Evidence map›Paper›PMID 42452028›Full record

ArticlePolymers2026

Data-Driven Multivariate Characterization of Hydrogen-Induced Response Evolution in EPDM, NBR, and FKM Elastomers.

Nitesh Subedi, Alfredo Becerril Corral, Md Monjur Hossain Bhuiyan, Omkar Gautam, Md Ariful Islam, Zahed Siddique

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In one paragraph

Article in Polymers, 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

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

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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

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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

6 authors.

Nitesh SubediSchool of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA.ORCID 0009-0004-1830-9716
Alfredo Becerril CorralSchool of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA.
Md Monjur Hossain BhuiyanSchool of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA.ORCID 0009-0008-6651-1889
Omkar GautamSchool of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA.ORCID 0009-0006-8475-1291
Md Ariful IslamSchool of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA.
Zahed SiddiqueSchool of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA.ORCID 0000-0003-2930-078X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hydrogen-compatible elastomeric seals are critical for the reliability and safety of high-pressure hydrogen infrastructure. However, hydrogen exposure can alter the mechanical response and surface condition of elastomeric materials through coupled transport-mechanical interactions. This study presents a comparative experimental and data-driven investigation of the pressure-dependent degradation behavior of ethylene propylene diene monomer (EPDM), nitrile butadiene rubber (NBR), and fluorocarbon elastomer (FKM) O-ring seals following 192 h exposure to hydrogen pressures ranging from 800 to 7000 psi at room temperature. Tensile testing was performed directly on complete O-ring geometries, and descriptor-based analysis was used to quantify peak-response behavior, energy absorption, stiffness evolution, and normalized deformation characteristics. Multivariate statistical methods, principal component analysis (PCA), clustering analysis, and Random Forest regression were applied to identify material-specific degradation patterns. NBR maintained the highest overall load-bearing capability and stiffness-related response across the investigated pressure range, whereas EPDM exhibited more compliant and non-monotonic deformation behavior. FKM showed the strongest pressure sensitivity, with substantial increases in force- and stiffness-related descriptors at elevated hydrogen pressures. Optical image analysis revealed pronounced increases in defect density and defect area fraction for NBR, while FKM exhibited comparatively stable surface-state behavior. PCA and clustering analyses identified distinct material-dependent degradation trajectories, and Random Forest regression achieved an R

Indexed as

elastomer sealshydrogen agingmachine learningmechanical degradationprincipal component analysissurface defects

Identifiers

PMID42452028
PMCPMC13364005

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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.