Evidence map›Paper›PMID 35266647›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2022

Macroscale Robust Superlubricity on Metallic NbB

Jia Wang, Chang Liu, Kaifei Miao, Kan Zhang, Weitao Zheng, Changfeng Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Sensor for a Solid-Liquid Tribological System.Sensors (Basel, Switzerland) · 2025
    Review
  4. Macroscale Robust Superlubricity on Metallic NbBAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    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

6 authors.

Jia WangState Key Laboratory of Superhard Materials, Department of Materials Science and Key Laboratory of Automobile Materials, MOE, Jilin University, Changchun, 130012, China.ORCID 0000-0002-2538-6224
Chang LiuInternational Center for Computational Methods and Software, College of Physics, Jilin University, Changchun, 130012, China.ORCID 0000-0003-0824-1098
Kaifei MiaoState Key Laboratory of Superhard Materials, Department of Materials Science and Key Laboratory of Automobile Materials, MOE, Jilin University, Changchun, 130012, China.
Kan ZhangState Key Laboratory of Superhard Materials, Department of Materials Science and Key Laboratory of Automobile Materials, MOE, Jilin University, Changchun, 130012, China.ORCID 0000-0003-1354-2784
Weitao ZhengState Key Laboratory of Superhard Materials, Department of Materials Science and Key Laboratory of Automobile Materials, MOE, Jilin University, Changchun, 130012, China.ORCID 0000-0002-9028-278X
Changfeng ChenDepartment of Physics and Astronomy, University of Nevada, Las Vegas, Las Vegas, NV, 89154, USA.ORCID 0000-0002-6110-1118

Funding

China Postdoctoral Science Foundation 2017TD-09China Postdoctoral Science Foundation 2020M681031National Key R&D Program of China 2016YFA0200400National Natural Science Foundation of China 51602122National Natural Science Foundation of China 51905206National Natural Science Foundation of China 51972139
6 · The paper itself

Abstract

Robust superlubricity (RSL), defined by concurrent superlow friction and wear, holds great promise for reducing material and energy loss in vast industrial and technological operations. Despite recent advances, challenges remain in finding materials that exhibit RSL on macrolength and time scales and possess vigorous electrical conduction ability. Here, the discovery of RSL is reported on hydrated NbB

Indexed as

FrictionmacroscalemetallicNbB2superlow wearsuperlubricity

Identifiers

PMID35266647
PMCPMC9069360

What OpenQuestion holds

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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.