Method—AMIDR: A Complete Pulse Method for Measuring Cathode Solid-State Diffusivity
Bibliographic record
Abstract
The Atlung Method for Intercalant Diffusion and Resistance (AMIDR) is a novel, high accuracy method for measuring solid state diffusivity and interface resistance related to the Atlung Method for Intercalant Diffusion (AMID) with several key differences. Most notably, AMIDR is designed to analyze the voltage response over time of “complete” pulses, pulses that last until an impedance steady state is reached. These differences allow for AMIDR to return diffusivity results with a higher degree of confidence than Galvanostatic Intermittent Titration Technique (GITT) and at a faster rate with higher state of charge (SOC) resolution than Electrochemical Impedance Spectroscopy (EIS). In this study, three different lithium transition metal oxides were studied. These active materials showed very similar kinetic behaviour that varied with dependence on the fraction of Ni atoms filling sites in the Li layer. AMIDR comes with a user-friendly python program complete with a user interface that is intended to assist other researchers in measuring active material diffusivity in a controlled, repeatable manner. This program, along with instruction on its use, the results of this study from raw data to the final key kinetic metrics, and a video summary of AMIDR design are available for download at https://github.com/MitchBall/AMIDR .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.013 |
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 source (direct Gemma or distilled Codex), 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".