Multi-parameter viscoelastic material model for denture adhesives based on time-temperature superposition and multiple linear regression analysis.

Adhesive swelling Denture adhesives Material modelling Multi-parameter linear regression analysis Rheology Temperature Time-temperature superposition Viscoelastic behavior pH

Journal

BMC biomedical engineering
ISSN: 2524-4426
Titre abrégé: BMC Biomed Eng
Pays: England
ID NLM: 101756092

Informations de publication

Date de publication:
02 Sep 2024
Historique:
received: 02 05 2024
accepted: 24 06 2024
medline: 2 9 2024
pubmed: 2 9 2024
entrez: 1 9 2024
Statut: epublish

Résumé

Restorative solutions designed for edentulous patients such as dentures and their accompanying denture adhesives operate in the complex and dynamic environment represented by human oral physiology. Developing material models accounting for the viscoelastic behavior of denture adhesives can facilitate their further optimization within that unique physiological environment. This study aims to statistically quantify the degree of significance of three physiological variables - namely: temperature, adhesive swelling, and pH - on denture adhesive mechanical behavior. Further, based on these statistical significance estimations, a previously-developed viscoelastic material modelling approach for such denture adhesives is further expanded and developed to capture these variables' effects on mechanical behavior. In this study a comparable version of Denture adhesive Corega Comfort was analysed rheologically using the steady state frequency sweep tests. The experimentally derived rheological storage and loss modulus values for the selected physiological variables were statistically analyzed using multi parameter linear regression analysis and the Pearson's coefficient technique to understand the significance of each individual parameter on the relaxation spectrum of the denture adhesive. Subsequently, the parameters are incorporated into a viscoelastic material model based on Prony series discretization and time-temperature superposition, and the mathematical relationship for the loss modulus is deduced. The results of this study clearly indicated that the variation in both the storage and loss modulus values can be accurately predicted using the oral cavity physiological parameters of temperature, swelling ratio, and pH with an adjusted R This multi-parameter viscoelastic material model is intended to facilitate future detailed numerical investigations performed with implementation of denture adhesives using the finite element method.

Sections du résumé

BACKGROUND BACKGROUND
Restorative solutions designed for edentulous patients such as dentures and their accompanying denture adhesives operate in the complex and dynamic environment represented by human oral physiology. Developing material models accounting for the viscoelastic behavior of denture adhesives can facilitate their further optimization within that unique physiological environment. This study aims to statistically quantify the degree of significance of three physiological variables - namely: temperature, adhesive swelling, and pH - on denture adhesive mechanical behavior. Further, based on these statistical significance estimations, a previously-developed viscoelastic material modelling approach for such denture adhesives is further expanded and developed to capture these variables' effects on mechanical behavior.
METHODS METHODS
In this study a comparable version of Denture adhesive Corega Comfort was analysed rheologically using the steady state frequency sweep tests. The experimentally derived rheological storage and loss modulus values for the selected physiological variables were statistically analyzed using multi parameter linear regression analysis and the Pearson's coefficient technique to understand the significance of each individual parameter on the relaxation spectrum of the denture adhesive. Subsequently, the parameters are incorporated into a viscoelastic material model based on Prony series discretization and time-temperature superposition, and the mathematical relationship for the loss modulus is deduced.
RESULTS RESULTS
The results of this study clearly indicated that the variation in both the storage and loss modulus values can be accurately predicted using the oral cavity physiological parameters of temperature, swelling ratio, and pH with an adjusted R
CONCLUSIONS CONCLUSIONS
This multi-parameter viscoelastic material model is intended to facilitate future detailed numerical investigations performed with implementation of denture adhesives using the finite element method.

Identifiants

DOI: 10.1186/s42490-024-00083-z PMID: 39218936
pubmed: 39218936
doi: 10.1186/s42490-024-00083-z
pii: 10.1186/s42490-024-00083-z
doi:

Types de publication

Journal Article

Langues

eng

Pagination

8

Informations de copyright

© 2024. The Author(s).

