(Invited) Tribute to Prof. Zempachi Ogumi : In Operando Studies and in Situ Techniques for Li-Ion and Lithium Metal Polymer Batteries
Bibliographic record
Abstract
Prof. Ogumi is one the leading pioneers of lithium-ion technology in Japan and worldwide. His research studies on battery materials include LiCoO 2 , graphite, and highly oriented pyrolytic graphite (HOPG), Much of his research involved in situ techniques that utilized X-ray, Raman spectroscopy and atomic force spectroscopy (AFM) to investigate the SEI (passivation layer) and lithium intercalation in graphite and HOPG in propylene carbonate (PC)- and ethylene carbonate (EC)-based electrolytes. In this presentation, we will show data and video movies that were obtained during studies of lithium-ion and solid-state batteries using various In operando studies and in situ techniques involving scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy, X-ray diffraction and ultraviolet-visible absorption spectroscopy (UV-vis). These in situ studies are helpful to understand the mechanisms for volume expansion of anodes consisting of lithium metal (20 %), graphite (10 %) and LTO (0 %). Another example that will be discussed is the dimensional changes of the anode, cathode and electrolyte that occur during charge/discharge. The mechanism of lithium dendrite formation was also studied, and details will be discussed in this presentation. [Don’t know what is meant by Bleand and deleted because I‘m not sure it is needed.] Lithium/solid polymer electrolyte (SPE)/sulfur cells were studied by two in situ techniques: SEM and UV-vis. During the operation of the cell, extensive polysulfide dissolution in the solid polymer electrolyte (cross-linked polyethylene oxide) leads to the formation of a catholyte. A clear micrograph was obtained of the thick passivation layer on the sulfur-rich anode and the decreased SPE thickness during cycling confirmed the failure mechanism; the capacity decays by reducing the amount of active material, which contributes to a charge inhibiting mechanism called polysulfide shuttle. The formation of elemental sulfur is clearly visible in real time during the charge process beyond 2.3 V. The non-destructive UV-vis also shows the characteristic absorption peaks that evolve with cycling, demonstrating the accumulation of various polysulfide species, and the predominant formation of S 4 2- and of S 6 2- during discharge and charge, respectively. This finding implies that the charge and discharge reactions are not completely reversible and proceed along different pathways.
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 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 | 0.001 | 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 teacher head, 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".