Evidence map›Paper›PMID 41726630›Full record

ArticleACS omega2026

Prediction of Cross-Link Density of Prevulcanized Latex Using InGaAs NIR Spectroscopy.

Suntaree Dachapan, Khwantri Saengprachatanarug, Arthit Phuphaphud, Panmanas Sirisomboon, Chin Hock Lim, Jetsada Posom

Abstract read
In one paragraph

Article in ACS omega, 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
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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

6 authors.

Suntaree DachapanDepartment of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand.ORCID https://orcid.org/0009-0009-3544-5652
Khwantri SaengprachatanarugDepartment of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand.
Arthit PhuphaphudDepartment of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand.
Panmanas SirisomboonDepartment of Agricultural Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok 10520, Thailand.ORCID https://orcid.org/0000-0003-4689-3222
Chin Hock LimThai Rubber Latex Group Public Company Limited, Nongyai, Chonburi 20190, Thailand.
Jetsada PosomDepartment of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand.ORCID https://orcid.org/0000-0001-5976-3836

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cross-link density plays a critical role in determining the mechanical strength, elasticity, and long-term performance of prevulcanized (PV) latex products. This study aimed to evaluate the feasibility of near-infrared (NIR) spectroscopy for predicting cross-link density in PV latex using InGaAs-based instruments. Two spectrometers operating in the 960-1700 nm range were investigated: a noncontact MicroNIR and a contact AvaSpec system. Partial least-squares regression (PLSR) models were developed using two data sets. Data set I contained only NIR spectra, whereas Data set II combined spectra with industrial process variables, including holding time and latex grade. Cross-link density was referenced using the Prevulcanizate Relaxed Modulus (PRM, 100% and 300% elongation) and Toluene Swelling Index (TSI, 3 and 6 h) methods. Models based solely on Data set I showed limited predictive performance, while Data set II yielded markedly improved accuracy, highlighting the importance of integrating process information. The TSI-based models consistently surpassed PRM, with TSI-3 h identified as the most reliable reference. Using MicroNIR, the best TSI-3 h and TSI-6 h models achieved SEP values of 5.64 × 10

Identifiers

PMID41726630
PMCPMC12917818

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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.