Examining natural rock varnish and weathering rinds with laser-induced breakdown spectroscopy for application to ChemCam on Mars

Analysis of Rock Varnish from the Mojave Desert by Handheld Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) is a form of optical emission spectroscopy that can be used for the rapid analysis of geological materials in the field under ambient environmental conditions. We describe here the innovative use of handheld LIBS for the in situ analysis of rock varnish. This thinly laminated and compositionally complex veneer forms slowly over time on rock surfaces in dryland regions and is particularly abundant across the Mojave Desert climatic region of east-central California (USA). Following the depth profiling examination of a varnished clast from colluvial gravel in Death Valley in the laboratory, our in situ analysis of rock varnish and visually similar coatings on rock surfaces was undertaken in the Owens and Deep Spring valleys in two contexts, element detection/identification and microchemical mapping. Emission peaks were recognized in the LIBS spectra for the nine elements most abundant in rock varnish-Mn, Fe, Si, Al, Na, Mg, K, Ca and Ba, as well as for H, Li, C, O, Ti, V, Sr and Rb. Focused follow-up laboratory and field studies will help understand rock varnish formation and its utility for weathering and chronological studies.

An ecophysiological explanation for manganese enrichment in rock varnish

Rock varnish is a prominent feature of desert landscapes and the canvas for many prehistoric petroglyphs. How it forms—and, in particular, the basis for its extremely high manganese content—has been an enduring mystery. The work presented here establishes a biological mechanism for this manganese enrichment, underpinned by an apparent antioxidant strategy that enables microbes to survive in the harsh environments where varnish forms. The understanding that varnish is the residue of life using manganese to thrive in the desert illustrates that, even in extremely stark environments, the imprint of life is omnipresent on the landscape.

Desert varnish is a dark rock coating that forms in arid environments worldwide. It is highly and selectively enriched in manganese, the mechanism for which has been a long-standing geological mystery. We collected varnish samples from diverse sites across the western United States, examined them in petrographic thin section using microscale chemical imaging techniques, and investigated the associated microbial communities using 16S amplicon and shotgun metagenomic DNA sequencing. Our analyses described a material governed by sunlight, water, and manganese redox cycling that hosts an unusually aerobic microbial ecosystem characterized by a remarkable abundance of photosynthetic Cyanobacteria in the genus Chroococcidiopsis as the major autotrophic constituent. We then showed that diverse Cyanobacteria, including the relevant Chroococcidiopsis taxon, accumulate extraordinary amounts of intracellular manganese—over two orders of magnitude higher manganese content than other cells. The speciation of this manganese determined by advanced paramagnetic resonance techniques suggested that the Cyanobacteria use it as a catalytic antioxidant—a valuable adaptation for coping with the substantial oxidative stress present in this environment. Taken together, these results indicated that the manganese enrichment in varnish is related to its specific uptake and use by likely founding members of varnish microbial communities.

The SuperCam Instrument Suite on the NASA Mars 2020 Rover: Body Unit and Combined System Tests

The SuperCam instrument suite provides the Mars 2020 rover, Perseverance, with a number of versatile remote-sensing techniques that can be used at long distance as well as within the robotic-arm workspace. These include laser-induced breakdown spectroscopy (LIBS), remote time-resolved Raman and luminescence spectroscopies, and visible and infrared (VISIR; separately referred to as VIS and IR) reflectance spectroscopy. A remote micro-imager (RMI) provides high-resolution color context imaging, and a microphone can be used as a stand-alone tool for environmental studies or to determine physical properties of rocks and soils from shock waves of laser-produced plasmas. SuperCam is built in three parts: The mast unit (MU), consisting of the laser, telescope, RMI, IR spectrometer, and associated electronics, is described in a companion paper. The on-board calibration targets are described in another companion paper. Here we describe SuperCam's body unit (BU) and testing of the integrated instrument. The BU, mounted inside the rover body, receives light from the MU via a 5.8 m optical fiber. The light is split into three wavelength bands by a demultiplexer, and is routed via fiber bundles to three optical spectrometers, two of which (UV and violet; 245-340 and 385-465 nm) are crossed Czerny-Turner reflection spectrometers, nearly identical to their counterparts on ChemCam. The third is a high-efficiency transmission spectrometer containing an optical intensifier capable of gating exposures to 100 ns or longer, with variable delay times relative to the laser pulse. This spectrometer covers 535-853 nm ( 105 - 7070 cm - 1 Raman shift relative to the 532 nm green laser beam) with 12 cm - 1 full-width at half-maximum peak resolution in the Raman fingerprint region. The BU electronics boards interface with the rover and control the instrument, returning data to the rover. Thermal systems maintain a warm temperature during cruise to Mars to avoid contamination on the optics, and cool the detectors during operations on Mars. Results obtained with the integrated instrument demonstrate its capabilities for LIBS, for which a library of 332 standards was developed. Examples of Raman and VISIR spectroscopy are shown, demonstrating clear mineral identification with both techniques. Luminescence spectra demonstrate the utility of having both spectral and temporal dimensions. Finally, RMI and microphone tests on the rover demonstrate the capabilities of these subsystems as well.

