文献类型：期刊文献

英文题名：Response surface methodology approach for dyeing process optimization of Ayous (Triplochiton scleroxylon) wood with acid dye

作者：Wu, Shiqian[1,2] Peng, Limin[1,2] Fu, Feng[1,2] Feng, Yun[1] He, Jinrong[1] Wang, Huishan[1]

第一作者：Wu, Shiqian

机构：[1] Research Institute of Wood Industry, Chinese Academy of Forestry, Beijing, 100091, China; [2] Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing, 210037, China

年份：2023

卷号：81

期号：4

起止页码：1045-1058

外文期刊名：European Journal of Wood and Wood Products

收录：EI(收录号：20231013662160);Scopus(收录号：2-s2.0-85149110110)

语种：英文

外文关键词：Dyeing - Optimization - Process control - Surface properties - Temperature

摘要：Dyeing of wood is an important value-adding process. An important indicator in the assessment of the performance of wood dyeing process is the dye penetration. In the present study, the existing method of response surface methodology was extended to study the dyeing process optimization of Ayous (Triplochiton scleroxylon) wood with acid dye using the radial dye penetration percentage as an indicator. The experiments were carried out on the basis of a single factor experiment, and the optimal condition was determined by means of the Box–Behnken Design of response surface methodology. The effects of temperature, dye concentration, dyeing time and accelerant mass fraction on the radial dye penetration percentage of Ayous wood were optimized. The experimental results showed that the maximum radial dye permeability can be achieved under optimum dyeing temperature (86.03?°C), dye concentration (0.31%), dyeing time (8?h), and accelerant mass fraction (2.23%). Under these conditions, the maximum dye-uptake and radial dye penetration percentage were found to be 14.28% and 22.34%, respectively. The results of analysis of variance indicated that the mathematical model proposed in this study can be used to predict the dye-uptake and radial dye penetration percentage of acid dye on Ayous wood by changing the process parameters. ? 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.