Raman investigation of the uranium compounds U<sub>3</sub>O<sub>8</sub>, UF<sub>4</sub>, UH<sub>3</sub> and UO<sub>3</sub> under pressure at room temperature
Bibliographic record
Abstract
Our current state-of-the-art X-ray diffraction experiments are primarily sensitive to the position of the uranium atom. While the uranium - low-Z element bond (such as U-H or U-F) changes under pressure and temperature the X-ray diffraction investigations do not reveal information about the bonding or the stoichiometry. Questions that can be answered by Raman spectroscopy are (i) whether the bonding strength changes under pressure, as observed by either blue- or red-shifted peaks of the Raman active bands in the spectrum and (ii) whether the low-Z element will eventually be liberated and leave the host lattice, i.e. do the fluorine, oxygen, or hydrogen atoms form dimers after breaking the bond to the uranium atom. Therefore Raman spectra were also collected in the range where those decomposition products would appear. Raman is particularly well suited to these types of investigations due to its sensitivity to trace amounts of materials. One challenge for Raman investigations of the uranium compounds is that they are opaque to visible light. They absorb the incoming radiation and quickly heat up to the point of decomposition. This has been dealt with in the past by keeping the incoming laser power to very low levels on the tens of milliWatt range consequently affecting signal to noise. Recent modern investigations also used very small laser spot sizes (micrometer range) but ran again into the problem of heating and chemical sensitivity to the environment. In the studies presented here (in contrast to all other studies that were performed at ambient conditions only) we employ micro-Raman spectroscopy of samples situated in a diamond anvil cell. This increases the trustworthiness of the obtained data in several key-aspects: (a) We surrounded the samples in the DAC with neon as a pressure transmitting medium, a noble gas that is absolutely chemically inert. (b) Through the medium the sample is thermally heat sunk to the diamond anvils, diamond of course possessing the very best heat conductivity of any material. Therefore local heating and decomposition are avoided, a big challenge with other approaches casting doubts on their results. (c) This in turn benefits the signal/noise ratio tremendously since the Raman features of uranium-compounds are very small. The placement of the samples in DACs allows for higher laser powers to impinge on the sample spot while keeping the spot-size larger than in previous studies and keep the samples from heating up. Raman spectroscopy is a very sensitive non-invasive technique and we will show that it is even possible to distinguish the materials by their origin / manufacturer as we have studied samples from Cameco (Canada) and IBI-Labs (US-Florida) and can compare with ambient literature data for samples from Strem (US-MA) and Areva (Pierrelatte, France).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.004 |
| Meta-epidemiology (narrow) | 0.019 | 0.017 |
| Meta-epidemiology (broad) | 0.021 | 0.008 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.018 | 0.015 |
| Research integrity | 0.018 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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; both teacher heads agree on what is shown here.
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".