and Microporous Canola Stalk-Derived Hydrothermal Carbon via

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Optimizing the Preparation of Meso- and Microporous Canola Stalk-derived hydrothermal carbon via response surface methodology for Methylene Blue removal Mohammad Salimi, Salar Balou, Komeil Kohansal, Khosrow Babaei, Ahmad Tavasoli, and Mahmoud Andache Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b02440 • Publication Date (Web): 17 Oct 2017 Downloaded from http://pubs.acs.org on October 18, 2017

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Optimizing the Preparation of Meso- and Microporous Canola Stalk-derived hydrothermal carbon via response surface methodology for Methylene Blue removal Mohammad Salimi, Salar Balou, Komeil Kohansal, Khosrow Babaei, Ahmad Tavasoli, Mahmoud Andache School of Chemistry, College of Science, University of Tehran, Tehran, Iran

Abstract

In this work, Design of Experiments –Response Surface Methodology (RSM) was implemented to predict the importance of hydrothermal carbonization (HTC) key parameters and their interactions in the preparation of Canola Stalk-derived hydrochar via HTC technique. According to the RSM results, temperature and reaction time were found to be the most important control factors. The possible optimum conditions were found to be 207 C and 82 min for temperature and time, respectively in order to achieve a hydrochar with the maximum mass yield (solid yield 53.38 %), carbon recovery rate (52.66) and O/C ratio (0.69). Furthermore, the optimized hydrochar was successfully activated via potassium hydroxide (KOH), under mild activation conditions. Synthesized microporous activated carbon demonstrated the highly improved Brunauer–Emmett–Teller (BET) surface area of 474.87 m2 g-1 compared to the low BET surface area of mesoporous hydrochar (SBET of 2.69 m2. g-1). Porous activated carbon was used as an adsorbent for Methylene blue removal that showed a promising dye removal capacity of 93.4 mg. g-1. The morphological and chemical compositions of the solid materials were analyzed by various techniques, including elemental analysis, Field Emission Scanning Electron Microscope (FESEM), BET analysis, Fourier transform infrared (FTIR) spectroscopy and Energy-dispersive X-ray spectroscopy.

Keywords: Hydrothermal, D-optimal, Response Surface, Experimental Design, Carbonization, KOH Activation



Corresponding author. Tel: +98-21-61113643. E-mail: [email protected]

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Introduction In recent years, formation of valuable carbon materials has been scrutinized through the hydrothermal carbonization of renewable resources such as crude biomass1. The enthusiasm for the continuous researches and implementations in this field is due to Structural and functional divergence of carbonaceous materials that creates marvelous opportunities for innovation in a more sustainable and versatile design, low cost, simple and costeffective preparation and wider applications2. Our planet earth provides a recyclable, highly reachable and a renewable resource called biomass, through which the synthesis of uniform carbonaceous particles via relative moderate conditions has undergone a resurgence3. These carbonaceous materials due to their unique features such as controllable particle size distribution, hydrophobicity, and tunable porosity4 have demonstrated significant prominence in extensive applications such as fuel pellets5, adsorption/separation6, catalysis7, water and air purification8, batteries9, supercapacitors10, fuel cells11, soil enrichment12, CO2 sequestration13, bioimaging, drug delivery and etc.1415. A large number of biomass materials have been used for hydrothermal carbonization (HTC) processes, including various categories of feedstocks like dedicated energy crops, agricultural crops, forestry residues, algae, biomass processing residues, municipal waste, and animal waste 1617. Among these materials, agricultural residues suffer from certain disadvantages such as Disposal problems, little intrinsic value, and low energy density1819. On the contrary, these residues can be considered as abundant and inexpensive sources of biomass20. Among these carbonaceous wastes, using Canola Stalks (CS) as a feedstock for fabricating value-added carbon structures would seem highly desirable and unique because no usage of CS as HTC feedstock has been reported until now21. Moreover, CS has shown significant characteristics in adsorption/desorption applications22. Xu et al investigated the behavior of chars as methyl violet absorbers produced from three different straws among which CS-derived char showed the greatest electrostatic interaction on its surface, which led to the highest adsorption capacity23. Tong et al reported the high removal capacity of Cu (II) from aqueous solutions by the biochars obtained from CS24.


