Computational Fluid Dynamics (CFD) Applied to a Glass Vaporization Chamber for Introduction of Micro- or Nano-Size Samples into Lab-Based ICPs and to a CFD-Derived (and Rapidly Prototyped Via 3D Printing) Smaller-Size Chamber for Portable Microplasmas
Bibliographic record
Abstract
Computational fluid dynamics (CFD) is used extensively in many industries ranging from aerospace engineering to automobile design. We applied CFDs to simulate flows inside vaporization chambers designed for micro- or nano-sample introduction into conventional, lab-based inductively coupled plasmas (ICPs). Simulation results were confirmed using smoke visualization experiments (akin to those used in wind tunnels) and were verified experimentally using an ICP-optical emission spectrometry (ICP-OES) system with a fast-response photomultiplier tube (PMT) detector, an ICP-OES system with a slower-response charge injection device (CID) detector, and an ICP-mass spectrometry (ICP-MS) system. A pressure pulse (defined as a momentary decrease of the optical emission intensity of ICP background) was not observed when employing widely used ICPs either with a CID detector or with ICP-MS. Overall, the simulations proved to be highly beneficial, for example, detection limits improved by as much as five times. Using CFD simulations as a guide, a rapidly prototyped, 3D-printed and smaller-size vaporization chamber (a scaled-down version of that used with ICPs) is being evaluated for potential use with a portable, battery-operated microplasma. Details are provided in this chapter.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".