The effects of ACQ and water glass on the color change and decay resistance of carbonized bamboo

In this study, samples of bamboo and carbonized bamboo were impregnated with alkaline copper quaternary (ACQ) and water glass, the resulting differences in color and resistance to decay by Gloeophyllum trabeum were evaluated. The results showed that the impregnated bamboo and carbonized bamboo greatly reduced their lightness (L*). The red-green color index (a*) first decreased and then increased, while the yellow-blue color index (b*) first increased and then decreased. The total chromatic aberration (ΔE) was largest for bamboo and carbonized bamboo impregnated with ACQ and allowed to decay. Carbonized bamboo impregnated with ACQ and water glass and bamboo impregnated with ACQ reached level I (strong decay resistance). The decay resistance of bamboo and carbonized bamboo was as follows: ACQ impregnated > water glass impregnated > CK. Scanning electron microscopy further confirmed that the bamboo and carbonized bamboo were impregnated with ACQ had fewer hyphae, the maintained intact structure, and good decay resistance.

Box-Behnken design for process parameters optimalization of bamboo-based composite panel manufacturing

High performance bamboo-based composite panel taking bamboo mats, bamboo curtains and poplar veneers are used as raw material, is manufactured from the each layers slab was crisscrossed, impregnated with phenolic resin, compressed and cured. The product was optimized by Box-Behnken model design and data analysis. The results show that the best parameter conditions were hot pressing temperature of 140°C, hot pressing time of 94 s.mm-1, and hot pressing pressure of 2.5 MPa. The model was validated according to the optimal process parameters and the static bending strength (MOR), elastic modulus (MOE), thickness expansion rate of water absorbing, adhesive strength and density are 98.95 MPa, 8.81 GPa, 4.7%, 1.25 MPa, 0.89 g.cm-3, respectively. The actual value is close to the predicted value, confirming that the obtained model can accurately predict the MOR of the product using the three factors of hot pressing as variables under different conditions.