Visual methods for interpreting optical nonlinearity at the molecular level.

The emergence of nonlinear optical (NLO) measurement approaches has provided new windows into molecular and macromolecular structure within thin films and materials. The greatest barriers in mining this structural information increasingly appear in meaningfully relating these macroscopic results back to molecular-level descriptions, driven largely by the increasing complexity of the molecular systems and interfacial architectures under interrogation. As NLO methods continue their expansion into increasingly diverse disciplines, so grows the need for tools to guide this evolution without sacrificing the mathematical rigor of more traditional tensor representations. Recent developments reviewed in this Account are designed to facilitate interpretation of complex assemblies using relatively simple but still quantitatively accurate visual representations of the polarization-dependent optical nonlinearity, both for individual chromophores and for polymeric assemblies of coupled chromophores. Although the primary focus of this Account is on second-order nonlinear optical effects, including second harmonic generation and sum frequency generation, many of these same concepts also directly apply to higher-order phenomena.

NLOPredict: visualization and data analysis software for nonlinear optics.

A data analysis and visualization program was developed to assist in the interpretation of second-order nonlinear optical (NLO) processes, including vibrational sum-frequency generation and electronically resonant second harmonic generation. A novel diagrammatic approach allows concise visual representations of the resonant NLO molecular response. By mapping the predicted NLO response as a function of molecular orientation, molecular modeling results can be combined with experimental measurements for orientational analysis. A method is developed and implemented to predict the nonlinear optical properties of the amide backbones in complete proteins with known structures. NLOPredict is available for most computer operating systems from http://sda.iu.edu/nlopredict/.