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According to the literature, there are several conventional technologies for converting raw biomass to valueadded materials25. As an example of these technologies, hydrothermal carbonization (HTC) has several advantages, which make it a promising process for this purpose26. In HTC process, agricultural wastes (such as canola straw) are converted to valuable carbon structures in extended periods of time ranging from 30 min to eight hours27. Under mild processing temperatures (130 -300 C) and at autogenous pressures, with presence or absence of additional catalysts, water acts as a subcritical media that not only catalyzes the process but also avoids precursors drying costs28. At the aforementioned operational condition, generation of reactive intermediate species will promote the decomposition of biomass through four complex steps chronologically: dehydration, condensation, polymerization, and aromatization2930. In the end, The HTC process will reach an equilibrium state, which results in the production of hydrochar and its pertinent soluble and some amount of gaseous products30. Hydrochar as the main product of the process has the maximum amount of carbon content which its surface morphology and bulk properties may vary according to the designated operational conditions and simultaneous or post thermal treatments3132. In order to enhance the surface morphology and physiochemical properties of hydrochar, further physical or chemical activation is performed33.Recently, many methods of chemical activation have been reported in which the carbonaceous materials and chemical agents (KOH, NaOH, K2CO3, and ZnCl2) react at relatively high temperatures343536. According to literature, the chief activator of these chemical agents is KOH which many reports have demonstrated its high potential in promoting the carbon surface structure thus leading to a well synthesized Micropore hydrochar3738. Methylene Blue (MB) is a chemically and photolytically stable color which due to its high chromaticity is broadly used for drying cotton, wool, and silk39. Residual MB in textile wastewater is observable even in negligible concentrations and due to their complex aromatic structure, their natural biodegradation is slow or nearly impossible, therefore, if it finally infiltrates underground waters, then it will cause serious health problems such as carcinogenicity and mutagenic effects either on humans or aquatic creatures39. Consequently, these serious problems have brought various methods of methylene blue removal to the center of attention40. Among which adsorption is one of the most convenient and effective methods36. Amidst various conventional adsorbents, 3 ACS Paragon Plus Environment

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carbonaceous materials with the high specific surface area are very convenient and effective for this purpose due to their cost-effective, abundant resources and undeniable marvelous physiochemical properties41. The innovative aspects of the present work are to gather significant experimental and statistical information about the hydrothermal carbonization of canola straws by the Design of Experiments/Response Surface Methodology (DOE/RSM) 42. With such valuable information, we can predict the optimum operational condition for the synthesis of our desirable HTC carbon. Through a response surface experimental design, the emphasis of reaction temperature and retention time on hydrochar properties were investigated. Finally, the most appropriate hydrochar with the highest mass yield was selected for activation with KOH and then was used for MB removal. The dye removal process was evaluated under optimized contact time, initial MB concentrations, temperatures, and solution pH according to the literature363543. In order to investigate the impact of HTC conditions on synthesized hydrochars, they were characterized by various techniques, including elemental analysis, Field Emission Scanning Electron Microscope (FESEM), Brunauer–Emmett–Teller (BET) surface area analysis, Fourier transform infrared (FTIR) spectroscopy, UV–visible spectrophotometry and Energy-dispersive X-ray spectroscopy. Finally, the obtained results were described with statistical correlations and graphical methods. The main novel investigations of this article are listed below: 1) HTC of CS as widely grown agricultural wastes of the Mazandaran for biomass-derived hydrochar production for the very first time by DOE/RSM experimental design 2) Novel investigation on utilization of HTC-derived hydrochar as an adsorbent for MB removal from wastewater as an alternative for conventional ones 3) Novel comparison of HTC-Derived hydrochars, chemically activated hydrochars, and conventional adsorbents performances in dye removal process. Experimental section Feed materials The stalks of canola used within this experiment were sampled in February 2017 from cropland in a suburb of Sari, Iran. Stalks were air dried, transported in a container to the laboratory then were washed and dried at 120 °C for 24 hours. Dried stalks were ground and sieved to a powder of approximately 150 microns in diameter; ACS Paragon Plus Environment

