Quantification Of Lithium Research Articles

Reflectance spectroscopy analysis and lithium content estimation in lithium-rich rocks and stream sediments: Insights from Tuanjie Peak, Western Kunlun, China

Lithium, a rare metal of strategic importance, has garnered heightened global attention. This investigation delves into the laboratory visible-near infrared and short-wavelength infrared reflectance (VNIR-SWIR 350 nm–2500 nm) spectral properties of lithium-rich rocks and stream sediments, aiming to elucidate their quantitative relationship with lithium concentration. This research seeks to pave new avenues and furnish innovative technical solutions for probing sedimentary lithium reserves. Conducted in the Tuanjie Peak region of Western Kunlun, Xinjiang, China, this study analyzed 614 stream sediments and 222 rock specimens. Initial steps included laboratory VNIR-SWIR spectral reflectance measurements and lithium quantification. Following the preprocessing of spectral data via Savitzky-Golay (SG) smoothing and continuum removal (CR), the absorption positions (Pos2210nm, Pos1910nm) and depths (Depth2210, Depth1910) in the rock spectra, as well as the Illite Spectral Maturity (ISM) of the rock samples, were extracted. Employing both the Successive Projections Algorithm (SPA) and genetic algorithm (GA), wavelengths indicative of lithium content were identified. Integrating the lithium-sensitive wavelengths identified by these feature selection methods, A quantitative predictive regression model for lithium content in rock and stream sediments was developed using partial least squares regression (PLSR), support vector regression (SVR), and convolutional neural network (CNN). Spectral analysis indicated that lithium is predominantly found in montmorillonite and illite, with its content positively correlating with the spectral maturity of illite and closely related to Al-OH absorption depth (Depth2210) and clay content. The SPA algorithm was more effective than GA in extracting lithium-sensitive bands. The optimal regression model for quantitative prediction of lithium content in rock samples was SG-SPA-CNN, with a correlation coefficient prediction (Rp) of 0.924 and root-mean-square error prediction (RMSEP) of 0.112. The optimal model for the prediction of lithium content in stream sediment was SG-SPA-CNN, with an Rp and RMSEP of 0.881 and 0.296, respectively. The higher prediction accuracy for lithium content in rocks compared to sediments indicates that rocks are a more suitable medium for predicting lithium content. Compared to the PLSR and SVR models, the CNN model performs better in both sample types. Despite the limitations, this study highlights the effectiveness of hyperspectral technology in exploring the potential of clay-type lithium resources in the Tuanjie Peak area, offering new perspectives and approaches for further exploration.

Quantification of lithium and calcium in novel hydroxyapatite-based materials for osteoplasty using flame photometry

Quantification of lithium and calcium in novel hydroxyapatite-based materials for osteoplasty using flame photometry

Existing and Emerging Technologies for Therapeutic Monitoring of Lithium: A Scoping Review.

Lithium is an effective psychoactive drug. It has a narrow therapeutic margin, with subtherapeutic levels or intoxication commonly occurring. Therapeutic drug monitoring (TDM) of lithium has several barriers. This scoping review aims to describe and analyze existing and emerging technologies for lithium TDM and to describe the lithium quantification parameters (precision, accuracy, detection limit) attributed to each technology. PubMed, Scopus, Web of Science, and Google Scholar were searched. Studies that described lithium quantification and complied with PRISMA-ScR guidelines were included. Articles selection was conducted by 2 researchers. Good precision was defined if its relative standard deviation <3%; acceptable, from 3% to 5%; and low, >5%. Accuracy was considered good if the error <5%; acceptable, 5%1 to 0%; and low if it was >10%. Of the 2008 articles found, 22 met the inclusion criteria. Of these, 14 studies concerned laboratory devices, in which precision was found to be low in one third of cases, and half had good precision. Accuracy of one third was good, another third was low, and the remaining third did not report accuracy. The other 8 studies concerned portable devices, in which precision was low in more than 60% of the cases and good in 25% of the studies. Accuracy was low in 50% of the cases, and good in just over a third. Limits of detection included the therapeutic range of lithium in all studies. Among emerging technologies for lithium TDM, precision and accuracy remain a challenge, particularly for portable devices.

