In-Situ Scanning Transmission X-Ray Microscopy Studies of MnO<sub>2</sub>-Based Supercapacitor Electrodes
Bibliographic record
Abstract
Supercapacitors (SCs) as energy storage devices provide higher energy density than conventional capacitors and higher power density than batteries1. Understanding how charge is efficiently stored in the electrodes or across the electrolyte/electrode interface is key to developing advanced SC electrodes. Scanning transmission x-ray microscopy (STXM) studies2 have been used to investigate MnO2 based supercapacitor electrodes using a novel three-electrode based in-situ flow electrochemical device (Fig. 1)3, 4. Near-edge X-ray absorption fine structure (NEXAFS) spectra of MnO2 films in-situ deposited and subjected to several different electrochemical processes were measured with high spatial resolution at the Mn L3 and O K edges (Fig. 2) at both working electrode (WE) and counter electrode (CE) regions. In this work, the redox state changes associated with pseudocapacitance during charging/discharging processes in a potential window of -0.5 VAu to +0.9 VAu (+0.1 VRHE to +1.5 VRHE) have been investigated. The spectroscopic data and quantitative chemical mapping by in-situ STXM measurements demonstrated that an as-electrodeposited MnO2 film was reduced to both Mn3+ and Mn2+ oxidation states through a reversable Mn4+ ↔ Mn3+/Mn2+ redox reaction. A significant change from a quasi-uniform MnO2 film to a dendritc MnO2 structure was observed during discharging at +1.5 VRHE (Fig. 3, Fig. 4) corresponding to redeposition of Mn2+ dissolved into electrolyte during the reduction process5. In-situ STXM measurements at the CE showed there is deposition of MnO2 during the reduction reaction (charging process) at +0.1 VRHE. Mn L3 features of Mn2+ appeared in the electrolyte region during the reduction process and disappeared during the oxidation process, confirming the dissolution/redeposition mechanism. We have developed a novel and versatile platform for in situ studies of electrochemical processes, including supercapacitors, batteries, and electro-catalysts3, 4. References A. G. Olabi, Q. Abbas, A. Al Makky, and M. A. Abdelkareem, Energy, 248 123617 (2022). K. V. Kaznatcheev, C. Karunakaran, U. D. Lanke, S. G. Urquhart, M. Obst, and A. P. Hitchcock, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 582 (1), 96-99 (2007). A. P. Hitchcock, C. Zhang, H. Eraky, L. Shahcheraghi, F. Ismail, and D. Higgins, Microscopy and Microanalysis, 27 (S2), 59-60 (2021). C. Zhang, N. Mille, H. Eraky, S. Stanescu, S. Swaraj, R. Belkhou, D. Higgins, and A. Hitchcock, (2023). T.-H. Wu, Y.-Q. Lin, Z. D. Althouse, and N. Liu, ACS Applied Energy Materials, 4 (11), 12267-12274 (2021). Figure 1
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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 | 0.000 |
| 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) | 0.001 | 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".