Field Lithium Quantification with Mineral-Specific LIBS Calibration
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Solution Overview
Problem
The challenge of accurately quantifying lithium in complex mineral matrices using laser-induced breakdown spectroscopy (LIBS) is hindered by matrix effects, and existing methods require sample preparation that complicates field measurements.
Innovation Solution
A method and system that utilize a trained mineral classification model to determine the mineral class of a lithium-containing mineral, followed by applying a calibration curve specific to that class to quantify lithium content without sample processing, employing techniques like short-time Fourier transform and neural networks for spectral data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser-induced breakdown spectroscopy (LIBS) is used for quantitative analysis of lithium, then lithium content can be measured, but matrix effects from other elements inhibit or enhance spectral line intensity, reducing measurement precision
Solution Approach 1:
The patent introduces an internal standard element (such as calcium or magnesium) as an intermediary to compensate for matrix effects. The internal standard element experiences the same matrix effects as the analyte element, allowing ratio-based correction of spectral line intensities to eliminate interference from other elements in the sample matrix
Solution Approach 2:
The patent changes the parameter used for quantitative analysis from absolute spectral line intensity to the ratio of spectral line intensity of the analyte element to that of the internal standard element. This parameter transformation makes the measurement insensitive to matrix effects that affect both elements equally
2Measurement precision
If sample preparation (grinding into powder and pressing into flakes) is performed for LIBS analysis of rock/mineral, then measurement accuracy can be improved, but field measurement speed is reduced and implementation becomes difficult
Solution Approach 1:
The patent extracts the requirement for sample preparation from the field measurement process. By developing a method that works directly on intact rock/mineral surfaces, the time-consuming steps of grinding and pressing are removed, enabling rapid in-situ analysis without sacrificing measurement accuracy through proper spectral correction techniques
Solution Approach 2:
The method enables the sample to serve itself by analyzing the intact surface directly without requiring external preparation equipment or processes. The laser ablates and analyzes the surface in place, and the spectral data is corrected using the internal standard element approach, making the system self-sufficient for field deployment
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables rapid and accurate field quantification of lithium with suppressed matrix effects, improving analytical accuracy and efficiency by eliminating the need for sample preparation and reducing reliance on extensive sample collections.
Implementation Method 1
quantitative analysis of ultralight elements can be implemented through only a laser-induced breakdown spectroscopy (LIBS) technology. Through the LIBS technology, plasmas can be excited by irradiating a surface of a sample with an ultrashort laser pulse
Implementation Method 2
plasmas can be excited by irradiating a surface of a sample with an ultrashort laser pulse, and plasmas of different elements radiate spectral lines with different wavelengths
Data Source
AI summary
The present disclosure provides a field quantitative analysis method and system of lithium, and relates to the technical field of field quantitative analysis of lithium. The method includes: measuring a laser-induced breakdown spectroscopy of a lithium-containing mineral, to obtain spectral data of the lithium-containing mineral; taking the spectral data as an input, and determining a mineral class of the lithium-containing mineral based on a trained mineral classification model; and taking the spectral data as the input, and determining content of lithium in the lithium-containing mineral based on a calibration curve corresponding to the mineral class.