Metal ferrite nanoparticles as tracers in hydraulically fractured wells
Bibliographic record
Abstract
A variety of metal ferrite nanoparticles were synthesized via thermal decomposition reaction and characterized with transmission electron microscopy, small angle X-ray scattering, inductively coupled plasma – optical emission spectroscopy, X-ray photoelectron spectroscopy, thermogravimetric analysis, and a superconducting quantum interference device in order to develop a cost-effective means of tracing hydraulic fractures in wells. In addition, the nanoparticles were developed as a means of determining sources of contamination in the environment surrounding a well by way of “fingerprinting” the different potential sources. This is achieved through the manipulation of the quantities of metal cations substituted into the crystal structure of magnetite, allowing for the creation of unique and desired magnetic characteristics. In order to determine the feasibility of using nanoparticles as tracers, the quantity needed to be able to detect the nanoparticles as determined, as well as how the magnetic properties change as temperature increases as a function of nanoparticle composition. Finally, the feasibility of making industrial quantities of the nanoparticles was investigated.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".