Facile Impregnation of Graphene into Porous Wood Filters for the

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Facile Impregnation of Graphene into Porous Wood Filters for the Dynamic Removal and Recovery of Dyes from Aqueous Solutions Sheila Goodman, Renata Bura, and Anthony B. Dichiara ACS Appl. Nano Mater., Just Accepted Manuscript • DOI: 10.1021/acsanm.8b01275 • Publication Date (Web): 20 Sep 2018 Downloaded from http://pubs.acs.org on September 21, 2018

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Facile Impregnation of Graphene into Porous Wood Filters for the Dynamic Removal and Recovery of Dyes from Aqueous Solutions Sheila M. Goodman, Renata Bura, Anthony B. Dichiara* School of Environmental & Forest Sciences, University of Washington, Seattle, WA 98195, U.S. Abstract: Ever increasing industrialization leads to a rise in contaminated water resources due to the release of pollutants, such as organic dyes, into aquatic environments. Carbon nanosorbents, such as graphene, often exhibit faster uptake, higher capacity, and superior regeneration than activated carbon, which is the world’s most widely used adsorbent for point-of-use water purification. However, continuous-flow adsorption treatments using graphene-based adsorbents are relatively scarce and are challenged by pressure drop and low flow through efficiency. Solidliquid separation after treatment is another great concern when dealing with carbon nanosorbents. One way to address these issues consists of impregnating basswood, which is uniquely design for fluid transportation, with graphene to promote fast and efficient adsorption, eliminate the need for dispersing and recovering the nanomaterials, and limit pressure drop as well as nanoparticle aggregation. The properties of the modified wood filters to adsorb and desorb methylene blue in a dynamic system were examined based on a central composite design. Results show that graphene was well-dispersed and immobilized on the wood vessel sidewalls by a vacuum impregnation process. The Yan model provided a good fit to the experimental breakthrough curves and high uptake capacity up to 46 mg/g were obtained even at relatively low feed concentration. Spent filters were recovered by solvent-exchange and reused for five sorption cycles with regeneration efficiency higher than 80%. The present study has important implications for the safe and efficient utilization of nanosorbents in environmental remediation and separation applications. Keywords: Graphene, wood, adsorption, water treatment, central composite design

*Corresponding author: [email protected] ACS Paragon Plus Environment

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1. Introduction Fresh water is an essential resource to sustain life on Earth and a crucial feedstock in the majority of agricultural and industrial processes. With growing population, the demand for fresh water is ever increasing, however, the available supplies are rapidly decreasing due to extended droughts and rising pollution caused by human activities.1 The United Nations estimates that three in ten people lack access to clean drinking water.2 In addition, water remediation becomes more challenging as new types of contaminants are released into hydrological environments. Organic dyes are among the most widespread pollutants and are commonly employed in a large variety of applications, such as tanning of textiles, papers, and leathers,3,4 processing of food, plastics, and cosmetics,5 and tracing of biomedical agents and ground water.6 Besides their toxic, mutagenic, carcinogenic, and detrimental sanitary effects, few ppm levels of dyes can impart undesirable color to the water body, which reduces sunlight penetration and resists photochemical and biological attacks to aquatic life.7 In particular, methylene blue (MB) is one of the most widely used soluble basic dyes in water, which are typically more toxic than anionic dyes.8 MB can cause severe eye and skin irritations, vomiting, nausea, diarrhea, profuse sweating, mental confusion, gastritis and difficulty breathing.9 The removal of dyes, such as MB, from aqueous media is critical and the different treatments for dye wastewater include physical, chemical, and biological methods. Among these techniques, adsorption is one of the most promising approaches owing to its relatively low cost, easy operation, and high efficiency even at exceedingly low concentrations. Adsorption processes, which consist of the transfer of solution-phase chemicals to the surface of a solid adsorbent with high binding affinity, are limited in their ability to remove contaminants by the capacity of the adsorbent material. Carbon nanomaterials, such as nanotubes (CNTs) and graphene, have attracted growing interest as adsorbents due to their higher uptake 2 ACS Paragon Plus Environment

