In the study of mineral rock, traditional geoscience analysis instruments are difficult to detect the elements of poor ore: such as optical microscope, electron probe, electron scanning microscope, LIF or XRF technology. The main reason is that the metal phase in the mineral is small (μm), or the elements in the colloidal component are difficult to detect, or both, and undergo a rather complicated pretreatment. In addition, these traditional geoanalytical instruments cannot perform in-situ or non-contact measurements. 
The main components of the sandstone-type uranium deposit in this case are quartz, clay matrix and auxiliary minerals (such as oxides, sulfides or carbonates); its mineralization is the intrusion of ore-forming fluid into the intergranular voids or the clay between the quartz sands. The result of the matrix reaction. The difficulty in analyzing the U elements is:
§ Element distribution is very uneven, valuable information is often hidden in a small area of ​​the sample;
§ U, Zr, Ti, Nb in ore is irregularly associated or isolated, and it is difficult to detect effective information, but its associated distribution information is very important for mining science;
§ Small particle volume (μm);
§ Some metal phases are colloidal.
The LIBS elemental analysis technology is the most effective technology to meet the above-mentioned difficulties and meet the experimental needs and the most promising technology. In addition, without sample pretreatment, the experimental method is fast and simple, and all elements in the periodic table can be detected at the same time. The sensitivity is high, and the surface spatial distribution of the sample can be mapped—all of which are unmatched by traditional methods.
In fact, the application of LIBS technology in geosciences is advancing rapidly. For example, people have applied it to the analysis of ore pollutants or impurities, in-situ qualitative, quantitative analysis, ore origin analysis, and even in the Mars Science Laboratory. "Rovers have long applied LIBS technology to the 7 m long range analysis of Mars Rock.
General methods for uranium mine detection and their detection capabilities
§ Through the special method of double excitation, the stability and repeatability of LIBS analysis are greatly improved, and the diameter of the ablation pit is reduced to improve the mapping resolution;
§ In the LIBS analysis line of sandstone-type uranium deposits, the uranium characteristic line is very complicated and dense; at the same time, the spectral line is wide, causing characteristic line interference, and the resolution of the commonly used spectrometer is difficult to detect; these factors lead to high overall background radiation signal. There are few clear and identifiable uranium characteristic lines. In this study, different algorithms of AtomAnalyzer line analysis software were used to identify the best spectral analysis bands of elements in ore and process the data to obtain the most effective features of U elements. Line and its mapping image;
§ More importantly, the analytical detection method of element mapping enables us to understand the distribution of mineral phases; and based on the correlation of its distribution, we know the distribution of minerals associated or isolated. At the same time, we understand the accumulation of metal elements in the formation of sandstone.
§ The improved PCA algorithm built into the AtomAnalyzer spectral data analysis and processing software developed by AtomTrace reduces the time required for massive spectral line data analysis and processing in this case by 85%. The built-in SOM algorithm obtains routine calculations in complex geological samples. Method for obtaining element distribution information, such as distribution information of Si in U blank or low abundance regions, and subtracting too many dimensions of spectral data to simplify the operation;
§ All experimental procedures use AtomTrace's self-developed control software to perform precise timing control on secondary excitation, station movement, and spectral detection, and accurately pre-define the Mapping path and measurement position. 3D profile measurements can also be made through the system. The matching spectral data analysis and processing software AtomAnalyzer can display the online mapping results of selected analysis elements.
Experimental methods and analysis results:
The following figure shows the comparison of spectral data between depleted uranium and uranium-rich regions:
Using the PCA algorithm, the unknown components corresponding to the LIBS measurement line of any uneven sample can be analyzed. However, this measurement generates 22500 × 26000 spectral data variables, and it is necessary to read 33 GB of huge data from RAM for processing by PCA algorithm, which means huge computational time and takes a long time. Therefore, the AtomTrace team used the improved PCA algorithm in the AtomAnalyzer software to simplify the calculation process and data reading mode, reducing the analysis workload by 85% and obtaining good analysis results. This method has not been tried before.
The results of the Mapping analysis are shown below: 
a) U m characteristic line intensity distribution; b) 590 -595 nm background area line intensity distribution,
c) PC1 optimization algorithm U m numerical distribution; d) PC1 optimization algorithm 590-595nm background area numerical distribution
3. Based on the above experiments, the characteristic element U-Zr-P-Ti in uranium ore is further analyzed by SOM algorithm (neuron algorithm, or node algorithm) in AtomAnalyzer.
