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Record W2902737143 · doi:10.3390/catal8120621

Insights into the Recent Progress and Advanced Materials for Photocatalytic Nitrogen Fixation for Ammonia (NH3) Production

2018· article· en· W2902737143 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCatalysts · 2018
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPhotocatalysisNitrogen fixationNanotechnologyWater splittingMaterials scienceHydrogen productionEnvironmental scienceNitrogenChemistryHydrogenCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Ammonia (NH3) is one of the key agricultural fertilizers and to date, industries are using the conventional Haber-Bosh process for the synthesis of NH3 which requires high temperature and energy. To overcome such challenges and to find a sustainable alternative process, researchers are focusing on the photocatalytic nitrogen fixation process. Recently, the effective utilization of sunlight has been proposed via photocatalytic water splitting for producing green energy resource, hydrogen. Inspired by this phenomenon, the production of ammonia via nitrogen, water and sunlight has been attracted many efforts. Photocatalytic N2 fixation presents a green and sustainable ammonia synthesis pathway. Currently, the strategies for development of efficient photocatalyst for nitrogen fixation is primarily concentrated on creating active sites or loading transition metal to facilitate the charge separation and weaken the N–N triple bond. In this investigation, we review the literature knowledge about the photocatalysis phenomena and the most recent developments on the semiconductor nanocomposites for nitrogen fixation, following by a detailed discussion of each type of mechanism.

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.

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 score0.108
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.015
GPT teacher head0.293
Teacher spread0.278 · 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