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capacity, faster sorption kinetics, and superior regeneration efficiencies than activated carbon, the most widely used material for water purification to date.10,11,12,13,14 This is mostly attributed to the fact that the microporosity in activated carbon is often clogged, while the open pore structure of carbon nanomaterials offers more direct access to their surface for adsorption.15 Despite these advantages and the need for adequate point-of-use technologies, applications of carbon nanomaterials in continuous flow adsorption systems are scarce.16,17,18 Packing sufficient quantities of adsorbents in a column for the dynamic treatment of environmentally relevant volumes of wastewater is challenging, and often the outstanding sorption properties of carbon nanomaterials obtained in batch systems are not fully exploited in continuous-flow processes.19 Pressure drop and low flow-through efficiency combined with the tendency of hydrophobic carbon-based adsorbents to readily form aggregates in water significantly hinder the performance of adsorption columns packed with nanomaterials.20,21 ,22 Furthermore, the solid-liquid separation after treatment is another great concern when dealing with graphene, CNTs and their derivatives.23,24 In the present study, we propose a novel approach to address these issues and improve the performance of carbon nanomaterial-packed adsorption columns by immobilizing graphene nanoplatelets (GnPs) pre-adsorbed with alkali lignin onto a mesoporous wood template for the dynamic removal of MB from aqueous solutions. The adsorption properties of the GnPimpregnated wood filters were evaluated and compared to traditional fixed-bed adsorption columns packed with GnP powders. The influence of the flow rate and initial MB concentration on the continuous-flow adsorption process were examined. A solvent-based desorption method was considered for the regeneration of spent wood filters, and the recycled materials were reused in multiple adsorption/desorption cycles.

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2. Experimental method 2.1. Materials and chemicals Tilia americana (basswood) was purchased from Crosscut Hardwoods. Graphene nanoplatelets (GnPs) were obtained from Sigma Aldrich with an average of 5-7 atomic layers, a Raman D/G of 0.28, and a sheet resistance of 10±5 Ω/sq, as per the manufacturer specifications. The alkali lignin (AL, 99%) and methylene blue (MB, 99%) were purchased from Tokyo Chemical Industry Company and TCI America respectively. HPLC grade acetone and acetonitrile were purchased from Fischer chemical with a purity greater than 99.5%. All dispersions were conducted using deionized (DI) water and all materials were used as received without any further treatment unless otherwise specified.

2.2. Preparation of GnP-decorated basswood filters Aqueous dispersions of GnPs pre-adsorbed with AL were prepared by double acoustic irradiation following a previously established procedure.20 Briefly, 0.5g of AL was first dissolved in 200 mL DI water using bath sonication for 15 minutes at 25 °C. Then, pristine GnPs were added to the AL solution, at a ratio of GnP:AL 2:1 w/w and the mixture was sonicated using a double acoustic irradiation system for 45 minutes. The as-prepared GnP dispersions were loaded in basswood discs of 29 mm diameter and 6 mm thickness using a vacuum impregnation method. Prior to GnP impregnation, the wood discs were sonicated in acetone for 30 minutes and rinsed with DI water to remove extractives and other organic impurities. The washed wood discs were oven dried at 60 °C for 2 hours and sealed in a vacuum chamber. The aqueous GnP suspension was introduced under vacuum, dropwise onto the wood surface, allowing for capillary action to pull the GnP solution into the porous wood structure. After drop casting 200 mL GnP dispersion,

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the wood disk remained under vacuum for 24 hours. After GnP impregnation, each wood filter was cut in half such that the thickness was reduced to 3 mm, and thoroughly washed using alternating acetone and DI water to remove any un-adsorbed GnPs. Washing was monitored by UV-Vis absorption spectroscopy and was conducted until no appreciable change in the filtrate was observed with additional rinsing. The final GnP content in each wood disc after washing was estimated to 70 +/- 5 mg using a mass balance on the GnPs in solutions.

2.3. Characterization The morphology of as prepared wood filters was examined by optical and electron microscopies using a Zeiss Axiocam ERc5s digital camera mounted on a Zeiss Axiolab light microscope and a Sirion XL30 electron microscope. For scanning electron microscopy (SEM), the samples were coated with a gold-palladium layer and the observations were conducted under high vacuum conditions at an accelerating voltage of 5 kV. To probe the distribution of GnPs in the wood filters, Raman spectra were recorded at various positions over the range of 900-1800 cm-1 with a spectral resolution of 1 cm-1 by a Renishaw InVia Raman microscope equipped with a 785 nm laser. UV-vis absorption spectroscopy measurements were performed in quartz cuvettes using a Perkin Elmer Lambda 750 spectrophotometer operating in the 200-1200 nm range with a spectral resolution of 1 nm.

