Characteristics of impregnated wood by nano silica from betung bamboo leaves

Abstract, Sengon (Falcataria moluccana Miq.) as a fast-growing wood species that has low quality. Therefore, wood modification is needed to improve its wood qualities. The objective of this study was to analyse the effect of monoethylene glycol (MEG) and nano silica of betung bamboo leaves impregnation treatment on physical, mechanical properties and durability of sengon wood. 5-years-old Sengon wood from community forest, MEG and nano silica (average size = 436.16 nm) from betung bamboo leaves were used. The impregnation solutions were consisted of water treated (untreated), MEG, MEGSilika 0.5% and MEGSilika 1%. Impregnation process with 0.5 bar (60 minutes) vacuum and 2.5 bar (120 minutes) pressure. Physical properties (density and colour alteration), mechanical properties (Modulus of Elasticity (MOE), Modulus of Rupture (MOR) and hardness) and durability against subterranean (Coptotermes curvignathus) attack. The results showed that the weight percent gain (WPG) and density of treated Sengon wood were increased as the nano silica concentration increased. While colour alteration (Δε) of treated samples were declining. Mechanical properties (MOE, MOR and hardness) were also improved. Durability based on laboratory tested against subterranean attack resulted that the percentage of termite mortality from the treated samples increased, while the percentage of weight loss decreased.


Introduction
Based on a report from the Ministry of Environment and Forestry (KLHK), the supply of raw materials for the timber industry from natural forests is decreasing. In 2015, the supply was 8.3 million m 3 , while in 2018 it was 5.7 million m 3 , meanwhile the supply of raw materials from plantation forests and community forests has increased from 37.3 million m 3 in 2015 to 46.6 million m 3 in 2018. In particular, the supply of raw materials from community forests increased by 4.8 million m 3 in 2015 to 6.2 million m 3 in 2018 [1]. Thus, there is a gap between need and demand, thus making community plantation forests and community forests a solution for the supply of raw materials. Wood produced from community forests is generally a fast-growing species.
Sengon (Falcataria moluccana) is a fast-growing wood species that has several drawbacks, namely low specific gravity, strength, durability, density and dimensional stability. Sengon wood has a wood specific gravity of 0.24-0.49 with an average of 0.33, wood density 0.3−0.5 g/cm 3 , hardness 112-122

Preparation of Nano Silica Bamboo Betung Leaves
The betung bamboo leaves originated from the area around Bogor. Betung bamboo leaves were dried under the sun until reached air dry which were then burned without fuel to form charcoal. Then the bamboo leaves charcoal were burned at a temperature of 700 o C for 6 hours using a furnace. The ash obtained was then refluxed in 100 mL of 3 N NaOH for 3 hours. The solution was filtered with filter paper and the residue was washed using distilled water until the pH was neutral and oven-dried for 103±2 o C. The silica obtained was dissolved in PEG-6000 in a ratio of 1:5. The next stage is the manufacture of nanosilica by ultrasonication method for 2 hours. The results of the process were refurnicated for 3 hours at a temperature of 700 o C to obtain nano silica. The resulting nano silica was measured using PSA test analysis. The size of nano silica particles from bamboo leaves produced is 436.16 nm.

Preparation of impregnation solution
The process of mixing nano silica using a Cole Parmer brand sonicator, with an amplitude of 40% for 2 hours. The sonication method can be used to accelerate the dissolution of a material by breaking down the intermolecular using ultrasonication with a high frequency such as 20 kHz to 56 kHz.

