Investigation for the influence of Sm2O3 and CeO2 nanoparticles on the microstructure and electrochemical behavior of epoxy and prediction of mechanical characterizations of adhesive joining of CFPEEK via machine learning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F25%3A10260200" target="_blank" >RIV/61989100:27230/25:10260200 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.webofscience.com/wos/woscc/full-record/WOS:001568964100001" target="_blank" >https://www.webofscience.com/wos/woscc/full-record/WOS:001568964100001</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jmrt.2025.08.253" target="_blank" >10.1016/j.jmrt.2025.08.253</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Investigation for the influence of Sm2O3 and CeO2 nanoparticles on the microstructure and electrochemical behavior of epoxy and prediction of mechanical characterizations of adhesive joining of CFPEEK via machine learning

Popis výsledku v původním jazyce

With the increase demand for lightweight material combined with high mechanical and electrochemical properties, in this study we proposed a novel polymer nanocomposites (PNCs). Due to the unique characterizations of rare earth metal oxides nanoparticles, cerium oxide (CeO&lt;inf&gt;2&lt;/inf&gt;)/samarium oxide (Sm&lt;inf&gt;2&lt;/inf&gt;O&lt;inf&gt;3&lt;/inf&gt;) were integrated to enhance microstructural, mechanical, electrochemical and the joint efficiency performance of epoxy resin matrix. The influences of various dispersion content of CeO&lt;inf&gt;2&lt;/inf&gt;/Sm&lt;inf&gt;2&lt;/inf&gt;O&lt;inf&gt;3&lt;/inf&gt; were explored. The adhesive joint efficiency and maximum shear force were determined by performing single lap joint through applying a thin layer of the synthesized PNCs to join carbon fiber polyetheretherketone (CFPEEK). Superior ultimate tensile strength was obtained by doping 7 wt% CeO&lt;inf&gt;2&lt;/inf&gt;/Sm&lt;inf&gt;2&lt;/inf&gt;O&lt;inf&gt;3&lt;/inf&gt; as the enhancement reached 483.482 % and 490.380 % respectively. The maximum joint efficiency reached 68.43 % and was achieved by doping 3 wt% of CeO&lt;inf&gt;2&lt;/inf&gt;. An optimum enhancement in electrical conductivity was achieved by 1 wt% and 5 wt% of CeO&lt;inf&gt;2&lt;/inf&gt;, while optimum enhancement in insulation or coating properties obtained by 5 wt% of Sm&lt;inf&gt;2&lt;/inf&gt;O&lt;inf&gt;3&lt;/inf&gt;. In addition, machine learning algorithms, including artificial neural networks, random forest, extreme gradient boosting (XGBoost), and k-nearest neighbors were applied to predict the investigated material properties. XGBoost provided robust predictions across both mechanical and electrochemical properties. © 2025 The Authors.

Název v anglickém jazyce

Investigation for the influence of Sm2O3 and CeO2 nanoparticles on the microstructure and electrochemical behavior of epoxy and prediction of mechanical characterizations of adhesive joining of CFPEEK via machine learning

Popis výsledku anglicky

With the increase demand for lightweight material combined with high mechanical and electrochemical properties, in this study we proposed a novel polymer nanocomposites (PNCs). Due to the unique characterizations of rare earth metal oxides nanoparticles, cerium oxide (CeO&lt;inf&gt;2&lt;/inf&gt;)/samarium oxide (Sm&lt;inf&gt;2&lt;/inf&gt;O&lt;inf&gt;3&lt;/inf&gt;) were integrated to enhance microstructural, mechanical, electrochemical and the joint efficiency performance of epoxy resin matrix. The influences of various dispersion content of CeO&lt;inf&gt;2&lt;/inf&gt;/Sm&lt;inf&gt;2&lt;/inf&gt;O&lt;inf&gt;3&lt;/inf&gt; were explored. The adhesive joint efficiency and maximum shear force were determined by performing single lap joint through applying a thin layer of the synthesized PNCs to join carbon fiber polyetheretherketone (CFPEEK). Superior ultimate tensile strength was obtained by doping 7 wt% CeO&lt;inf&gt;2&lt;/inf&gt;/Sm&lt;inf&gt;2&lt;/inf&gt;O&lt;inf&gt;3&lt;/inf&gt; as the enhancement reached 483.482 % and 490.380 % respectively. The maximum joint efficiency reached 68.43 % and was achieved by doping 3 wt% of CeO&lt;inf&gt;2&lt;/inf&gt;. An optimum enhancement in electrical conductivity was achieved by 1 wt% and 5 wt% of CeO&lt;inf&gt;2&lt;/inf&gt;, while optimum enhancement in insulation or coating properties obtained by 5 wt% of Sm&lt;inf&gt;2&lt;/inf&gt;O&lt;inf&gt;3&lt;/inf&gt;. In addition, machine learning algorithms, including artificial neural networks, random forest, extreme gradient boosting (XGBoost), and k-nearest neighbors were applied to predict the investigated material properties. XGBoost provided robust predictions across both mechanical and electrochemical properties. © 2025 The Authors.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20301 - Mechanical engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Materials Research and Technology

ISSN

2238-7854

e-ISSN

—

Svazek periodika

38

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

22

Strana od-do

4917-4938

Kód UT WoS článku

001568964100001

EID výsledku v databázi Scopus

2-s2.0-105025686540