Evidence map›Paper›PMID 42729911›Full record

ReviewACS materials Au2026

Toward Transformative Ambient Rare Earth Metal Electrorefining: A Perspective on Electrolyte Design and Circular Processing.

Abderrahman Atifi

Abstract readReview
In one paragraph

Review in ACS materials Au, 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

1 author.

Abderrahman AtifiEnergy and Environment Science & Technology, Idaho National Laboratory, Idaho Falls, Idaho 83415, United States.ORCID https://orcid.org/0000-0002-0163-5660

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ambient electrochemical production of rare earth metals (REMs) in organic electrolytes has emerged as a promising alternative to conventional high-temperature and chemically intensive processes. Over the past two decades, a limited number of research groups have demonstrated the feasibility of REM electrodeposition under room temperature conditions. However, practical implementation remains limited by challenges in metal stability, selectivity, electrolyte performance, and scalability. This perspective critically assesses reported ambient REM electrochemical systems, including ionic liquid, solvent-based, ligand-coordinated, and mediated strategies. Particular attention is given to efforts toward coupling REM production with rare earth element recovery, including direct and indirect electrorefining of spent NdFeB magnets. While conceptually promising, these approaches reveal key limitations, such as complex hydrometallurgical processing, limited anodic dissolution and loss of REM selectivity. Another central focus is the insufficient validation of electrodeposition product quality and performance, as reported characterization techniques often provide inconclusive evidence regarding purity and metallic REM formation. Future progress requires integrated advances in coordination chemistry, interfacial electrochemistry, electrolyte and electrode design, alongside process engineering and technoeconomic assessment. Within this framework, a conceptual M2REM (Magnet-To-Rare Earth Metal) is illustrated as an example of integrated electrorefining platform for the direct and ambient transformation of spent magnets into REMs, paving the way for energy-efficient and circular rare earth metal processing.

Indexed as

Ambient ElectrorefiningCritical MaterialsMagnet RecyclingOrganic ElectrolyteRare Earth Metal

Identifiers

PMID42729911
PMCPMC13564147

What OpenQuestion holds

Textmetadata
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.