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Record W4400296665 · doi:10.3390/ma17133271

Mechanical Properties and Durability of Composite Cement Pastes Containing Phase-Change Materials and Nanosilica

2024· article· en· W4400296665 on OpenAlexfundno aff
Javier Ziga-Carbarín, Lauren Y. Gómez-Zamorano, A. Cruz-López, Soorya Pushpan, Sofia Vázquez‐Rodríguez, Magdalena Balonis

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsnot available
FundersUniversidad Autónoma de Nuevo LeónCanadian Institute for Theoretical Astrophysics
KeywordsMaterials scienceComposite materialCompressive strengthComposite numberCementPortland cementPozzolanThermal conductivityPhysisorptionFly ashAbsorption of waterDurabilityAdsorption

Abstract

fetched live from OpenAlex

Escalating global surface temperatures are highlighting the urgent need for energy-saving solutions. Phase-change materials (PCMs) have emerged as a promising avenue for enhancing thermal comfort in the construction sector. This study assessed the impact of incorporating PCMs ranging from 1% to 10% by mass into composite Portland cement partially replaced by fly ash (FA) and nanosilica particles (NS). Mechanical and electrochemical techniques were utilized to evaluate composite cements. The results indicate that the presence of PCMs delayed cement hydration, acting as a filler without chemically interacting within the composite. The combination of FA and PCMs reduced compressive strength at early ages, while thermal conductivity decreased after 90 days due to the melting point and the latent heat of PCMs. Samples with FA and NS showed a significant reduction in the CO2 penetration, attributed to their pozzolanic and microfiller effects, as well as reduced water absorption due to the non-absorptive nature of PCMs. Nitrogen physisorption confirmed structural changes in the cement matrix. Additionally, electrical resistivity and thermal behavior assessments revealed that PCM-containing samples could reduce temperatures by an average of 4 °C. This suggested that PCMs could be a viable alternative for materials with thermal insulation capacity, thereby contributing to energy efficiency in the construction sector.

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 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 score0.004
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.106
GPT teacher head0.301
Teacher spread0.195 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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