Analysis of Pollution in High Voltage Insulators via Laser-Induced Breakdown Spectroscopy

Surface pollution deposition in a high voltage surface can reduce the surface flashover voltage, which is considered to be a serious accident in the transmission of electric power for the high conductivity of pollution in wet weather, such as rain or fog. Accordingly, a rapid and accurate online pollution detection method is of great importance for monitoring the safe status of transmission lines. Usually, to detect the equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD), the pollution should be collected when power cut off and bring back to lab, time-consuming, low accuracy and unable to meet the online detection. Laser-induced breakdown spectroscopy (LIBS) shows the highest potential for achieving online pollution detection, but its application in high voltage electrical engineering has only just begun to be examined. In this study, a LIBS method for quantitatively detecting the compositions of pollutions on the insulators was investigated, and the spectral characteristics of a natural pollution sample were examined. The energy spectra and LIBS analysis results were compared. LIBS was shown to detect pollution elements that were not detected by conventional energy spectroscopy and had an improved capacity to determine pollution composition. Furthermore, the effects of parameters, such as laser energy intensity and delay time, were investigated for artificial pollutions. Increasing the laser energy intensity and selecting a suitable delay time could enhance the precision and relative spectral intensities of the elements. Additionally, reducing the particle size and increasing the density achieved the same results.

Metal Contamination Distribution Detection in High-Voltage Transmission Line Insulators by Laser-induced Breakdown Spectroscopy (LIBS)

The fast detection of classical contaminants and their distribution on high-voltage transmission line insulators is essential for ensuring the safe operation of the power grid. The analysis of existing insulator contamination has traditionally relied on taking samples during a power cut, taking the samples back to the lab and then testing them with elemental analysis equipment, especially for sugars, bird droppings, and heavy metal particulates, which cannot be analysed by the equivalent salt deposit density (ESDD) or non-soluble deposit density (NSDD) methods. In this study, a novel method called laser-induced breakdown spectroscopy (LIBS) offering the advantages of no sample preparation, being nearly nondestructive and having a fast speed was applied for the analysis of metal contamination. Several LIBS parameters (laser energy and delay time) were optimized to obtain better resolution of the spectral data. The limit of detection (LOD) of the observed elements was obtained using a calibration curve. Compared to calibration curves, multivariate analysis methods including principal component analysis (PCA), k-means and partial least squares regression (PLSR) showed their superiority in analyzing metal contamination in insulators. Then, the elemental distribution of natural pollution was predicted using LIBS to fully capture information about the bulk elements (Na, Ni, Cu, Mn, Ca, etc.) of entire areas with PLSR. The results showed that LIBS could be a promising method for accurate direct online quantification of metal contamination in insulators.

Analytical Methods to Distinguish the Positive and Negative Spectra of Mineral and Environmental Elements Using Deep Ablation Laser-Induced Breakdown Spectroscopy (LIBS)

Environments affect mineral surfaces, and the surface contamination or alteration can provide potential information to understanding their regional environments. However, when investigating mineral surfaces, mineral and environmental elements appear mixed in data. This makes it difficult to determine their atomic compositions independently. In this research, we developed four analytical methods to distinguish mineral and environmental elements into positive and negative spectra based on depth profiling data using laser-induced breakdown spectroscopy (LIBS). The principle of the methods is to utilize how intensity varied with depth for creating a new spectrum. The methods were applied to five mineral samples exposed to four environmental conditions including seawater, crude oil, sulfuric acid, and air as control. The proposed methods are then validated by applying the resultant spectra to principal component analysis and data were classified by the environmental conditions and atomic compositions of mineral. By applying the methods, the atomic information of minerals and environmental conditions were successfully inferred in the resultant spectrum.

Insights into microbial involvement in desert varnish formation retrieved from metagenomic analysis

Desert varnishes are dark rock coatings observed in arid environments and might resemble Mn-rich coatings found on Martian rocks. Their formation mechanism is not fully understood and the possible microbial involvement is under debate. In this study, we applied DNA metagenomic Shotgun sequencing of varnish and surrounding soil to evaluate the composition of the microbial community and its potential metabolic function. We found that the α diversity was lower in varnish compared to soil samples (p value < 0.05), suggesting distinct populations with significantly higher abundance of Actinobacteria, Proteobacteria and Cyanobacteria within the varnish. Additionally, we observed increased levels of transition metal metabolic processes in varnish compared to soil samples. Nevertheless, potentially relevant enzymes for varnish formation were detected at low to insignificant levels in both niches, indicating no current direct microbial involvement in Mn oxidation. This finding is supported by quantitative genomic analysis, elemental analysis, fluorescence imaging and scanning transmission X-ray microscopy. We thus conclude that the distinct microbial communities detected in desert varnish originate from settled Aeolian microbes, which colonized this nutrient-enriched niche, and discuss possible indirect contributions of microorganisms to the formation of desert varnish.

Automatic classification of laser-induced breakdown spectroscopy (LIBS) data of protein biomarker solutions

We perform multi-class classification of laser-induced breakdown spectroscopy data of four commercial samples of proteins diluted in phosphate-buffered saline solution at different concentrations: bovine serum albumin, osteopontin, leptin, and insulin-like growth factor II. We achieve this by using principal component analysis as a method for dimensionality reduction. In addition, we apply several different classification algorithms (K-nearest neighbor, classification and regression trees, neural networks, support vector machines, adaptive local hyperplane, and linear discriminant classifiers) to perform multi-class classification. We achieve classification accuracies above 98% by using the linear classifier with 21-31 principal components. We obtain the best detection performance for neural networks, support vector machines, and adaptive local hyperplanes for a range of the number of principal components with no significant differences in performance except for that of the linear classifier. With the optimal number of principal components, a simplistic K-nearest classifier still provided acceptable results. Our proposed approach demonstrates that highly accurate automatic classification of complex protein samples from laser-induced breakdown spectroscopy data can be successfully achieved using principal component analysis with a sufficiently large number of extracted features, followed by a wrapper technique to determine the optimal number of principal components.