Analysis of Lithium Aging Using Machine Learning-Enhanced Spectroscopy Techniques.

Lithium compounds such as lithium hydride (LiH) and lithium hydroxide (LiOH) have a wide range of industrial applications, but are highly reactive in environments with H2O and CO2. These reactions lead to the ingrowth of secondary lithium compounds, which can alter the homogeneity and affect the application of particular lithium chemicals. This study performed an exploratory analysis of different lithium compounds using laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy. Machine learning models are trained on the recorded spectral data to discriminate emission features that differ between LiH, LiOH, and Li2CO3 to perform high-fidelity classification. Support vector machine classifiers yield perfect prediction accuracy between the three compounds with optimal training time. Multivariate methods are then used to produce regression models quantifying the ingrowth of LiOH in LiH. Performing a mid-level data fusion of selected LIBS and Raman features with partial least-squares regression produces the superlative model with a root mean square error of 2.5 wt% and a detection limit of 6.3 wt%.

Directional microwave emission from femtosecond-laser illuminated linear arrays of superconducting rings.

We examine the electromagnetic emission from two photo-illuminated linear arrays composed of inductively charged superconducting ring elements. The arrays are illuminated by an ultrafast infrared laser that triggers microwave broadband emission detected in the 1-26 GHz range. Based on constructive interference from the arrays a narrowing of the forward radiation lobe is observed with increasing element count and frequency demonstrating directed GHz emission. Results suggest that higher frequencies and a larger number of elements are achievable leading to a unique pulsed array emitter concept that can span frequencies from the microwave to the terahertz (THz) regime.

Machine learning in analytical spectroscopy for nuclear diagnostics [Invited].

Analytical spectroscopy methods have shown many possible uses for nuclear material diagnostics and measurements in recent studies. In particular, the application potential for various atomic spectroscopy techniques is uniquely diverse and generates interest across a wide range of nuclear science areas. Over the last decade, techniques such as laser-induced breakdown spectroscopy, Raman spectroscopy, and x-ray fluorescence spectroscopy have yielded considerable improvements in the diagnostic analysis of nuclear materials, especially with machine learning implementations. These techniques have been applied for analytical solutions to problems concerning nuclear forensics, nuclear fuel manufacturing, nuclear fuel quality control, and general diagnostic analysis of nuclear materials. The data yielded from atomic spectroscopy methods provide innovative solutions to problems surrounding the characterization of nuclear materials, particularly for compounds with complex chemistry. Implementing these optical spectroscopy techniques can provide comprehensive new insights into the chemical analysis of nuclear materials. In particular, recent advances coupling machine learning methods to the processing of atomic emission spectra have yielded novel, robust solutions for nuclear material characterization. This review paper will provide a summation of several of these recent advances and will discuss key experimental studies that have advanced the use of analytical atomic spectroscopy techniques as active tools for nuclear diagnostic measurements.

LIBS and Raman spectroscopy in tandem with machine learning for interrogating weatherization of lithium hydride.

Lithium compounds such as lithium hydride (L i H) and anhydrous lithium hydroxide (L i O H) have various applications in industry but are highly reactive when exposed to moisture and C O 2. These reactions create new molecular compounds that degrade applications. Environmental conditions such as temperature and moisture are examples of environmental conditions that are of interest for these reactions. To interrogate the effects of such weatherization, experiments were conducted in an environmental chamber (Plas-Labs 890-THC glove box) employing a pulsed laser and an echelle spectrograph in a novel single setup to conduct both Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS) in tandem. These measurements in conjunction with data fusion and machine learning techniques are used to develop training and testing of environmental conditioning of Li compounds. Modeling of environmental characterizations involving lithium-based compounds enabled by the presented measurements and analytical techniques has significant implications on industrial technologies, such as batteries, and other nuclear applications.

Laser Applications to Chemical, Security, and Environmental Analysis: introduction to the feature issue.

