Deep Spectroscopy Lab

Spectroscopy allows one to probe the time evolution of quantum states so as to reveal the underlying structure of molecules at a fundamental level. Following in the footsteps of nuclear magnetic resonance (NMR) spectroscopy, which is capable of elucidating structure of complex molecules in solution, multi-dimensional coherent spectroscopy (MDCS) holds the potential to reveal inter- and intramolecular couplings that are hidden in one-dimensional spectroscopic methods.

Combining spatial, temporal, and spectral resolution is critical to uncovering the basic photo-physics of carrier generation and relaxation in a large class of materials such as 2D and 3D perovskites and other semi-conductor materials. We are pushing the boundaries of what is possible to achieve sub-diffraction resolution along with high-resolution chemical and dynamical information. Big data approaches are implemented to analyze large, multi-dimensional data from such measurements.

Materials discovery lags far behind other technological areas where machines assist humans in making complex decisions. While big data approaches have long been recognized as vital to the development of advanced materials, the current challenge is the lack of high-volume and high-quality data. We are combining robotic synthesis, rapid characterization and data reduction, with AI to rapidly search large regions of chemical and physical space towards new means of efficient materials discovery.

Rapid identification and analysis of complex chemical and biological targets represents an important goal in standoff sensing. However, remote sensing is often hampered by detrimental effects of obscurants that may dramatically reduce image quality in standoff detection scenarios. We are developing nonlinear optical methods that can overcome these challenges to obtain high-contrast images even in challenging environments

Our group is interested in understanding the implications of architecture and organization on energy transport. Previously, we modeled energy transfer in large assemblies of LH2-like complexes, which are important in certain photosynthetic organisms. We have also studied the role of topology on energy transfer and devised strategies that may improve efficiency in artifical systems that harvest and transduce light.

We are always in search of new ideas and collaborations. Our research interests are at the intersection of chemistry, biology, physics, and engineering. Current interests include real-time analysis of 3D printed biopharmaceuticals, AI-enabled nonlinear spectrosocpy of live cells, super-resolution microscopy, single-molecule nonlinear spectroscopy, and deep learning approaches to multi-dimensional spectral analysis.