Pith. sign in

REVIEW 2 cited by

How reactive is water at the nanoscale and how to control it?

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2508.13034 v1 pith:G635PUHA submitted 2025-08-18 physics.chem-ph cond-mat.mes-hall

classification physics.chem-phcond-mat.mes-hall
keywords waternanoscalereactivitychemistrydissociationenhancedpriorstudies
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Nanoconfined water plays a key role in nanofluidics, electrochemistry, and catalysis, yet its reactivity remains a matter of debate. Prior studies have reported both enhanced and suppressed water self-dissociation relative to the bulk, but without a consistent explanation. Here, using enhanced sampling molecular dynamics with machine-learned potentials trained at first-principles accuracy, we investigate dissociation behavior in water confined within 2D slit pores and nanodroplets, using graphene and hexagonal boron nitride as model materials. We find that reactivity is extremely sensitive to water density, confinement width, geometry, material flexibility, and surface chemistry. Despite this complexity, we show that chemical potential -- together with interfacial interactions -- governs dissociation trends and explains the variability observed in prior studies. This thermodynamic perspective reconciles previous contradictions and reveals how nanoscale environments can drastically shift water reactivity. Our findings provide molecular-level insight and offer a design lever for modulating water chemistry at the nanoscale.

Discussion (0). Sign in to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Controlling the phase behaviour of ultraconfined water via bilayer graphene stacking

    physics.chem-ph 2026-06 unverdicted novelty 7.0 of 10

    AA stacking in bilayer graphene raises melting temperature of ultraconfined water by >100 K, stabilizes different ice polymorphs, and alters proton transfer relative to AB stacking via changes in the hydrogen-bond network.

  2. VASP Plugins: Linking the Vienna ab-initio Simulation Package with Python

    cond-mat.mtrl-sci 2026-07 accept novelty 5.5 of 10

    A C++/pybind11 shared-memory plugin layer exposes VASP SCF and ionic data as NumPy arrays so Python can modify structure, forces, local potential, and occupancies in place.

Pith tools