Graph-theoretic microstate analysis reveals altered dynamics in common-cation mixed electrolytes
- 1Department of Chemistry, University of Utah Salt Lake City UT USA
- 2Pacific Northwest National Laboratory Richland WA USA
Abstract
Mixed aqueous electrolytes are increasingly valuable in industrial applications, where they often behave very differently from their single-salt counterparts, yet the underlying molecular mechanisms remain elusive. Here, we present a comprehensive molecular dynamics simulation study of ion networks in NaNO2(aq), NaNO3(aq), and their mixtures. New graph-theoretic workflows combined with principal component analysis identify ion aggregate macro-states, based on number of cations in the cluster, and microstates, based on inter-ion connectivity patterns, enabling detailed investigation of state transitions in mixed versus single-salt electrolyte systems. We find that NO2− preferentially partitions into aggregates, which influences both growth/contraction pathways of macrostates and microstate interconversion. Relative to the single-salt solutions, the mixed electrolyte exhibits faster macrostate aggregate growth and contraction but slower interconversion between microstates. We attribute these behaviors to substantial changes in the aggregation free energy landscape, which may help explain reported solubility shifts in the NaNO2(aq)/NaNO3(aq) two-salt solution. More broadly, these data provide molecular-level evidence that anion competition in two-salt electrolytes directly shapes concentration-dependent ion aggregation, a finding relevant to properties that span conductivity in battery and electrochemical applications to solubility in industrial wastes. The graph-theoretic workflow introduced here for identifying microstates and their transitions is broadly extensible and represents a significant computational advance for studying electrolyte systems.
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BibTeX
@article{wei2026graphtheoretic,
title = {{Graph-theoretic microstate analysis reveals altered dynamics in common-cation mixed electrolytes}},
author = {Yihui Wei and Trent R. Graham and Carolyn I. Pearce and Aurora E. Clark},
journal = {Chemical science},
year = {2026},
month = oct,
doi = {10.1039/d6sc04361e},
url = {https://europepmc.org/article/PMC/PMC13669861},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Graph-theoretic microstate analysis reveals altered dynamics in common-cation mixed electrolytes
AU - Yihui Wei
AU - Trent R. Graham
AU - Carolyn I. Pearce
AU - Aurora E. Clark
PY - 2026
DA - 2026/10/01
JO - Chemical science
DO - 10.1039/d6sc04361e
UR - https://europepmc.org/article/PMC/PMC13669861
AB - Mixed aqueous electrolytes are increasingly valuable in industrial applications, where they often behave very differently from their single-salt counterparts, yet the underlying molecular mechanisms remain elusive. Here, we present a comprehensive molecular dynamics simulation study of ion networks in NaNO2(aq), NaNO3(aq), and their mixtures. New graph-theoretic workflows combined with principal component analysis identify ion aggregate macro-states, based on number of cations in the cluster, and microstates, based on inter-ion connectivity patterns, enabling detailed investigation of state transitions in mixed versus single-salt electrolyte systems. We find that NO2− preferentially partitions into aggregates, which influences both growth/contraction pathways of macrostates and microstate interconversion. Relative to the single-salt solutions, the mixed electrolyte exhibits faster macrostate aggregate growth and contraction but slower interconversion between microstates. We attribute these behaviors to substantial changes in the aggregation free energy landscape, which may help explain reported solubility shifts in the NaNO2(aq)/NaNO3(aq) two-salt solution. More broadly, these data provide molecular-level evidence that anion competition in two-salt electrolytes directly shapes concentration-dependent ion aggregation, a finding relevant to properties that span conductivity in battery and electrochemical applications to solubility in industrial wastes. The graph-theoretic workflow introduced here for identifying microstates and their transitions is broadly extensible and represents a significant computational advance for studying electrolyte systems.
SN - 2041-6520
SN - 2041-6539
ER -