Quantification of Lithium in State-of-the-Art low Voltage STEM

Quantification of Lithium in State-of-the-Art low Voltage STEM

Quantification of lithium using handheld instruments: application of LIBS and XRF spectroscopy to assay the lithium content of mineral processing products

Two lithium assay methods have been developed using handheld tools, offering fast and reliable results. These methods are crucial for inline optimization of processes, particularly in the extraction of lithium from hard rock deposits.

Quantification of lithium in hyper-stoichiometric lithium titanate by external (in air) particle induced gamma-ray emission (PIGE) method

Quantification of lithium in hyper-stoichiometric lithium titanate by external (in air) particle induced gamma-ray emission (PIGE) method

Quantification of lithium in molten chlorides by optical emission spectrometry using a novel molten-salt-electrode microplasma source

A new molten-salt-electrode microplasma (MSEMP) source for optical emission spectrometry (OES) was constructed, equipped with a molten salt electrode and a metal hollow tube (fed with helium) counter electrode. The use of the MSEMP-OES for constituent analysis of molten salt was primarily evaluated. The acquirement of characteristic spectral lines of some elements in several molten chloride samples verified the good qualitative ability of the proposed MSEMP-OES. Solid copper was dissolved via charge transfer and excited in glow discharge, indicating its potential application in solid sample analysis. The temperature and composition of molten salt were found to have no influence on the lithium response and the accurate quantification of lithium in molten salt was achieved. This work provides new insights for promoting the application of microplasma technology in the in-situ analysis of elements, even in special samples.

Improving spatially-resolved lithium quantification in drill core samples of spodumene pegmatite by using laser-induced breakdown spectroscopy and pixel-matched reference areas

Laser ablation-inductively coupled plasma-time of flight mass spectrometry (LA-ICP-TOFMS) concentrations were used to develop accurate calibration models for laser-induced breakdown spectroscopy (LIBS) mappings of pegmatitic drill cores samples. Both methods were applied on the same area of drill core samples, providing two spatially-resolved datasets for this area. The datasets were aligned pixel by pixel to create a pixel-matched reference area that covered the heterogeneity of the complete drill core. This way, different matrix effects affecting LIBS intensities could be taken into account and accurate spatial quantification of Li2O, SiO2, Al2O3, Na2O, and K2O from LIBS measurements was enabled.In particular, LIBS intensities and LA-ICP-TOFMS concentrations of individual pixels of the reference area were used as the input for a linear Partial Least Square Regression (PLSR) and a non-linear Least Square Support Vector Machines (LS-SVM) calibration model. Varying numbers between 100 and 2000 pixels were used for model creation, and root mean square error (RMSE) and R2 of each model were compared. Better values were achieved for the LS-SVM calibration model. Based on these results, the PLSR model was discarded and only the LS-SVM model with 1000 train pixels was further validated.For two different validation areas, LA-ICP-TOFMS concentrations were compared to LIBS-based concentrations obtained from the LS-SVM calibration model. The spatially-resolved quantification results of the LIBS data agree very well with the independently analysed LA-ICP-TOFMS concentrations, which is e.g. reflected in R2 values between 0.83 and 0.96 (mean 0.89) for Li2O, SiO2, Al2O3, Na2O, and K2O. In general, it was shown that the combination of LA-ICP-TOFMS and LIBS yields a comprehensive dataset for robust multivariate calibration. This enables spatially-resolved LIBS-based quantification of pegmatite samples that are subject to significant physical and chemical matrix effects.

Lithium quantification based on random forest with multi-source geoinformation in Coipasa salt flats, Bolivia

With the widespread use of Lithium (Li) batteries, there is an urgent demand to explore Li deposits. This study aims to apply efficient remote sensing methodologies with multi-resolution images of Sentinel-2, ASTER, and JILIN GP and soil geoinformation to locate Li by mapping its alterations and directly identifying the minerals that contain it. The principal component analysis (PCA) is applied to the satellite bands to gain an initial understanding and analysis of the temporal and spatial behaviour in the Coipasa salt flats in western Bolivia. Then, we employed the Random Forest (RF) method for defining repeatable mineral exploration targets and predictive modelling of mineral prospecting using geographical information system (GIS) tools. Predictive maps are created that contemplate the source, sediment transport, and chemical deposition processes crucial to produce this mineral. The predictive models used satellite bands and physical and chemical soil grid maps; the training data is extracted from sixteen soil and salt samples evaluated using the results of a laboratory test utilizing Atomic Absorption Spectrophotometry. The results demonstrate the high reliability of our predictive models: the values of the Area Under the Curve (AUC) of the Receiver Operating Characteristic Curve (ROC) are between 0.90 and 0.92. The results also show that the combination of PCA on satellite images and terrain information, such as physical, chemical, and morphological properties of the terrain, improves the model to predict the formation of Li ore within the Coipasa salt flats.

