Second-Life Evaluation of Li-Ion Battery Graphite after Separation and Pre- and Postpurification Treatments of Black Mass
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Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide This study assessed the viability of using two types of prepurified recycled graphite derived from spent battery materials, namely, black mass (BM), and compared their effectiveness to that of virgin battery-grade commercial natural graphite (NG). The first type of recycled graphite, prepurified carbon residue (PCR), was obtained through reductive acid leaching and thermomechanochemical processes with a carbon content of 97.6%. The second type, prepurified concentrate (PConcentrate), was produced via thermal-assisted flotation and thermomechanochemical processes, with a carbon content of 98.6%. Both types of recycled graphite, PCR and PConcentrate, underwent further purification using either an ultrahigh-temperature (UHT) approach or a thermochlorine treatment (TCT). These were followed by an amorphous carbon coating process to meet the graphite specifications for battery use. The structural analyses confirmed that both PCR and PConcentrate met the specifications for battery-grade graphite after purification and carbon coating. The electrochemical assessments showed that cells with recycled graphite, PConcentrate-TCT and PCR-TCT, exhibited specific capacities of 99 and 96 mAh/g, respectively, comparable to 99 mAh/g achieved by cells with commercial NG at a 2C rate. Additionally, after 250 charge/discharge cycles at 1C, cells with recycled graphite retained about 86% capacity, surpassing the 75% retention of cells with a commercial NG anode. Our results concluded that overall, spent graphite sourced and extracted from BM by flotation resulted in superior electrochemical performances. Moreover, graphite purified under UHT exhibited superior cyclability compared to TCT, while TCT purification resulted in higher specific capacity of the electrodes.
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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 | 0.000 | 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) | 0.000 | 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 it