Upcycling Spent Lithium Iron Phosphate Battery Into Fe-CN

Xianhui Ke, Kun Qian, Xiaoning Li, Xinyu Zheng, Zhongyong Yuan, Tianyi Ma, Wei Jin

Abstract read

In one paragraph

Article in Angewandte Chemie (International ed. in English), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Xianhui KeSchool of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou, P.R. China.

Kun QianSchool of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou, P.R. China.

Xiaoning LiCentre For Atomaterials and Nanomanufacturing (CAN), RMIT University, Melbourne, VIC, Australia.ORCID https://orcid.org/0000-0001-5991-0955

Xinyu ZhengSchool of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou, P.R. China.

Zhongyong YuanCollaborative Innovation Center of Materials Science, Nankai University, Tianjin, China.ORCID https://orcid.org/0000-0002-3790-8181

Tianyi MaCentre For Atomaterials and Nanomanufacturing (CAN), RMIT University, Melbourne, VIC, Australia.ORCID https://orcid.org/0000-0002-1042-8700

Wei JinSchool of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou, P.R. China.ORCID https://orcid.org/0000-0003-2671-1989

Funding

National Natural Science Foundation of China 22306066National Natural Science Foundation of China 22406139National Natural Science Foundation of China 52570168Natural Science Foundation of Jiangsu Province BK20240049Natural Science Foundation of Jiangsu Province BK20241000Shanghai Synchrotron Radiation Facility (SSRF) with beamline BL16U1Suzhou Project ZXL2024374

6 · The paper itself

Abstract

Increasing environmental pollution and shortage of critical resources call for technologies capable of achieving total resource recovery from waste materials. In this study, high leaching rates of 99.16% for lithium and 97.37% for iron were obtained from spent lithium iron phosphate (LFP) batteries through electrochemical (EC) advanced oxidation processes (EAOPs), and associated leaching mechanism was subsequently investigated. Moreover, residual C, Fe, and P elements in leach residue were directly converted into a P, N-doped asymmetric single-atom Fe catalyst (Fe-CN

Indexed as

coordination environmentperoxymonosulfate activationsingle‐atom catalystsspent lithium‐ion batteriesupcycling

Identifiers

PMID41757593

DOI10.1002/anie.2788872

PMCPMC13053904

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.