2.4. Continuous flow adsorption As-prepared wood filters were wrapped with Teflon tape to ensure an adequate seal with the syringe walls, and fitted into 29-mm diameter rubber caps, which were sealed into the bottom

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of a 140 cc monojet syringe. The syringe system was equipped with a 74900 Cole Palmer liquid flow controller and placed in a vertical position, as illustrated in Figure 1.

GnPs Lignin

Methylene blue solution

Vacuum Impregnation Filtrate measured with UV-Vis

Figure 1. Experimental setup for the dynamic adsorption of MB from water using GnPimpregnated wood filters.

Before pumping the MB solutions, each filter was wet with 100 mL of DI water to prevent swelling and shrinkage of wood during adsorption. Noteworthy, neither wood splinters nor GnPs were found in the filtrate based on both visual inspection and UV-vis spectroscopy after rinsing. Three feed concentrations of MB, C0, (i.e. 10, 12, and 14 mg/mL) and three liquid flow rates (3.0, 3.5, and 4.0 mL/min) were examined and adsorption data were systematically analyzed in a 32 factorial design, where all combinations of MB concentrations and flow rates were tested with triplicate centroid conditions, as listed in Table 1. The filtrate concentration at the outlet of the syringe, Ct, was measured at different time intervals by UV/vis absorption spectroscopy using a measured extinction coefficient from Beer's law analysis at the maximum absorption peak for MB (i.e. 664 nm). Filtrate samples were collected every minute until breakthrough was reached, and every five minutes henceforth. Breakthrough was expressed in terms of normalized concentration

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(i.e. Ct/C0) and was declared when the ratio of the filtrate concentration over the feed concentration reached 0.1. This value was selected to reflect the regulation limit for MB levels in humans and aquatic species established by the National Institutes of Health and the National Center for Biotechnology Information (i.e 2 mg/kg).25 All experiments were conducted at 25 °C for the time required to treat 100 mL of MB solution at each designated flow rate. After treatment of 100 mL MB solution, the cumulative filtrate concentration was measured by UV-vis absorption spectroscopy. Long-term experiments were also performed by refilling the syringes with another 100 mL of the same feed solution multiple times until complete saturation of the wood filters was achieved. The Thomas and Yan models were fitted to the experimental, long-term adsorption data using Origin 8.0 software.26,27 For comparison purposes, experiments were conducted under the same conditions using wood discs in the absence of GnPs. Similarly, 140 cc monojet syringes were also packed with 0.5 g GnP powder to the same depth as the wood filters (i.e. 3 mm). The GnPs were supported and surrounded by polyester fibers to prevent bed expansion during treatment. Table 1. Experimental matrix of the centroid design MB Concentration (mg/L) Flow Rate (mL/min) 1 10 3.0 2 12 3.0 3 14 3.0 4 10 3.5 5* 12 3.5 6* 12 3.5 7* 12 3.5 8 14 3.5 9 10 4.0 10 12 4.0 11 14 4.0 *denotes a triplicate of the centroid point

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2.5. Batch adsorption Aqueous solutions of MB were prepared at concentrations of 10, 12, and 14 mg/mL with a pH of 8.02 monitored with an EcoSense pH10A pH-meter. Dried powders of GnPs with a mass of 0.5 g were added to 100 mL MB solution. The mixtures were placed on an orbital shaker operated at 120 rpm for 20 minutes. The contact period (i.e. 20 minutes) was chosen based on the time required to treat 100 mL of solution at a given flow rate (i.e. 4.0 mL/min) in the continuous flow system. After 20 minutes, the supernatant was decanted away and the MB concentration was measured by UV-vis absorption spectroscopy. The amount of MB adsorbed per mass of GnP, q (mg of MB per g of GnP), was determined by subtracting the mass of MB in solution after 20 minutes from the initial mass of MB in solution.