The eighteenth topical meeting on Laser Applications to Chemical, Security, and Environmental Analysis (LACSEA) was held in Vancouver, Canada from 11-15 July 2022, as part of the Optica Optical Sensors and Sensing Congress in a hybrid format allowing on-site and online attendance. The meeting featured a broad range of distinguished papers focusing on recent advances in laser and optical spectroscopy. A total of 52 contributed and invited papers were presented during the meeting, including topics such as photo-acoustic spectroscopy, imaging, non-linear technologies, frequency combs, remote sensing, environmental monitoring, aerosols, combustion diagnostics, hypersonic flow diagnostics, nuclear diagnostics, fs/ps applications, and machine learning and computational sensing.

Development of advanced machine learning models for analysis of plutonium surrogate optical emission spectra.

This work investigates and applies machine learning paradigms seldom seen in analytical spectroscopy for quantification of gallium in cerium matrices via processing of laser-plasma spectra. Ensemble regressions, support vector machine regressions, Gaussian kernel regressions, and artificial neural network techniques are trained and tested on cerium-gallium pellet spectra. A thorough hyperparameter optimization experiment is conducted initially to determine the best design features for each model. The optimized models are evaluated for sensitivity and precision using the limit of detection (LoD) and root mean-squared error of prediction (RMSEP) metrics, respectively. Gaussian kernel regression yields the superlative predictive model with an RMSEP of 0.33% and an LoD of 0.015% for quantification of Ga in a Ce matrix. This study concludes that these machine learning methods could yield robust prediction models for rapid quality control analysis of plutonium alloys.

Rapid quantitative analysis of trace elements in plutonium alloys using a handheld laser-induced breakdown spectroscopy (LIBS) device coupled with chemometrics and machine learning.

We present the first reported quantification of trace elements in plutonium via a portable laser-induced breakdown spectroscopy (LIBS) device and demonstrate the use of chemometric analysis to enhance the handheld device's sensitivity and precision. Quantification of trace elements such as iron and nickel in plutonium metal via LIBS is a challenging problem due to the complex nature of the plutonium optical emission spectra. While rapid analysis of plutonium alloys has been demonstrated using portable LIBS devices, such as the SciAps Z300, their detection limits for trace elements are severely constrained by their achievable pulse power and length, light collection optics, and detectors. In this paper, analytical methods are evaluated as a means to circumvent the detection constraints. Three chemometric methods often used in analytical spectroscopy are evaluated; principal component regression, partial least-squares regression, and artificial neural networks. These models are evaluated based on goodness-of-fit metrics, root mean-squared error, and their achievable limits of detection (LoDs). Partial least squares proved superior for determining content of iron and nickel in plutonium metal, yielding LoDs of 15 and 20 ppm, respectively. These results of identifying the undesirable trace elements in plutonium components are critical for applications such as fabricating radioisotope thermoelectric generators or nuclear fuel.

Time-Gated Single-Shot Picosecond Laser-Induced Breakdown Spectroscopy (ps-LIBS) for Equivalence-Ratio Measurements.

Time-gated picosecond laser-induced breakdown spectroscopy (ps-LIBS) for the determination of local equivalence ratios in atmospheric-pressure adiabatic methane-air flames is demonstrated. Traditional LIBS for equivalence-ratio measurements employ nanosecond (ns)-laser pulses, which generate excessive amounts of continuum, reducing measurement accuracy and precision. Shorter pulse durations reduce the continuum emission by limiting avalanche ionization. Furthermore, by contrast the use of femtosecond lasers, plasma emission using picosecond-laser excitation has a high signal-to-noise ratio (S/N), allowing single-shot measurements suitable for equivalence-ratio determination in turbulent reacting flows. We carried out an analysis of the dependence of the plasma emission ratio Hα (656 nm)/NII (568 nm) on laser energy and time-delay for optimization of S/N and minimization of measurement uncertainties in the equivalence ratios. Our finding shows that higher laser energy and shorter time delay reduces measurement uncertainty while maintaining high S/N. In addition to atmospheric-pressure flame studies, we also examine the stability of the ps-LIBS signal in a high-pressure nitrogen cell. The results indicate that the plasma emission and spatial position could be stable, shot-to-shot, at elevated pressure (up to 40 bar) using a lower excitation energy. Our work shows the potential of using ps-duration pulses to improve LIBS-based equivalence-ratio measurements, both in atmospheric and high-pressure combustion environments.

Measurement of electron density and temperature from laser-induced nitrogen plasma at elevated pressure (1-6 bar).