Impregnation Process
The impregnation process with MEG and nano silica solution was carried out in several stages ( Figure  1). The stages of this process were adapted from [11] impregnated sengon wood using MEG and nano-SiO2.  Using the CIELab method, the L* value was used to express the brightness parameter with a scale of 0 (black) -100 (white). The a* value is used to represent the red to green color parameters. A value of +a (0 to +80) for red and a value of -a (0 to -80) for green. While the value of b* represents the parameters for the colors blue to yellow. Values +b (0 to +70) for yellow and -b (0 to -70) for blue [23]. The color change (ΔE) is calculated from the formula: = Difference in brightness (L test sample after treatment -L test sample before treatment) Δa = Difference in red or green (a test sample after treatment -a test sample before treatment) Δb = Difference in yellow or blue (b test sample after treatment -b test sample before impregnation treatment Delta E (ΔE) is a quantity to determine changes in color brightness that can be seen with the naked eye. The amount of color change in the wood can be determined using the guidelines in Table 3.  [24]. The test is carried out by inserting a steel ball with a diameter of 1 cm with a cross-sectional area of 1 cm 2 into the wood. The ball is pressed down to a depth of 0.5 cm. The value of wood hardness is measured by the formula.
= Weight of test sample before feeding (g) W2 = Weight of the test sample after being fed (g) The termite mortality can be calculated by the formula: = 150 × 100% Information: D = Number of dead termites (tails) 150 = Number of working caste termites at the start of feeding (tails)

Data Analysis
The experimental design used was a completely randomized design (CRD) with 1 factor, namely the variation factor of the concentration of the impregnation solution with 4 levels, namely untreated (water treated), MEG, MEGSilica 0.5% and MEGSilica 1%. The test was carried out using the IBM SPSS Statistics (Statistical Package for service solutions) version 22.0 calculation program and continued with Duncan's test at a 95% confidence interval.

Tissue Basah
Sample Test

Dental Cement
Acrilic tube

Plastic Net
The The equation model used by [29] is as follows: ij = μ + τi+∈ ij Information: i = 1, 2, …, t and j = 1, 2, …, r Yij = response or observation value from the treatment of the i-th concentration of the solution and the j-repetition µ = general average I = effect of the i-th treatment ∈ij = the effect of experimental error from the treatment of the i-th concentration of the solution and the j-th replication  The increase in WPG value is thought to be due to the addition of a mixture of MEG and nano silica which can replace free water and bound water in the cavity and cell walls of the wood so that impregnants in the form of MEG and nano silica can enter the wood. According to [30] that impregnation using a polymer causes penetration of the polymer into the cell wall and bonds can occur with the components that make up the wood cell wall. Based on [19] through SEM analysis, it was explained that the cause of the increase in WPG value in impregnated sengon wood was due to the addition of nano silica which could increase the distribution of MEGSilica solution.

Density.
Wood density is the ratio between weight and volume of wood. The test results on the resulting density value showed an increase in each treatment ( Figure 5). The density values in untreated, MEG, MEGSilica 0.5% and MEGSilica 1% were 0.28 g/cm 3 , 0.39 g/cm 3 , 0.41 g/cm 3 and 0.44 g/cm 3 , respectively. Based on the results obtained, the addition of the mixed concentration of MEG nano silica can increase the density value of each treatment. The results of the analysis of diversity showed that MEG and nano silica had a significant effect on the density value. Based on the results of Duncan's test, it showed that MEG treatment was not significantly different from 0.5% MEG silica treatment, but MEG and 0.5% MEG silica treatments were significantly different from 1% silica MEG treatment and significantly different from the untreated. The increase in the density value in each treatment was due to the penetration and expansion of the cell wall, the development occurred because the polymer had entered and was able to fill the space in the cell wall. The tendency to increase the density value along with the increase in the resulting WPG value. The WPG value increases, the resulting density value also increases ( Figure 6). This is in accordance with what was stated by [31], that the higher the wood density value, the more wood substances in the cell wall, which means the thicker the cell wall. The polymer content in wood is also influenced by the concentration of the impregnated material, polymerization method, the anatomical structure of the wood and the use of additives [10]. In addition, a vacuum system is used in the impregnation process. will remove excess air and water in the cell wall that can inhibit the entry of the impregnant solution.   Figure 7. There was a change in the values of L, a and b of sengon wood, after the impregnation treatment using MEG and nano silica solutions. After being given treatment, the value of the color change parameter (L, a, b) decreased, which means there was a change in the color of the wood. The color test results in Figure 7 show a decrease in the brightness value (L) after the impregnation treatment. Treatment with MEGSilica 0.5% and MEGSilica 1% on the graph showed an increase in the brightness value (L) of sengon wood. While the treatment using MEG decreased the value of wood brightness. This is presumably due to the addition of nano silica contained in the wood which can increase the brightness value of the wood. Yellowish value (a*) increased at MEGSilica 0.5% and decreased a value at MEGSilica 1%. The same thing also happened to the value (b*) where at MEGSilica 1%, the a and b values obtained did not show a change in color (Figure 8). According to [30], color changes can occur due to the addition of the degree of crystallinity, degree of polymerization and OH content.  Figure 9 shows the highest color change value occurred in the treatment with MEG concentration (14.2) followed by MEGSilica 0.5% (10.95) and untreated (7.53) treatment. The color change produced in the untreated treatment, MEG and MEGsilica 0.5% reached a value of 6. This indicates that the treatment caused a large color change. While the treatment with MEGSilica 1% concentration was classified as a moderate change, which was 5.28. The results of the analysis of variance showed that MEG and nano silica had a significant effect on the value of wood discoloration. Duncan's test results showed that the treatment with 1% MEG silica concentration was not significantly different from the untreated but significantly different from the MEG and 0.5% MEG silica treatment. MEG and MEGSilica 0.5% were not significantly different.  Figure 9. Value of color change of various MEG and nano silica impregnation treatments on sengon wood.
The impregnation process is expected to cause changes in the composition or chemical structure of the treated wood due to the formation of new compounds in the impregnated wood. The color change in the wood became darker in the MEG treatment due to the reaction between MEG and the components that make up the wood cell wall. The color change of wood after MEG and nano silica treatment resulted in a lighter color change when compared to MEG treatment. This is due to the presence of nano silica contained in the mixture of MEG and nano silica. This is in line with the research of [15] which stated that the color change in wood with furfuryl alcohol treatment showed a darker wood color change, but the color became lighter after the addition of SiO2 caused by conjugation or the formation of certain molecules in the nano-SiO2 network in PFA (Polymer Furfuryl Alcohol).

