Long Molecular Wires and the Auto-ionization of Water
Creators
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1.
University of Chicago
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2.
California Institute of Technology
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3.
Argonne National Laboratory
Abstract
Water auto-ionization is critical in a wide range of chemical, biological, physical, and industrial processes. In this work, we describe a series of hitherto unknown collective molecular processes leading to auto-ionization. Specifically, by combining machine-learned interatomic potentials and spectral adaptive biasing force techniques, we determine the relevant free energy landscape of water auto-ionization. At ambient conditions, the free energy profile reveals two distinct saddle points, each leading to the formation of three- and four-member water wires. The wires feature an individual Zundel ion and a proton diffusion-like transition state, respectively. At elevated temperatures, the auto-ionization process exhibits a more concerted hydrogen transfer mechanism and reveals an alternative pathway involving the synchronous diffusion of Zundel ion pairs, with the ion pair corresponding to an energetic local minimum on the free energy surface. These findings help resolve long-standing conflicting views of the mechanism of water auto-ionization and provide new avenues for the study of proton behavior in different aqueous environments.
Copyright and License
The content is available under CC BY NC ND 4.0
Additional Information
Version notes for v.2: We added more details of hydrogen bond water wire and network analysis, which suggests that at the later transition state involving longer water wires, the existence of Eigen-like, highercoordination configurations facilitate a double-gating proton transfer mechanism.
Funding
Department of Energy, Office of Science, Basic Energy Sciences, DE-SC0023383
Department of Energy, Office of Science, Office of Advanced Scientific Computing Research. DE-SC0022158
National Science Foundation, NRT Grant No. 2022023
Supplemental Material
The document includes details on first principles calculations, MLIP-MD simulations with enhanced sampling, and the training of machine-learned interatomic potentials (MLIPs). Additionally, it covers the generation of free energy surfaces, the calculation of minimum free energy paths and transition states using CI-NEB, and the analysis of water wire distributions. Validation of MLIP calculations is also presented, alongside a calculation of pKw and the free energy profile for the early stages of water autoionization. Finally, it discusses the training data set used for the model.
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Additional details
Funding
- Office of Basic Energy Sciences
- DE-SC0023383
- Office of Advanced Scientific Computing Research
- DE-SC0022158
- National Science Foundation
- NRT 2022023
Dates
- Submitted
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2024-09-19Version 1
- Submitted
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2025-03-21Version 2