Laser-induced plasmas experience Stark broadening and shifts of spectral lines carrying spectral signatures of plasma properties. In this paper, we report time-resolved Stark broadening measurements of a nitrogen triplet emission line at 1-6 bar ambient pressure in a pure nitrogen cell. Electron densities are calculated using the Stark broadening for different pressure conditions, which are shown to linearly increase with pressure. Additionally, using a Boltzmann fit for the triplet, the electron temperature is calculated and shown to decrease with increasing pressure. The rate of plasma cooling is observed to increase with pressure. The reported Stark broadening based plasma diagnostics in nitrogen at high pressure conditions will be significantly useful for future studies on high-pressure combustion and detonation applications.

Simultaneous LIBS signal and plasma density measurement for quantitative insight into signal instability at elevated pressure.

Laser-induced breakdown spectroscopy (LIBS) evaluates the emission spectra of ions, radicals, and atoms generated from the breakdown of molecules by the incident laser; however, the LIBS signal is unstable at elevated pressures. To understand the cause of the signal instability, we perform simultaneous time-resolved measurements of the electron density and LIBS emission signal for nitrogen (568 nm) and hydrogen (656 nm) at high pressure (up to 11 bars). From correlations between the LIBS signal and electron number density, we find that the uncontrollable generation of excess electrons at high pressure causes high instability in the high-pressure LIBS signal. A possible method using ultrafast lasers is proposed to circumvent the uncontrolled electron generation and improve signal stability at high pressure.

All Fiber-Coupled OH Planar Laser-Induced-Fluorescence (OH-PLIF)-Based Two-Dimensional Thermometry.

Two-color, planar laser-induced fluorescence (PLIF)-based two-dimensional (2D) thermometry techniques for reacting flows, which are typically developed in the laboratory conditions, face a stiff challenge in their practical implementation in harsh environments such as combustion rigs. In addition to limited optical access, the critical experimental conditions (i.e., uncontrolled humidity, vibration, and large thermal gradients) often restrict sensitive laser system operation and cause difficulties maintaining beam-overlap. Thus, an all fiber-coupled, two-color OH-PLIF system has been developed, employing two long optical fibers allowing isolation of the laser and signal-collection systems. Two OH-excitation laser beams (∼283 nm and ∼286 nm) are delivered through a common 6 m long, 400 µm core, deep ultraviolet (UV)-enhanced multimode fiber. The fluorescence signal (∼310 nm) is collected by a 3 m long, UV-grade imaging fiber. Proof-of-principle temperature measurements are demonstrated in atmospheric pressure, near adiabatic, CH4/O2/N2 jet flames. The effects of the excitation pulse interval on fiber transmission are investigated. The proof-of-principle measurements show significant promise for thermometry in harsh environments such as gas turbine engine tests.

FLEET velocimetry for combustion and flow diagnostics.

We report the use of femtosecond laser electronic excitation tagging (FLEET) for velocimetry at a 100-kHz imaging rate. Sequential, single-shot, quantitative velocity profiles of an underexpanded supersonic nitrogen jet were captured at a 100-kHz rate. The signal and lifetime characteristics of the FLEET emission were investigated in a methane flame above a Hencken burner at varying equivalence ratios, and room temperature gas mixtures involving air, methane, and nitrogen. In the post-flame region of the Hencken burner, the emission lifetime was measured as two orders of magnitude lower than lab air conditions. Increasing the equivalence ratio above 1.1 leads to a change in behavior, with a doubled lifetime. By measuring the emission in a cold methane flow, a short-lived signal was measured that decayed after the first microsecond. As a proof of concept for velocimetry in a reacting environment, the exhaust of a pulsed detonator was measured by FLEET. Quantitative velocity information was obtained that corresponded to a maximum centerline velocity of 1800 m/s for the detonation wave. Extension of FLEET to larger scale, complex flow environments is now a viable option.

Sensitivity, stability, and precision of quantitative Ns-LIBS-based fuel-air-ratio measurements for methane-air flames at 1-11 bar.

