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Record W4388977462 · doi:10.1021/acssuschemeng.3c04497

Mechanistic Insights into the Phase Formation of an Atypical Iron Oxynitride (Fe<sub><i>x</i></sub>O<sub><i>y</i></sub>N<sub><i>z</i></sub>) System and Its Multifunctional Photocatalytic Applications

2023· article· en· W4388977462 on OpenAlexaff
Mithun Prakash Ravikumar, Toan‐Anh Quach, Bharagav Urupalli, K. Manjunatha, M. Mamatha Kumari, M.V. Shankar, Sheng Yun Wu, Trong‐On Do, Sakar Mohan

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2023
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversité Laval
FundersNational Science and Technology CouncilDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsMaterials scienceNitrideOxideMetalPhotocatalysisPhase (matter)Chemical engineeringInorganic chemistryNanotechnologyChemistryMetallurgyCatalysis

Abstract

fetched live from OpenAlex

Apart from metal oxides, materials with different anionic setups such as metal chalcogenides and metal oxyhalides have been largely explored for photocatalytic applications. In this direction, metal oxynitrides also exhibit interesting properties, and the development of the oxynitride phase of the conventional metal oxides has gained significant interest in photocatalysis research. In this context, an iron oxynitride (Fe x O y N z ) system is developed from iron nitride (Fe x N) via solid-state annealing at relatively low temperatures. The formation of the oxynitride phase is driven by the partial replacement of lattice nitrogen with oxygen, which is confirmed via the new peaks appearing in the XRD patterns followed by the Rietveld refinement analysis. The XPS analysis of the samples indicated that the oxynitride phase is stabilized via the N 3– -Fe 3+/2+ -O 2– network in the system. The structure–property relationship of the formed iron oxynitride phase is analyzed by using various optical (UV–vis, PL, and TRPL), photoelectrochemical (CV, LSV, EIS, photocurrent, Mott–Schottky), surface (BET), and magnetic property (SQUID) analysis techniques. These obtained results suggest that the iron nitride counterpart synergistically contributed to the overall enhancements in the properties of the resulting oxynitride phase. Consequently, the photocatalytic properties of the developed iron nitride, oxide, and oxynitride systems are studied for dye degradation and H 2 generation under solar irradiation. A maximum of ∼97% dye degradation in 180 min and an evolution of H 2 at a rate of 897.6 μmol g –1 h –1 are observed over the developed iron oxynitride system, and the rate of evolution of H 2 is greater than those in the bare iron oxide (790.8 μmol g –1 h –1 ) and nitride (664.8 μmol g –1 h –1 ) systems. The observed improved magnetic properties and photostabilities of the synthesized Fe x O y N z system enabled its easy recovery and reusability, which are confirmed through postcharacterizations. The insights gained from various characterizations and experimental studies suggest that the iron oxynitride could be considered an atypical pristine system rather than a modified system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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".

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Citations13
Published2023
Admission routes1
Has abstractyes

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