Journal of The Electrochemical Society, 150 �3 � A385-A397 �2003� 0013-4651/2003/150�3�/A385/13/$7.00 © The Electrochemical Society, Inc. Conduction in Multiphase ParticulateÕFibrous Networks Simulations and Experiments on Li-ion Anodes
Bibliographic record
Abstract
Several promising Li-ion battery technologies incorporate nanoarchitectured carbon networks, typically in the form of whisker/ particle blends bonded with thermoplastic binders to form the anodes. Degradation of these materials is currently a persistent problem, with damage presenting as blistering and/or delamination of the electrode. Both material composition and morphology play a role in these critical failure modes, and are explored in the present work as they affect conduction in practical battery materials. Lawrence Berkeley National Laboratories and the Institut de Recherche d’Hydro-Quebec supplied the materials studied in this work. Our present approach builds on our previous numerical work, incorporating real material morphology and careful selection of boundary conditions to reduce the numerical difficulties posed by singularities in the field solution, due to phase contrast, sharp corners, etc. In order to allow use of these models for various shapes of particles, we provide a few simple geometrical relations for calculation of total surface area for various morphologies of electrode materials. A four-point-probe technique was employed to obtain the experimental conductivities. Although the existence of contact resistance is well known, there is little literature regarding a technique to measure its value; here, we also present a method for quantifying it, assuming that the anode layer is comprised of two layers. Voltage functions for each layer are determined by enforcement of voltage continuity at the interfaces, current intensities at the inlet and outlet on both sides of interface, and assumption of zero voltage in the second layer as z → �. The four-point-probe technique is suitable for the electrode materials tested, offering reasonable experimental precision in a simple setup. The results of this study offer some insight into the design of active materials. The model shows
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.111 | 0.065 |
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".