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Record W4399352433 · doi:10.1016/j.enbenv.2024.06.001

Characterization, optimization, and performance evaluation of PCM with Al2O3 and ZnO hybrid nanoparticles for photovoltaic thermal energy storage

2024· article· en· W4399352433 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.

fundA Canadian funder is recorded on the work.
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

VenueEnergy and Built Environment · 2024
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsnot available
FundersDepartment of Mechanical Engineering, University of Alberta
KeywordsMaterials sciencePhotovoltaic systemPhase-change materialResponse surface methodologyThermal conductivityParaffin waxThermal energy storageThermalComposite materialThermodynamicsWaxChemistryChromatographyElectrical engineering

Abstract

fetched live from OpenAlex

The electrical efficiency of the photovoltaic (PV) panel is affected significantly with increased cell temperature. Among various approaches, the use of Phase Change Materials (PCMs) with nanoparticles is currently one of the most effective for reducing and managing the temperature of PV panels. In this study, paraffin wax as PCM with different loading levels (0.5%, 1%, and 2%) of hybrid nanoparticles Al2O3 and ZnO were successfully synthesized and their effects on the performance of the Photovoltaic-Thermal (PVT) system were investigated experimentally. Additionally, a prediction model was developed to analyze the interaction between the operating factors (independent variable) and response factors (dependent variable) of the PVT/PCM and PVT with Hybrid nano-PCM (PVT/HNPCM) systems based on response surface methodology (RSM). Experimental results showed that compared to only PCM, the thermal conductivity of HNPCM increased by 24.68%, 28.57%, and 41.56% for the inclusion of 0.5%, 1%, and 2% hybrid nanomaterial respectively. The electrical efficiency of the PVT/HNPCM, and PVT/PCM system enhanced by 31.46% and 28.70% respectively compared to the conventional PV system in this study. With a cooling-water mass flow rate of 0.0021 kg/s, the highest thermal efficiency of 47% was achieved for the PVT/PCM system, whereas 51.28% was achieved for the PVT/HNPCM system. The analysis of the variance test yielded a P value <0.0001 which is less than 0.05 for the model of overall efficiency for PVT/PCM and PVT/HNPCM system, indicating the suggested model's appropriateness and statistical significance. These optimal conditions are observed when the solar intensity ranges from 774 W/m2 to 809 W/m2 and the mass flow rate is 0.002 kg/s for both the PVT/PCM and PVT/HNPCM systems. However, these systems advance sustainable urban development and climate goals by combining PV panels' electrical generation with thermal energy harvesting, boosting overall energy efficiency in the built environment.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.013
GPT teacher head0.200
Teacher spread0.187 · 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