Evidence map›Paper›PMID 38131921›Full record

ArticleGels (Basel, Switzerland)2023

Towards Understanding Aerogels' Effect on Construction Materials: A Principal Component Analysis Approach.

Emil Obeid, Hamdi Chaouk, Rabih Mezher, Eddie Gazo Hanna, Omar Mouhtady, Jalal Halwani, Khaled Younes

Abstract read
In one paragraph

Article in Gels (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Emil ObeidCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait.ORCID 0000-0002-0171-4668
Hamdi ChaoukCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait.
Rabih MezherCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait.ORCID 0000-0002-0061-6441
Eddie Gazo HannaCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait.
Omar MouhtadyCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait.ORCID 0000-0001-8502-2337
Jalal HalwaniWater and Environment Sciences Laboratory, Lebanese University, Tripoli P.O. Box 6573/14, Lebanon.ORCID 0000-0001-9049-2309
Khaled YounesCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait.ORCID 0000-0003-0966-2433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the applicability of Principal Component Analysis (PCA) for distinguishing construction materials. The approach enhances data presentation, revealing distinct clusters and variable impacts on materials. This perspective provides valuable insights into concrete materials, guiding materials science and engineering practices. Our findings show the capacity of PCA to show a clear distinction between concrete and non-concrete composites. Compressive strength significantly affects certain composites, being influenced by aerogel loading. The peculiar role of aerogel density among the other factors is attributed to their possession of the smallest thermal conductivity. To address moderate total variance of PCA, segregation into concrete (C) and non-concrete (NC) categories is explored, offering a more robust distinction and higher clustering. Concrete materials show higher variance, emphasizing the effectiveness of the segregation approach. PCA highlights aerogel density's influence on thermal conductivity on concrete materials. For non-concrete materials, a moderately higher variance is noted, emphasizing the critical role of aerogel-related properties (size and density). These findings underscore the importance of aerogel characteristics in shaping material behaviour.

Indexed as

concreteconstruction materialsmachine learningmaterials sciencePCA

Identifiers

PMID38131921
PMCPMC10743007

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.