Evidence map›Paper›PMID 40550798›Full record

ArticleScientific data2025

Long-Term Sweat Testing Dataset for Second-Life Batteries.

Matthew Beatty, Dani Strickland, Joe Warren, John Chan, Pedro Ferreira

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. 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

5 authors.

Matthew BeattyWolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, UK.
Dani StricklandWolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, UK. D.Strickland@lboro.ac.uk.
Joe WarrenPowervault, Unit 9, Garrick Industrial Centre, Irving Way, London, NW9 6AQ, UK.
John ChanPowervault, Unit 9, Garrick Industrial Centre, Irving Way, London, NW9 6AQ, UK.
Pedro FerreiraWolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, UK.

Funding

Wellcome Trust 103951
6 · The paper itself

Abstract

This paper describes a long-term cycling dataset of repurposed lithium-ion batteries originally used in electric vehicles. After their initial automotive use - referred to as their "first life" - these batteries were redeployed for stationary energy storage applications, representing their "second life". The dataset covers six distinct use cases modelled to represent real-world energy storage applications. Unlike other published datasets, which focus on new or first-life cells, this work exclusively features second-life batteries with no available data from prior usage. It is aimed at supporting research into battery degradation, state of health prediction, and performance benchmarking under aged conditions. Data was collected using a Chroma 17020 batter cycler and originally stored as large, continuous log files. This paper outlines the steps taken to reorganise and clean the data - handling missing values and segmenting it into individual cycles - while preserving its raw experimental content. Cycling occurred intermittently between 2019 and 2025, offering a uniquely long observation period. The dataset supports both academic and industrial research into battery ageing and second-life applications.

Identifiers

PMID40550798
PMCPMC12185753

What OpenQuestion holds

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LicenceCC BY
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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.