Evidence map›Paper›PMID 36844748›Full record

ArticleACS sustainable chemistry & engineering2023

Circular Economy Electrochemistry: Creating Additive Manufacturing Feedstocks for Caffeine Detection from Post-Industrial Coffee Pod Waste.

Evelyn Sigley, Cristiane Kalinke, Robert D Crapnell, Matthew J Whittingham, Rhys J Williams, Edmund M Keefe, Bruno Campos Janegitz, Juliano Alves Bonacin, Craig E Banks

Abstract read
In one paragraph

Article in ACS sustainable chemistry & engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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

9 authors.

Evelyn SigleyFaculty of Science and Engineering, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, United Kingdom.
Cristiane KalinkeFaculty of Science and Engineering, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, United Kingdom.
Robert D CrapnellFaculty of Science and Engineering, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, United Kingdom.
Matthew J WhittinghamFaculty of Science and Engineering, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, United Kingdom.
Rhys J WilliamsFaculty of Science and Engineering, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, United Kingdom.
Edmund M KeefeFaculty of Science and Engineering, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, United Kingdom.
Bruno Campos JanegitzDepartment of Nature Sciences, Mathematics, and Education, Federal University of Säo Carlos (UFSCar), 13600-970 Araras, Säo Paulo, Brazil.ORCID https://orcid.org/0000-0001-9707-9795
Juliano Alves BonacinInstitute of Chemistry, University of Campinas (Unicamp), 13083-859 Campinas, Säo Paulo, Brazil.
Craig E BanksFaculty of Science and Engineering, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, United Kingdom.ORCID https://orcid.org/0000-0002-0756-9764

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recycling of post-industrial waste poly(lactic acid) (PI-PLA) from coffee machine pods into electroanalytical sensors for the detection of caffeine in real tea and coffee samples is reported herein. The PI-PLA is transformed into both nonconductive and conductive filaments to produce full electroanalytical cells, including additively manufactured electrodes (AMEs). The electroanalytical cell was designed utilizing separate prints for the cell body and electrodes to increase the recyclability of the system. The cell body made from nonconductive filament was able to be recycled three times before the feedstock-induced print failure. Three bespoke formulations of conductive filament were produced, with the PI-PLA (61.62 wt %), carbon black (CB, 29.60 wt %), and poly(ethylene succinate) (PES, 8.78 wt %) chosen as the most suitable for use due to its equivalent electrochemical performance, lower material cost, and improved thermal stability compared to the filaments with higher PES loading and ability to be printable. It was shown that this system could detect caffeine with a sensitivity of 0.055 ± 0.001 μA μM

Identifiers

PMID36844748
PMCPMC9945317

What OpenQuestion holds

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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.