A most effective, though still underestimated, issue in dealing with the energy requirements of modern societies concerns the conservation of energy. This concerns, for example, building houses with better insulation and intelligent (coated) windows (keeping IR photons outside when the sun is burning, and keeping them inside, when the weather is cool), improving the efficiency of electricity-producing turbines or of airplane jet engines (e.g. by better thermal-barrier coatings), using more efficient light sources (solid state or organics), etc.
Furthermore, we note that a significant part of the consumed energy is transformed into “waste heat”. For computers and combustion engines this is very obvious. At this point, heat is usually cooled away (with noticeable costs) and not transformed back into a useful energy.
These issues are at the heart of materials science. We need better theories and modeling methods that help us to screen materials with respect to their specific function, such as electron-phonon coupling, heat transport and Seebeck coefficients in nanostructures, or carrier transport in organic LEDs. Parallel to these issues is the materials informatics challenge: how can we efficiently screen materials, what are the proper descriptors of a large theoretical materials library, and what is the accuracy (and reliability) of present day theories? Some concepts along these lines have been developed already, and bio-informatics has developed several tools that the materials community may well adjust and adopt.
It is the goal of this workshop to bring together mathematicians, physicists, computer scientists, materials scientists and engineers who work in the area of energy conservation and waste heat recovery. We expect this workshop will attract junior as well as senior participants.
This workshop will include a poster session; a request for posters will be sent to registered participants in advance of the workshop.
(University of California, Davis (UC Davis))
Richard James (University of Minnesota, Twin Cities)
Jennifer Lukes (University of Pennsylvania)
Matthias Scheffler (Fritz-Haber-Institut der Max-Planck-Gesellschaft)