2.6. Regeneration and reuse After completing the dynamic treatment of the first 100 mL MB solution at 4.0 mL/min, the wood filters were removed from the syringe and washed with copious amounts of either acetone or acetonitrile until no appreciable change was observed by UV-vis absorption spectroscopy. The regenerated wood filters were then re-sealed back into the bottom of the syringe and tested for another 100 mL of MB solution under the same operating conditions (i.e. 14 mg/mL, 4.0 mL/min). A total of five successive adsorption/desorption cycles were conducted and the cumulative filtrate concentration was measured by UV-vis absorption spectroscopy at the end of each treatment cycle. The effectiveness of the solvent regeneration was assessed based on the regeneration efficiency (RE) defined as: 𝑅𝐸 (%) =

𝑞𝑖 ∗ 100 𝑞0

(1)

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where qi (mg/g) indicates the adsorption capacity of any given cycle i, and q0 (mg/g) indicates the adsorption capacity of the initial cycle prior to any solvent regeneration.11

3. Results and discussion 3.1. Wood filter characterization The structure of the wood filters before and after GnP impregnation was examined by SEM, as illustrated in Figure 2. Hardwoods, such as the basswood used in this study, are comprised of a complex mesoporous structure of long, partially aligned, tubular channels commonly referred to as vessels. The vessels can have diameters up to several hundred micrometers and are uniquely designed to transport fluid throughout the wood.28 Laterally aligned vessels are connected through pits or holes in the sidewalls that allow for water transport perpendicular to the vessel direction, enabling fluid transportation in all directions throughout the wood structure (Figure 2a-c). Since vessels can account for up to 60% of the wood by volume, continuous flow water purification is a reasonable application for hardwoods.28 In such case, the inner walls of the vessels must be decorated with active nanoparticles in order to remove or degrade contaminants. Representative SEM images of GnP-impregnated basswood after washing and rinsing (Figure 2d-f) reveal that the GnPs have been immobilized successfully onto the walls of the wood as small clusters without blocking the vessels and pits. A reasonable mechanism for the deposition of GnPs on the vessel walls is that the aromatic rings on the GnP are able to adsorb onto the aromatic rings in the cellulose within the wood structure through 𝜋 − 𝜋 stacking.29,30 The GnP dispersion across the wood is relatively uniform and minimal GnP aggregation was observed. This allows for contaminated water to adequately flow through the vessels and pits, ensuring a good contact with the

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immobilized GnPs to promote adsorption. Note that commercially available multi-walled carbon nanotubes (Cheap Tubes Inc.) were also utilized to impregnate wood filters, however, the uptake of methylene blue was found to be lower than when graphene was used. The surface area and mean pore diameter of the graphene nanoplatelets were determined by nitrogen physisorption at 77 K using a Micrometrics TriStar 3030 and were found to be 743.05 m2/g and 0.29 cm3/g, respectively. These values were much higher than those of multi-walled carbon nanotubes, hence explaining the difference in adsorption between these materials. In addition, the curvature of the CNT surface may reduce the strength of the π-π interactions between methylene blue and the aromatic rings present.

Pristine Wood

(b)

(a)

20 µm

(d)

(c)

20 µm

5 µm

20 µm

(e)

20µm

5 µm

5 µm

5 µm

(f)

GnP Wood 10

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Figure 2. Representative photographs and SEM micrographs of 3-mm thick pristine (a-c) and GnP-impregnated (d-f) basswood discs, with transverse (b,d) and longitudinal (c,e) views. Red circles indicate GnPs immobilized on the wood sidewalls (d,e).

Although the vacuum impregnation method was able to pull the GnPs into the whole thickness of the wood and through the full length of the vessels, a gradient in GnP content exists from each side of the 3-mm thick filters. The GnP distribution along the wood thickness was determined from optical microscope observations by counting the average number of GnP clusters present in each of the five sections of equal area evenly dividing the wood filters using ImageJ software, as illustrated in Figure 3a. Note that position P5 corresponds to the center of the wood during GnP impregnation and before the filters were cut in half. The GnP loading gradually decreased when progressing through the thickness of the wood filter from the outside edge (P1) to the center (P5). The middle positions (i.e. P2, P3, P4) did not exhibit any statistical differences in GnP content. These results are consistent with Raman spectroscopy analysis (insets in Figure 3bd), where the intensity of the characteristic graphene peaks at 1350 and 1580 cm-1 increased as one gets closer to the central section of the wood filters. The G band at 1580 cm-1 is assigned to the stretching vibration of carbon sp2 bonds in a hexagonal lattice, and the D band at 1350 cm -1 corresponds to the disordered sp2 phase plus possible contributions of the scattering of sp3-bonded carbon.31 The integrated intensity of the G band was reduced by 27% from section P1 to section P3, which is in a good agreement with the optical microscope observations, where the estimated GnP content decreased by approximately 30% from section P1 to section P3. Similar trends were observed in other sections of the GnP-impregnated wood filters.

