Van der Waals Heterostructures—Recent Progress in Electrode Materials for Clean Energy Applications
Bibliographic record
Abstract
The unique layered morphology of van der Waals (vdW) heterostructures give rise to a blended set of electrochemical properties from the 2D sheet components. Herein an overview of their potential in energy storage systems in place of precious metals is conducted. The most recent progress on vdW electrocatalysis covering the last three years of research is evaluated, with an emphasis on their catalytic activity towards the oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER). This analysis is conducted in pair with the most active Pt-based commercial catalyst currently utilized in energy systems that rely on the above-listed electrochemistry (metal-air battery, fuel cells, and water electrolyzers). Based on current progress in HER catalysis that employs vdW materials, several recommendations can be stated. First, stacking of the two types vdW materials, with one being graphene or its doped derivatives, results in significantly improved HER activity. The second important recommendation is to take advantage of an electronic coupling when stacking 2D materials with the metallic surface. This significantly reduces the face-to-face contact resistance and thus improves the electron transfer from the metallic surface to the vdW catalytic plane. A dual advantage can be achieved from combining the vdW heterostructure with metals containing an excess of d electrons (e.g., gold). Despite these recent and promising discoveries, more studies are needed to solve the complexity of the mechanism of HER reaction, in particular with respect to the electron coupling effects (metal/vdW combinations). In addition, more affordable synthetic pathways allowing for a well-controlled confined HER catalysis are emerging areas.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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; both teacher heads agree on what is shown here.
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".