Evidence map›Paper›PMID 40731544›Full record

ReviewMaterials (Basel, Switzerland)2025

Multiscale Simulation of Nanowear-Resistant Coatings.

Xiaoming Liu, Kun Gao, Peng Chen, Lijun Yin, Jing Yang

Abstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Quantitative Wear Models for Microscale Material Removal.Nanomaterials (Basel, Switzerland) · 2026
    Review
  2. Review
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.

Xiaoming LiuInner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China.
Kun GaoSchool of Chemical Engineering and Technology, Sun Yat-sen University, Zhuhai 519082, China.
Peng ChenInner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China.
Lijun YinInner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China.
Jing YangSchool of Chemical Engineering and Technology, Sun Yat-sen University, Zhuhai 519082, China.ORCID 0000-0003-0870-6107

Funding

Supported by Self-funded project of Inner Mongolia Power(Group) CO.,LTD, Inner Mongolia Power Research Institute(Inner Mongolia Power Research Institute[2023]Issue81) 2023-ZC-1-02
6 · The paper itself

Abstract

Nanowear-resistant coatings are critical for extending the service life of mechanical components, yet their performance optimization remains challenging due to the complex interplay between atomic-scale defects and macroscopic wear behavior. While experimental characterization struggles to resolve transient interfacial phenomena, multiscale simulations, integrating ab initio calculations, molecular dynamics, and continuum mechanics, have emerged as a powerful tool to decode structure-property relationships. This review systematically compares mainstream computational methods and analyzes their coupling strategies. Through case studies on metal alloy nanocoatings, we demonstrate how machine learning-accelerated simulations enable the targeted design of layered architectures with 30% improved wear resistance. Finally, we propose a protocol combining high-throughput simulation and topology optimization to guide future coating development.

Indexed as

atomic scalemacroscalemultiscale simulationwear-resistant coating

Identifiers

PMID40731544
PMCPMC12298261

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.