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Figure 3. (a) Distribution of the number of GnP clusters as a function of the position through the thickness of the wood filters. (b-d) Representative Raman spectra and optical microscopy images (insets) of the GnP-impregnated wood filters collected at different positions across the specimen thickness.

3.2. Wood filters vs powdered adsorbents Figure 4 shows representative UV-vis spectra of the cumulative filtrate concentration after pumping 100 mL of DI water spiked with 10 mg/mL MB through pristine and GnP-decorated wood discs. Before the MB solution treatment, 100 mL of DI water was pumped through the filters

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to prevent swelling and shrinkage of wood during adsorption. It is also worth noting that no GnP was detected in the effluent at any time in the process, confirming the good immobilization of GnPs on the vessel sidewalls, which is of paramount importance considering the high interest in reducing the footprint of nanomaterials on the environment. Complete dye discoloration from blue to clear is observed during the dynamic adsorption studies with GnP-impregnated wood filters (Figure 4b). In the absence of GnPs, however, minimal changes in the solution color and UV-vis spectra were detected (Figure 4a). This suggests that GnP is the active material promoting solution discoloration, while the contribution of wood is negligible. The solution discoloration is attributed to the adsorption of MB from the feed solution onto the surface of GnPs embedded in wood. Compared to catalytic methods where colorless byproducts of the dye degradation process may induce secondary pollution, adsorption systems are highly desirable due to their unique ability to generate up to a certain time fluid with zero contaminants. The MB adsorption on GnPs originates from the interaction between delocalized π electrons in neighboring aromatic rings of GnPs and MB. The functionalization of GnPs with anionic lignin may also offer the possibility for cationic MB molecules to adsorb via Coulombic interactions. For comparison purposes, adsorption studies were conducted using sole GnP powder in batch and continuous flow configurations. In the absence of wood, the syringe was packed with GnP powder surrounded by layers of polyester fibers. A mass of 0.5 g of GnP was used to match the same volume in the column as the wood filters. All dynamic studies were tested at a 10 mg/L feed MB concentration and a flow rate of 4.0 mL/min. Batch experiments using the same mass of GnP and MB concentration were also performed. The effectiveness of each type of adsorbent (i.e. pristine wood, GnP-decorated wood, and GnP powder in batch and fixed bed systems) was determined by their respective removal efficiencies (%) and the corresponding normalized

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concentration,

𝐶𝑡=20 𝐶0

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, of the effluent after treatment of 100 mL MB solution for 20 minutes. Results

from this comparative study are depicted in Figure 4c. As expected, the pristine wood filter had the lowest removal efficiency and therefore the highest cumulative normalized MB concentration in the filtrate among all materials tested, reaffirming that GnP is the active adsorbent in the system. The packed GnP powder resulted in a higher removal efficiency (87.4 %) than its batch counterpart (72.5 %). This is consistent with previous research about the batch adsorption of organic dyes, where the dye concentrations remained at several ppm after treating relatively small volumes (< 25 mL) of solutions at hundreds of ppm level.32,33 The difference between batch and continuous flow systems can be explained by the fact that, in a dynamic system, the adsorbent is in equilibrium with the feed, while in a batch process, the adsorbent is in equilibrium with the residual bulk concentration, which is necessarily lower than the feed. Such variations in concentration can lead to significant changes in uptake values, as concentration gradient is a driving force for adsorption.19 Both the batch and fixed bed processes with GnP powder exhibited cumulative normalized filtrate concentration greater than breakthrough (0.1), indicating that more adsorbents are needed to match environmental regulations under these conditions. The wood filter, however, maintained a cumulative normalized filtrate concentration below 0.1 (i.e. 0.08), and exhibited the highest removal efficiency (91.1 %) despite using seven times less adsorbents. This indicates that the degree of adsorbent utilization is dramatically enhanced in the wood filters. The reduced performance of the GnP powder can be attributed to limitations in mass transfer and axial dispersion. In addition, no pressure drop was noticed during the treatment with the wood filters, while the pressure had to be adjusted to maintain a constant flow rate when the column was packed with GnP powder.

