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Record W4392161045 · doi:10.18280/acsm.480109

Synthesis, Characterization, and Infrared Blocking Efficiency of Polyvinyl Alcohol Composites Filled with Cadmium Sulfide and Zinc Sulfide NPs

2024· article· en· W4392161045 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2024
Typearticle
Languageen
FieldChemistry
TopicPigment Synthesis and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsPolyvinyl alcoholZinc sulfideSulfideZincCadmium sulfideCharacterization (materials science)Materials scienceInfraredCadmiumComposite materialNanotechnologyMetallurgy

Abstract

fetched live from OpenAlex

This investigation explores the efficiency of composite coatings, leveraging polyvinyl alcohol (PVA) matrices embedded with zinc sulfide (ZnS) and cadmium sulfide (CdS) nanoparticles, for their infrared (IR) radiation blocking potential.Such coatings are strategically synthesized via a sol-gel method, targeting applications that demand IR attenuation, including but not limited to, construction, architectural fenestrations, vehicular glazing, and thermal insulation domains.In these composites, meticulous integration of ZnS and CdS nanoparticles within the PVA framework was demonstrated to significantly bolster their IR reflective or absorptive properties, consequently curtailing heat transference.It has been observed that nanoparticle concentration and coating thickness serve as critical factors, directly correlating with the IR-blocking proficiency-enhanced concentrations and augmented thicknesses invariably yield superior performance metrics.The surface morphology, assessed through Atomic Force Microscopy (AFM), revealed a positive correlation between nanoparticle concentration and surface roughness, paralleling an increase in particle size.This observation is corroborated by scanning electron microscopy, attesting to the uniform nanoparticle distribution.Fourier-transform infrared spectroscopy (FTIR) analysis identified novel peaks at approximately 1280 and 1700 cm -1 , indicative of a chemical interaction between ZnS nanoparticles and the PVA matrix, as evidenced by the presence of reactive functional groups on the ZnS nanoparticle surface.Thermogravimetric analysis (TGA) imparted insights into the thermal stability of the specimens, with CdS composites exhibiting a weight loss of 98.73%, in stark contrast to the 91.04% manifested by the ZnS counterparts.The disparity is attributed to the higher boiling point of CdS (1750℃) vis-à -vis ZnS (1700℃), underscoring the material's intrinsic thermal resilience.The findings from this research underscore the potential of PVA-ZnS and PVA-CdS coatings as viable candidates for IR-blocking applications, positing an innovative solution to thermal management challenges in various sectors.

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)0.001
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 score0.010
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.242
Teacher spread0.221 · 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