Tincone-New Hybrid Organic-Inorganic Anode Material for High Performance Li-Ion Battery
Bibliographic record
Abstract
Atomic layer deposition (ALD) is a nanomaterial synthesis method that draws more and more attention in the past few decades. Due to its self-limit growth nature, ALD has become a powerful tool for fabricating uniform and conformal thin film[1]. Molecular layer deposition (MLD), as a derivative of ALD, is a technique specially for organic or organic-inorganic hybrid films. Due to the carbon chains were involved [2], MLD thin film shows several more merits than ALD such as low growth temperature, flexibility and low density, which are very meaningful when applied in battery material. Studies of MLD film in battery field are usually focus on the following aspects. For example, applying MLD film as a post-treatment for electrode. In this way, MLD coating can suppress electrode volume change issue during discharge/charge processes because of its flexibility. [3] Secondly, if added an annealing process, MLD film with organic component would turn into porous carbon/metal oxide matrix. The post-anneal treatment would improve the contact between active material and conductive carbon, and also bring more site for heteroatom doping [4]. Although there are lots of studies of MLD film in battery field, only few researchers use MLD film as an organic electrode material. In our study, we synthesised Tincone MLD film on Nitrogen doped carbon nanotube (N-CNT), and test the electrochemical properties of this hybrid organic-inorganic anode material Tincone/N-CNT in Li-ion battery. As a result, Tincone film shows electrochemical activity in CV test, and good lithium storage ability in cycling test. The capacity retention of Tincone/N-CNT is 89% after 100 cycles. As a usage of MLD film for electrode material, Tincone/N-CNT enriches the ways of applying MLD method in battery field as well as energy storage area. Keywords: MLD battery；Tincone；Lithium ions battery References: [1] Meng X , Wang X , Geng D , et al. Atomic layer deposition for nanomaterial synthesis and functionalization in energy technology[J]. Mater. Horiz, 2017, 4(2):133-154. [2] Choudhury D , Sarkar S K , Mahuli N . Molecular layer deposition of alucone films using trimethylaluminum and hydroquinone[J]. Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films, 2015, 33(1):01A115. [3] Luo, L.; Yang, H.; Yan, P.; Travis, J. J., et al. Surface-coating regulated lithiation kinetics and degradation in silicon nanowires for lithium ion battery. ACS Nano 2015, 9, 5559−5566. [4] Chen, C., et al., Nanoporous nitrogen-doped titanium dioxide with excellent photocatalytic activity under visible light irradiation produced by molecular layer deposition. Angew Chem Int Ed Engl, 2013. 52(35): p. 9196-200.
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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) | 0.000 | 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) | 0.002 | 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".