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subsequently, the acquired powder was stored in a closed flask at room temperature for further applications. Deionized water and acetone (where ever was necessary) were used as a solvent to extract stacked materials from the reactor during the whole experiment. Synthesis of porous carbons and Activation HTC process The carbonization experiments were carried out using a two-factor D-optimal Response surface experimental design42. Carbonization temperature (factor A) with four respective levels (200,225,250, and 275 C) and reaction time (factor B) varying on three discrete levels (30-60-120 min) were selected as the main controlled factors30.Finally, 12 randomized alternative runs (shown in Table 1) were suggested by the design expert application version 10.0.4.0 and company Stat-Ease, Inc. 2016. All carbonization experiments were respectively performed, according to the determined randomized test orders by the mentioned application, in a hydrothermal 50mL non-stirred stainless-steel horseshoe-shaped pipe reactor with approximate pipe diameter and length of 8mm and 100 cm, respectively (shown in Figure 1). The reactor is heated by immersion in a neutral molten salt bath with an electrical heating element of 6 KW heating power. The molten salt bath temperature was measured and controlled by a Digital Temperature Indicator Controller and is stirred by a drill stirrer to avoid the possible heat accumulation. In order to measure the pressure variation inside the reactor, a high-pressure gauge was used. In the first place, 3g canola powder was completely mixed with 15 ml deionized water and loaded into the reactor. Immediately after passing argon gas through the reactor to evacuate existing oxygen and air, Reactor outlets were fully closed and sealed carefully to avoid any possible leak. The reactor was fully immersed into the molten salt bath that had reached the specified reaction temperature and maintained at that temperature for the desired reaction time set by the experimental design. As seen in Figure 2, at the temperature of 280 °C and Feed/Water ratio of 0.2, the reactor's final pressure was close to 132 bars. After each experiment, the reactor was cooled by being submerged in a cold-water bath, the cooling process which was not considered as reaction time. Reactor products were discharged by a vacuum pump and the obtained mixture of solid and liquid phases were separated by centrifugation, the liquid phase was stored in the refrigerator for further analysis without any treatment. The solid products were washed with distilled water and 5 ACS Paragon Plus Environment

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then dried for 12 hours at 120 °C. Dried hydrochars were powdered and stored in a closed flask for further applications and analysis. Each sample was appropriately designated by an H-x-y code where x stands as HTC temperature and y as the reaction time and H are the Abbreviations of hydrothermal carbonization. Activation process The hydrochars were chemically activated by conventional potassium hydroxide impregnation method HTCderived hydrochar and KOH were thoroughly mixed at a weight ratio of 1:2, dissolved in an excess amount of deionized water, refluxed overnight at 70 °C temperature and finally dried in an oven at 60 °C for 8 hours 4445. The obtained black powder (char) was located in a pyrolysis reactor (detailed description is available at 46) and heated to 700 C under argon gas flow and maintained at this temperature for two hours. After the reactor was cooled down to the lab's temperature, the activated samples were brought out from the reactor, washed several times with an excess amount of a 10 wt. % HCl until its pH became neutral47. In the end, the char was dried in an oven for eight hours at 60 C, powdered and stored in flasks for further applications and analysis. In contrast with the H-x-y codes designated for HTC carbons, the activated carbons were denoted as A-x-y where A refers to activated carbon while x and y represent the activation temperature and time respectively. Characterization of materials CHNS Analysis The analyses of the presented CHNS elements in the carbon materials structure were performed using (FlashEA 1112 series, Thermo Finnigan Company, USA) and oxygen contents were calculated by subtraction from the total amounts of CHNS percentage values48. FT-IR Spectroscopy The surface chemistry of chemical functional groups was studied by FTIR spectroscopy. FTIR spectra were recorded using the KBr disc method with BRUKER FT-IR spectrometer in the range 500-4000 cm-149. Surface morphology Analysis The surface characteristics and morphologies of the hydrochars were examined by the FESEM imaging (SIGMA VP-500, ZEISS, Germany). Furthermore, Energy-dispersive X-ray spectroscopy (EDS) on SEM (SEM