Comprehensive comparison of linear and non-linear methodologies for lithium quantification in geological samples using LIBS

Laser-induced breakdown spectroscopy allows fast chemical analysis of light elements without significant sample preparation, turning it into a promising technique for on-site mining operations. Still, the performance for quantification purposes remains its major caveat, obstructing a broader application of the technique. In this work, we present an extensive comparison of the performances of distinct algorithms for quantification of Lithium in a mining prospection stage, using spectra acquired with both a commercial handheld device and a laboratory prototype. Covering both linear and non-linear methodologies, the results show that, when covering a wide range of concentrations typical on a mining operation, non-linear methodologies manage to achieve errors compatible with a semi-quantitative performance, offering performances better than those obtained with linear methods, which are more affected by saturation and matrix effects. The findings enclosed offer support for future applications in the field and may possibly be generalized for other elements of interest in similar mining environments.

Towards robust calibration models for laser-induced breakdown spectroscopy using unsupervised clustered regression techniques

One of the caveats of laser-induced breakdown spectroscopy technique is the performance for quantification purposes, in particular when the matrix of the sample is complex or the problem spans over a wide range of concentrations. These two questions are key issues for geology applications including ore grading in mining operations and typically lead to sub-optimal results. In this work, we present the implementation of a class of clustered regression calibration algorithms, that previously search the sample space looking for similar samples before employing a linear calibration model that is trained for that cluster. For a case study involving lithium quantification in three distinct exploration drills, the obtained results demonstrate that building local models can improve the performance of standard linear models in particular in the lower concentration region. Furthermore, we show that the models generalize well for unseen data of exploration drills on distinct rock veins, which can motivate not only further research on this class of methods but also technological applications for similar mining environments.

Quantification of Lithium and Mineralogical Mapping in Crushed Ore Samples Using Laser Induced Breakdown Spectroscopy

This article reports on the quantification of lithium and mineralogical mapping in crushed lithium ore by laser-induced breakdown spectroscopy (LIBS) using two different calibration methods. Thirty crushed ore samples from a pegmatite lithium deposit were used in this study. Representative samples containing the abundant minerals were taken from these crushed ores and mixed with resin to make polished disks. These disks were first analyzed by TIMA (TESCAN Integrated Mineral Analyzer) and then by a LIBS ECORE analyzer to determine the minerals. Afterwards, each of the thirty crushed ore samples (&lt;10 mm) were poured into rectangular containers and analyzed by the ECORE analyzer, then mineral mapping was produced on the scanned surfaces using the mineral library established on the polished sections. For the first method the lithium concentrations were inferred from the empirical mineral chemistry formula, whereas the second one consisted of building a conventional calibration curve with the crushed material to predict the lithium concentration in unknown crushed materials.

Advances in Therapeutic Monitoring of Lithium in the Management of Bipolar Disorder.

Since the mid-20th century, lithium continues to be prescribed as a first-line mood stabilizer for the management of bipolar disorder (BD). However, lithium has a very narrow therapeutic index, and it is crucial to carefully monitor lithium plasma levels as concentrations greater than 1.2 mmol/L are potentially toxic and can be fatal. The quantification of lithium in clinical laboratories is performed by atomic absorption spectrometry, flame emission photometry, or conventional ion-selective electrodes. All these techniques are cumbersome and require frequent blood tests with consequent discomfort which results in patients evading treatment. Furthermore, the current techniques for lithium monitoring require highly qualified personnel and expensive equipment; hence, it is crucial to develop low-cost and easy-to-use devices for decentralized monitoring of lithium. The current paper seeks to review the pertinent literature rigorously and critically with a focus on different lithium-monitoring techniques which could lead towards the development of automatic and point-of-care analytical devices for lithium determination.

