Evidence map›Paper›PMID 34149052›Full record

ArticleAIAA journal. American Institute of Aeronautics and Astronautics2019

Towards a priori uncertainty quantification in coarse-grained molecular dynamics: Generalized multipole potentials.

Paul N Patrone, Andrew M Dienstfrey, Geoffrey B McFadden

Open access · greenAbstract read
In one paragraph

Article in AIAA journal. American Institute of Aeronautics and Astronautics, 2019. 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
0.1field-weighted citation impact, top 58% of its field
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, 1 citations in OpenAlex.

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

3 authors at 2 institutions in 2 countries.

Paul N PatroneApplied and Computational Mathematics Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg MD, 20899, USA.
Andrew M DienstfreyApplied and Computational Mathematics Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg MD, 20899, USA.
Geoffrey B McFaddenApplied and Computational Mathematics Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg MD, 20899, USA.
National Institute of Standards · EGNational Institute of Standards and Technology · US

Funding

Intramural NIST DOC 9999-NIST
6 · The paper itself

Abstract

In computational materials science, coarse-graining approaches often lack a priori uncertainty quantification (UQ) tools that estimate the accuracy of a reduced-order model before it is calibrated or deployed. This is especially the case in coarse-grained (CG) molecular dynamics (MD), where "bottom-up" methods need to run expensive atomistic simulations as part of the calibration process. As a result, scientists have been slow to adopt CG techniques in many settings because they do not know in advance whether the cost of developing the CG model is justified. To address this problem, we present an analytical method of coarse-graining rigid-body systems that yields corresponding intermolecular potentials with controllable levels of accuracy relative to their atomistic counterparts. Critically, this analysis: (i) provides a mathematical foundation for assessing the quality of a CG force field without running simulations; and (ii) provides a tool for understanding how atomistic systems can be viewed as appropriate limits of reduced-order models. Simulated results confirm the validity of this approach at the trajectory level and point to issues that must be addressed in coarse-graining fully non-rigid systems.

Identifiers

PMID34149052
PMCPMC8209989
OpenAlexW2904936577

What OpenQuestion holds

Textmetadata
LicenceTDM
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.