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Investigation of oil exudation from commercial asphalt binders

2025· article· en· W4412692994 on OpenAlexafffund
Jianmin Ma, Jerron Zhang, Simon A.M. Hesp

Bibliographic record

VenueConstruction and Building Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsAsphaltEnvironmental sciencePetroleum engineeringMaterials scienceWaste managementPulp and paper industryComposite materialEngineering

Abstract

fetched live from OpenAlex

Oil exudation is attracting attention with the increased application of softeners and rejuvenators in the asphalt industry. This study systematically evaluated the oil exudation potential of 19 asphalt binder samples sourced from various North American paving projects. Rheological properties in terms of intermediate temperature performance grade (ITPG), limiting phase angle temperatures (T 30° and T 45° ), as well as differences in the limiting phase angle temperatures (∆T cδ ) were characterized before and after accelerated oil exudation treatment. The results show that T 30° emerges as the most sensitive and reliable indicator for assessing oil exudation effects. In contrast, metrics such as ITPG, T 45° , and ∆T cδ were less effective. The results further revealed that properly designed reclaimed asphalt pavement (RAP)-modified asphalts—incorporating high-quality RAP and compatible rejuvenators or softeners—are free of oil exudation even at elevated RAP contents, underscoring the critical role of judicious material selection and blending processes. However, binders containing significant quantities of re-refined engine oil bottoms (REOB) exhibited pronounced oil exudation, which is likely to exacerbate cracking failure through deteriorating the binder-aggregate bonding strength in addition to physical hardening. While high grade spans generally correlated with increased oil exudation, notable exceptions were observed when using rejuvenators or softeners compatible with RAP or polymers. These insights underscore the necessity of effective specification criteria and strategic additive selection to mitigate oil exudation, ultimately contributing to enhanced pavement durability and performance.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.368

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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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