Références

Papadiochou S, Emmanouil I, Papadiochos I. Denture adhesives: a systematic review. J Prosthet Dent. 2015;113:391–7.
doi: 10.1016/j.prosdent.2014.11.001
Neill DJ, Roberts BJ. The effect of denture fixatives on masticatory performance in complete denture patients. J Dent. 1973;1:219–22.
doi: 10.1016/0300-5712(73)90064-X
Chew CL, Boone ME, Swartz ML, Phillips RW. Denture adhesives: their effects on denture retention and stability. J Dent. 1985;13:152–9.
doi: 10.1016/0300-5712(85)90089-2
Munoz CA, Gendreau L, Shanga G, Magnuszewski T, Fernandez P, Durocher J. A clinical study to evaluate denture adhesive use in well-fitting dentures. J Prosthodont. 2012;21:123–9.
doi: 10.1111/j.1532-849X.2011.00795.x
Grasso JE, Rendell J, Gay T. Effect of denture adhesive on the retention and stability of maxillary dentures. J Prosthet Dent. 1994;72:399–405.
doi: 10.1016/0022-3913(94)90560-6
Marin DO, Leite AR, Paleari AG, Rodriguez LS, Oliveira Junior NM, Pero AC, et al. Effect of a denture adhesive on the satisfaction and kinesiographic parameters of complete denture wearers: a cross-over randomized clinical trial. Braz Dent J. 2014;25:391–8.
doi: 10.1590/0103-6440201302409
Özcan M, Kulak Y, De Baat C, Arikan A, Ucankale M. The effect of a new denture adhesive on bite force until denture dislodgement. J Prosthodont. 2005;14:122–6.
doi: 10.1111/j.1532-849X.2005.00020.x
Abdelnabi MH, Swelem AA, Al-Dharrab AA. Influence of denture adhesives on occlusion and disocclusion times. J Prosthet Dent. 2016;115:306–12.
doi: 10.1016/j.prosdent.2015.07.014
Ramakrishnan AN, Röhrle O, Ludtka C, Varghese R, Koehler J, Kiesow A, et al. Finite element evaluation of the Effect of Adhesive creams on the stress state of dentures and oral mucosa. Appl Bionics Biomech. 2021;2021:1–9.
doi: 10.1155/2021/5533770
Quiney D, Ayre WN, Milward P. The effectiveness of adhesives on the retention of mandibular free end saddle partial dentures: an in vitro study. J Dent. 2017;62:64–71.
doi: 10.1016/j.jdent.2017.05.008
Fallahi A, Khadivi N, Roohpour N, Middleton AM, Kazemzadeh-Narbat M, Annabi N, et al. Characterization, mechanistic analysis and improving the properties of denture adhesives. Dent Mater. 2018;34:120–31.
doi: 10.1016/j.dental.2017.09.015
Gill SK, Roohpour N, An Y, Gautrot JE, Topham PD, Tighe BJ. Hydrophobic and hydrophilic effects on water structuring and adhesion in denture adhesives. J Biomed Mater Res A. 2018;106:1355–62.
doi: 10.1002/jbm.a.36341
Nishi Y, Nomura T, Murakami M, Kawai Y, Nishimura M, Kondo H, et al. Effect of denture adhesives on oral moisture: a multicenter randomized controlled trial. J Prosthodont Res. 2020;64:281–8.
doi: 10.1016/j.jpor.2019.08.004
Kore DR, Kattadiyil MT, Hall DB, Bahjri K. In vitro comparison of the tensile bond strength of denture adhesives on denture bases. J Prosthet Dent. 2013;110:488–93.
doi: 10.1016/j.prosdent.2013.09.014
Love WB, Biswas S. Denture adhesives—pH and buffering capacity. J Prosthet Dent. 1991;66:356–60.
doi: 10.1016/0022-3913(91)90263-V
Darwish M, Nassani MZ. Evaluation of the effect of denture adhesives on surface roughness of two chemically different denture base resins. Eur J Dent. 2016;10:321–6.
doi: 10.4103/1305-7456.184155
Rencher AC, Christensen WF. Methods of Multivariate Analysis. Wiley Series in Probability and Statistics; 2012.
Montgomery DC, Peck EA, Vining GG. Introduction to Linear Regression Analysis. Wiley; 2021.
Sedgwick P. Pearson’s correlation coefficient. BMJ. 2012;345.
Cohen I, Huang Y, Chen J, Benesty J, Benesty J, Chen J, Huang Y, Cohen I. Noise reduction in Speech Processing. Berlin: Springer; 2009. pp. 1–4.
doi: 10.1007/978-3-642-00296-0
Kotu V, Deshpande B. Data Science: concepts and practice. Morgan Kaufmann; 2018.
de Souza Mendes PR, Thompson RL. Time-dependent yield stress materials. Curr Opin Colloid Interface Sci. 2019;43:15–25.
doi: 10.1016/j.cocis.2019.01.018
Shishesaz M, Reza A. The effect of viscoelasticity of polymeric adhesives on shear stress distribution in a single-lap joint. J Adhes. 2013;89:859–80.
doi: 10.1080/00218464.2012.750581
Kano H, Kurogi T, Shimizu T, Nishimura M, Murata H. Viscosity and adhesion strength of cream-type denture adhesives and mouth moisturizers. Dent Mater J. 2012;31:960–8.
doi: 10.4012/dmj.2012-004
Bergstrom JS. Mechanics of solid polymers: theory and computational modeling. Elsevier; 2015.
Ramakrishnan AN, Röhrle O, Ludtka C, Koehler J, Kiesow A, Schwan S. Mapping the role of oral cavity physiological factors into the viscoelastic model of denture adhesives for numerical implementation. J Appl Biomater Funct Mater. 2023;21. https://doi.org/10.1177/22808000231201460 .
Gill SK, Roohpour N, Topham PD, Tighe BJ. Tunable denture adhesives using biomimetic principles for enhanced tissue adhesion in moist environments. Acta Biomater. 2017;63:326–35.
doi: 10.1016/j.actbio.2017.09.004
Owens RG, Phillips TN. Computational rheology. London: World Scientific Publishing Company; 2002.
doi: 10.1142/p160
Pisal PB, Patil SS, Pokharkar VB. Rheological investigation and its correlation with permeability coefficient of drug loaded carbopol gel: influence of absorption enhancers. Drug Dev Ind Pharm. 2013;39:593–9.
doi: 10.3109/03639045.2012.692377
Nakagawa S, Johnson PC, Schielzeth H. The coefficient of determination R
Ramakrishnan AN, Roehrle O, Ludtka C, Varghese R, Koehler J, Kiesow A, et al. Finite element evaluation of the effect of adhesive creams on the stress state of dentures and abutment teeth. J Mech Med Biol. 2022;22. https://doi.org/10.1142/S0219519422500270 .
Narayanaswamy O. A model of structural relaxation in glass. J Am Ceram Soc. 1971;54:491–8.
doi: 10.1111/j.1151-2916.1971.tb12186.x