Mechanical Properties of Wood 3.2.1. MOE (Modulus of Elasticity). Modulus of Elasticity (MOE) is an indication of wood stiffness,
namely the ability of wood to withstand changes in shape. According to [31] modulus of elasticity is the stiffness property of a material or material to withstand changes in shape or bending that occur due to loading up to the proportion limit.   The MOE value in MEG impregnated wood and nano silica from bamboo betung leaves ( Figure 10) increased in untreated, MEG, MEGSilica 0.5% and MEGSilica 1%. The results of the analysis of variance showed that the MEG and nano silica treatments had a significant effect on the MOE value. Duncan's test results showed that the MOE value in MEGSilica 1% was significantly different from the untreated, MEG and MEGSilica 0.5%, while the MOE value in the MEG treatment was not significantly different from the MEGSilica 0.5% treatment but significantly different from the MOE value of the untreated.
The increase in the MOE value obtained is thought to be due to the addition of a mixture of MEG and nano silica solutions that enter the sengon wood. This indicates that the addition of nano silica with various concentrations can affect the morphology of sengon wood. This is supported by [30] who suggests that when the cell wall is filled with a polymer, the polymer will bond to the hydroxyl cellulose so that it occupies the space normally occupied by water molecules. It is suspected that impregnated silica nanoparticles crystallize in the wood, thereby increasing the strength of the wood.
Based on [19] on SEM analysis, it shows that MEGSilica impregnation treatment causes MEG and nano silica to enter the pits and some pits are covered by MEGSilica and even cover almost all vessel walls on sengon. Figure 11a shows the pits on the walls of the sengon wooden vessel partially covered by MEG. The pits that were originally empty after being treated with impregnation using MEG and nano silica became filled and almost covered by nano silica (Figure 11b). Furthermore, Figure 11c shows a better morphological change that MEG and nano silica can enter the pits, stick to and even partially cover the walls of the sengon wood vessel. The incoming nano silica fills the vessel providing a bulking effect on sengon wood. This causes the weight of sengon wood to increase so that the WPG value increases. The presence of nano silica covering the pits is also able to prevent the entry of water into the pits on the vessel wall. The trend of increasing the MOE value is accompanied by an increase in the WPG value and the resulting density value (Figure 12). The higher the WPG value produced, the resulting density value increases so that the MOE value obtained increases. The addition of MEG and nano silica caused more and more nano silica enter the wood and fill the lumen and cell wall of the wood with the help of MEG. This is supported by [13] which showed that impregnation treatment using MEG and nano-SiO2 was able to increase the MOE and MOR values in wood. This indicates that the addition of nano silica with various concentrations of 0.5% MEGSilica and 1% MEGSilica can affect the morphology of sengon wood so as to increase the WPG value and density which in turn can increase the MOE value.   Figure 12. Relationship of MOE value with WPG value (a) and density (b) on sengon wood impregnated with nano silica

