Issue No. 01 - Jan.-Feb. (2018 vol. 20)
Jacqueline M. Cole , University of Cambridge and Argonne National Laboratory
A new initiative in data science is using the Mira and Theta supercomputers at the US Department of Energy's Argonne National Laboratory to discover new dye materials suitable for dye-sensitized solar cells. This project aims to develop a new material-by-design methodology by using natural language processing, machine learning, and data mining in conjunction with large-scale simulation and experiments. This synergistic computational and experimental science approach will enable the discovery of new light-absorbing dye molecules, which are needed for the development of solar-powered windows that have the potential to power buildings in an entirely energy-sustainable fashion.
data mining, design engineering, learning (artificial intelligence), natural language processing, solar cell arrays, structural engineering computing, sustainable development, windows (construction)
J. M. Cole, "Data-Driven Molecular Engineering of Solar-Powered Windows," in Computing in Science & Engineering, vol. 20, no. 1, pp. 84-87, 2018.