Evidence map›Paper›PMID 37763481›Full record

ArticleMaterials (Basel, Switzerland)2023

Adhesion Properties of Recycled High-Viscosity Asphalt-Aggregate Interface under Dynamic Water Erosion.

Kang Zhao, Shijie Song, Yang Wei, Guofen Li, Feng Guo

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kang ZhaoCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0002-3538-6121
Shijie SongCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.
Yang WeiCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0003-2915-3898
Guofen LiCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.
Feng GuoCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The drainage of asphalt pavement requires the use of a large amount of high-viscosity-modified asphalt, which faces the service environment under dynamic water erosion. The feasibility of recycling high-viscosity-modified asphalt should be investigated to facilitate sustainable infrastructure construction. This study used ultrasonic equipment to simulate dynamic water erosion test conditions and tested the adhesion performance of different types of recycled high-viscosity asphalt at various environmental temperatures. The adhesion energy index and microstructure of recycled high-viscosity asphalt were analyzed using the contact angle test and AFM test. The results demonstrate that the higher the environmental temperature, the worse the anti-stripping performance of recycled high-viscosity asphalt. From the perspective of adhesion performance indicators, a 6% recycling agent dosage is more conducive to restoring the performance of aged high-viscosity -modified asphalt. The AFM test showed that the microstructure of high-viscosity -modified asphalt represented significant changes with an increase in the recycling agent content, and the change in the adhesion force of recycled high-viscosity -modified asphalt was consistent with the results of macroscopic adhesion performance tests. This study illustrates the applicability of implementing regeneration technology for the recycling of aged drainage asphalt pavement.

Indexed as

adhesion performanceAFMdrainage asphalt pavementdynamic water erosionrecycled high-viscosity asphaltultrasonic numerical simulations

Identifiers

PMID37763481
PMCPMC10533079

What OpenQuestion holds

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Registered trials

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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.