Graphene and Germanane materials for energy applications-A review
Bibliographic record
Abstract
Research on 2D materials is a hot topic in academia and industry to explore novel materials like graphene and its analogues, silicene, germanane. Graphene's success has shown not only that it is possible to create stable, single-atom-thick sheets from a crystalline solid but that these materials have fundamentally different properties than the parent material. Graphene is a potential 2D material suitable for advanced applications especially when it is used in the form of graphane. This is because, graphane is found to have electronically stable compared to parent material due to van der Waals interactions. Germanane is a germanium graphane analogue, an advanced 2D material and it is better than graphene because, they do not form flat planar structure like as in graphene. Germanane can be a hydrogenated form of germanium network with hydrogen atoms are distributed equally above and below the Ge layer. Therefore, surface modification of Germanane is one of the hot topic of research. In this review, we elaborate on applications of graphene and germanane in sensing, supercapacitors and optoelectronic devices. Overall, this work demonstrates, electrochemical analysis of graphene for optoelectronic, supercapacitor and sensing applications. Light emitting diode (LED) can be prepared by stacking metallic graphene with various semiconducting monolayers. These, heterostructured material is expected to grow further on increasing the number of available 2D crystals and improving their electronic quality. Graphene-based nano-inks can be used to manufacture supercapacitors in the form of flexible and printable electronics. Another promising application of graphene will be in energy storage devices due to these novel properties like highly tunable surface area, outstanding electrical conductivity, good chemical stability and excellent mechanical behavior. Also, this paper summaries analysis of synthesis, structural modifications, thermal stability and enhanced optoelectronic properties of germanane in detail. A novel electrochemical sensor which had crucial properties such as being reproducible, repeatable, and stable was developed for phenol detection by using, the complex materials like methyl germanane and chemically activated pencil graphite electrodes. Germanane field effect transistors fabricated from multilayer single crystal flakes enhance the conductivity. Germanane, exhibits viable pathway towards the replacement of graphene applications [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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".