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DOE OSTI2023

Exploration of LIBS as a novel and rapid elemental mapping technique of nuclear fuels in the form of surrogate TRISO particles

Laser-induced breakdown spectroscopy (LIBS) was employed to characterize coatings on surrogate fuel particles. Tri-structural isotropic (TRISO) particles are a proposed nuclear fuel alternative for high temperature reactors. These particles are constructed of a ZrO 2 kernel (as a surrogate to uranium), surrounded by an inner pyrolytic carbon layer and are surrounded by an outer carbide layer (ZrC, presented here) to act as a barrier to fission products generated during nuclear reactions. These particles are embedded within a graphite compact and housed within the reactor core. Simply put, due to their robust nature, performing elemental analysis of these particles poses a challenge. Presented here, LIBS is explored as a method for characterizing elemental constituents of these particles, with the focus being on rapid elemental mapping and depth profiling. Different from traditional elemental analysis techniques (e.g., inductively coupled plasma – based methods), LIBS is advantageous because it can directly analyze the sample surface and can detect light elements such as C and O, making it a viable technique for the analysis of small, multilayered particles as spatial elemental information is warranted in the production of these particles. In the work presented here, LIBS was successfully used for discerning small layers (30–50 μm), detecting the location of carbon and oxygen layers, providing fast 2-D mapping (<5 min per particle) and rapid depth profiling (10 s per particle).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Fungal elemental profiling unleashed through rapid laser-induced breakdown spectroscopy (LIBS)

Elemental profiling of fungal species as a phenotyping tool is an understudied topic and is typically performed to examine plant tissue or non-biological materials. Traditional analytical techniques such as inductively coupled plasma–optical emission spectroscopy (ICP-OES) and inductively coupled plasma–mass spectrometry (ICP-MS) have been used to identify elemental profiles of fungi; however, these techniques can be cumbersome due to the difficulty of preparing samples. Additionally, the instruments used for these techniques can be expensive to procure and operate. Laser-induced breakdown spectroscopy (LIBS) is an alternative elemental analytical technique—one that is sensitive across the periodic table, easy to use on various sample types, and is cost-effective in both procurement and operation. LIBS has not been used on axenic filamentous fungal isolates grown in substrate media. In this work, as a proof of concept, we used LIBS on two genetically distinct fungal species grown on a nutrient-rich and nutrient-poor substrate media to determine whether robust elemental profiles can be detected and whether differences between the fungal isolates can be identified. This data set contains the raw LIBS spectral data for the summarized results described inRush, et. al. 2024

elemental profiling↗

DOE OSTI2023

Rapid in situ nutrient element distribution in plants and soils using laser-induced breakdown spectroscopy ($\mathrm{LIBS}$)

The aim of this study is to develop and test the applicability of a rapid in situ plant chemistry profiling technique to determine elemental composition of small-volume plant and soil samples obtained from a woody bioenergy crop species, Populus trichocarpa. Expanding the research tools available to characterize the nutrient element correlations among plant tissue types and soil depths is a critical need in the path of understanding productivity and adaptation of plants to variations in external abiotic and biotic factors and developing sustainable perennial bioenergy crops that are co-optimized for biomass valorization aboveground and carbon sequestration belowground. Several plant root, stem, and soil samples were tested using laser-induced breakdown spectroscopy (LIBS) to evaluate the presence and distribution of nutrient elements. Samples were tested as collected and after being dried and cross sectioned to evaluate the effectiveness of using LIBS for in situ analysis on plant samples. The collected LIBS spectra show the elemental peaks were the same in both the as collected and prepared samples for roots and stems. Qualitative amounts of elements such as H, C, N, O, Li, Na, Mg, K, Ca, Fe, Al, and Si were able to be identified rapidly in raw samples. Here in this report we demonstrate suitability of LIBS in obtaining rapid, in situ, elemental distribution in plant and soil samples, utilizing only small sample volumes and minimal sample preparation. This demonstration opens up a new rapid phenotyping avenue necessary to fill the asymmetrical knowledge gaps in belowground performance of plant systems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks

