Toward a Drift-Diffusion Device Conceptualization of Alkali-Ion Rocking-Chair Batteries
Bibliographic record
Abstract
Though rocking-chair batteries are ubiquitously associated with driving electronic devices, descriptions of their dynamical operation have generally been decoupled from the conventional drift-diffusion framework applied to solid-state electronic devices—the latter having enjoyed enormous success in the design of ubiquitous technologies including transistors, solid-state lasers, and light-emitting diodes. Building on long-standing Newman-type descriptions of battery operation, herein we discuss and present a theoretical framework for also conceptualizing the operation of alkali-ion rocking-chair batteries in terms of a competition between ion drift and diffusion via forces and concentration gradients, respectively. It is argued that the key link needed to facilitate a stronger physical bridge between coupled ionic and electronic degrees of freedom lies in the concept of a quasielectric field acting on ions between heterojunctions of ionic materials; a concept borrowed from the solid-state-device literature, where it has been extensively applied in heterojunction devices for decades, and extended in this work via the internal-energy contribution per ion particle. Within a model polymer redox battery system, for which a zero-vacuum reference energy for ions is also proposed, this approach is shown to capture standard battery concepts, including charging, discharging, capacity loss, internal resistances, nonequilibrium charge densities, and operating voltages. In this manner, the findings presented seek to provide a fundamental lasting bridge between electrochemical and electronic device descriptions.
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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 | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".