Evidence map›Paper›PMID 41531512›Full record

ArticleRSC advances2026

Functionalized carbon nanotubes for selective lithium recovery from spent lithium-ion batteries: a sustainable approach to resource recycling.

Mohamed E Eissa, Mohamed Abdel-Megid, Bahig M Atia, Mohamed A Gado, Mohamed F Cheira, Taha F Hassanein, Haeam A Abdelmonem

Abstract read
In one paragraph

Article in RSC advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Mohamed E EissaChemistry Department, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh 11623 Saudi Arabia miissa@imamu.edu.sa.
Mohamed Abdel-MegidChemistry Department, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh 11623 Saudi Arabia miissa@imamu.edu.sa.ORCID https://orcid.org/0000-0003-4153-3295
Bahig M AtiaNuclear Materials Authority P.O. Box 530, El-Maadi Cairo 11728 Egypt.ORCID https://orcid.org/0000-0003-3714-8255
Mohamed A GadoNuclear Materials Authority P.O. Box 530, El-Maadi Cairo 11728 Egypt.ORCID https://orcid.org/0000-0002-0543-9050
Mohamed F CheiraNuclear Materials Authority P.O. Box 530, El-Maadi Cairo 11728 Egypt.ORCID https://orcid.org/0000-0002-9297-9804
Taha F HassaneinChemistry Department, Faculty of Science, Capital University (formerly Helwan University) 11795 Helwan Cairo Egypt taha1m@yahoo.com.ORCID https://orcid.org/0000-0003-1829-9605
Haeam A AbdelmonemChemistry Department, Faculty of Women for Art, Science, and Education, Ain Shams University Heliopolis Cairo 11757 Egypt.ORCID https://orcid.org/0009-0001-1706-1155

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The intensive use of lithium-ion batteries (LIBs) has led to a surge in battery waste, which is a valuable secondary resource for metal recovery. Discarded LIBs, rich in critical metals like lithium and cobalt, offer a concentrated and economically attractive source, addressing supply limitations and environmental protection. The current study presents a novel, low-cost method for selectively recovering lithium ions from both synthetic solutions and LIB waste. Using a newly created adsorbent, mesoporous carbon nanotubes functionalized with aminomethylenephosphonic acid (CNT-AMP), lithium ions were selectively extracted. Extensive characterization of the structural and functional features of CNT-AMP and/or CNT-AMP/Li was carried out utilizing a variety of techniques, including FT-IR, XPS, BET, magnetization investigations, TEM,

Identifiers

PMID41531512
PMCPMC12794198

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Registered trials

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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.