Nanosecond laser-induced breakdown spectroscopy (ns-LIBS) is employed for quantitative local fuel-air (F/A) ratio (i.e., ratio of actual fuel-to-oxidizer mass over ratio of fuel-to-oxidizer mass at stoichiometry, measurements in well-characterized methane-air flames at pressures of 1-11 bar). We selected nitrogen and hydrogen atomic-emission lines at 568 nm and 656 nm, respectively, to establish a correlation between the line intensities and the F/A ratio. We have investigated the effects of laser-pulse energy, camera gate delay, and pressure on the sensitivity, stability, and precision of the quantitative ns-LIBS F/A ratio measurements. We determined the optimal laser energy and camera gate delay for each pressure condition and found that measurement stability and precision are degraded with an increase in pressure. We have identified primary limitations of the F/A ratio measurement employing ns-LIBS at elevated pressures as instabilities caused by the higher density laser-induced plasma and the presence of the higher level of soot. Potential improvements are suggested.

All-optically controlled concurrent slow-fast light pair.

We demonstrate how both normal and anomalous dispersion can be realized concurrently for a pair of weak probes in a doubly driven double-ladder configuration with independent and simultaneous control for group velocities of the pair. We have shown both analytically and numerically that, because of electromagnetically induced transparency and a χ((3))-based gain process, a slow-fast light pair can be realized in the same delay element with group indices ∼±10(7) accompanied by gain or relatively small absorption (down to ∼25%). We also identify parameter regions for realization of concurrent slow-slow and fast-fast light pairs with reduced absorptions.

Effects of collisions on electronic-resonance-enhanced coherent anti-Stokes Raman scattering of nitric oxide.

A six-level model is developed and used to study the effects of collisional energy transfer and dephasing on electronic-resonance-enhanced coherent anti-Stokes Raman scattering (ERE-CARS) in nitric oxide. The model includes the three levels that are coherently coupled by the three applied lasers as well as three additional bath levels that enable inclusion of the effects of electronic quenching and rotational energy transfer. The density-matrix equations that describe the evolution of the relevant populations and coherences are presented. The parametric dependencies of the ERE-CARS signal on collisional energy transfer and dephasing processes are described in terms of both a steady-state analytical solution and the numerical solutions to the governing equations. In the weak-field limit, the ERE-CARS signal scales inversely with the square of the dephasing rates for the electronic and Raman coherences. In accord with published experimental observations [Roy et al., Appl. Phys. Lett. 89, 104105 (2006)], the ERE-CARS signal is shown to be insensitive to the collisional quenching rate. Parametric dependencies on quenching, rotational energy transfer, and pure electronic dephasing are presented, demonstrating reduced collisional dependence for saturating laser fields.

Perturbative theory and modeling of electronic-resonance-enhanced coherent anti-Stokes Raman scattering spectroscopy of nitric oxide.

A theory is developed for three-laser electronic-resonance-enhanced (ERE) coherent anti-Stokes Raman scattering (CARS) spectroscopy of nitric oxide (NO). A vibrational Q-branch Raman polarization is excited in the NO molecule by the frequency difference between visible Raman pump and Stokes beams. An ultraviolet probe beam is scattered from the induced Raman polarization to produce an ultraviolet ERE-CARS signal. The frequency of the ultraviolet probe beam is selected to be in electronic resonance with rotational transitions in the A (2)Sigma(+)<--X (2)Pi (1,0) band of NO. This choice results in a resonance between the frequency of the ERE-CARS signal and transitions in the (0,0) band. The theoretical model for ERE-CARS NO spectra has been developed in the perturbative limit. Comparisons to experimental spectra are presented where either the probe laser was scanned with fixed Stokes frequency or the Stokes laser was scanned with fixed probe frequency. At atmospheric pressure and an NO concentration of 100 ppm, good agreement is found between theoretical and experimental spectral peak locations and relative intensities for both types of spectra. Factors relating to saturation in the experiments are discussed, including implications for the theoretical predictions.

Controlled parametric generation in a double-ladder system via all-resonant four-wave mixing.

We demonstrate parametric generation of a new coherent field with a polarization orthogonal to the signal field via an all-resonant four-wave mixing process in a double-ladder system. We show that the generation of the coherent field is an efficient resonantly enhanced process that can be realized with a fairly dilute medium and relatively weak drive fields. The large parameter domain that exists in this system provides good control for both the weak probe and the generated field. Potential applications in optical communication are outlined.