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(a)

(b)

(c)

Figure 4. Representative UV-vis spectra of aqueous solutions of MB before and after continuousflow treatment through (a) pristine wood disk and (b) GnP-decorated wood filter. Photographs of the color changes between the feed and the outlet solutions are shown in the insets. (c) Removal efficiencies and normalized cumulative outlet concentrations of various adsorption systems.

3.3. Long-term adsorption study To examine the efficacy of the wood filters further, breakthrough curves were obtained from long-term adsorption experiments, where the column was refilled multiple times with the same MB solution until adsorbent exhaustion was achieved. Breakthrough curves were expressed in terms of normalized concentration, defined as the ratio of the outlet concentration, Ct (mg/L), to the feed concentration, C0 (mg/L), as a function of time. For definiteness, the breakthrough and exhaustion times were taken as the times to reach Ct/C0 = 0.10 and Ct/C0 = 0.75, respectively. Since the breakthrough time is associated with the threshold level for MB concentration, it was used as a metric to assess the column performance in a practical setting. Breakthrough times were estimated through nonlinear fitting of the experimental data using the Thomas and Yan equations, which are among the most widely adopted models in column adsorption studies. The Thomas fit to the data has the general form:26

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1

𝐶𝑡 ⁄𝐶0 = 1+

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(2)

𝑘 𝑞 𝑀 ( 𝑇𝐻 0 −𝑘𝑇𝐻 𝐶0 𝑡) 𝑒 𝑄

where t is the time in (min), Q is the inlet flow rate in (mL/min), M is the mass of adsorbent in (g), and 𝑘𝑇𝐻 (𝑚𝐿/𝑚𝑔 ∙ 𝑚𝑖𝑛) and 𝑞0 (𝑚𝑔⁄𝑔) are the Thomas rate constant and maximum adsorption capacity, respectively. The nonlinear expression of the Yan model is described below.27

1

𝐶𝑡 ⁄𝐶0 = 1 − 1+(

𝑄2𝑡 𝑘𝑞0 𝑀

(3) )

𝑘 𝐶 ( 𝑌 0⁄𝑄)

where kY (L/mg∙min) and q0 (mg/g) refer to the Yan model constant and maximum adsorption capacity, respectively. The Yan model provided a better fit to the experimental data with correlation coefficient values being close to one, as exemplified in Figure 5. This is especially true at short processing times, where the Thomas model is known to deviate from experimental data close to t = 0.34 Therefore, the Yan model was employed to determine the breakthrough times at different feed concentrations and flow rates within the framework of a central composite design.

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Figure 5. Example of breakthrough curve for the dynamic adsorption of MB on GnP-decorated wood filter at 14 mg/L and 4.0 mL/min. The Yan model (kY = 242.73403 L/mg∙min; q0 = 45.5 mg/g) and Thomas model (kTH = 1.46427 mL/mg∙min; q0 = 56.8 mg/g) fits to the data are indicated by solid black lines and dotted blue line, respectively. Horizontal dotted and solid red lines indicate breakthrough (0.1) and saturation (0.75), respectively.

The Yan model was also utilized to estimate the adsorption capacity of the GnP-decorated wood filters at exhaustion. The uptake value was 45.5 mg/g, which is among the highest values reported for the adsorption capacity of MB on various adsorbents in continuous flow processes, as listed in Table 2. This result is especially remarkable considering that a significantly lower feed concentration was used. Higher concentration gradients typically provides a greater driving force for the mass transfer and subsequent adsorption on the sorbent surface.35 For comparison purposes, the Yan model was also used to determine the adsorption capacity of the pristine wood filter

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without any GnPs, which was found to be 4.8 mg/g, nearly ten times lower than its GnP impregnated counterpart.

