Published October 13, 2026 | Version v1.0

Code and Data for: Is Water a Mixture: Unsupervised Likelihood-Ratio Classification Reveals Two Water States That Merge Upon Increasing Temperature

  • 1. Department of Chemistry, Harvey Mudd College
  • 2. ROR icon Yale-NUS College

Description

Code and data accompanying the article "Is Water a Mixture: Unsupervised Likelihood-Ratio Classification Reveals Two Water States That Merge Upon Increasing Temperature".

Each water molecule is classified without supervision as a locally favored tetrahedral structure (LFTS), a disordered normal-liquid structure (DNLS), or transitional, using a likelihood ratio from a two-component Gaussian mixture over local order parameters, fitted once at TIP4P/2005, -20 C and then held fixed. The two groups are identified through their oxygen-oxygen structure factors, and the classifier is applied to TIP4P/2005, TIP5P and SWM4-NDP water from -30 to +90 C.

Contents:

  • code_figures_tables.zip: simulation (OpenMM), order parameter, classification and structure factor code, plus scripts that reproduce all figures and SI tables (run_all.sh runs the full pipeline).
  • data_TIP4P-2005.zip, data_TIP5P.zip, data_SWM4-NDP.zip: trajectories, order parameters and classification labels for each water model.
  • README.md: setup and usage instructions.

Correspondence: Bilin Zhuang (bzhuang@g.hmc.edu).

Files

code_figures_tables.zip

Files (3.0 GB)

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Additional details

Funding

U.S. National Science Foundation
CAREER: Develop a Hybrid Adaptive Particle-Field Simulation Method for Solutions of Macromolecules and a New Computational Chemistry Course for Lower-Division Undergraduates 2337602
U.S. National Science Foundation
Equipment: MRI Consortium: Track 1 Acquisition of a High-Performance Computing Cluster for Interdisciplinary Research at the Claremont Colleges 2408259

Software

Repository URL
https://github.com/HMC-FLUID-Lab/water-two-state-classification
Programming language
Python
Development Status
Active