3.1 According to the selected characteristic line, the image obtained by the traditional mapping method: 
a) Zr II 349.621 nm characteristic line intensity mapping map;
b) U II 409.013 nm characteristic line intensity mapping map;
c) Si I 251.431 nm characteristic line intensity mapping diagram 3.2 Mapping of traditional algorithm and SOM algorithm characteristic line value mapping 
a) 325.424 nm Ti II characteristic line intensity Mapping; c) Correlation between each measured line and Ti II node weight, red dot area has the highest correlation with Ti (no U element area)
b) 255.139 nm Nb II characteristic line intensity Mapping; d) correlation between each measured line and the node weight with the largest Nb response, the correlation between the red point area and the Nb node weight is the highest 3.3 node weight on the line SOM algorithm mapping obtained by integral 
a) the node response calculated from the 349.621 nm Zr II characteristic line intensity;
b) the node response calculated from the intensity of the 409.013 nm U II characteristic line;
c) Node response calculated from the characteristic line intensity of 251.41 nm Si I 3.4 Application of SOM algorithm to study the correlation and isolation of several selected element distributions 
a) the node response calculated from the intensity of the 325.424 nm Ti II characteristic line;
b) the node response calculated from the 358.1195 nm Fe I characteristic line intensity;
c) the node response calculated from the 255.139 nm Nb II characteristic line intensity;
d) Node response calculated from 288.158 nm Si I characteristic line intensity 3.5 Experimental conclusion:
This case is published in the AtomTrace team:
§ Element distribution is very uneven, valuable information is often hidden in a small area of ​​the sample;
§ U, Zr, Ti, Nb in ore is irregularly associated or isolated, and it is difficult to detect effective information, but its associated distribution information is very important for mining science;
§ Small particle volume (μm);
§ Some metal phases are colloidal.
The LIBS elemental analysis technology is the most effective technology to meet the above-mentioned difficulties and meet the experimental needs and the most promising technology. In addition, without sample pretreatment, the experimental method is fast and simple, and all elements in the periodic table can be detected at the same time. The sensitivity is high, and the surface spatial distribution of the sample can be mapped—all of which are unmatched by traditional methods.
In fact, the application of LIBS technology in geosciences is advancing rapidly. For example, people have applied it to the analysis of ore pollutants or impurities, in-situ qualitative, quantitative analysis, ore origin analysis, and even in the Mars Science Laboratory. "Rovers have long applied LIBS technology to the 7 m long range analysis of Mars Rock.
General methods for uranium mine detection and their detection capabilities
| Analytical method | Non-contact measurement | Element scan mapping |
| ICP-MS | no | no |
| ICP-AES | no | no |
| XRF | no | can |
| Raman spectral analysis | can | can |
| LIF | can | can |
| Gamma ray spectroscopy | can | no |
| LIBS | can | can |
AtomTrace is the sole derivative of the European Engineering Technology Center (CEITEC), and its members are researchers in the Laser Spectroscopy and Chemical Analysis Laboratory at the University of Brno. The laboratory started in 1997 and has nearly 20 years of experience in the field of LIBS application technology research and development. The Sci-Trace LIBS elemental analysis system developed and produced by the laboratory won the Czech Republic 2016 Best Cooperation Award. Prior to this, the AtomTrace team won the first place in the European LIBS Elemental Analysis Competition!
Today AtomTrace is the only laser spectrometry company listed in the world!
With SciTrace, you get the world's top professional team technical support and lab collaboration.
AtomTrace team SciTrace geology application publication
Although the advantages of LIBS elemental analysis techniques are certain, there are still challenges in detecting specific elements of specific samples. In this case, the AtomTrace team applied the SciTrace LIBS system's unique dual excitation, reaction chamber pressure control, system control and data analysis processing LIBS technology to perform high-resolution mapping of elemental sandstone-type uranium mines. With SciTrace, you get the world's top professional team technical support and lab collaboration.
