EDS and EELS of Lithium in a 0.5 to 30 keV Electron Microscope
Bibliographic record
Abstract
This paper will present quantitative EDS and EELS maps of Lithium-based materials acquired from 0.5 to 30 keV with a cryogenic specimen holder. State-of-the-art results acquired with the Hitachi SU-9000 dedicated STEM will be shown. This microscope has EELS capabilities that allow Li detection [1]. It is also equipped with the Extreme EDS system from Oxford Scientific that can detect the Kα line of Lithium. Figure 1 shows an EDS spectrum of LiFePO4 taken at 1 keV. After deconvolution of the sum spectra, the Li Kα line and the P Lι are seen. The Si Lι fluorescence peak must be included to obtain a good deconvolution. This shows that Si fluorescence is an issue for Li detection with this detector. Figure 2 shows a EELS Li spectrum of Spodumene, a LiAlSi2O6 mineral that accounts for 40 % of Li production worldwide, obtained with the Hitachi SU-9000 at 30 keV at – 155 °C. The spectrum was acquired with Spodumene Zeta. The edges of Si, Al, and Si are clearly visible. In EDS, it is not possible to see the Li line in spodumene. It is very difficult even with the high-energy resolution gratings because the third Li electron is bounded with O. The fact that the edges are always ionized in EELS is a strong advantage over EDS since it does not matter if there is or not an electron transition leading to X-ray emission, where is often the case that there are no Li Kα line with oxides cathode-based materials. Also, the emission rate in EELS is greater than about 10,000 than that of EDS owing to the fluorescence factor. The downside of EELS is the need for a transparent specimen and beam damage can also be an issue. Here, the use of a cryo-holder allowed to minimize beam damage and obtain the spodumene EELS Spectra. It is noted that several phases of spodumene exist and prior analyses with XRD for phase identification are performed, as shown in Figure 3 for spodumene Zeta. Crystalline phase analysis of Spodumene Zeta was conducted via a Bruker D8 Advance XRD utilizing a Cu K-alpha radiation with a tube voltage and current set to 40 kV and 40 mA, respectively. Primary beam divergent slit was set to 15 mm fixed illumination mode, and a Lynxeye XE-T 1D detector was utilized. The sample was mounted onto a Bruker low-background XRD plate and scanned across 5-120 2theta, with a step size of 0.02°, a step acquisition time of 0.5 seconds. The resulting spectrum was processed using Bruker Eva with peak matching carried out utilising the ICDD PDF5+ database. The dominate phase found was spodumene followed by quartz, with trace amount of analcime, clinochlore, and biotite also observed. Raman spectra of five different spodumene samples (Figure 4) were also recorded using a Bruker RAMII spectrometer with 1064nm laser, connected to a Vertex 70 for operation. A liquid nitrogen cooled Ge diode detector was used to collect spectra, which were acquired using a laser power of 100mW and 500scans with 5cm-1 resolution [2]. EDS spectrum of LiFePO4 at 1 keV. EELS spectra of Spodumene Zeta acquired at 30 keV. XRD spectra of Spodumene Zeta with phases identified including spodumene (PDF: 00-033-0786), quartz (PDF: 00-046-1045), analcime (PDF: 04-011-6750), clinochlore (PDF: 04-016-1848), and biotite (PDF: 01-076-0884). Raman spectra of five different Spodumene samples
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".