Multiscale, multiparadigm modeling for nano systems characterization and design

This chapter outlines our progress toward developing a first-principles-based hierarchical multiscale, multiparadigm modeling and simulation framework for the characterization and optimization of electronic and chemical properties of nanoscale materials and devices. In our approach, we build from the bottom-up by solving the quantum-mechanical (QM) Schrodinger equation for small systems. The results of these calculations lead to physical parameters that feed into methods capable of spanning longer length and time scale with minimum loss of accuracy. This is achieved by having higher-scale quantities self-consistently derived and optimized from the results at finer scales. In contrast to other methods, we are strictly first-principles-based, and all of our parameters at all scales relate to physically measurable or QM-computable observables. Our approach that is applicable to the forward (materials phenomenology) and inverse (“materials by design”) problems. The inverse problem involves top-down predictions of structures and compositions at a lower scale from desired properties at a higher scale. The advantages of our strategy over experimental- and phenomenological-based modeling and simulation approaches include the following: (1) providing access to details that are difficult or impossible to measure (e.g., excited electronic states in materials undergoing extreme conditions of pressure, temperature, etc.); (2) the ability to make useful predictions outside the range of experiments (i.e., since all calculations are ultimately related to first principles); and (3) providing sound, first-principles-based, steering for experiments.