LIBS−ML framework for real time feedstock characterization during continuous conveyor transport Heterogeneous waste derived feedstocks (e.g., waste coal, biomass and blends) introduce rapid variability in heating value and ash chemistry that affect gasifier operation, yet conventional laboratory characterization techniques are too slow to support proactive control. To address this gap, this study reports on an online, in situ, dynamic characterization framework that couple’s laser-induced breakdown spectroscopy (LIBS) with leakage safe machine learning (ML) regression to deliver real time, decision quality predictions of gasifier relevant properties. A controlled sample matrix spanning two different waste coals, two different biomasses, and engineered blends under two particle size conditions were constructed and benchmarked using standardized laboratory analyses for proximate/ultimate properties and ash composition. LIBS spectra were acquired dynamically as material flowed on a conveyor belt, using high energy 1064 nm laser ablation and shot averaging to improve repeatability and precision. Supervised regression models (multi layer perceptron (MLP) /artificial neural network (ANN), random forest (RF), and support vector regression (SVR)) and an optimized weighted ensemble were trained on emission line feature sets using nested cross validation with Bayesian hyperparameter tuning and validated against an independent hold out set. The proposed LIBS−ML workflow achieves near laboratory predictive fidelity across parametric targets (including higher heating value (HHV), ash content, fixed carbon, sulfur, major ash forming oxides, and initial deformation temperature (IDT)), with the weighted ensemble providing a robust default predictor under dynamic measurement conditions. These results demonstrate a practical pathway for real time feedstock characterization that can enable feedforward adjustments and more resilient gasifier operation for variable quality waste derived fuels.

Biomass↗

NASA NTRS2010

Partial Least Squares and Neural Networks for Quantitative Calibration of Laser-induced Breakdown Spectroscopy (LIBs) of Geologic Samples

The ChemCam instrument [1] on the Mars Science Laboratory (MSL) rover will be used to obtain the chemical composition of surface targets within 7 m of the rover using Laser Induced Breakdown Spectroscopy (LIBS). ChemCam analyzes atomic emission spectra (240-800 nm) from a plasma created by a pulsed Nd:KGW 1067 nm laser. The LIBS spectra can be used in a semiquantitative way to rapidly classify targets (e.g., basalt, andesite, carbonate, sulfate, etc.) and in a quantitative way to estimate their major and minor element chemical compositions. Quantitative chemical analysis from LIBS spectra is complicated by a number of factors, including chemical matrix effects [2]. Recent work has shown promising results using multivariate techniques such as partial least squares (PLS) regression and artificial neural networks (ANN) to predict elemental abundances in samples [e.g. 2-6]. To develop, refine, and evaluate analysis schemes for LIBS spectra of geologic materials, we collected spectra of a diverse set of well-characterized natural geologic samples and are comparing the predictive abilities of PLS, cascade correlation ANN (CC-ANN) and multilayer perceptron ANN (MLP-ANN) analysis procedures.

Anderson, R. B.↗

NASA NTRS2014

Relationship between LIBS Ablation and Pit Volume for Geologic Samples: Applications for in situ Absolute Geochronology

In planetary sciences, in situ absolute geochronology is a scientific and engineering challenge. Currently, the age of the Martian surface can only be determined by crater density counting. However this method has significant uncertainties and needs to be calibrated with absolute ages. We are developing an instrument to acquire in situ absolute geochronology based on the K‐Ar method. The protocol is based on the laser ablation of a rock by hundreds of laser pulses. Laser Induced Breakdown Spectroscopy (LIBS) gives the potassium content of the ablated material and a mass spectrometer (quadrupole or ion trap) measures the quantity of 40Ar released. In order to accurately measure the quantity of released 40Ar in cases where Ar is an atmospheric constituent (e.g., Mars), the sample is first put into a chamber under high vacuum. The 40Arquantity, the concentration of K and the estimation of the ablated mass are the parameters needed to give the age of the rocks. The main uncertainties with this method are directly linked to the measures of the mass (typically some μg) and of the concentration of K by LIBS (up to 10%). Because the ablated mass is small compared to the mass of the sample, and because material is redeposited onto the sample after ablation, it is not possible to directly measure the ablated mass. Our current protocol measures the ablated volume and estimates the sample density to calculate ablated mass. The precision and accuracy of this method may be improved by using knowledge of the sample's geologic properties to predict its response to laser ablation, i.e., understanding whether natural samples have a predictable relationship between laser energy deposited and resultant ablation volume. In contrast to most previous studies of laser ablation, theoretical equations are not highly applicable. The reasons are numerous, but the most important are: a) geologic rocks are complex, polymineralic materials; b) the conditions of ablation are unusual (for example, variable vacuum pressure), and c) the ablation is made with hundreds of successive laser pulses. In this work, we aim to understand the effects that occur on LIBS spectra when a homogeneous rock or a mineral is ablated under high vacuum. Understanding these effects is important to define best practices for LIBS measurements and may lead to improved measurement (or possibly prediction) of the ablated volume. We will describe our laboratory approach and first results, and discuss its utility for situ absolute geochronology campaigns.

