CHARACTERIZATION OF AN SIP SAMPLE HOLDER: LESSONS FROM EXPERIMENT
Bibliographic record
Abstract
When performing Spectral Induced Polarization (SIP) laboratory measurements unwanted/uncontrolled polarization effects have to be avoided. Those effects usually arise when the sample holder is wrongly designed. Especially, the position, the shape and the kind of the potential electrodes play a major role in the measurements. Prior to any use, the sample holder must be characterized (1) to determine the geometrical factor, and (2) to assess transfer function of the measuring system. Both can be assessed by carrying measurements on sample holder filled with electrolyte of different conductivities. We present here an inappropriately designed sample holder, which consists in a 20 cm-long, 7.4 cm-diameter PVC tube. Current electrodes are stainless steel plates and potential electrodes are two collar clamps fixed into the tube. Measurements were performed between 5 mHz and 20 kHz. All KCl electrolytes of different conductivities showed a clear phase peak at about 1 Hz. This peak cannot be caused by the solution, since there is no relaxation mechanism at very low frequency in the water; therefore it is due to the experimental design. The frequency at which the phase peak is maximum shows an inverse relationship with the electrolyte resistivity while the maximum phase amplitude is independent of the resistivity. We find an analytical function. A procedure of correction based on that model was however not enough to remove the parasitic polarization effects as shown for measurements with silica sand. Using COMSOL Multiphysics, we validate the geometrical factor and we assessed the effect of the surface capacitance of the electrodes. The phase peak observed experimentally can be reproduced. As well, the surface impedance influences the geometrical factor.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".