Evidence map›Paper›PMID 42204338›Full record

ArticleScientific reports2026

Design and characterization of visually opaque but near-infrared transparent coatings for better barcode readability.

Ravi Arukula, Taehyun Kim, Songwei Lu, Xiaoning Qi

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ravi Arukula *Department of Coatings and Polymeric Materials, North Dakota State University, Fargo, ND, 58108, USA.
Taehyun Kim *Department of Coatings and Polymeric Materials, North Dakota State University, Fargo, ND, 58108, USA.
Songwei LuCoatings Innovation Center, PPG Industries, Inc., 4325 Rosanna Drive, Allison Park, PA, 15101, USA.
Xiaoning QiDepartment of Coatings and Polymeric Materials, North Dakota State University, Fargo, ND, 58108, USA. xiaoning.qi@ndsu.edu.

Funding

NATIONAL CENTER FOR MANUFACTURING SCIENCES (NCMS) 2021119-142117
6 · The paper itself

Abstract

Coatings that are visually opaque yet transparent in the near-infrared (NIR) spectrum are desirable for secure identification and thermal management. In this study, we investigated a bilayer coating system comprising a clear sealer coat and a topcoat that is visually opaque but NIR transparent (NIRT) in three color variations: black, green, and tan. Using the coating system, we successfully concealed the encoded information (barcodes printed on synthetic paper sheets) in the visible spectrum while maintaining sufficient barcode readability (measured by delta gray values (∆GVs)) in the NIR spectrum. Among all coatings, the black NIRT coatings showed better performance, providing the highest NIR transmittance, sharp barcode edges, signal-to-noise ratio (SNR) (9.4 dB), and reliable readability up to 15.2 m (50 ft). The green and tan coatings also performed well, though adding white pigments slightly reduced contrast, readability, and SNR. To further optimize the barcode readability, we investigated the effects of two categories of factors: (1) materials-related factors (i.e., pigment type, pigment loading, additive selection, and particle size distribution), and (2) process-related factors (i.e., dispersion methods, blade type, mixing time, and dry film thickness). It was found that the average particle size strongly correlates with the final coating NIR transmittance and barcode readability. Specifically, coatings with an average particle size of 566.3 nm have the highest NIR transmittance and barcode readability. Larger average particle size (708.7 nm) results in coatings with moderate NIR transmittance and barcode readability. When the particle size distribution is bimodal (346.1 nm and 1845.7 nm), coatings' NIR transmittance and barcode readability are greatly reduced. These findings are consistent with Mie scattering theory. Large and broadly distributed particles around 750 nm scatter more incident NIR light and reduce barcode readability. In contrast, small and narrowly distributed particles scatter less, therefore enhancing both NIR transmittance and barcode readability. The bilayer coating system was also tested for solvent resistance, mandrel bend flexibility, and UV stability, with results demonstrating its suitability for field application. Overall, through analyzing key factors governing the balance between visual opacity, NIR transmittance, and barcode readability, we establish a feasible material-process-performance framework for designing visually opaque and NIR coatings.

Indexed as

Barcode concealmentBarcode readabilityMie scatteringNIR-transparent coatingsOptical performancePigment formulationRapid-curing coatingsVisually opaque coatings

Identifiers

PMID42204338
PMCPMC13442852

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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.