Devismes, D.↗

DOE OSTI2022

Neptunium transition probabilities estimated through laser induced breakdown spectroscopy (LIBS) measurements

in tis report calibration free–laser induced breakdown spectroscopy (CF-LIBS) approaches are promising for the analysis of radioactive materials; however, a lack of reported fundamental properties for these materials is an obstacle to implementation. Spectra of laser induced plasmas containing Np and Sr, along with Saha–Boltzmann methods, were used to estimate the first reported transition probabilities (TPs) of Np. These TPs enabled the first attempt at CF-LIBS analysis of radioactive samples to predict Np/Sr ratios with a mean error of 3.86%. The presented methodology of TP estimation will be applied to the study of other actinides and allow broader applications of CF-15 LIBS in the nuclear field.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

LIBS Applications to Liquids and Solids in Liquids

In this chapter, LIBS instrumentation and data collection system used for the analysis of liquids and solids in liquids are discussed. LIBS measurements of bulk liquid samples and solids submerged in aqueous media, measurements made by focusing laser pulses on liquid surfaces, and measurements of liquids after various sample treatments are presented. In addition, the working mechanism of NETL‐developed field‐deployable LIBS sensor and its preliminary performance in field measurements are also reported.

atomic emission spectroscopy↗

DOE OSTI2022

Radiative transition probabilities of neutral and singly ionized Europium estimated by laser-induced breakdown spectroscopy (LIBS)

Laser-induced breakdown spectroscopy (LIBS) is a versatile technique for compositional analysis for solids, liquids, or gasses. LIBS is an asset for the quantitative or qualitative analysis of resource limited materials like actinides and rare earths because it is quasi-nondestructive. Two Eu 2 O 3 pellets were synthesized to be a test and validation set, respectively. Spectral lines identified from the National Institute of Standards and Technology database with fundamental data reported were used to form Saha-Boltzmann plots. The Saha-Boltzmann plots were used to determine the plasma temperatures and electron densities of the laser-induced plasmas for both samples. These Saha-Boltzmann plots were then used to calculate previously unreported transition probabilities associated with identified peaks. Additionally, the transition probabilities presented in this paper provide the capability for calibration free LIBS to be performed more readily on europium samples and the spectroscopic analysis of stellar bodies. Eight previously unreported transition probabilities are presented in this paper; five for Eu I and three for Eu II. The transition probabilities for Eu I ranged from 0.172 to 7.38 × 10 7 s -1 and those for Eu II ranged from 1.56 to 6.75 × 10 7 s -1 .

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Exploration of a Combined LIBS and LA-ICP-MS Approach for Apatite Characterisation

A combined laser‐induced breakdown spectroscopy (LIBS) and laser ablation‐inductively coupled plasma‐mass spectrometry (LA‐ICP‐MS) method is demonstrated for comprehensive apatite analysis. These measurements provide elemental imaging that can be used as a screening technique for chemical selection of grains for subsequent analysis (e.g., U‐Pb geochronology) or can be used to understand elemental distributions within a single grain that would have direct textural‐chemical implications (e.g., zoning patterns). Adding LIBS as a simultaneous measurement, to LA‐ICP‐MS U‐Pb geochronology, allowed for the direct determination of F (H and O show promise for future applications) in addition to major and trace elements of interest. Here, the quantitative measurements were validated against a series of apatites with known values and used to characterise a wide range of samples. Fluorine detection limits were determined to be as low as 70 μg g ‐1 F (broadband CMOS detector) and 4.2 μg g ‐1 F (ICCD detector). U‐Pb age dating was simultaneously collected by LA‐ICP‐MS with the quantitative elemental data from LIBS, providing a comprehensive method for geochronology.

Apatite↗

DOE OSTI2025

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

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

Here, 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.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBs

The increasing demand for lithium-ion batteries (LIBs) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as well as waste production as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCAM). For this project, two samples of high purity recycled NMC hydroxide (~1 kg each) were received from N th Cycle’s Ohio demonstration facility. The NMC compositions of the two materials are similar, and the levels of impurities have been confirmed. Indeed, impurities like copper, boron and sodium are present in quantities that could negatively impact battery performance. However, some studies have demonstrated that the control of the quantity of elements like copper or boron may improve the electrochemistry properties of Lithium-NMC batteries. The principal objective is to determine the electrochemical performance of these 2 NMC hydroxide batches and clearly determine the effect of the impurities on the performance.

