Localized Investigations of the Electrochemical Properties of Lithium Battery Materials Using Micro-Pipets
Bibliographic record
Abstract
Lithium ion batteries are a commercially successful method for portable electrical energy, demonstrated by their use in portable electronics and the recent application as an alternative automotive power source to the internal combustion engine.1 However, for lithium ion batteries to be a competitive alternative to fossil fuels in the automotive industry, electrode materials with improved capacity and charge/discharge rates are required. As new anode and cathode materials are developed2 they are typically screened for advantageous properties by assembly into a working battery. This involves the fabrication of a film from a mixture of conductive material (e.g. carbon), a binder (e.g. polyvinylidene fluoride), and the active material of interest. A film is cast onto a conductive material to form the active electrode, before assembly within a coin cell. How the film is cast, the ratio of the individual components of the film, the drying procedure for the film and the final assembly of the coin cell can significantly alter the performance of the battery.3,4 In order to avoid misleading information about the effectiveness of a novel active material many coin cells are required to validate findings. Here we present micro-pipet measurements5 which demonstrate the suitability of the technique for probing lithium ion battery materials. Specifically, we probed dispersions of active materials to determine the oxidation and reduction potentials, and the charge capacity of the material. Data obtained on candidate materials by the micro-pipet method was compared to coin cell measurements, to critically assess this technique for characterisation of active battery materials. 1) Wagner, F. T.; Lakshmanan, B.; Mathias, M. F.; J. Phys. Chem. Lett., 2010, 1 (14), 2204–2219 2) Whittingham, M.S.; Chem. Rev., 2004, 104 (10), 4271–4302 3) Bruce, P. G.; Scrosati, B.; Tarascon, J.-M.; Angew. Chem.-Int. Ed. 2008, 47 (16), 2930-2946 4) Ban, C.; Wu, Z.; Gillaspie, D. T.; Chen, L.; Yan, Y.; Blackburn, J. L.; Dillon A. C.; Adv. Mater. 2010, 22, E145–E149 5) Williams, C. G.; Edwards, M. A; Colley, A. L.; Macpherson, J. V; Unwin, P. R.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".