Characterizing Li in partially lithiated layer materials using atomic‐resolution imaging, modeling, and simulation

AbstractUnderstanding of phase‐stability and nanoscale structural modulation during lithiation of layer materials demand comprehensive analysis of the Li‐containing phases in the solid‐state reaction products. Conventional chemical analysis methods in the transmission electron microscope (TEM) are not ideal to detect Li in partially intercalated nanodomains because Li atoms do not remain stationary under the focused electron beam. An alternate approach combining density functional theory (DFT) modeling and multislice image simulation has been explored in the present study to analyze the intercalated structures and to detect and quantify Li from the recorded high‐resolution TEM (HRTEM) micrographs of partially intercalated phases. HRTEM micrographs from partially lithiated graphite and MoS2 show variations in the interlayer spacings, but are not usually directly interpretable. Hypothetical intercalated microstructures of graphite and MoS2 supercells have been generated using atomic‐scale simulations with systematically varying Li concentrations. The measured interplanar spacings are compared with those of experimentally recorded HRTEM micrographs from lithiated graphite and MoS2. The results confirm the coexistence of different lithiated phases at localized domains. This understanding of phase transformation and the lithium quantification provides a basis for understanding the structural accommodation of layered materials during intercalation.

Lithium and Electrolyte Distribution in 18650-Type Lithium-Ion Batteries

Extensive cycling of lithium-ion batteries leads to a partial loss of their capacity due to various side effects like formation of the solid-electrolyte-interface (SEI), loss of active lithium, drying out of the cell [1, 2] etc. Typical profiles of side reactions, instantaneous temperature[3] and current density[4] are non-uniform, which leads to a heterogeneous lithium distribution in the battery. The loss of lithium inventory is typically correlated with the formation of SEI during cycling, whereas the quantitative role of the electrolyte in the cell operation and cell fatigue remains not fully understood yet.Primarily, this is related to the fact that quantification of the liquid electrolyte in an electrically and environmentally isolated system such as lithium-ion batteries is not a simple task. Opening the system would inhibit changes of its state, e.g. evaporation of electrolyte. Typical X-ray or neutron-based methods utilized in non-destructive cell characterization are not capable to quantify the amount of liquid electrolyte with desired accuracy. Recently it has been shown that liquid electrolyte (DMC-based) exhibit a long range order, when frozen at T<260 K [5]. This long range order can be detected by neutron diffraction and the amount of frozen electrolyte can be quantified. Furthermore, applying spatially-resolved neutron powder diffraction (Ref. [6]) pave the way for the simultaneous quantification of lithium amount in graphite and relative concentration of frozen electrolyte (Figure 1).The aim of the current study is a non-destructive quantification of lithium and electrolyte, their spatial distribution throughout the cell and concentration changes vs. cell fatigue. Combined experimental studies embedding electrochemistry, X-ray computed tomography, and neutron diffraction is applied for 18650-type cylinder cell based on NCA|C chemistry, where high-resolution neutron diffraction independently reveals a direct correlation between losses of active lithium in the graphite anode and those of liquid electrolyte (both volume-averaged). The 3D lithium distribution is probed by spatially resolved neutron powder diffraction, thereby displaying the non-trivial character of active lithium/electrolyte losses and complex profile of the cell capacity fading.[1] D. Petz, M.J. Mühlbauer, V. Baran, M. Frost, A. Schökel, C. Paulmann, Y. Chen, D. Garcés, A. Senyshyn, Journal of Power Sources 2020, 448, 227466.[2] B. Ziv, V. Borgel, D. Aurbach, J.-H. Kim, X. Xiao, B.R. Powell, Journal of The Electrochemical Society 2014, 161, A1672-A1680.[3] H. Dai, B. Jiang, X. Wei, Energies 2018, 11,[4] S.V. Erhard, P.J. Osswald, P. Keil, E. Höffer, M. Haug, A. Noel, J. Wilhelm, B. Rieger, K. Schmidt, S. Kosch, F.M. Kindermann, F. Spingler, H. Kloust, T. Thoennessen, A. Rheinfeld, A. Jossen, Journal of The Electrochemical Society 2017, 164, A6324-A6333.[5] A. Senyshyn, M.J. Mühlbauer, O. Dolotko, H. Ehrenberg, Journal of Power Sources 2015, 282, 235-240.[6] A. Senyshyn, M.J. Mühlbauer, O. Dolotko, M. Hofmann, H. Ehrenberg, Scientific Reports 2015, 5, 18380. Figure 1

Lithium-7 qNMR as a method to quantify lithium content in brines using benchtop NMR.