Auteurs

Anantha Narayanan Ramakrishnan (AN)

Department of Engineering and Natural Sciences, University of Applied Sciences, Hochschule Merseburg, Merseburg, Germany.
Institute for Modelling and Simulation of Biomechanical Systems, Faculty of Civil and Environmental Engineering, University of Stuttgart, Stuttgart, Germany.

Josephine Reymann (J)

Department of Biological and Macromolecular Materials, Fraunhofer Institute for Microstructure of Materials and Systems IMWS, Halle (Saale), Germany.
Department of Operative Dentistry and Periodontology, Martin-Luther-University Halle-Wittenberg, Halle, Germany.

Christopher Ludtka (C)

J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, USA.

Andreas Kiesow (A)

Department of Biological and Macromolecular Materials, Fraunhofer Institute for Microstructure of Materials and Systems IMWS, Halle (Saale), Germany.

Stefan Schwan (S)

Department of Engineering and Natural Sciences, University of Applied Sciences, Hochschule Merseburg, Merseburg, Germany. stefan.schwan@imws.fraunhofer.de.
Department of Biological and Macromolecular Materials, Fraunhofer Institute for Microstructure of Materials and Systems IMWS, Halle (Saale), Germany. stefan.schwan@imws.fraunhofer.de.

Classifications MeSH