Rishabh Datta is a PhD candidate in the department of Mechanical Engineering at Massachusetts Institute of Technology. As a research assistant at MIT's Plasma Science & Fusion Center, Rishabh works on high-energy-density pulsed-power driven plasmas. His areas of focus are magnetized shocks and radiatively-cooled magnetic reconnection. Click here for Rishabh's CV.
Rishabh Datta is a PhD candidate in the department of Mechanical Engineering at Massachusetts Institute of Technology. As a research assistant at MIT's Plasma Science & Fusion Center, Rishabh works on high-energy-density pulsed-power driven plasmas. His areas of focus are magnetized shocks and radiatively-cooled magnetic reconnection. Click here for Rishabh's CV.
Laboratory Astrophysics and Magnetized Plasmas
Reconnection occurs in a radiatively-cooled regime in many astrophysical plasmas, such as black hole accretion disks and their coronae, pulsar magnetospheres, and gamma-ray bursts. Our experiments on the Z Machine were the first to access a regime that shows both plasmoid formation and strong cooling. X-ray and visible spectroscopy, X-ray imaging, X-ray diodes and inductive probes were used to characterize the experiments, which were supplemented with three-dimensional resistive magnetohydrodynamic simulations of the experiment.
The adibatic index determines the amount of compression that shocks can generate, which is important in inertial and magneto-inertial confinement fusion. This project, awarded the ZNetUS-2024 grant, aims to measure the adibatic index in magnetized plasmas.
Magnetized shocks occur in both inertial confinement fusion plasmas, and in astrophysical systems. Our experiments show anisotropy in the shock structure, with a larger opening angle in the plane parallel to the magnetic field.
Computation and Numerical Modeling
We run resitive MHD simulations using GORGON to model a variety of physics, including radiative-cooling and guide field effect in reconnection experiments, planar wire arrays, and bow shocks.
Radiation transport modeling is necessary for interpreting visible or X-ray spectrosocpy data. Our radiation transport solver, which uses emissivity and opacity data computed using PrismSPECT or SCRAM, can be used to generate synthetic spectroscopic data.
Plasma Diagnostics, Optimization, and Machine Learning
Spectroscopy analysis can be time-consuming and computationally expensive for large datasets. Using machine learning, we can significanly reduce the time required to analyze spectroscopy data without a loss in prediction accuracy.
Commonly-used plasma diagnostics, such as interferometry or self-emission imaging, provide line-integrated views of the plasma along limited lines of sight. Using tomography, we can reconstruct the 3D structure of reconnection layers, z-pinches, and shocks.
We show that through simultaneous bow shock imaging and inductive probe measurements, velocity and temperature of the plasma can be measured using a cheap easy-to-implement diagnostic.
Photonics and Optical Modeling
The properties of electromagnetic waves in magnetized plasmas can be used to design tunable metamaterials, such as plasma lenses, polarizers, and waveguides. We explore this using ray-tracing and Fourier optics.
Surface plasmon polaritons, which emerge from the oscillation of surface plasma in metals, propagate at interfaces between media, typically between a metal and a dielectric medium. SPPs excited on metal-anisotropic dielectric surfaces can have potential applications in the areas of anisotropic and angle dependent sensing, tunable surface plasmon resonance, and directional SPP or signalexcitation and propagation. This project explores anisotropic SPPs using theoretical and FDTD simulations in Lumerical.
Negative index materials can be used to create tunable photonic band gaps that are robust to randomness and defects.