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Record W7116838922 · doi:10.1016/j.solener.2025.114206

Stress evolution and degradation in zero-busbar silicon photovoltaic modules under thermal cycling: A finite element study

2025· article· en· W7116838922 on OpenAlexafffund
Huiwen Liu, Selvakumar V. Nair, Hao Gu, Bo YANG, Jun Wu, Xinchun Yan, Ruirui Lv, Jingbing Dong, Yuanjie Yu, Tao Xu, Harry E. Ruda

Bibliographic record

VenueSolar Energy · 2025
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolderingFinite element methodStress (linguistics)Photovoltaic systemThermalReliability (semiconductor)Temperature cyclingDurabilitySilicon

Abstract

fetched live from OpenAlex

Zero-busbar silicon-based photovoltaic modules are emerging as innovative designs in renewable energy systems, yet their thermo-mechanical reliability under operational stresses remains a critical concern. This study employs transient-state finite element analysis (FEA) to investigate stress evolution in silicon cells, solder joints, and glue joints during thermal cycling. Numerical simulations reveal that structural symmetry significantly influences stress concentrations, particularly at cell-to-cell interconnections. The analysis further demonstrates that glue pad properties exhibit minimal impact on overall stress distribution, while multi-cycle thermal loading highlights progressive hysteresis behaviour in solder joints, driven by accumulated plastic deformation. These findings highlight the importance of geometric optimisation and solder joint durability in enhancing the long-term reliability of zero-busbar photovoltaic modules. This work provides actionable insights for designing robust, high-efficiency systems capable of withstanding real-world thermal stresses.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.634

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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations0
Published2025
Admission routes2
Has abstractyes

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