Cheoulwoo Oh, Eung‐Dab Kim, Young‐Jin Ko, Youngeun Kim, Min Jae Kim, Hyeon‐Seok Bang, Ho Seok Park, Chun‐Jae Yoo, Sang Uck Lee, Hyung‐Suk Oh, Kwang Ho Kim, Wooseok Yang

Bibliographic record

VenueAdvanced Science · 2025
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of British Columbia
FundersNational Research Foundation of KoreaMinistry of Science and ICT, South KoreaMinistry of Education, IndiaKorea Institute of Science and TechnologySungkyunkwan UniversityNational Research Foundation
KeywordsCatalysisElectrochemistryMolybdenumDensity functional theoryAdsorptionKraft paperLigninCarbideOxygen

Abstract

fetched live from OpenAlex

The sluggish kinetics of the oxygen reduction reaction (ORR) remain a major bottleneck for energy conversion systems such as fuel cells and metal-air batteries. Here, the synthesis of molybdenum single-atom catalysts (Mo SACs) derived from abundant and low-cost Kraft lignin is reported. By tuning nitrogen incorporation during carbonization, agglomerated Mo carbide clusters are progressively converted into atomically dispersed Mo active centers anchored on N-doped carbon. Extensive spectroscopic analyses confirm this structural evolution, while density functional theory calculations reveal that the optimized Mo coordination environment downshifts the d-band center, enabling the balanced adsorption of oxygen intermediates and thereby improving the intrinsic ORR activity. Electrochemical measurements demonstrate enhanced half-wave potential, near-four-electron transfer pathway, superior selectivity, and excellent durability, with ≈85% current retention over 50 h. Beyond performance, the use of minimally processed Kraft lignin underscores both the economic and environmental advantages of this approach, offering a scalable and sustainable pathway to practical ORR electrocatalysts.

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)0.000
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 score0.016
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.005
GPT teacher head0.242
Teacher spread0.237 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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