Development of Non-Linear Laser-Based Imaging Techniques for Diagnostics of Reactive Flows

Understanding reactive flows is crucial for advancing energy production, combustion efficiency, and plasma- assisted chemical processes. These systems often involve short-lived radicals and transient phenomena that require high-resolution, non-intrusive diagnostic techniques for accurate characterization. This thesis focuses on the development of advanced non-linear laser-based imaging methods to achieve such diagnostics with improved spatial and temporal precision. A primary challenge in laser diagnostics is the detection of short-lived radicals, such as atomic oxygen (O), which plays a critical role in combustion and plasma chemistry. Traditional two-photon laser-induced fluorescence (TPLIF) has been instrumental in probing these species, but its effectiveness is often limited by weak signals and interference from background light. To address these limitations, this work introduces Light-field Amplitude Control (LAC), a novel laser modulation strategy that enhances signal clarity and measurement precision by act- ively controlling the spatial and temporal characteristics of the excitation field. After LAC is introduced and experimentally characterized, it is subsequently applied to plasma and combustion environments, where it significantly enhances TPLIF signals while suppressing unwanted background emissions. Using LAC, this thesis demonstrates single-shot imaging of atomic oxygen in turbulent flames and plasma dis- charges at atmospheric pressure, enabling real-time analysis of oxygen distribution and chemical reaction dynamics. Additionally, the work explores air lasing as an alternative high-intensity, coherent emission process for radical detection, providing new insights into its underlying physics and potential applications in advanced spectroscopy. These advancements in laser-based diagnostics pave the way for more accurate and quantitative imaging of reactive species, benefiting both fundamental research and industrial applications. The techniques developed in this work contribute to fields such as plasma-assisted combustion, chemical manufacturing, and clean energy production, where precise knowledge of radical distributions is critical. Ultimately, these findings align with the broader goal of developing efficient, sustainable technologies to mitigate climate impact and optimize energy use.