Instrumentation for ultra-intense laser matter interaction studies at high repetition rates - Nedbailo, Ryan, author; Rocca, Jorge, advisor; Marconi, Mario, committee member; Yalin, Azer, committee member (Colorado State University. Libraries, 2022)
A new class of high-repetition rate (HRR) Peta-Watt-class (PW) laser systems make it possible to study laser matter interaction processes, like laser ion acceleration (LIA) and laser plasma instabilities (LPI), at unprecedented rates. These systems have the potential to generate immense amounts of data through rapid multivariable parameters scans of laser energy, pulse shape, spot size and others, in order to better diagnose and characterize the conditions underlying LPI and LIA. However, detection media, typically image plates, film, CR-39, presently limits the repetition rate at which data can be collected from these systems. Rep-rated diagnostics are being redesigned to match the capabilities of current multi-Hz present and near future, PW-class laser systems. Here we present the development of a compact Thomson Parabola Ion Spectrometer capable of characterizing various ion species of multi-MeV ion beams from >10^20 W/cm^2 laser produced plasmas at rates commensurate with the laser operation rates. This diagnostic makes use of a Polyvinyltoluene (PVT) based fast plastic scintillator (EJ-260), where the emitted light is collected by an optical imaging system coupled to a thermoelectrically cooled scientific complementary metal–oxide–semiconductor (sCMOS) camera. This offers a robust solution for data acquisition at HRR while avoiding the added complications and non-linearities of microchannel plate (MCP) based systems. Different ion energy ranges can be probed using the modular magnet setup, variable electric field, and a varying drift-distance. We have demonstrated operation and data collection with this system at up to 0.2 Hz from plasmas created by irradiating a solid target, limited only by the motorized target motion system. With the appropriate software and the use of machine learning techniques, on-the-fly ion spectral analysis will be possible, enabling real-time experimental control. The diagnostic design, calibration, and results from experiments at the ALEPH laser facility at Colorado State University (CSU) are presented. In addition, we describe the results of the development of a novel scheme for the generation of spike trains of uneven delay (STUD) laser pulses using an array of hexagonal mirrors. By individually driving the offset of each mirror segment, we can divide the wavefront of the laser creating a pulse train of arbitrary delay. This pulse-train forming device can be used to conduct experiments related to a proposed method of mitigating the effects of LPI for inertial confinement fusion (ICF). By periodically turning on and off the laser drive of the ICF process, it has been postulated that the growth of parametric instabilities can be mitigated by allowing damping during the off-cycle of the STUD pulses. The use of the pulse-train forming scheme demonstrated here will allow us to study the effects of pulse train delay and duration best suited to LPI mitigation.
Keywords: fusion; machine learning; diagnostic; plasma; laser