Evidence map›Paper›PMID 40695966›Full record

ArticleScientific reports2025

Effect of encapsulated waste oils and compaction method on the curing and strength of cold mix asphalt.

Hassan Ziari, Elaheh Nasiriamiri, Pooyan Ayar

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Hassan ZiariSchool of Civil Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran, Iran. h.ziari@iust.ac.ir.
Elaheh NasiriamiriSchool of Civil Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran, Iran.
Pooyan AyarSchool of Civil Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran, Iran. ayar@iust.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cold Mix Asphalt (CMA) is a sustainable alternative to conventional hot mix asphalt (HMA) due to its lower energy consumption and reduced environmental impact. However, CMAs often suffer from high moisture susceptibility, prolonged curing times, and inadequate mechanical performance. This study investigates the potential of calcium alginate capsules (CA capsules) containing waste sunflower oil (WSO) and waste engine oil (WEO) to improve CMA performance. Unlike previous research focusing on self-healing aspect of rejuvenating capsules, this work evaluates the impact of these CA capsules on curing efficiency, strength development, and mechanical behavior under different curing times and compaction methods: Marshall Compacted Mixture (MCM) and Gyratory Compacted Mixture (GCM). CA capsules were characterized using the Field Emission Scanning Electron Microscopy (FESEM)-EDS-Map and Thermogravimetric Analysis (TGA), and mechanical properties of CMA samples were assessed via indirect tensile strength (ITS), tensile strength ratio (TSR), rutting, and semi-circular bending (SCB) fracture tests.Weight measurements taken over the curing period showed that mixtures containing 0.5% CA capsules experienced greater moisture loss, thereby accelerating the curing process. GCM samples exhibited up to 90% higher ITS values than MCM samples, while samples with CA capsules showed an average 7-15% decrease in dry ITS. TSR values increased by up to 10% with 0.5% CA capsule addition, indicating improved moisture resistance. Fracture energy increased by 18-22% at - 20 °C in samples with 1% WSO, despite a slight reduction in fracture toughness. ANOVA analysis confirmed that compaction method had the greatest influence on ITS, TSR, and fracture energy, while CA capsule type mainly affected rutting depth. CA capsules with WEO led to deeper ruts than WSO, suggesting better compatibility of WSO with the asphalt matrix. These findings highlight that incorporating oil-based CA capsules-especially at 0.5-1% content-not only improves curing efficiency but also enhances the durability and sustainability of CMAs, particularly under low-temperature and high-moisture conditions.

Indexed as

Calcium alginate capsuleCold mix asphalt (CMA)Curing timeSustainabilityWaste oil

Identifiers

PMID40695966
PMCPMC12284127

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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.