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Record W4399735562 · doi:10.1142/s1793292024500966

Enhancing Water Repellency in Cement Concrete Through PDMS-Based Superhydrophobic Coatings

2024· article· en· W4399735562 on OpenAlexaff
Sandhya Dodia, Gaurav Jadav, Pradhumansinh Kher, D. K. Dhruv, Hitesh Rameshchandra Ashani, Smeetraj Gohel, Bharat Kataria, J. H. Markna

Bibliographic record

VenueNANO · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsLambton College
Fundersnot available
KeywordsMaterials scienceComposite materialCementWater repellent

Abstract

fetched live from OpenAlex

Surface coatings such as hydrophobic and transparent coatings were applied to cement concrete surfaces using Polydimethylsiloxane (PDMS) coatings, which have nanometer-sized particles. The degree of contact between the liquid and the coated surface reveals the surface’s ability to repel water, commonly referred to as hydrophobicity. By depositing silicon coating on the surface, we successfully achieved superhydrophobicity on cement concrete, providing excellent resistance against water damage. We are striving to replicate the natural superhydrophobic properties found in nature to create artificial surfaces with similar characteristics. In this study, we experimented to develop and evaluate superhydrophobic coatings on cement concrete. The application of PDMS on the cement concrete yielded fascinating results, with the typical contact angle of the coated layer measuring 178 degrees. We utilized ImageJ software to analyze the results. This innovative approach holds great promise for enhancing water repellency in the field of construction.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.015
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.003

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 head0.021
GPT teacher head0.265
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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