Cellulose nanostructures from wood waste with low input consumption
Graphical abstract
Introduction
The growing concern for environmental preservation leads to the development of new materials that combine high efficiency, low prices, and minimum environmental impacts. In this scenario, cellulose nanostructures appear as a remarkable alternative, since it presents interesting mechanical, electrical and optical properties associated with biodegradability and high availability of renewable sources. It presents a high surface area, Young's modulus of around 140 GPa, tensile strength up to 7500 MPa and low density (∼1.5 g cm−3). Besides, just as cellulose, nanocellulose is renewable, biodegradable and non-toxic (Abdul Khalil et al., 2016, Abitbol et al., 2016, Grishkewich et al., 2017).
Cellulose is an abundant material found in some bacteria and plants. The development of agriculture generates enormous amounts of waste, agro-residues, which can be applied to obtain nanocellulose (Ditzel et al., 2017, Kallel et al., 2016). The lignocellulose biomass is, generally, major composed of cellulose varying from 30 to 50% wt., hemicellulose with 19–45% wt. and lignin counting with 15–35% wt. (Lee et al., 2014). There are also other components such as fats, carbohydrates, and greases, defined as extractives, and mineral substances (ashes) (El Achaby et al., 2018).
The most common routes for nanocellulose obtaining involve the removal of physical barriers, hemicellulose, and lignin, that shield the structure from the process of cellulose scale down (de Castro et al., 2016, Mariano and Dufresne, 2017, Zhao et al., 2017). The processes, usually denominated pretreatments, consist of lignocellulose structure opening, leading to the removal of fiber constituents, swelling of the biomass, increase of the surface area and a decrease of components molar masses (Cao et al., 2017, Chen et al., 2018, Espinosa et al., 2017). Often, the procedures are repeated several times to increase the results. However, it also increases the energy and reagent consumption required for the process (Henriksson et al., 2007). After the pretreatment, the crystalline regions of cellulose must be released from the amorphous ones and other residual compounds as well (Benini et al., 2018, Chen and Lee, 2018). Those processes influence the surface and bulk properties along with the cellulose source as thermal stability, polymorphism, and dimension of the nanoparticles, which can bring valorization of unexplored biomass since different cellulose sources and isolation methods can provide new structures and different properties (Abdul Khalil et al., 2016, Klemm et al., 2018, Zhao et al., 2017).
It is usual to classify nanocelluloses according to their structure as bacterial nanocellulose (BNC), cellulose nanofiber (CNF) and cellulose nanocrystals (CNCs) (Klemm et al., 2018). Mechanical and enzymatic isolation from pure cellulose usually provide NFC, that is individual or associated nanofibrils, removed from the plant cell wall (Sirviö et al., 2015). The enzymatic isolation method presents great potential. It does not generate or utilize toxic products, being extraordinarily specific and acting in mild conditions of temperature and pressure (Chen et al., 2018).
Enzymes are proteins specialized in catalyzing biological reactions, such as cellulose hydrolysis breakage. In nature, cellulose/hemicellulose is degraded by a group generally named as cellulases, which presents a high degree of synergism during the hydrolysis. The commercial cellulase enzyme preparations are usually a complex mixture of them, what improves their conversion and decreases costs of isolation (Chen et al., 2018, Henriksson et al., 2007, Karim et al., 2017). Recently, the technique of enzymatic hydrolysis has been studied and presents good results. Tang et al. (2015) studied enzymatic hydrolysis followed by ultrasonication after application of alkaline and acid pretreatment in corrugated containers and obtained an increase of 25% in the yield of nanostructures extraction after 36 h of hydrolysis. Cui et al. (2016) produced nanostructures from microcrystalline cellulose pulp, using only the enzymatic method and obtained rod-like particles with a length of 200–400 nm with a yield of 20% conversion after 120 h of hydrolysis. Similarly, Chen et al. (2018) obtained particles of approximately 30 nm with monodispersion using an enzymatic complex to hydrolyze eucalyptus pulp for 5 h (Chen et al., 2018).
Generally, enzymatic hydrolysis tends to result in lower yields than other methods. However, it is an isolation process eco-friendlier than usual acid hydrolysis, as confirmed by Life Cycle Assessment (LCA), within a cradle-to-grave approach (Kargarzadeh et al., 2018). LCA aims the improvement of operations processes while reducing environmental impacts along the product lifecycle. According to ISO 14040:2006 Life Cycle Impact Assessment (LCIA) can be used to evaluate the ecological consequences of the studied phases of a product system. Thus, LCIA appears as a helpful tool for assessing cellulose nanostructures obtaining (Piccinno et al., 2018, Tan et al., 2018). Although LCA has already been used for evaluating nanomaterials application, studies addressing their manufacturing processes are still scarce. Kargarzadeh et al. (2017) pointed out the fact that electricity consumption, raw material efficiency, and water consumption are the main environmental concerns regarding cellulose nanofiber (CNF) production. Abitbol et al. (2016) emphasize that among the isolation methodologies, the enzymatic stands out by its high productivity and low water consumption.
This work proposed the obtaining of nanostructures from Pinus taeda usual wood flour, obtained as industrial waste, utilizing a commercial enzymatic complex. It also evaluates the effects of the enzymatic hydrolysis in this material, which has not yet been clarified by the literature, due to natural recalcitrance from the subtract. The novel method avoids pretreatment application to first cellulose pulp obtaining, as usually reported (Asad et al., 2018, Dubey et al., 2018), and presents environmentally promising results. The morphology and properties of the obtained structures were characterized, searching for a process to increase value to the pinewood waste, while reducing inputs consumption.
Section snippets
Materials
Wood flour obtained from softwood boards (Pinus taeda) after their utilization as transportation pallets were the cellulosic source for nanostructure extraction. The wood dust was milled in a cutting mill (SL 31, Solab, Brazil), to obtain particles smaller than 50 mesh. The enzymes applied at the enzymatic hydrolysis were the commercial cellulase complexes Cellic CTec2® and Cellic HTec2®, mainly composed of endoglucanases and xylanase respectively. The enzymatic catalysts were supplied by
Results and discussion
As shown in Fig. 2, the nanocellulose was produced from pine wood by two different routes, one consisting of the direct use of enzymes in the wood residue, defined as NT samples, and the other consisting in applying a two steps pretreatment, named PT samples.
The pretreatment was applied to Pinus wood flour to remove the recalcitrant compounds, lignin, hemicellulose, and others, which limit hydrolysis efficiency, according to the literature (Long et al., 2017). The compositional analysis
Conclusions
Cellulose nanostructures were obtained from wood waste using a commercial enzyme complex with (PT) or without (NT) the application of pretreatment. For PT samples, two steps of pretreatment removed recalcitrant compounds, exposing cellulose structures. The enzymatic hydrolysis generated particles with RH of around 200 nm for samples PT and NT with reaction times of 24 and 48 h, observed in DLS, and presenting a significant concentration of particles below 250 nm, as found in NTA. The samples of
Acknowledgements
The authors are grateful to UFABC, Núcleo REVALORES and Multiuser Central Facilities (UFABC) for the experimental support, to the Editor of the Journal of Cleaner Production and all anonymous Reviewers, who offered essential contributions to the improvement of this paper. This work was supported by CNPq (grant numbers 306401/2013-4, 447180/2014-2, 163593/2015-9) and FAPESP (grant number 2016/12700-5).
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