Evidence map›Paper›PMID 39202807›Full record

ArticleMolecules (Basel, Switzerland)2024

Designing Accurate Moment Tensor Potentials for Phonon-Related Properties of Crystalline Polymers.

Lukas Reicht, Lukas Legenstein, Sandro Wieser, Egbert Zojer

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2024. 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. Article
  2. 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

4 authors.

Lukas ReichtInstitute of Solid State Physics, NAWI Graz, Graz University of Technology, 8010 Graz, Austria.
Lukas LegensteinInstitute of Solid State Physics, NAWI Graz, Graz University of Technology, 8010 Graz, Austria.
Sandro WieserInstitute of Solid State Physics, NAWI Graz, Graz University of Technology, 8010 Graz, Austria.ORCID 0000-0002-2701-0028
Egbert ZojerInstitute of Solid State Physics, NAWI Graz, Graz University of Technology, 8010 Graz, Austria.ORCID 0000-0002-6502-1721

Funding

Austrian Science Fund (FWF) 10.55776/P33903Austrian Science Fund (FWF) 10.55776/P36129
6 · The paper itself

Abstract

The phonon-related properties of crystalline polymers are highly relevant for various applications. Their simulation is, however, particularly challenging, as the systems that need to be modeled are often too extended to be treated by ab initio methods, while classical force fields are too inaccurate. Machine-learned potentials parametrized against material-specific ab initio data hold the promise of being extremely accurate and also highly efficient. Still, for their successful application, protocols for their parametrization need to be established to ensure an optimal performance, and the resulting potentials need to be thoroughly benchmarked. These tasks are tackled in the current manuscript, where we devise a protocol for parametrizing moment tensor potentials (MTPs) to describe the structural properties, phonon band structures, elastic constants, and forces in molecular dynamics simulations for three prototypical crystalline polymers: polyethylene (PE), polythiophene (PT), and poly-3-hexylthiophene (P3HT). For PE, the thermal conductivity and thermal expansion are also simulated and compared to experiments. A central element of the approach is to choose training data in view of the considered use case of the MTPs. This not only yields a massive speedup for complex calculations while essentially maintaining DFT accuracy, but also enables the reliable simulation of properties that, so far, have been entirely out of reach.

Indexed as

active learningforce fieldmachine-learned potentialmolecular dynamicsmoment tensor potentialP3HTphonon calculationpolyethylenepolythiophenethermal conductivity

Identifiers

PMID39202807
PMCPMC11357232

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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.