The nanofluidic capacitor: Differential capacitance in the absence of reservoirs
Bibliographic record
Abstract
Within the framework of the classical, mean-field Poisson-Boltzmann (PB) theory, we carry out direct numerical simulations to determine the differential capacitance of a closed nanochannel of a circular cross section, embedded in a polymeric host with charged walls and sealed at both ends by metal electrodes under an external potential bias. Our approach employs the modified PB equation, which accounts for the finite size of ions and the dependency of the electrolyte's relative permittivity on the local electric field. In view of the absence of reservoirs, the modified PB equation becomes subject to global algebraic constraints, without prior knowledge of a bulk electrolyte concentration. Equilibrium ion distributions and differential capacitance curves are investigated as functions of electrolyte properties and the surface charge density modulation. This modulation leads to asymmetric differential capacitance curves that can be tuned. More generally, our approach provides a transparent numerical framework for accurately simulating confined nanofluidic systems with new physical properties that may be exploited in novel iontronic circuit elements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".