Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 257

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

High-Performance Graphite Recovered from Spent Lithium-Ion Batteries

Ma, Xiaotu, Chen, Mengyuan, Chen, Bin, Meng, Zifei, Wang, Yan·2019·ACS Sustainable Chemistry & Engineering

Abstract

With the wide usage of Li-ion batteries (LIBs) in portable electronics, electric vehicles, and grid storage, recycling and reusing LIBs have attracted wide attention. However, due to the low added value and rigorous separation steps, recycling and recovering graphite anode materials are discarded. Although some direct physical recycling processes have been reported, all of them are limited by rigorous separation steps and lab scales. In this paper, a scalable recycling process for graphite anode materials from spent LIBs by a hydrometallurgical process without separation steps is reported. After the leaching process, graphite was separated by filtration as a residue with impurities. Then, all residual cathode materials, other metal impurities, most binding materials, and aluminum oxide were removed after releaching and fusion steps. Finally, high-quality graphite powder was obtained, and the recycled graphite exhibits a comparable discharge capacity of 377.3 mAh/g at 0.1 C.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acssuschemeng.9b05003

Cites

25 of 25 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 25 references

Cited by

See all 257

Metadata

Authors
Ma, X., Chen, M., Chen, B., Meng, Z., & Wang, Y.
Venue
ACS Sustainable Chemistry & Engineering
Published
2019-11-13
Volume
7
Issue
24
Pages
19732-19738
ISSN
2168-0485 (ISSN-L)
OpenAlex
W2984501898
Cited by
257
References
25
FWCI
11.44
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: High-Performance Graphite Recovered from Spent Lithium-Ion Batteries. https://app.cochat.ai/papers/10.1021/acssuschemeng.9b05003
The paper
Ma, X., Chen, M., Chen, B., Meng, Z., & Wang, Y. (2019). High-Performance Graphite Recovered from Spent Lithium-Ion Batteries. ACS Sustainable Chemistry & Engineering. https://doi.org/10.1021/acssuschemeng.9b05003

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.