AtomTrace team SciTrace geology application publication
- ÄŒelko, L. ; Gadas, P. ; Häkkänen, H. ; HrdliÄka, A. ; Kaiser, J. ; Kaski, S. ; Modlitbová, P. ; Novotný, J. ; Novotný, K. ; Prochazka, D. ; Sládková, L. Detection of fluorine using laser-induced breakdown spectroscopy and Raman spectroscopy, [J] Journal of Analytical Atomic Spectrometry (2017), DOI: 10.1039/C7JA00200A
- HrdliÄka, A. ; Kaiser, J. ; Klus, J. ; Novotný, J. ; Novotný, K. ; Prochazka, D. ; Å karková, P. ; Vrábel, J. Impact of Laser-Induced Breakdown Spectroscopy data normalization on multivariate Classification accuracy,. [J] Journal of Analytical Atomic Spectrometry (2017), DOI: 10.1039/C6JA00322B
- Jakub Klus, Petr Mikysekd, David Prochazka, Pavel PoÅ™Ãzka, Petra Prochazková, Jan Novotný, Tomáš Trojek, Karel Novotný, Marek SlobodnÃk, Jozef Kaiser., Application of self-organizing maps to the study of U-Zr-Ti-Nb distribution in Sandstone-hosted uranium ores, [J] Spectrochimica Acta Part B 131 (2016) 66–73
- Burget, R. ; Kaiser, J. ; Klus, J. ; Mašek, J. ; Modlitbová, P. ; Novotný, J. ; Novotný, K. ; Prochazka, D. ; Rajnoha, M. , Multivariate classification of echellograms: a new perspective in Laser-Induced Breakdown Spectroscopy analysis, [J] Scientific Reports (2017), DOI: 10.1038/s41598-017-03426-0
- Brada, M. ; Kaiser, J. ; Klus, J. ; Novotný, J. ; Novotný, K. ; Prochazka, D. ; VÃtková, G. , Assessment of the most effective part of echelle laser-induced plasma spectra for further Classification using Czerny-Turner spectrometer, [J] Spectrochimica Acta Part B: Atomic Spectroscopy (2016), DOI: 10.1016/j.sab.2016.09.004
- Jakub Klus, Petr Mikysekd, David Prochazka, Pavel PoÅ™Ãzka, Petra Prochazková, Jan Novotný, Tomáš Trojek, Karel Novotný, Marek SlobodnÃk, Jozef Kaiser, Multivariate approach to the chemical mapping of uranium in sandstone-hosted uranium ores analyzed using double pulse laser- Induced breakdown spectroscopy, [J] Spectrochimica Acta Part B: Atomic Spectroscopy (2016) 143–149, DOI: 10.1016/j.sab.2016.08.014
§ Through the special method of double excitation, the stability and repeatability of LIBS analysis are greatly improved, and the diameter of the ablation pit is reduced to improve the mapping resolution;
§ In the LIBS analysis line of sandstone-type uranium deposits, the uranium characteristic line is very complicated and dense; at the same time, the spectral line is wide, causing characteristic line interference, and the resolution of the commonly used spectrometer is difficult to detect; these factors lead to high overall background radiation signal. There are few clear and identifiable uranium characteristic lines. In this study, different algorithms of AtomAnalyzer line analysis software were used to identify the best spectral analysis bands of elements in ore and process the data to obtain the most effective features of U elements. Line and its mapping image;
§ More importantly, the analytical detection method of element mapping enables us to understand the distribution of mineral phases; and based on the correlation of its distribution, we know the distribution of minerals associated or isolated. At the same time, we understand the accumulation of metal elements in the formation of sandstone.
§ The improved PCA algorithm built into the AtomAnalyzer spectral data analysis and processing software developed by AtomTrace reduces the time required for massive spectral line data analysis and processing in this case by 85%. The built-in SOM algorithm obtains routine calculations in complex geological samples. Method for obtaining element distribution information, such as distribution information of Si in U blank or low abundance regions, and subtracting too many dimensions of spectral data to simplify the operation;
§ All experimental procedures use AtomTrace's self-developed control software to perform precise timing control on secondary excitation, station movement, and spectral detection, and accurately pre-define the Mapping path and measurement position. 3D profile measurements can also be made through the system. The matching spectral data analysis and processing software AtomAnalyzer can display the online mapping results of selected analysis elements.
Experimental methods and analysis results:
- First, the XRF technique was applied to scan the entire sample for elemental distribution with a scan resolution of 1-2 mm. Find areas with high abundance of uranium. The figure below shows the spatial distribution of U element abundance:
A: sample image 70 × 44mm; B: U element sample surface distribution Mapping;
The red frame area is further analyzed by applying LIBS (15 × 15mm).
