Double Approach Towards 3D Electrodeposited RuO<sub>x</sub> Porous Structure for High Energy/High Power Micro-Supercapacitors
Bibliographic record
Abstract
Hydrous RuOx has been one of the well-studied materials for application in supercapacitors owing to its excellent properties (high conductivity similar to metals, redox activity capable of fast faradaic reactions and structural water enabling swift proton transfer and decreased diffusion distance). The main issue regarding supercapacitors is that, they suffer from low energy density compared to batteries. One way to overcome this problem is to increase surface area of the active material and hence the energy stored through 3D structuration of current collector. Multiple techniques have been used in this regard like 3D printing, pholitography methods...etc. However, these techniques are pretty complex, time consuming and have constraining conditions. Hence, it’s necessary to develop economic and simple routes for 3D structuration of electrodes for micro-supercapacitors. One simple, time efficient and easy to set up method that can be used under ambient conditions is the electrochemical structuration using dynamic hydrogen bubble template (DHBT). With this strategy, 3D scaffolds which can hold small quantities of intrinsic pseudocapacitve materials like RuOx can be fabricated. The challenge in this latter case is magnified, needing controlled decoration of active materials for efficient utilization and full benefit of the 3D framework. Hence, the pursuit of superior micro-supercapacitors not only needs controlled deposition, but also requires stable 3D scaffolds to maximize capacitance per footprint area1. We have previously shown electrodeposition of active RuOx on porous gold electrodes for micro-supercapacitors achieving a capacitance of 3 F/cm².2 One other approach would be to deposit the active material directly by the DHBT method. As RuOx is a good conductor this would not hinder its efficiency (this would not be the case for MnO2 for example). The difficulty here is that, not all metals can be deposited by the DHBT technique as other factors play a crucial role such as the exchanged current density towards H2 evolution and mechanical stability3. In the current work, we report two different strategies for the 3D deposition of RuOx. The first is the successful fabrication of highly porous 3D platinum current collector using DHBT followed by a conformal coating of hydrous RuOx to achieve a specific capacitance as high as 7 F/cm². The second is the direct electrodeposition of the active material, RuOx, in a 3D porous structure. These two approaches are characterized and discussed within the framework of fabricating superior micro-supercapacitors with excellent capacitance and low internal resistance. References 1. N. A. Kyeremateng, T. Brousse, and D. Pech, Nat. Nanotechnol., 12, 7–15 (2017) 2. A. Ferris, S. Garbarino, D. Guay, and D. Pech, Adv. Mater., 27, 6625–6629 (2015) 3. Plowman, B. J., Jones, L. A., & Bhargava, S. K. Chem. Commun., 51, 4331–4346 (2015) Figure 1
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".