Mycobacterium abscessus is a non-tuberculous mycobacterial (NTM) species that causes severe pulmonary infections, particularly in immunocompromised patients and those with preexisting lung diseases such as cystic fibrosis. Treating M. abscessus infections is challenging due to its intrinsic antibiotic tolerance and capacity to develop multidrug resistance. To identify novel molecules that can target this pathogen and enhance current treatments, we screened a library of FDA-approved drugs (n = 2,400). Our data shows that Netupitant, a drug commonly used to prevent chemotherapy-induced nausea and vomiting, exhibits potent antibacterial activity against a broad range of M. abscessus clinical isolates, including multidrug-resistant strains, with a minimum inhibitory concentration (MIC) ranging from 4 to 16 µg/mL. Furthermore, in combination with amikacin, a standard treatment for M. abscessus infections, Netupitant demonstrated strong synergistic interactions, as confirmed by checkerboard microdilution and time-kill assays. These findings highlight Netupitant’s potential as a novel therapeutic option for M. abscessus, particularly in combination with existing antibiotics. Future studies exploring its mechanism of action and in vivo efficacy could further advance antibacterial drug discovery for difficult-to-treat NTM infections.

Optical metasurfaces used in nanophotonic devices are designed and optimized to display remarkable emergent photonic properties beyond what is possible for single-component materials. Traditionally, metasurfaces are designed in response to a particular incident angle of light impinging on its surface. However, in practice these metasurfaces have limited functionality if the incident angle varies. A metamaterial whose function is independent of incident angle would overcome this limitation and be more efficient in practice. For example, angle independent metamaterials that trap light in solar panels can function efficiently for all solar positions. Because a forward approach of screening many candidate materials through trial-and-error is time-consuming and expensive, in this poster we instead employ an inverse computational-based design strategy. We develop a strategy to optimize geometry/dielectric design of nanoparticles (NPs) metamaterials that have an optical response independent of angle of incidence of light. We leverage a computationally efficient and differentiable electromagnetic simulator based on couple dipole methods, the “mutual polarization method”, to perform numerical optimization of these materials. By encoding multiple incident angles and polarization states into an objective function, we ensure that the optimizer reduces the angle-variation of the metamaterials it designs. We use our inverse design tool to create multilayer plasmonic nanoparticle films, whose extinction spectra are insensitive to incident angle and polarization. We also show that we can use our inverse design method to control the spectral line shape of these NP films. Our inverse methodology will greatly accelerate the development time to synthesize new nanophotonic materials.

As the demand for electronics increases, so does the need for efficient recycling methods of electronic waste. The goal of electronic waste recycling is to recover critical metal components that can be used again in future electronics. However, a key challenge is selective separation of metal component mixtures into pure phases. My research in Dr. Zachary Sherman’s lab studies a promising and low-energy solution to this problem involving magnetic separation using external magnets and magnetic fields. Many precious metal ions are magnetizable in the presence of an external magnetic field, and therefore metal ion mixtures can be separated magnetophoretically by taking advantage of differences in their magnetic susceptibility. Using Brownian dynamic simulations to model transport of metal ion mixtures, I have quantified the magnetophoretic separation efficiencies of mixtures of paramagnetic, diamagnetic, and nonmagnetic ions mixtures when exposed to an external magnetic field. I have investigated how separation efficiency is affected by a variety of physical parameters including the strength of the external magnetic field, relative concentrations of ion species, strength of interactions among ions, and the magnetic susceptibilities. I also show that hydrodynamic flows generated by ion motion as well as ion structuring and aggregation have an enormous impact on separation efficiency. These results will guide further research to determine the optimal conditions for selective separation and purification of metal components.