Evidence map›Paper›PMID 41900187›Full record

ArticleMicromachines2026

A Battery-Free, Data-Informed UV Dose Sensor Made of Laser-Induced Graphene and Bio-Derived Electrolytes.

Mohammadreza Chimerad, Pouya Borjian, Faisal Bin Kashem, Swaminathan Rajaraman, Hyoung J Cho

Abstract read
In one paragraph

Article in Micromachines, 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

5 authors.

Mohammadreza ChimeradDepartment of Mechanical & Aerospace Engineering, College of Engineering & Computer Science, University of Central Florida, Orlando, FL 32816, USA.
Pouya BorjianDepartment of Mechanical & Aerospace Engineering, College of Engineering & Computer Science, University of Central Florida, Orlando, FL 32816, USA.ORCID 0000-0002-0891-8030
Faisal Bin KashemDepartment of Electrical and Computer Engineering, NanoScience Technology Center, University of Central Florida, Orlando, FL 32816, USA.ORCID 0000-0001-7391-9964
Swaminathan RajaramanDepartment of Electrical and Computer Engineering, NanoScience Technology Center, University of Central Florida, Orlando, FL 32816, USA.
Hyoung J ChoDepartment of Mechanical & Aerospace Engineering, College of Engineering & Computer Science, University of Central Florida, Orlando, FL 32816, USA.ORCID 0000-0002-6563-4317

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a sustainable, battery-free UV (ultraviolet) dose sensor designed for intelligent food packaging applications. The device integrates laser-induced graphene (LIG) electrodes, a ZnO-CNT (carbon nanotube) UV-active composite, and a bio-derived ionochromic cell composed of blueberry anthocyanins and a NaCl electrolyte. This work advances the platform by introducing a quantitative and predictive dose-color mapping framework for cumulative UV detection under zero-bias operation. A controlled charge-injection protocol was employed to emulate UV-generated photocurrent, enabling systematic investigation of charge-transfer-driven ionochromic kinetics across five current levels (0.2-3 mA). HSB (hue-saturation-brightness)-based colorimetric analysis was performed to quantify the time-dependent chromatic evolution, and a numerical fitting model was developed to map charge accumulation to color shifts. Using this calibration, the color response at microampere-level photocurrents-corresponding to real zero-bias UV operation-can be predicted. The resulting model enables estimation of the cumulative time required for the ionochromic cell to transition from red to purple under realistic UV intensities. By combining self-powered sensing with predictive colorimetric modeling, this work significantly enhances the functionality of battery-free UV indicators, enabling quantitative dose measurement without external electronics for safer food-supply-chain monitoring.

Indexed as

dose modelingflexible sensorsintelligent food packagingionochromic celllaser-induced graphenesustainable materialsUV sensors

Identifiers

PMID41900187
PMCPMC13027796

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.