Evidence map›Paper›PMID 41043168›Full record

ArticleJournal of the American Chemical Society2025

Accurate Prediction of Mechanical Property of Organic Crystals Using Molecular Dynamics-Based Nanoindentation Simulations.

Sara M Elgengehi, Durga Prasad Karothu, Weiwei He, Rabindranath Paul, Serdal Kirmizialtin, Panče Naumov

Abstract read
In one paragraph

Article in Journal of the American Chemical Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. MXtalTools: A Toolkit for Machine Learning on Molecular Crystals.Journal of chemical information and modeling · 2026
    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.

Sara M ElgengehiCenter for Smart Engineering Materials, New York University Abu Dhabi, PO Box, 129188 Abu Dhabi, United Arab Emirates.
Durga Prasad KarothuCenter for Smart Engineering Materials, New York University Abu Dhabi, PO Box, 129188 Abu Dhabi, United Arab Emirates.ORCID 0000-0001-5956-6496
Weiwei HeProgram in Chemistry, Division of Science and Mathematics, New York University Abu Dhabi, PO Box, 129188 Abu Dhabi, United Arab Emirates.
Rabindranath PaulCenter for Smart Engineering Materials, New York University Abu Dhabi, PO Box, 129188 Abu Dhabi, United Arab Emirates.ORCID 0000-0003-4870-4608
Serdal KirmizialtinCenter for Smart Engineering Materials, New York University Abu Dhabi, PO Box, 129188 Abu Dhabi, United Arab Emirates.ORCID 0000-0001-8380-5725
Panče NaumovCenter for Smart Engineering Materials, New York University Abu Dhabi, PO Box, 129188 Abu Dhabi, United Arab Emirates.ORCID 0000-0003-2416-6569

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing reliable methods to predict the mechanical response of organic crystals is essential due to their growing recognition as soft, compliant, lightweight, and ultrafast smart dynamic materials that have applications ranging from pharmaceuticals to biomaterials. Traditional experimental methods, such as nanoindentation, come with practical convenience such as simplicity and efficacy; however, they are restrictive with regard to the surface quality and are subject to other experimental constraints such as the availability of suitable samples and accessibility of as-grown crystal faces. Computational approaches, including quantum mechanics and classical molecular dynamics (MD), offer an alternative approach that is independent of the sample, yet they are known to vary greatly in their predictive accuracy. To account for this shortfall of predictive tools, in this study, we systematically benchmark three major computational methods, including density functional theory (DFT), MD-based approaches based on deformation, and direct nanoindentation simulations, against experimental Young's moduli. Our results show that the MD-simulated process of indentation conforms most favorably with the experiments and has the lowest mean absolute error. The intermolecular interactions, crystal size, indenter spacing, and unloading rates are identified as the key factors that determine the stiffness, as given by the modulus. Our findings underscore the importance of incorporating both thermal effects and experimental conditions into computational models for improved predictive accuracy and highlight the potential of nanoindentation simulations as a reliable tool for the assessment of the mechanical properties and, possibly, also for the design of organic crystals with predetermined mechanical properties and dynamic behavior.

Identifiers

PMID41043168
PMCPMC12532296

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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.