MOR (Modulus of Rupture).
Modulus of Rupture (MOR) is the ability of a material to withstand loads up to the maximum limit. The stiffer the wood, the more difficult it is to change its shape, and vice versa. The MOR value is closely related to the MOE value of the wood and also the density. The higher the density of a wood, the higher the MOR value. Modification of wood with impregnation technology using a mixture of MEG and nano silica solutions causes an increase in the MOR value in the sengon wood test sample. The resulting MOR values are presented in Figure 13.  The results of the analysis of variance showed that MEG and nano silica had a significant effect on the MOR value. Based on the results of Duncan's test that the MOR values of sengon wood in the MEG treatment was not significantly different from the treatment among untreated, 0.5% MEGSilica, while the 1% MEGSilica treatment was significantly different from the 0.5% MEGSilica treatment and significantly different from untreated.
The increasing MOR values were caused by the addition of MEG and nano silica ( Figure 14). This trend was in line with the increase in the WPG value and the density obtained. The increase in the WPG value indicates an increase in the density value which causes an increase in the resulting MOR value. Based on research [12] the addition of MEG and nano-SiO2 can cause polymer penetration into the wood cell wall, because the polymer is able to fill the pits on the cell wall. This is also supported by [32]  suggested that the addition of nano-SiO2 concentrations could increase the MOR value of wood due to compression of the wood pores which in turn could increase the stiffness of the wood.
(a) (b) Figure 14. Relationship of MOR with WPG (a) and density (b) of sengon wood.

Hardness.
Wood hardness is influenced by several factors, namely density, elasticity, wood fiber size, bonding power between wood fibers and the composition of wood fibers [33] Impregnation technology using a mixture of MEG and nano silica solutions causes an increase in the hardness value of the sengon wood test sample. Hardness values are presented in Figure 15. The hardness value showed an increase in each treatment ( Figure 15). The highest hardness value was 1% MEGSilica. Based on the results of the analysis of variance shows that the MEG and nano silica treatments have a significant effect on the hardness value. Duncan's test results showed that the hardness values were significantly different among MEG, 0.5% MEGSilica and 1% MEGSilica treatment against the untreated on sengon wood.
The hardness values tend to increase along with the addition of the WPG value ( Figure 16). The higher the WPG value obtained, the higher the hardness value produced, presumably due to the addition of MEG and nano silica. This is supported by [19] which suggests that the addition of MEG and nano silica can cause nano silica to enter the wood and fill the lumen and cell walls of the wood with the help of MEG as a medium, so that the wood strength increase due to the presence of crystallized nano silica. in the wood. This is also in line with [13] which concluded that the impregnation treatment using MEG and nano-SiO2 was able to increase the hardness value of wood.  Figure 16. Relationship of hardness value with WPG on sengon wood.

