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Record W4206431285 · doi:10.14447/jnmes.v24i2.a07

Influence of Surfactant Additives on Photochemical Synthesized Silver Nanoparticles using UV Pulsed Laser Irradiations in Aqueous Silver Nitrate Solution

2021· article· en· W4206431285 on OpenAlexvenueno aff
Umair Yaqub Qazi

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2021
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsnot available
Fundersnot available
KeywordsSilver nanoparticleAqueous solutionChemistrySilver nitratePulmonary surfactantMicelleAdsorptionHydrocarbonFluorescenceCarbon fibersPhotochemistryInorganic chemistryNuclear chemistryMoleculeNanoparticleChemical engineeringOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

The effect of different additives on the AgNPs formation process was explored in this study. AgNPs were synthesized in an aqueous solution of silver nitrate-containing surfactants by photoreduction of silver ions. The concentration dependency of AgNPs formation suggested that stability was induced by the equilibrium of AgNPs adsorbed by surfactants with higher carbon chain molecules such as SDS and AOT. These results open up a new window both for structural control and the development process. It also indicated that different additives had an impact on the morphology of NPs. The hydrocarbon chain influenced the growth process and demonstrated that <10 carbon chain surfactants such as SMS, SOS, did not constitute the CGC and had a minor effect on the mechanism of growth. However, the NPs formation begun at a lower limit indicated as CGC. It was observed only with hydrocarbon chains of > 10 carbon atoms such as AOT, SDS. Fluorescence results confirmed that after laser irradiation, hemi-micelle formation after the development of AgNPs.

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)0.001
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 score0.029
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of New Materials for Electrochemical SystemsSame topicLaser-Ablation Synthesis of NanoparticlesFrench-language works237,207