Evidence map›Paper›PMID 42866652›Full record

ArticleiScience2026

Baseline techno-economic and life cycle assessment of black mass production.

Tanongsak Yingnakorn, Chatisa Kansomket, Chaiyasit Longbutsri, Sean Scott, Tapany Patcharawit, Jake M Yang, Andrew P Abbott, Sakhob Khumkoa

Abstract read
In one paragraph

Article in iScience, 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

8 authors.

Tanongsak YingnakornSchool of Metallurgical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand.
Chatisa KansomketSchool of Metallurgical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand.
Chaiyasit LongbutsriSchool of Metallurgical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand.
Sean ScottSchool of Chemistry, University of Leicester, Leicester LE1 7RH, UK.
Tapany PatcharawitSchool of Metallurgical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand.
Jake M YangSchool of Chemistry, University of Leicester, Leicester LE1 7RH, UK.
Andrew P AbbottSchool of Chemistry, University of Leicester, Leicester LE1 7RH, UK.
Sakhob KhumkoaSchool of Metallurgical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recycling lithium-ion batteries hinges on economically producing black mass-the electrode powder concentrate that feeds downstream metal recovery-yet public baselines pairing real process economics with environmental impacts remain scarce. Here we show that a purely mechanical flowsheet-shredding, zigzag air classification, and circular screen vibration-applied identically to two structurally distinct feedstocks recovers black mass at 93.28 wt % separation efficiency from electric-vehicle modules and 75.77 wt % from mobile phone cells. Built on measured pilot data, loaded processing costs of $0.31-0.73/kg yield net profits of $4.39-5.53/kg under realistic feedstock purchase prices, with a probability of unprofitability below 0.2% across simulated market scenarios. Life cycle assessment attributes most impacts to grid electricity, with a global warming potential of 0.210-0.241 kg CO

Indexed as

baselineblack masscarbon footprintelectric vehiclelife cycle assessmentlithium-ion batteriesmechanical separationtechno-economic assessment

Identifiers

PMID42866652
PMCPMC13657251

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.