Using Scanning Ion Conductance Microscopy to Measure Ion Conductivity and Permeability in Porous Materials
Bibliographic record
Abstract
Composite electrodes can significantly improve the performance of an electrochemical device by maximizing surface area and active material loading. Typically, additives such as carbon are used to improve conductivity and a polymer is used as a binder leading to a heterogeneous surface film with thickness on the order of tens of microns. For such composite electrodes, good ionic conduction within the film is critical to capitalize on the increased loading of active material and surface area. Ionic conductivity within a film can be tricky to measure directly and homogenization models based on porosity are often used as a proxy. Scanning Ion Conductance Microscopy (SICM) has traditionally been a topography-mapping microscopy method. We will outline a new function and demonstrate SICM’s capacity for measuring ion conductivity within lithium-ion battery composite electrodes.
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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 | 0.001 | 0.001 |
| 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".