Table 2. Comparison of different continuous-flow adsorption systems for the removal of MB from aqueous solutions. Adsorbent GnP-decorated wood filter Pristine wood filter Natural zeolite Silica sands Modified ball clay Rice husk Graphite oxide coated sand Activated carbon from olive Activated carbon from waste Modified chitin on sand

C0 (mg/L) 14 10 30 50 50 50 100 100 100 100

Q (mL/min) 4.0 4.0 2.2 2.7 5.0 8.2 2.0 3.0 5.0 10.0

q (mg/g) 45.5 4.8 4.4 5.3 25.6 4.4 0.9 107.4 7.0 29.8

bed depth (cm) Reference 0.3 this study 0.3 this study 36 15.0 37 35 2.5 39 25.4 18 15.0 40 3.0 41 6.0 42 25.0

3.4. Effects of flow rate and feed concentration A centroid design (Table 1) was developed to investigate the adsorption behavior of the GnP-decorated wood filters under various conditions. Linear and quadratic models were fit to the breakthrough time and the cumulative normalized outlet concentration as a function of flow rate and feed concentration. The corresponding surface response plots are given in Figure 6. Although the analysis of variance demonstrated that both regressions were statistically significant with a 95% confidence level, the quadratic model (equation 4) provided a better fit to the breakthrough data with a correlation coefficient value of 0.87 compared to the linear model (equation 5, R2 = 0.85). Similarly, the quadratic model (equation 6) provided a better fit to the cumulative normalized outlet concentration data with a correlation coefficient value of 0.98 compared to the linear model (equation 7, R2 = 0.73). Note that the fitting could be improve further using a polynomial model. 18 ACS Paragon Plus Environment

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𝐵𝑟𝑒𝑎𝑘𝑡ℎ𝑟𝑜𝑢𝑔ℎ𝑄𝑢𝑎𝑑 = −0.333(±0.559)𝑥 2 + 4.517(±13.436)𝑥

(4)

+ 6.945(±8.944)𝑦 2 − 60.876(±62.676)𝑦 + 133.126(±116.719) 𝐵𝑟𝑒𝑎𝑘𝑡ℎ𝑟𝑜𝑢𝑔ℎ𝐿𝑖𝑛 = −3.473(±0.668)𝑥 − 12.264(±2.672)𝑦 + 96.216(±12.358)

(5)

𝐶𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒𝑄𝑢𝑎𝑑 = 0.009 (±0.001)𝑥 2 − 0.185(±0.031)𝑥 − 0.043(±0.020)𝑦 2 + 0.331(±0.142)𝑦 + 0.433(±0.265)

(6)

𝐶𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒 𝐿𝑖𝑛 = 0.028(±0.007)𝑥 + 0.056(±0.027)𝑦 − 0.427(±0.138)

(7)

Results show that adsorption is strongly affected by changes in initial MB concentration and flow rate. Breakthrough was achieved in less than 2 min at the highest feed concentration and flow rate, while it took nearly 25 min at the lowest conditions. Increasing the feed concentration corresponds to increase in the concentration gradient, which reduces the time required to reach breakthrough.16 Similarly, binding sites become more quickly saturated at higher flow rates, resulting in shorter breakthrough times. Since breakthrough time is indicative of when the adsorbent needs to be regenerated or replaced, decreasing the inlet concentration and flow rate allows for larger volumes of effluent to be treated to the desired level of purity, as reflected by longer breakthrough times due to reduced mass transfer coefficient and slower saturation of the system. In addition, the surface plots for the cumulative normalized outlet concentration exhibited a similar trend, indicating that higher removal efficiencies were obtained at lower feed concentrations and flow rates. The removal efficiencies varied from 83.2% to 95.5% within the range of conditions considered in this study. These observations are consistent with other studies reporting the fixed bed adsorption of different organic compounds on carbonaceous materials. 19 ACS Paragon Plus Environment

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Figure 6. Quadratic (a,c) and linear (b,d) surface response plots for breakthrough time (a,b) and cumulative normalized outlet concentration (c,d) as a function of flow rate and feed concentration of MB.

