Electroactive Light Metal Nanostructures for Corrosion Protection and Electrochemical Energy Storage
Bibliographic record
Abstract
Stability in electrochemical systems is governed by interactions at the local scale where isolated inhomogeneities can define system performance. This concept plays a key role in failure of battery systems and corrosion of materials. For rechargeable batteries, replacement of graphite with metal anodes provides considerable promise for sizable gains in gravimetric and volumetric energy densities. However, out of equilibrium processes guide formation of anisotropic, dendritic growths which are capable of short circuiting the cell and causing catastrophic failure of the system. Magnesium-based batteries have garnered significant interest as an alternative to lithium-ion largely due to its designation as a ‘dendrite free’ system. \nThis would allow for the use of metal anodes providing significant improvements in capacity compared to graphite but requires controlled and consistent plating and stripping of the active metal over hundreds of cycles. Here, we detail our investigations into the electrodeposition of magnesium in varying electric fields, electrolyte concentrations, and with the addition of growth-directing ligands, providing understanding of mechanisms of deposition across a wide range of deposit morphologies. Through combining in situ video microscopy studies of electrodeposition of Mg in symmetric cells with 3D tomographic characterization and mesoscale modeling we demonstrate some of the first definitive examples of dendritic growth on magnesium anodes and elucidate mechanisms of formation. \nIn corroding systems, local inhomogeneities often serve as key sites in failure, often dominating electrochemical activity. For corrosion inhibition, our approach has involved modular design of nanocomposite coatings enabling multiple modes of corrosion protection. Here we outline our efforts in design of magnesium nanoparticle and exfoliated graphite-based nanocomposites for protection of high-strength aluminum alloys. Mechanisms of corrosion inhibition have been elucidated through extended submersion testing coupled with electrochemical impedance spectroscopy measurements.
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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".