Functional nanomaterials for sustainable chemistry, nanosensing, and clean energy will be modeled in close synergy with leading experimental groups worldwide. Such combined modeling/experimental approach will lead to advanced materials for catalysis of new feedstocks, fine chemicals, nanosensing, and light harvesting and utilization. New methods will be developed to model at conditions mimicking as closely as possible experimental operating conditions and to represent realistic materials as close as possible compared to experiment.  To this end methods will be developed that account for defects and spatial heterogeneities in the materials from the nano- to the mesoscale.  To bridge the length time scale gap between theory and experiment, new methods will be developed based on techniques originating from machine learning, advanced quantum mechanical many-body techniques and enhanced sampling.