Journal of Materials Science

, Volume 52, Issue 5, pp 2720–2729 | Cite as

Antifungal effects of copper and silver nanoparticles against white and brown-rot fungi

  • Petr PařilEmail author
  • Jan Baar
  • Petr Čermák
  • Peter Rademacher
  • Robert Prucek
  • Martin Sivera
  • Aleš Panáček
Original Paper


In this study, the antifungal effects of copper and silver nanoparticles against two wood-rotting fungi were investigated. European beech (Fagus sylvatica L.) and Scots pine (Pinus sylvestris L.) sapwood specimens of dimensions 50 × 25 × 15 mm3 were vacuum impregnated using dispersions of copper and silver nanoparticles within two concentrations, i.e. 1 and 3 g/l. Beech wood specimens were tested against white-rot fungus (Trametes versicolor) and pine wood against brown-rot fungus (Poria placenta) according to EN113. Furthermore, leachability, retention and protection efficiency (mass loss due to decay) were analysed afterwards. The highest value of retention was observed for pine sapwood (~2 kg/m3) for both nanoparticle solutions. The amount of nanoparticles in the wood did not increase proportionally with an increasing concentration, but only 1.5–2 times increase was reached. An average leaching of 15–35% was observed for copper nanoparticles, depending on used wood species and concentration. Significantly, lower leaching (max. 15%) was observed for pine sapwood impregnated by silver nanoparticles with a concentration of 3 g/l. The highest antifungal effect [under 5% of mass loss (ML)] against both tested fungi was found for nano-copper treatment at the concentration of 3 g/l. However, this effect of treatment seems to be almost negligible after the leaching test. Therefore, this study aims to present fundamental material properties of wood treated with copper and silver nanoparticles, and provide groundwork for further research (e.g. fixation of substances in the wood structure, etc.).


Silver Nanoparticles Copper Nanoparticles European Beech Medium Density Fibreboard Sodium Borohydride Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was carried out at Research Center Josef Ressel in Brno-Útěchov. It was financially supported by the Internal Grant Agency (IGA) of the Faculty of Forestry and Wood Technology, Mendel University in Brno, (LDF_PSV_2016015).


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Petr Pařil
    • 1
    Email author
  • Jan Baar
    • 1
  • Petr Čermák
    • 1
  • Peter Rademacher
    • 1
  • Robert Prucek
    • 2
  • Martin Sivera
    • 2
  • Aleš Panáček
    • 2
  1. 1.Department of Wood ScienceMendel University in BrnoBrnoCzech Republic
  2. 2.Department of Physical Chemistry, Faculty of Science, Regional Centre of Advanced Technologies and MaterialsPalacký UniversityOlomoucCzech Republic

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