Curve‐fitting regression: improving light element quantification with XRF

Kikongi, Philippe; Salvas, Joanny; Gosselin, Ryan

doi:10.1002/xrs.2760

Cited by 15 publications

(9 citation statements)

References 15 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the contents of most of the elements slightly decreased because of the extremely large particle size of WL, which limits the intrusion depth of HNO 3 treatment . After the HNO 3 treatment of WL (HN-WL), the B content was not detected because of photon reabsorption that limits the analysis depth of light elements (i.e., B) in XRF analysis . Because the near-surface B content of HN-WL was removed by HNO 3 treatment, the B content could not be detected.…”

Section: Resultsmentioning

confidence: 99%

Waste Liquid-Crystal Display Glass-Directed Fabrication of Silicon Particles for Lithium-Ion Battery Anodes

Kang

Kim

Noh

et al. 2019

ACS Sustainable Chem. Eng.

View full text Add to dashboard Cite

The rapid increase of waste liquid-crystal display (LCD) is becoming a serious problem. Among the constituents of waste LCD panels, glass substrates are not completely recycled and buried in landfills because of the lack of recycling technologies. In order to establish a recycling strategy with sustainable process and application, we fabricated silicon (Si) materials into lithium-ion battery (LIB) anodes through the magnesiothermic reduction of waste LCD glasses. To synthesize high-quality Si materials, an optimized pretreatment process is proposed to remove undesirable contents from waste LCD glasses. In order to achieve high areal capacity for practical applications, we conducted facile and cost-effective electrode maturation, which improves the cohesion and adhesion of the Si anodes. The electrochemical measurement results showed that the waste LCD glass-derived Si electrodes exhibited high areal and gravimetric capacities of 6.3 mA h cm–2 and 3438 mA h g–1, respectively, in the initial cycle. The electrodes maintained a high areal capacity of 3.1 mA h cm–2 during the 100th cycle. This reduced Si materials and electrode-manufacturing process can be a cost-effective and sustainable recycling technology for waste LCD glass management and anode materials for LIBs.

show abstract

Section: Resultsmentioning

confidence: 99%

Waste Liquid-Crystal Display Glass-Directed Fabrication of Silicon Particles for Lithium-Ion Battery Anodes

Kang

Kim

Noh

et al. 2019

ACS Sustainable Chem. Eng.

View full text Add to dashboard Cite

show abstract

“…XRF spectra were interpolated through multiple Gaussian [31][32][33][34] functions in the proximity of the energy lines of the expected elements to obtain the peak area. The considered peaks were Cu Kα, Zn Kα, Au Lα, Pd Kα and Sn Kα; in addition Cu Kβ and Zn Kβ were also fitted to avoid errors due to peak overlaps.…”

Section: Methodsmentioning

confidence: 99%

Coatings Thickness Determination Using X-ray Fluorescence Spectroscopy: Monte Carlo Simulations as an Alternative to the Use of Standards

Giurlani¹,

Berretti²,

Innocenti³

et al. 2019

Preprint

View full text Add to dashboard Cite

X-ray fluorescence is largely employed in the measurement of the thickness of coatings. Despite of its diffusion, the task is not straightforward because of the complex physics involved that results in high dependence on matrix effects. Thickness quantification is in practice accomplished using the Fundamental Parameters approach, adjusted with empirical measurements of standards with known composition and thickness. This approach has two major drawbacks: i) there are no standards for any possible coating and coating architecture and ii) even relying on standards, the quantification of unknown samples requires the precise knowledge of the matrix nature (e.g., in case of multilayer coatings the thickness and the composition of each underlayer). In this work, we describe a semiquantitative approach to coatings thickness measurement based on the construction of calibration curves through simulated XRF spectra built with Monte Carlo simulations.  Simulations have been performed with the freeware software XMI-MSIM.  We have assessed the accuracy of the methods by comparing the results with those obtained by i) XRF thickness determination with standards and ii) FIB-SEM cross-sectioning. Then we evaluated which parameters are critical in this kind of indirect thickness measurements.

show abstract

“…Light elements, with an atomic number below 11, cannot be accurately quantified by XRF. For these elements, it is difficult to ionize an atom with the photoelectric excitation and the produced signals are trapped within the sample itself (Kikongi et al, 2017). The light elements, such as carbon, are of particular interest in this study and therefore it was necessary to quantify their composition with an alternative method.…”

Section: Bulk Chemical Compositionmentioning

confidence: 99%

Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries

Vanderbruggen¹,

Gugala²,

Blannin³

et al. 2021

Preprint

View full text Add to dashboard Cite

Mechanical recycling processes aim to separate particles based on their physical properties, such as size, shape and density, and physico-chemical surface properties, such as wettability. Secondary materials, including electronic waste, are highly complex and heterogeneous, which complicates recycling processes. In order to improve recycling efficiency, characterization of both recycling process feed materials and intermediate products is crucial. Textural characteristics of particles in waste mixtures cannot be determined by conventional characterization techniques, such as X-ray fluorescence and Xray diffraction spectroscopy. This paper presents the application of automated mineralogy as an analytical tool, capable of describing discrete particle characteristics for monitoring and diagnosis of lithium ion battery (LIB) recycling approaches. Automated mineralogy, which is well established for the analysis of primary raw materials but has not yet been tested on battery waste, enables the acquisition of textural and chemical information, such as elemental and phase composition, morphology, association and degree of liberation. For this study, a thermo-mechanically processed black mass (< 1 mm fraction) from spent LIBs was characterized with automated mineralogy. Each particle was categorized based on which LIB component it comprised: Al foil, Cu foil, graphite, lithium metal oxides and alloys from casing. A more selective liberation of the anode components was achieved by thermo-mechanical treatment, in comparison to the cathode components. Therefore, automated mineralogy can provide vital information for understanding the properties of black mass particles, which determine the success of mechanical recycling processes. The introduced methodology is not limited to the presented case study and is applicable for the optimization of different separation unit operations in recycling of waste electronics and batteries. Element and LIB components Spectra examples and name for the reference list Cu from foilAl from foil C from graphite Metals from lithium metal oxides: Co, Ni, Mn and mix Si from filler particles Others from alloys particlesSupplementary material S2 -Compositional thresholds of the collected spectra.

show abstract

Curve‐fitting regression: improving light element quantification with XRF

Cited by 15 publications

References 15 publications

Waste Liquid-Crystal Display Glass-Directed Fabrication of Silicon Particles for Lithium-Ion Battery Anodes

Waste Liquid-Crystal Display Glass-Directed Fabrication of Silicon Particles for Lithium-Ion Battery Anodes

Coatings Thickness Determination Using X-ray Fluorescence Spectroscopy: Monte Carlo Simulations as an Alternative to the Use of Standards

Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries

Contact Info

Product

Resources

About