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Record W4205690426 · doi:10.1002/ange.202110158

Solar Urea: Towards a Sustainable Fertilizer Industry

2021· article· en· W4205690426 on OpenAlexafffund
Meikun Xia, Chengliang Mao, Alan Gu, Athanasios A. Tountas, Chenyue Qiu, Thomas E. Wood, Young Feng Li, Ulrich Ulmer, Yangfan Xu, Camilo J. Viasus, Jessica Ye, Chenxi Qian, Geoffrey A. Ozin

Bibliographic record

VenueAngewandte Chemie · 2021
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsUniversity of Toronto
FundersConnaught FundNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceAlexander von Humboldt-Stiftung
KeywordsUreaFertilizerRenewable energyChemistryEnvironmentally friendlyDissociation (chemistry)Solar energyCatalysisNanotechnologyMaterials scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Urea, an agricultural fertilizer, nourishes humanity. The century‐old Bosch–Meiser process provides the world's urea. It is multi‐step, consumes enormous amounts of non‐renewable energy, and has a large CO 2 footprint. Thus, developing an eco‐friendly synthesis for urea is a priority. Herein we report a single‐step Pd/LTA‐3A catalyzed synthesis of urea from CO 2 and NH 3 under ambient conditions powered solely by solar energy. Pd nanoparticles serve the dual function of catalyzing the dissociation of NH 3 and providing the photothermal driving force for urea formation, while the absorption capacity of LTA‐3A removes by‐product H 2 O to shift the equilibrium towards urea production. The solar urea conversion rate from NH 3 and CO 2 is 87 μmol g −1 h −1 . This advance represents a first step towards the use of solar energy in urea production. It provides insights into green fertilizer production, and inspires the vision of sustainable, modular plants for distributed production of urea on farms.

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 categoriesInsufficient payload (model declined to judge)
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 score0.049
Threshold uncertainty score1.000

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)0.0010.000

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 head0.016
GPT teacher head0.239
Teacher spread0.222 · 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

Citations32
Published2021
Admission routes2
Has abstractyes

Explore more

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