Evidence map›Paper›PMID 38862108›Full record

ArticleACS applied materials & interfaces2024

Sodium Triflate Water-in-Salt Electrolytes in Advanced Battery Applications: A First-Principles-Based Molecular Dynamics Study.

Majid Rezaei, Sung Sakong, Axel Groß

Abstract read
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Article in ACS applied materials & interfaces, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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5 · Who and what money

Authors and funding

3 authors.

Majid RezaeiInstitute of Theoretical Chemistry, Ulm University, Oberberghof 7, 89081 Ulm, Germany.ORCID 0000-0003-2844-2313
Sung SakongInstitute of Theoretical Chemistry, Ulm University, Oberberghof 7, 89081 Ulm, Germany.ORCID 0000-0001-9777-7489
Axel GroßInstitute of Theoretical Chemistry, Ulm University, Oberberghof 7, 89081 Ulm, Germany.ORCID 0000-0003-4037-7331

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Offering a compelling combination of safety and cost-effectiveness, water-in-salt (WiS) electrolytes have emerged as promising frontiers in energy storage technology. Still, there is a strong demand for research and development efforts to make these electrolytes ripe for commercialization. Here, we present a first-principles-based molecular dynamics (MD) study addressing in detail the properties of a sodium triflate WiS electrolyte for Na-ion batteries. We have developed a workflow based on a machine learning (ML) potential derived from ab initio MD simulations. As ML potentials are typically restricted to the interpolation of the data points of the training set and have hardly any predictive properties, we subsequently optimize a classical force field based on physics principles to ensure broad applicability and high performance. Performing and analyzing detailed MD simulations, we identify several very promising properties of the sodium triflate as a WiS electrolyte but also indicate some potential stability challenges associated with its use as a battery electrolyte.

Indexed as

first-principles calculationsmachine learningmolecular dynamicspolarizable force fieldsodium-ion batterywater-in-salt electrolyte

Identifiers

PMID38862108
PMCPMC11212028

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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.