A tunable microscopic model of network liquids with a liquid-liquid phase transition, analyzed via RFOT theory, predicts nanonucleation near the glass transition and links thermodynamic and kinetic anomalies when matched to water-like conditions.
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cond-mat.soft 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
A neural-network temperature classification task plus XAI is used to benchmark 16 structural descriptors for their ability to capture temperature-dependent local order in supercooled water.
Non-equilibrium MD simulations show ion-specific shifts in Soret coefficient from thermophilic to thermophobic behavior with rising temperature in alkali halide solutions, linked to water structure and heat of transport.
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Polyamorphism in Glassy Network Materials
A tunable microscopic model of network liquids with a liquid-liquid phase transition, analyzed via RFOT theory, predicts nanonucleation near the glass transition and links thermodynamic and kinetic anomalies when matched to water-like conditions.
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Machine learning evaluation of structural descriptors for supercooled water
A neural-network temperature classification task plus XAI is used to benchmark 16 structural descriptors for their ability to capture temperature-dependent local order in supercooled water.
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Thermodiffusion in Aqueous Alkali Halide Solutions from Ambient to Supercooled Conditions: Ion-Specific, Structural, and Mass Effects
Non-equilibrium MD simulations show ion-specific shifts in Soret coefficient from thermophilic to thermophobic behavior with rising temperature in alkali halide solutions, linked to water structure and heat of transport.