Nano-Plasticity of an Electrified Ionic Liquid/Electrode Interface: Uncovering Hard–Soft Structuring via Controlled Metal Fill Factor
Bibliographic record
Abstract
Ionic liquids (ILs) nanostructuring at electrified interfaces is of both fundamental and practical interest as these materials are increasingly gaining prominence in energy storage and conversion processes. However, much remains unresolved about IL potential-controlled (re)organization under highly polarized interfaces, mostly due to the difficulty of selectively probing both the distal and proximal surface layers of adsorbed ions. In this work, the structural dynamics of the innermost layer (<10 nm from the surface) were independently interrogated from that of the ionic layers in the sub-surface region (>100 nm from the surface), using an infrared (IR) spectroscopy approach. By tuning the metal fill factor of gold films deposited on conductive metal oxide-modified IR internal reflection elements, the charge-driven (re)structuring of the inner and distal layers of 1-butyl-1-methylpyrrolidinium trifluoromethanesulfonate is unveiled. Within a relatively wide potential region (∼±1 V) bounding the potential of zero charges, the ionic liquid is shown to undergo a reversible (i.e., soft) reorganization whereby the innermost layer of anions (cations) is exchanged by a layer of cations (anions). Kinetically unhindered changes in the number density of constituent cations and anions largely follow electrostatic expectations in the subsurface region, whereas the innermost layer exhibits a pronounced hysteresis and very slow relaxation. Under larger negative potential bias, IL restructuring is characterized by a highly irreversible (i.e., hard) and intense interfacial densification of the BMPy + cations, consistent with the formation of nanoscale segregated liquids. The outcomes of this work reveal a plastic IL nanostructuring under a strong electric field.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".