- Further analysis and processing of selected high-abundance regions using SciTrace double-excitation LIBS technology, the parameters are as shown in the table below
| parameter | Numerical value |
| Initial excitation laser pulse energy (mJ) | 30 |
| Secondary excitation laser pulse energy (mJ) | 80 |
| Ablative pit diameter (μm) | 50 |
| Secondary excitation time interval (μs) | 0.5 |
| Gate delay (μs) | 1.5 |
| Door width (μs) | 20 |
| Mapping spatial resolution (μs) | 100 |
| Mapping measurement points | 150*150 |
The following figure shows the comparison of spectral data between depleted uranium and uranium-rich regions:
- Background (590–595 nm) line contrast; b) band spectral contrast of uranium ion characteristic line (409.01 nm); c) full band spectral line contrast
Using the PCA algorithm, the unknown components corresponding to the LIBS measurement line of any uneven sample can be analyzed. However, this measurement generates 22500 × 26000 spectral data variables, and it is necessary to read 33 GB of huge data from RAM for processing by PCA algorithm, which means huge computational time and takes a long time. Therefore, the AtomTrace team used the improved PCA algorithm in the AtomAnalyzer software to simplify the calculation process and data reading mode, reducing the analysis workload by 85% and obtaining good analysis results. This method has not been tried before.
The results of the Mapping analysis are shown below:
c) PC1 optimization algorithm U m numerical distribution; d) PC1 optimization algorithm 590-595nm background area numerical distribution
3. Based on the above experiments, the characteristic element U-Zr-P-Ti in uranium ore is further analyzed by SOM algorithm (neuron algorithm, or node algorithm) in AtomAnalyzer.
3.1 According to the selected characteristic line, the image obtained by the traditional mapping method:
b) U II 409.013 nm characteristic line intensity mapping map;
c) Si I 251.431 nm characteristic line intensity mapping diagram 3.2 Mapping of traditional algorithm and SOM algorithm characteristic line value mapping
b) 255.139 nm Nb II characteristic line intensity Mapping; d) correlation between each measured line and the node weight with the largest Nb response, the correlation between the red point area and the Nb node weight is the highest 3.3 node weight on the line SOM algorithm mapping obtained by integral
b) the node response calculated from the intensity of the 409.013 nm U II characteristic line;
c) Node response calculated from the characteristic line intensity of 251.41 nm Si I 3.4 Application of SOM algorithm to study the correlation and isolation of several selected element distributions
b) the node response calculated from the 358.1195 nm Fe I characteristic line intensity;
c) the node response calculated from the 255.139 nm Nb II characteristic line intensity;
d) Node response calculated from 288.158 nm Si I characteristic line intensity 3.5 Experimental conclusion:
- Zr II line intensity Mapping and U II line intensity Mapping reflect the companion relationship between the two, and both are opposite to the Si I line intensity Mapping, and are isolated.
- The Ti element is isolated from the Nb element.
- The elements of Fe and Nb are associated with each other, while in the areas where they are distributed, the U element is less abundant.
- Zr and Nb are isolated, and the reason can be understood as the known "Zr is a replacement metal element of Nb".
- Finally, the position where the Si element appears, the abundance of Fe, U, Ti, Nb decreases.
This case is published in the AtomTrace team:
- Jakub Klus, Petr Mikysekd, David Prochazka, Pavel PoÅ™Ãzka, Petra Prochazková, Jan Novotný, Tomáš Trojek, Karel Novotný, Marek SlobodnÃk, Jozef Kaiser, Multivariate approach to the chemical mapping of uranium in sandstone-hosted uranium ores analyzed using double pulse laser- Induced breakdown spectroscopy, Spectrochim. Acta B At. Spectrosc.123 (2016) 143–149
- Jakub Klus, Petr Mikysekd, David Prochazka, Pavel PoÅ™Ãzka, Petra Prochazková, Jan Novotný, Tomáš Trojek, Karel Novotný, Marek SlobodnÃk, Jozef Kaiser, Application of self-organizing maps to the study of U-Zr-Ti-Nb distribution in sandstone -hosted uranium ores, Spectrochimica Acta Part B 131 (2016) 66–73
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