Real-Time Convolutional Voltammetry Enhanced by Energetic (Hot) Electrons and Holes on a Surface Plasmon Waveguide Electrode
Bibliographic record
Abstract
Surface plasmon polaritons (SPPs) propagating along a waveguide working electrode are sensitive to changes in the local refractive index, which follow changes in the concentration of reduced and oxidized species near the working electrode. The real-time response of the output optical power from a waveguide working electrode is proportional to the time convolution of the electrochemical current density, precluding the need to compute the latter a posteriori via numerical integration. Convolutional voltammetry yields complementary results to conventional voltammetry and can be used to determine the diffusion constant, bulk concentration, and the number of transferred electrons of electroactive species. The theoretical optical response of a waveguide working electrode is derived and validated experimentally via chronoamperometry and cyclic voltammetry measurements under low power SPP excitation, for various concentrations of potassium ferricyanide in potassium nitrate electrolyte at various scan rates. Increasing the SPP power induces a regime where the SPPs no longer act solely as a probe of electrochemical activity, but also as a pump creating energetic electrons and holes via absorption in the working electrode. In this regime, the transfer of energetic carriers (electrons and holes) to the redox species dominates the electrochemical current density, which becomes significantly enhanced relative to equilibrium conditions (low SPP power). In this regime the output optical power remains proportional to the time convolution of the current density, even with the latter significantly enhanced by the transfer of energetic carriers.
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 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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".