Momentum tunnelling between nanoscale liquid flows.

The world of nanoscales in fluidics is the frontier where the continuum of fluid mechanics meets the atomic, and even quantum, nature of matter. While water dynamics remains largely classical under extreme confinement, several experiments have recently reported coupling between water transport and the electronic degrees of freedom of the confining materials. This avenue prompts us to reconsider nanoscale hydrodynamic flows under the perspective of interacting excitations, akin to condensed matter frameworks.

Prototype of an App Designed to Support Self-Management for Health Behaviors and Weight in Women Living With Breast Cancer: Qualitative User Experience Study.

Background: Accessible self-management interventions are required to support people living with breast cancer.

Objective: This was an industry-academic partnership study that aimed to collect qualitative user experience data of a prototype app with built-in peer and coach support designed to support the management of health behaviors and weight in women living with breast cancer.

Methods: Participants were aged ≥18 years, were diagnosed with breast cancer of any stage within the last 5 years, had completed active treatment, and were prescribed oral hormone therapy.

On the increase of the melting temperature of water confined in one-dimensional nano-cavities.

Water confined in nanoscale cavities plays a crucial role in everyday phenomena in geology and biology, as well as technological applications at the water-energy nexus. However, even understanding the basic properties of nano-confined water is extremely challenging for theory, simulations, and experiments. In particular, determining the melting temperature of quasi-one-dimensional ice polymorphs confined in carbon nanotubes has proven to be an exceptionally difficult task, with previous experimental and classical simulation approaches reporting values ranging from ∼180 K up to ∼450 K at ambient pressure.

Ultracompact Electrical Double Layers at TiO(110) Electrified Interfaces.

Metal-oxide aqueous interfaces are important in areas as varied as photocatalysis and mineral reforming. Crucial to the chemistry at these interfaces is the structure of the electrical double layer formed when anions or cations compensate for the charge arising from adsorbed H or OH. This has proven extremely challenging to determine at the atomic level.

Introduction to machine learning potentials for atomistic simulations.

Machine learning potentials have revolutionised the field of atomistic simulations in recent years and are becoming a mainstay in the toolbox of computational scientists. This paper aims to provide an overview and introduction into machine learning potentials and their practical application to scientific problems. We provide a systematic guide for developing machine learning potentials, reviewing chemical descriptors, regression models, data generation and validation approaches.