Wood Durability 3.3.1. Subterranean Termite C. curvignathus Testing.
Wood durability is the resistance of a type of wood to biological organisms that destroy wood such as insects, fungi and marine animals. In order to express its durability, the durability of wood is expressed in the durable class. In Indonesia, there are five classes of durable, namely Class I (very durable) to Class V (very not durable) [34]. Figure 17 shows the weight loss value of untreated was higher than the MEG, 0.5% MEGSilica and 1% MEGSilica treatments. For comparison, the weight loss value of untreated pine sample as was 17.54%. Pine wood was considered as termite's favourite food and also as an indicator of the suitability environmental conditions during the test. If the test environment conditions are suitable then the wood will be eaten by termites during the test. [35] these environmental conditions include humidity and temperature. The results of the analysis of variance showed that the MEG and nano silica treatments had a significant effect on the percentage value of weight loss of the subterranean termite test samples. Duncan's test showed that the untreated samples with other concentration treatments were significantly different. MEG silica concentration of 1% was significantly different from other treatments, while the treatment with MEG concentration and 0.5% MEG silica was not significantly different. 17 For comparison, the untreated pine wood had the percentage of weight loss value of 17.54%. According to research [36] stated that the weight loss of untreated test samples was at least 15%. Meanwhile, the weight loss value for MEG, 0.5% MEGSilica and 1% MEGSilica treatments decreased. The higher the WPG value, the lower the percentage of weight loss ( Figure 18). It was due to the addition of a mixture of MEG and nano silica solutions into the wood. This is supported by the research of [37] which showed that the addition of nano-SiO2 particles could increase resistance to wood destroying organisms with a low percentage of weight loss. The increase in the value of wood hardness also affects the percentage of weight loss because the harder the wood, the harder it is for termites to consume it, in other words, the harder the wood, the harder it is to be damaged by termites [38].

Termite Mortality.
Termite mortality can be used as a criterion for the toxicity of a material to the termite [39]. This is because mortality is the termite mortality rate observed in the testing process. Based on the results showed that the percentage of mortality had increased. The highest mortality value of the test samples occurred in the 1% MEGSilica treatment of 89.17%. For comparison, untreated pine wood has a mortality percentage value of 24.33%. Figure 19. Percentage of average mortality in the test samples after three weeks of feeding the subterranean termite C. curvignathus.  16 The results of variance showed that MEG and nano silica treatments had a significant effect on the mortality values of subterranean termites. Based on Duncan's test, each treatment was significantly different between the untreated, MEG, MEGSilica 0.5% and MEGSilica 1%.
The value of termite mortality in wood treated with MEGSilica was higher than untreated. The higher the mortality value, the more resistant the wood is to C. curvignathus subterranean termites. The resulting increase in mortality value is thought to be due to the addition of a mixture of MEG and nano silica mixed concentrations in each treatment. MEG and nano silica can increase the toxicity which causes the termites have difficulty in eating the wood test sample. Termites do not like toxic materials [40]. The trend of increasing subterranean termite mortality is in line with the increase in WPG value ( Figure 20). The higher the WPG value, the higher the percentage of termite mortality. This is supported by research by [41] which shows that the addition of silica nanoparticles can increase the toxicity of plants against insect attacks. High toxicity can terminate termites. Based on research by [42] nano-SiO2 particles are toxic particles other than ZnO, TiO2 and Al2O3. In addition, according to [43], the preservation treatment is said to be effective if the termite mortality is more than 70%. Test samples with concentrations of MEG, 0.5% MEGSilica and 1% MEGSilica obtained a mortality percentage value above 70%. In other words, wood preservation using a mixture of MEG and nano silica solutions can be said to be effective.

General Discussion
Modification of wood by impregnation method with MEG and nano silica showed an increase in each parameter of physical and mechanical properties and wood durability. Based on [13], impregnation using monoethylene glycol and nano-SiO2 was able to increase the mechanical properties and durability of impregnated sengon wood. MEGSiO2 0.5% treatment was the most optimum concentration. These results are not in line with the results of the study. This is due to the different size of nanoparticles between nano silica from bamboo betung leaves (436.16 nm) and nano-SiO2 (diameter 15 ± 5 nm). The size of nanoparticles can affect the entry of nanoparticles into pits and vessel walls on sengon wood. Nano silica can enter the wood and spread in the lumen and cell walls of the wood with the help of MEG. This is also supported by [19] through SEM analysis showing morphological changes that the addition of a mixture of MEG and nano silica can enter pits, stick to, and even cover the walls of sengon wood vessels.
Based on the results in Table 5, it shows that MEGSilica 1% impregnation treatment is the most optimum value. Sengon wood impregnated with 1% MEGSilica treatment showed an increase in the wood strength class from strength class IV -V to strength class III-IV and durable class IV -V to durable class III-IV.