Alteration of Oxygen Evolution Mechanisms in Layered LiCoO<sub>2</sub> Structures By Intercalation of Alkali Metal Ions
Bibliographic record
Abstract
The word ‘Sustainability’, including carbon neutrality, has dominated the direction of social development over the past decade. In particular, energy conversion reactions through electrochemical methods are one of the efficient methods of obtaining small carbon footprint fuels. The oxygen evolution reaction (OER) is a key step in determining the overall reaction efficiency of fuel-related electrochemical reactions such as CO2 reduction reaction and H2 evolution reaction. However, electron transfer is sluggish for OER due to 4 electrons per one O2 molecule. This promotes multiple studies on the metal oxide electrocatalyst structure. The Alkali-transition metal oxides with the layered structure are one of the attractive OER electrocatalyst series. For example, lithium cobalt oxide (LiCoO2, LCO) presented OER activity through Li+ extraction (delithiation) from the lattice structure. In this work, we investigated the insertion effect of large alkaline cations (A+: Na+, K+, and Cs+) at the delithiated LCO for OER activity and stability. The intercalations of hydrated Na+ and K+ induced significant phase transformation of the delithiated LCO structure. In addition, the relative ratio between Co and alkali metal species determined the average Co oxidation state of LCO. We found that OER activity was improved in the order of Li+ < Na+ < K+, which was associated with the increased Co valence state and the Co-O bond covalency. Consistently, density functional theory (DFT) simulation also predicted the formation of efficient OER active sites by the K+ insertion. In comparison, Cs+ insertion exhibited the highest OER activity and demonstrated different OER processes. Due to the larger Cs+ size, the cation insertion was predominantly achieved at the delithiated LCO surface, resulting in imposing tensile strain to the surface edge. This catalyst showed the significant pH dependency on the OER property, suggesting the lattice-oxygen-based pathway for LCO. However, the bulk structure was preserved with little phase transformation, demonstrating better OER stability than others. In the presentation, I will discuss the catalytic activity responsible for the cation sizes and two different mechanisms in detail. 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 | 0.000 | 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 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".