Data Analytics

Computer modeling can be used to provide multi-scale insights and make predictions about the materials and phenomena in water desalination devices, or water quality sensors, and this can guide R&D work to improve their performance and efficiency dramatically beyond current limitations.

Nanomaterials can selectively sense the presence and concentration of various contaminants in water by changes induced in, for example, their electrical, electrochemical, and optical properties. While the details of the microscopic processes may not be completely accessible to experiments due to inherent limitations, an atomic-scale understanding of the mechanism of action gained through simulations could be used to modify the nanomaterial to develop new sensors.


Here we are using materials simulation methods combined with high-performance computers to predict the properties of, and design, new nanomaterials which can be used to improve sensors, 2D nanosheet membranes used for desalination, or the electrodes used in capacitive deionization units.

Setup of the basic models and preliminary simulation results have been obtained in the area of arsenic (III) sensors, while methodology design and planning of the projects are in progress for other areas.

The impact of the work will be to greatly improve efficiency and performance of water technologies being developed in ICCW, their partners, and elsewhere.

We are seeking academia-industrial partners to collaborate and also funders for these projects and will provide more details of specific projects on request.