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The article was published on 2013-01-01 and is currently open access. It has received 3 citations till now.

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Progress in Adhesion and Adhesives

K. L. Mittal
TL;DR: In this paper, a general method to completely tackle the adhesion problem with movable boundary conditions, from the viewpoint of energy variation, was introduced, and based on this theoretical framework, the developed line of reasoning was used to investigate adhesion behaviors of several condensed systems.
Journal ArticleDOI

Films based on crosslinked TEMPO-oxidized cellulose and predictive analysis via machine learning.

TL;DR: Optimization was carried out as a function of film composition following the “random forest” machine learning algorithm for regression analysis, and the design of tailor-made TOCNF-based films can be achieved with reduced experimental expenditure.
Journal ArticleDOI

Nondestructive and noncontact evaluation of cellulose nanofiber-reinforced composites using terahertz time-domain spectroscopy

TL;DR: In this paper , the authors used terahertz time-domain spectroscopy to estimate the mechanical properties of the CNF nanocomposites and confirmed that there was a good linearity between the concentration of CNF filler in the matrix after injection or extrusion molding.
References
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BookDOI

Progress in Adhesion and Adhesives

K. L. Mittal
TL;DR: In this paper, a general method to completely tackle the adhesion problem with movable boundary conditions, from the viewpoint of energy variation, was introduced, and based on this theoretical framework, the developed line of reasoning was used to investigate adhesion behaviors of several condensed systems.
Journal ArticleDOI

Films based on crosslinked TEMPO-oxidized cellulose and predictive analysis via machine learning.

TL;DR: Optimization was carried out as a function of film composition following the “random forest” machine learning algorithm for regression analysis, and the design of tailor-made TOCNF-based films can be achieved with reduced experimental expenditure.