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    An investigation of surface properties of thermally modified wood during natural weathering for 48 months
    (Elsevier Sci Ltd, 2018) Dizman Tomak, Eylem; Ustaomer, Derya; Ermeydan, Mahmut Ali; Yildiz, Sibel
    Weathering period and exposure conditions can affect the degradation rate of wood surfaces. Longer weathering exposure periods are more reliable for end-use performance evaluations, and therefore it is desirable to investigate the role of long exposure periods on wood properties. This study aimed to investigate the effect of thermal modification on surface composition, roughness and color of ash, iroko, Scots pine and spruce wood species during natural weathering in East Black Sea Region of Turkey for 48 months. All measurements were performed at 6 month intervals. Regarding the results, surface roughness increased as the weathering period increased. Surface quality and color stability of the samples were enhanced with the thermal modification for all wood species, and those properties were much better for hardwoods than softwoods. FTIR data showed that changes in surface composition of thermally modified and unmodified wood were so high even at the first weathering exposure period. Thus, thermal modification may not be an effective protection method in long term outdoor conditions if the surface appearance and color stability is required.
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    Changes in surface and mechanical properties of heat treated wood during natural weathering
    (Elsevier Sci Ltd, 2014) Dizman Tomak, Eylem; Ustaomer, Derya; Yildiz, Sibel; Pesman, Emrah
    In this study, it was aimed to investigate the changes in moisture content, color, surface roughness, compression strength parallel to grain, modulus of rupture and modulus of elasticity of heat treated ash, iroko, Scots pine and spruce wood species during natural weathering for two years. Samples were removed at 6-month intervals for performance evaluation, and test results were compared with the controls. Moisture content of heat treated samples was found to be lower than that of control samples for all exposure periods. Heat treatment significantly changed original wood color as well as weathering factors. Wood surfaces become rougher within longer weathering exposure period. Natural weathering factors caused a decrease for all strength properties. Reduction rate for strength properties of heat treated samples was relatively lower than that of control samples. Heat treatment also seemed to improve color stability and surface quality of samples after weathering. (C) 2014 Elsevier Ltd. All rights reserved.
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    COMBINING ARTIFICIAL NEURAL NETWORK AND MOTH-FLAME OPTIMIZATION ALGORITHM FOR OPTIMIZATION OF ULTRASOUND-ASSISTED AND MICROWAVE-ASSISTED EXTRACTION PARAMETERS: BARK OF Pinus brutia
    (Univ Bio-Bio, 2022) Gurgen, Aysenur; Atilgan, Basak; Yildiz, Sibel; Gonultas, Oktay; Imamoglu, Sami
    In this study, the extraction parameters of Pinus brutia bark were optimized using a hybrid artificial intelligence technique. Firstly, the bark samples were extracted by ultrasound-assisted extraction and microwave-assisted extraction which are defined as 'green' extraction methods at different conditions. The selected extraction parameters for ultrasound-assisted extraction were 0:100; 20:80; 40:60; 80:20 (%) ethanol: water ratios; 40 degrees C, 60 degrees C extraction temperatures and 5 min, 10 min, 15 min, 20 min extraction times and for microwave-assisted extraction were 90, 180, 360, 600, 900 (W) microwave power, 0:100; 20:80; 40:60; 60:40; 80:20 (%) ethanol: water ratios. Then Stiasny number, condensed tannin content and reducing sugar content of all extracts were determined. Next, the prediction models were developed for each studied parameter using Artificial Neural Network. Finally, the extraction parameters were optimized using Moth-Flame Optimization Algorithm. After that optimization process, while the extraction time was the same (5 min), the ethanol: water ratio and extraction temperature values differed for the optimization of all studied assays of ultrasound-assisted extraction. Also, microwave power and ethanol: water ratio variables were found in different values for each assay of microwave-assisted extraction. The results showed that the Artificial Neural Network and Moth-Flame Optimization could be a novel and powerful hybrid approach to optimize the extraction parameters of Pinus brutia barks with saving time, cost, chemical and effort.