The study objective was to impart urea-formaldehyde (UF) bonded particleboards higher and longer-lasting hydrophobicity than that resulting from conventionally used paraffin. Alkyl ketene dimer (AKD) is a paper sizing agent that can theoretically esterify wood compounds and result in a surface modification. Particles were 1) impregnated with an aqueous AKD-solution and cured at 130• C prior to gluing, or 2) sprayed with a mixture of AKD-solution and UF-resin in a single step. Boards with and without paraffin wax were used as controls. Thickness swelling after 2, 24, and 48 h immersion was decreased by 90, 62, and 59% when the chips were impregnated with AKD in comparison to untreated control boards. Water uptake after 2, 24, and 48 h was reduced by 91, 75, and 60%. AKD-impregnation with subsequent curing decreased the internal bond strength by 53%, indicating that AKD impedes the adhesion. The mixture of AKD and UF-glue did not result in considerable hydrophobicity. Increased methyl/methylene and carbonyl bands in FTIR-spectra after toluene-extraction suggest that AKD partially formed ester bonds at the wood surface. Die Verwendung von

Service life planning with timber requires reliable models for quantifying the effects of exposure-related parameters and the material-inherent resistance of wood against biotic agents. The Meyer-Veltrup model was the first attempt to account for inherent protective properties and the wetting ability of wood to quantify resistance of wood in a quantitative manner. Based on test data on brown, white, and soft rot as well as moisture dynamics, the decay rates of different untreated wood species were predicted relative to the reference species of Norway spruce (Picea abies). The present study aimed to validate and optimize the resistance model for a wider range of wood species including very durable species, thermally and chemically modified wood, and preservative treated wood. The general model structure was shown to also be suitable for highly durable materials, but previously defined maximum thresholds had to be adjusted (i.e., maximum values of factors accounting for wetting ability and inherent protective properties) to 18 instead of 5 compared to Norway spruce. As expected, both the enlarged span in durability and the use of numerous and partly very divergent data sources (i.e., test methods, test locations, and types of data presentation) led to a decrease in the predictive power of the model compared to the original. In addition to the need to enlarge the database quantity and improve its quality, in particular for treated wood, it might be advantageous to use separate models for untreated and treated wood as long as the effect of additional impact variables (e.g., treatment quality) can be accounted for. Nevertheless, the adapted Meyer-Veltrup model will serve as an instrument to quantify material resistance for a wide range of wood-based materials as an input for comprehensive service life prediction software.

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Leaving wooden façades uncoated has become popular in modern architecture, especially for large buildings like multi-story houses, in order to circumvent frequent maintenance, particularly repainting. To obtain a quick and even artificial graying of the entire façade that gradually turns into natural graying, a one-off treatment with iron (II) sulfate may be applied. Its mode of action is commonly ascribed to a reaction with phenolic wood extractives, especially hydrolyzable tannins. This does not however sufficiently explain iron (II) sulfate’s ability to color wood species containing only marginal amounts of phenolic extractives; moreover, little is known about the influence of the wooden substrate and light conditions on the color development of façades treated with iron (II) sulfate. In the present study, we investigated the influence of wood extractives, exposure conditions, and nine different wooden substrates on iron (II) sulfate’s staining effect. Spruce specimens with and without extractives were treated with a 4% iron (II) sulfate solution and exposed to sunlight behind window glass. Both wood types darkened slowly but significantly during 51 weeks of exposure. This shows that artificial graying with iron (II) sulfate (1) does not require precipitation unlike natural graying, (2) takes place without initial wood extractives, and (3) proceeds at a slow rate. Specimens protected from sunlight changed their color only slightly, suggesting that photo-induced phenoxyl and ketyl radicals from photolysis of lignin’s ether bonds oxidize iron (II) to iron (III). Specimens made of spruce, pine, larch, and western red cedar (WRC) and exposed outdoors decreased strongly in lightness during the first two months of exposure. In contrast, a staining effect of iron (II) sulfate in terms of artificial graying was not seen on acetylated radiata pine, possibly because iron ions are hindered from entering the cell wall. Specimens partly protected by a roof overhang showed an uneven color development; this is due to the protection from radiation and not from precipitation as is known for natural graying.

Durability-based designs with timber require reliable information about the wood properties and how they affect its performance under variable exposure conditions. This study aimed at utilizing a material resistance model (Part 2 of this publication) based on a dose–response approach for predicting the relative decay rates in above-ground situations. Laboratory and field test data were, for the first time, surveyed globally and used to determine material-specific resistance dose values, which were correlated to decay rates. In addition, laboratory indicators were used to adapt the material resistance model to in-ground exposure. The relationship between decay rates in- and above-ground, the predictive power of laboratory indicators to predict such decay rates, and a method for implementing both in a service life prediction tool, were established based on 195 hardwoods, 29 softwoods, 19 modified timbers, and 41 preservative-treated timbers.

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Wood chips were treated with alkyl ketene dimer (AKD) using three different processes to impart water resistance to particleboards. In the first process, AKD was blended with UF resin. Thickness swelling and water uptake after a 24 h immersion period (20 and 69%) were lower than in the control boards (28 and 81%) but were higher than in the paraffin references (10 and 22%). In process 2, AKD and UF resin were sprayed separately on the chips resulting in a greater reduction of thickness swelling (15%) and water uptake (49%) than in process 1. Paraffin references revealed a thickness swelling and water uptake of 7 and 25%, respectively. An extension of the pressing time in processes 1 and 2 did not increase water repellence. In process 3, particleboards were made from AKD-treated chips that were cured at 130• C (24 h) prior to gluing. They showed a thickness swelling of 7% and a water uptake of 25%, whereas particleboards with paraffin exhibited levels of 8 and 29%. The thickness swelling and water uptake of boards with AKD increased when the curing time was reduced from 24 to 12 to 6 h (130 • C). Changing the curing temperature from 130 to 100• C (12 h) had no effect on board properties. The IB of boards made from pre-cured chips with AKD (24 h/130• C) was 44% lower than in controls and 35% lower than in paraffin references. This indicates that AKD impedes the adhesion.

A feasibility study was carried out to assess the possibility of developing prediction models for monitoring drying conditions of wood coatings in one of Europe's largest and most modern coating plants for exterior cladding. These models were based on data from real-time Process Analytical Technology (PAT) sensors, measuring airflow and air direction, temperature and relative humidity). The study revealed that the information from the PAT sensors gave sufficient input to accurately model the complex drying conditions and their interrelations. Modelling was carried out using both Principal Component Analysis (PCA) and PLS-regression in both its PLS1 and PLS2 manifestations. In addition, the diagnostic prediction performance RMSEP between PLS1 and PLS2 models were not significantly different. This is advantageous for an industrial implementation concerning recalibration operations: PLS1 requires 40 separate calibrations whereas PLS2 requires only one, because PLS1-R is a regression of a singular output variable (yvariable) and PLS2-R of several simultaneous, correlated output variables. While a single calibration based on PLS2 will take approximately one hour, the PLS1 approach will take more than a week.