Evidence map›Paper›PMID 42835910›Full record

ArticleBeilstein journal of nanotechnology2026

Atom-scale contributions to nanofriction response in transition metal dichalcogenides.

Suresh Ravisankar, Ravikant Kumar, Antonio Cammarata, Thilo Glatzel, Tomas Polcar

Abstract read
In one paragraph

Article in Beilstein journal of nanotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Suresh RavisankarDepartment of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, 16627 Prague 6, Czech Republic.ORCID https://orcid.org/0009-0000-9861-0576
Ravikant KumarDepartment of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, 16627 Prague 6, Czech Republic.ORCID https://orcid.org/0009-0003-7720-2196
Antonio CammarataDepartment of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, 16627 Prague 6, Czech Republic.ORCID https://orcid.org/0000-0002-5691-0682
Thilo GlatzelDepartment of Physics, University of Basel, Klingelbergstrasse 82, 4056 Basel, Switzerland.ORCID https://orcid.org/0000-0002-3533-4217
Tomas PolcarDepartment of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, 16627 Prague 6, Czech Republic.ORCID https://orcid.org/0000-0002-0863-6287

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigate the nanoscale friction behaviour of MX

Indexed as

deep neural networkdensity functional theoryFourier transformmachine learning force fieldmolecular dynamicsnanofrictionnonmonotonictransition metal dichalcogenides

Identifiers

PMID42835910
PMCPMC13635904

What OpenQuestion holds

Textmetadata
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.