ReviewJACS Au2023
Elucidating the Molecular Origins of the Transference Number in Battery Electrolytes Using Computer Simulations.
Review in JACS Au, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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.
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Who cites it
8 citing papers in PubMed, 35 citations in OpenAlex.
- Lessons Learned on Obtaining Reliable Conductivity Estimates From Molecular Dynamics Simulations.Chemphyschem : a European journal of chemical physics and physical chemistry · 2026Article
- Ion transport for simultaneous nickel electrodeposition and sulfuric acid recovery in single-membrane, dual-chamber electrolyzers.RSC advances · 2026Article
- Methanesulfonate in Phosphate Electrolyte Superstructure Enables Ampere-Hour Practical Aqueous Batteries.Research (Washington, D.C.) · 2026Article
- Orbital-Selective Photoinduced Polaron Dynamics in NaJACS Au · 2025Article
- Cluster analysis as a tool for quantifying structure-transport properties in simulations of superconcentrated electrolyte.Chemical science · 2024Article
- Ion Conductivity in Salt-Doped Polymers: Combined Effects of Temperature and Salt Concentration.ACS macro letters · 2024Article
- Ligand-channel-enabled ultrafast Li-ion conduction.Nature · 2024Article
- Bridging Trans-Scale Electrode Engineering for Mass COJACS Au · 2023Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rate at which rechargeable batteries can be charged and discharged is governed by the selective transport of the working ions through the electrolyte. Conductivity, the parameter commonly used to characterize ion transport in electrolytes, reflects the mobility of both cations and anions. The transference number, a parameter introduced over a century ago, sheds light on the relative rates of cation and anion transport. This parameter is, not surprisingly, affected by cation-cation, anion-anion, and cation-anion correlations. In addition, it is affected by correlations between the ions and neutral solvent molecules. Computer simulations have the potential to provide insights into the nature of these correlations. We review the dominant theoretical approaches used to predict the transference number from simulations by using a model univalent lithium electrolyte. In electrolytes of low concentration, one can obtain a quantitative model by assuming that the solution is made up of discrete ion-containing clusters-neutral ion pairs, negatively and positively charged triplets, neutral quadruplets, and so on. These clusters can be identified in simulations using simple algorithms, provided their lifetimes are sufficiently long. In concentrated electrolytes, more clusters are short-lived and more rigorous approaches that account for all correlations are necessary to quantify transference. Elucidating the molecular origin of the transference number in this limit remains an unmet challenge.
Identifiers
What OpenQuestion holds
Registered trials
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.