A novel 7Li quantitative NMR (qNMR) method to analyze lithium was developed to determine the lithium content in real brine samples using benchtop NMR instruments. The method was validated, and limits of detection and quantification of 40 and 100 ppm, respectively, were determined. Linearity, precision, and bias were also experimentally determined, and the results are presented herein. The results were compared to those obtained using atomic absorption (AA) spectroscopy, currently one of the few validated methods for the quantification of lithium. The method provides both accurate and precise results, as well as excellent correlation with AA. The absence of matrix effects, combined with no need for sample preparation or deuterated solvents, shows potential applicability in the mining industry.

Application of Lithium Assay kit LS for quantification of lithium in whole blood and urine.

A commercially available kit for the quantitation of lithium, the Lithium Assay kit LS, was originally developed to measure lithium in serum or plasma using a conventional microplate reader. We investigated whether use of the kit could be extended to quantify lithium in whole blood and urine samples collected at autopsy. The calibration curve for whole blood showed good linearity ranging from 0.5 to 20µg/mL with a coefficient of determination of 0.998 when samples were pretreated with methanol followed by acetonitrile. Moreover, for urine, we obtained excellent linearity with a coefficient of determination of 0.999 without any pretreatment. The accuracies and precisions were 106.3-174.7% and 1.9-18.1% for whole blood and 83.3-118.8% and 5.7-33.8% for urine. The values in the lower concentration range (0.5-1µg/mL) were not satisfactory, whereas those in the higher range (2-20µg/mL) were acceptable. The Lithium Assay kit LS was successfully applied to the measurement of lithium in whole blood and urine samples collected at autopsies. This method appears to be useful for forensic toxicological investigations because of its simplicity and speed.

Spatial lithium quantification by backscattered electron microscopy coupled with energy-dispersive X-ray spectroscopy

The quantification of lithium in electron microscopes by energy-dispersive X-ray spectroscopy (EDS) is highly challenging due to the low energy of the characteristic X-rays. Only special windowless detectors can detect Li, yet the sensitivity is suboptimal (i.e., ~20 wt. %). We introduce the use of quantitative backscattered electron microscopy in combination with measurements using a standard EDS sensor to achieve spatially resolved quantification of Li. The method is demonstrated using two Mg-Li alloys with 4 and 20 wt. % Li and good accuracy with a deviation of only ~1.2 wt. % and ~2.5 wt. %, respectively, is achieved.

Spatial Lithium Quantification by Backscattered Electron Microscopy Coupled with Energy-Dispersive X-Ray Spectroscopy

The quantification of lithium in electron microscopes by energy-dispersive X-ray spectroscopy (EDS) is highly challenging due to the low energy of the characteristic X-rays. Only special windowless detectors can detect Li, yet the sensitivity is suboptimal (i.e., ~20 wt. %). We introduce the use of quantitative backscattered electron microscopy in combination with measurements using a standard EDS sensor to achieve spatially resolved quantification of Li. The method is demonstrated using two Mg-Li alloys with 4 and 20 wt. % Li and good accuracy with a deviation of only ~1.2 wt. % and ~2.5 wt. %, respectively, is achieved.

Spatiotemporal Quantification of Lithium both in Electrode and in Electrolyte with Atomic Precision via Operando Neutron Absorption.

The commercial uptake of lithium–sulfur (Li-S) batteries is undermined by their rapid performance decay and short cycle life. These problems originate from the dissolution of lithium polysulfide in liquid electrolytes, causing charge and active material to shuttle between electrodes. The dynamics of intractable polysulfide migration at different length scales often tend to escape the probing ability of many analytical techniques. Spatial and temporal visualization of Li in Li-S electrodes and direct mechanistic understanding of how polysulfides are regulated across Li-S batteries starting from current collector and active layer coating to electrode–electrolyte interface are still lacking. To address this we employ neutron depth profiling across Li-S electrodes using the naturally occurring isotope, 6Li, which yields direct spatial information on Li-S electrochemistry. Using three types of Li-S electrodes, namely, carbon–sulfur, carbon–sulfur with 10% lithium titanium oxide (LTO), and carbon–sulfur with LTO membrane, we provide direct evidence for the migration, adsorption, and confinement of polysulfides in Li-S cells at work. Our findings further provide insights into the dynamics of polysulfide dissolution and re-utilization in relation to Li-S battery capacity and longevity to aid rational electrode designs toward high-energy, safe, and low-cost batteries.