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March 1, 2026SHILAP Revista de lepidopterologíaOpen Access

Modeling the effect of carbon black type and dosage on the mixing dynamics of rubber blends using a general regression neural network

Ivan Kopal Juliána Vršková Ivan Labaj Marta Harničárová Ján Valíček

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Key Points

This study aims to evaluate how different types and amounts of carbon black affect the mixing dynamics of rubber blends.
Utilized a general regression neural network for modeling
Analyzed various types of carbon black and their dosages
Examined the mixing dynamics of rubber blends
Found significant effects of carbon black type on mixing efficiency
Demonstrated that dosage variations alter mixing characteristics
Provided models that can predict optimal mixing conditions

Implication

This modeling study finds how carbon black type and dosage impact mixing dynamics in rubber blends, suggesting improvements in material processing.

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Cite This Study

Kopal et al. (2026) studied this question.

synapsesocial.com/papers/69ada804bc08abd80d5bb34d https://doi.org/10.17512/jamcm.2026.1.08

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Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Artificial neural network modeling for predicting the carbon black content derived from unserviceable tires for elastomeric composite production2024
2Effect of dispersion on the dynamic properties of filler‐loaded rubbersOriginal Research · 1965 · 159 citations
3Influence of Carbon Black on the Morphology and Mechanical Properties of Phase‐Separated Synthetic Rubber Blends2025
4Learning based model for predicting mechanical properties and sustainable filler band for NBR composites using lignin and carbon black2024
5Effects of Carbon Black Surface Modification on the Morphology and Properties in Blends with Natural Rubber Studied with High‐Resolution X‐Ray Computed Tomography2024 · 10 citations

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