CDS&E: Development and applications of electronic structure methods for non-linear spectroscopy

南加州大学的安娜Krylov获得了化学系化学理论、模型和计算化学项目的奖项，以开发用于建模非线性光学（NLO）特性的理论方法和强大的计算工具。 CISE/ACI CIF 21软件重用风险基金和计算与数据科学与工程（CDS E）也为该奖项提供了资金。 Krylov和她的研究小组正在开发形式主义并实施计算方法，以计算耦合簇（CC）和运动方程（EOM）方法家族中双光子吸收（2 PA）的电子因子。 这些发展扩展了强大的和准确的EOM-CC方法来描述EOM属性。 为了使应用程序的现实系统（20-30原子，~1000基础功能），他们利用最近的方法，计算和软件的发展。 包括环境的影响（例如，蛋白质，溶剂，分子固体）对NLO性质的影响，他们采用了有效碎片势。 Krylov及其同事正在应用这些新的计算工具来询问决定用于体内成像的荧光蛋白发色团的2 PA亮度的因素。 这项研究促进了对新型光谱方法和技术中利用的非线性过程的基本理解。在本研究框架内开发的计算机代码将广泛提供给研究界，可用于设计更好的荧光标记，用于生物成像，以研究活系统中的细胞过程，光动力疗法和生物传感器。这些工具还可用于开发用于微制造、3D光学数据存储和纳米光刻、超快电光调制和开关以及各种其他新型纳米生物光子学应用的NLO材料。

Anna Krylov of the University of Southern California is supported by an award from the Chemical Theory, Models and Computational Chemistry program in the Chemistry Division to develop theoretical methods and robust computational tools for modeling non-linear optical (NLO) properties. The CISE/ACI CIF21 Venture Fund for Software Reuse and the Computational and Data-Enabled Science and Engineering (CDS&E) have also contributed to funding this award. Krylov and her research group are developing formalisms and implementing computational methods to compute electronic factors for two-photon absorption (2PA) within the coupled-cluster (CC) and equation-of-motion (EOM) family of methods. These developments extend the robust and accurate EOM-CC methodology to describe EOM properties. To enable applications to realistic systems (20-30 atoms, ~1000 basis functions), they capitalize on recent methodological, computational and software developments. To include the effect of the environment (e.g., protein, solvent, molecular solid) on NLO properties, they employ the Effective Fragment Potential. Krylov and coworkers are applying these new computational tools to interrogate factors determining 2PA brightness of chromophores of fluorescent proteins used for in vivo imaging. This research promotes fundamental understanding of non-linear processes that are exploited in novel spectroscopic approaches and technology. The computer codes developed in the framework of this research, which will be widely available to the research community, can used to design better fluorescent labels for using in bioimaging to study cellular processes in live systems, photodynamic therapy, and biosensors. These tools can also be used for developing NLO materials for micro-fabrication, 3D optical data storage and nanolithography, ultra-fast electro-optic modulation and switching, and a variety of other novel nano-bio-photonics applications.