25 ENERGY STORAGE↗

NASA NTRS2018

Determination of Trace Silicone Contamination on Composites by Quantitative XPS and LIBS

Surface treatment and surface characterization techniques are critical to ensure that adherends are chemically activated and free of contaminants prior to adhesive bonding. Silicone contamination from mold-release agents and other sources can interfere with interfacial bonding, decreasing the durability and performance of bonded composite structures. Tools and methods are needed that can be used in a production environment to reliably detect low levels of contaminants in a rapid, simple, and cost-effective manner to improve bond reliability. In this work, surface characterization of carbon fiber reinforced polymer (CFRP) composites was performed using laser induced breakdown spectroscopy (LIBS) and the results were compared with those obtained from X-ray photoelectron spectroscopy (XPS). The objective was to investigate the ability to quantify the surface species measured by LIBS since it offers many advantages over XPS in terms of ease of use, sample preparation, and real-time results. The as-processed CFRP panels had trace surface silicone contamination from the fabrication process, the source of which was not investigated. The composites were laser treated at select average laser power levels, resulting in varying levels of contamination reduction. The Si atomic percentage measurements using XPS were conducted both before and after laser ablation. The XPS results were compared with those obtained from LIBS to assess the reliability of each technique for surface contaminant characterization. The results showed an excellent correlation in Si atomic concentration between the two techniques.

Ledesma, Rodolfo↗

NASA NTRS2020

A Review of LIBS for Real-Time Detection of Trace Silicone Contaminants on CFRP Surfaces

Laser ablation is the removal of material by laser pulses through photochemical, photothermal, or photophysical mechanisms, which is useful to prepare an adherend surface for adhesive bonding. Laser surface treatment is a method that has been under research for the past decade at NASA Langley Research Center (LaRC) to prepare surfaces for adhesive joining of aerospace composite materials and metallic alloys. Laser ablation of composite materials increases surface area and removes the surface contaminants introduced during material handling and fabrication processes. By adjustment of laser parameters, it is possible to obtain repeatable surface conditions, and superficial contaminants can be selectively and efficiently removed without damaging the underlying carbon fibers or the carbon fiber reinforced polymer (CFRP) substrate. Laser induced breakdown spectroscopy (LIBS) is a surface characterization and inspection technique that can be seamlessly integrated into the laser surface treatment process. At NASA LaRC, a single laser system has been used for both laser surface treatment and LIBS, which enables in-situ monitoring of surface contaminants. This work focuses on the advancements at LaRC using LIBS to detect surface silicone contaminants on aerospace CFRP materials and to provide surface quality control in adhesive bonding.

Rodolfo I Ledesma↗

NASA NTRS2020

A Review of LIBS for Real-Time Detection of Trace Silicone Contaminants on CFRP Surfaces

Rodolfo I Ledesma↗

DOE OSTI2025

Rapid characterization of MSW and RDF feedstocks for waste-to-energy process using LIBS and ML techniques

The heterogeneity in the composition of municipal solid wastes (MSW) poses significant challenges in the production of biofuel and bioproducts. This research aims to enhance the accuracy and efficiency of waste analysis and characterization by introducing a fast characterization approach for MSW-derived refuse-derived fuels (RDF) by combining Laser-Induced Breakdown Spectroscopy (LIBS) with advanced machine learning (ML) techniques. The approach combines data pre-processing of LIBS spectra of RDF, and the development of ML models trained on domain and theory-based spectral features for predicting process parameters. These models are adept at predicting key process parameters like High Heating Value (HHV), carbon content, and volatile matter. This approach can achieve an average RRMSE of 2.13% and R 2 of 0.98 or higher for all considered parameters on testing data. This work demonstrates significant potential for improving waste sorting, processing efficiency, and environmental compliance over traditional labor- and time-intensive laboratory waste analysis and characterization.

09 BIOMASS FUELS↗

DOE OSTI2024

Electrochemical leaching of spent LIBs: Kinetics, novel reactor, and modeling

The use of electrons as main reagent for the recovery and recycling of critical metals from spent lithium-ion batteries (LIBs) is a process electrification strategy that can be used to close the life-cycle loop of LIBs through more sustainable methods. Electrochemical leaching, a process that uses a reductant that is constantly regenerated electrochemically for the leaching of lithium-ion battery black mass (LIBBM), has shown high extraction efficiencies and sustainable scores. However, slow kinetics, reactor design challenges and lack of deeper understanding of the underlying processes are barriers to the optimization, scale-up, and market adoption of this technology. In this paper, a kinetic study and mathematical model for dissolving LIBBM is presented to better understand the underlying mechanisms aiming to reduce the processing time and make predictions for future design and scale-up. The effect of acid and electrochemically mediated reductant concentrations, LIBBM loading, and cathode/reactor designs were explored. As a result, the leaching time was reduced from 7h to under 1h at a pulp density of 73 g/L, without external heating. A novel reactor with parallel baffle electrodes (PBE) was developed, which significantly reduced the leaching time by improving convection in a stirred slurry electrochemical reactor. Dimensionless numbers were deduced from an unsteady state model, which can be used in dimensional analysis for future process design and scale-up.

25 ENERGY STORAGE↗