3.5. Regeneration and reuse of GnP-decorated wood filters While spent wood filters can be burnt after treatment to limit solid waste and produce energy, the ability to regenerate and reuse adsorbents can restore the original uptake capacity, extend the lifespan of the material, and recover valuable chemicals. Physisorption being the main mechanism involved in the adsorption of MB, there is no strong chemical association between MB and GnP, hence the weak adsorbate/adsorbent interactions can be reversed, providing opportunities

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to recycle spent wood filters. Organic dyes are typically removed from the adsorbent surface by ion-exchange, which involves washing the spent materials with solvents, such as methanol, N,Ndimethyl formamide, acetonitrile, and acetone. A solvent-exchange procedure was utilized for the desorption of MB from spent wood filters. After treatment of 100 mL MB solution, the wood filters were thoroughly washed with either acetone or acetonitrile until no appreciable change in the UVVis spectra of the filtrate was observed. Noteworthy, no GnP was detected at any time during rinsing, once again confirming the good immobilization of GnPs onto the wood surface. The recycled wood filters were reused for further MB adsorption and the evolutions of the regeneration efficiency (RE) after multiple regeneration cycles are plotted in Figure 7. The desorption of MB adsorbed on the wood filters by acetone was rapid and the RE reached more than 99% after the first desorption cycle, indicating that the sites available for MB adsorption were almost completely recovered by solvent-exchange. After the second regeneration cycle, however, the RE dropped to approximately 60% and held relatively steady for the subsequent adsorption/desorption cycles. The variations in RE between the first and subsequent regeneration cycles is attributed to the fact that the wood filter is only partially saturated with MB molecules after the first treatment cycle. This is explained by the concept of mass transfer zone (MTZ) in dynamic adsorption systems. The MTZ, which is the region where adsorption takes place, has a leading edge where the adsorbent is still unused and a trailing edge where the adsorbent is already equilibrated (i.e. the liquid phase has the composition of the feed), while the adsorbent in the MTZ is only partially saturated. When molecules from the feed are leaching through the column, it indicates that the leading edge of the MTZ has reached the end of the wood filter. At this time, the adsorbent has only two zones: equilibrated zone where the adsorbent is saturated and MTZ where the adsorbent is only partially saturated. Under the treatment conditions of 100 mL at 14 mg/L MB and 4 mL/min, the normalized

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concentration exiting the column after 25 min is approximately

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𝐶𝑡 ⁄𝐶 = 0.3, as reported in Figure 0

5. Although MB molecules are exiting the column, the normalized concentration is much lower than the exhaustion concentration (i.e. 0.30 < 0.75), indicating that there are still vacant sites available for adsorption. Therefore, both vacant sites and occupied sites that have been freed by solvent-exchange contribute to the RE in cycle 1. After the second cycle, however, all adsorption sites have been occupied, meaning that the RE in cycle 2 and beyond solely reflect the ability of acetone to desorb MB from the wood filters. Results show that acetone is able to recover about 60% of the spent wood filter, which is consistent with previous MB desorption studies using solvent-exchange. For instance, ethanol was reported to desorb about 50% of MB from carbonaceous adsorbents at room temperature.43 The partial regeneration can be attributed to the fact that acetone is only capable of desorbing MB adhered on the external GnP surface, but not within its mesoporous structure. When acetonitrile was used in the desorption process, more MB molecules were recovered and the RE remained close to 80% after five adsorption cycles (i.e. four regeneration cycles). The RE with acetonitrile followed the same general trend as when acetone was utilized, with a drop after the first regeneration cycle and a relatively steady state in subsequent cycles. Moreover, similar volumes of solvent were used in each case, revealing that acetonitrile yielded higher desorption rates than acetone. These results indicate that acetonitrile was able to not only desorb MB from the external surface of the adsorbent, but also within some of the mesopores as well, which is consistent with previous research reporting the desorption of organic compounds from carbonaceous materials.43

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Figure 7. Evolution of the regeneration efficiency for GnP-decorated wood filters tested at 14 mg/L MB and 4 mL/min across multiple adsorption/desorption cycles. Errors were below 1%.

4. Conclusion In summary, GnPs pre-adsorbed with lignin were immobilized into porous basswood by vacuum impregnation for the removal of MB from aqueous solutions in a dynamic process. The as-prepared GnP-decorated wood filters limit the risk of nanoparticle leaching, eliminate the need for dispersing and recovering the nanomaterials, improve the degree of adsorbent utilization, and can be regenerated or burnt, thereby decreasing the waste generated after the adsorbent is exhausted. Although more research is required to determine the range of compounds that may be adsorbed, this study provides a first and important step towards more widely deployable technologies for point-of-use water purification.

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Acknowledgements This work was funded by the USDA National Institute of Food and Agriculture, McIntire Stennis project #1009515. Sheila M. Goodman gratefully acknowledges the School of Environment and Forest Sciences at the University of Washington for scholarship support.

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