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equipped with an Oxford Energy Dispersive Spectrometer (EDS) with a germanium detector, Oxford Instrument, England) were used for the elemental analysis or chemical characterization of hydrochars1350. The surface area, pore volume and average pore diameter of the hydrochars were measured through Brunauer– Emmett–Teller (BET) surface area analysis by ASAP-2010 V2 Micrometrics -TriStarll system. The samples were degassed at 200 ˚C for 4h under 50 mTorr vacuum and their BET area, pore volume and average pore diameter of the samples were calculated from CO2 adsorption and desorption isotherms at 273 K 135152. Visible and Ultraviolet Spectroscopy (UV/Visible) In order to investigate dye removal efficiency, Visible and Ultraviolet Spectroscopy (UV/Visible equipped with Charge Coupled Device (CCD) detector) were used (SPECORD 250, Analytik jena, Germany)53. Total Organic Carbon (TOC) Analysis The aqueous phase of gasification products was analyzed by a TOC analyzer (TOC-L, Shimadzu, Japan) to determine its carbon content48. Dye removal experiment and measurements The dye removal capability of carbon materials was examined concerning the Methylene Blue removal percentage, and a comparative study was conducted between the dye removal efficiency of H-207-82 and A-700120. To the best of our knowledge and According to the literature, contact time is the most important variable which affects the dye removal process5455. Therefore, its impacts on the present dye removal experiment were studied on six discrete levels (10-20-30-40-50-60 min). For All other important factors such as initial concentration, solution pH, and adsorption media temperature, the constant optimized level was selected according to the literature and used throughout all experiments5455. Dye removal experiments were performed using 200 mL of MB solution with 40 ppm concentration in 250 mL Erlenmeyer flasks with the adsorbent dosage of 100 mg. A pH meter was used to measure the solution pH, and pH was kept constant at pH 7 by using 0.1 M HCl and 0.1 M NaOH solution. Each experiment flask was shaken isothermally at room temperature (25 ± 2 C) in a shaker with 120 round per minute agitation speed for desired contact time. Each test sample as a mixture of adsorbent and diluted MB solution was separated by centrifugation, The Methylene blue concentrations in the solutions were analyzed spectrophotometrically using UV-Vis 7 ACS Paragon Plus Environment

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spectrophotometer at 668 nm. After the process, the hydrochar was washed with distilled water, dried for 8 hours at 60 °C and stored in a closed flask for further studies. The remaining residual dye solutions were denoted as HM-x, and AM-x, where x stands for the contact time (10,20,30,40,50,60 min) and H, A, and M are the Abbreviations of hydrohars, Activated hydrochars, and methylene blue, respectively. The amount of dye removal per unit mass of each adsorbent (HM-x, and AM-x) was determined through this equation: 𝑄=

(𝐶0 −𝐶𝑡 )𝑉

Eq. (1)

𝑊

Where Q stands as equilibrium adsorption capacity (mg.g-1) and Co is the initial concentration (mg.L-1), and Ct is the remaining concentration of dye after desired contact time (mg.L-1). W (g) represents the weight of the adsorbent and V (L) is the volume of the solution 5536. Control parameters and DOE/RSM procedures Optimized experimental designs are greatly indebted to The DOE/RSM methodology as a replacement for the conventional time-consuming experiments with one variable at a time56. The RSM was used to optimize the hydrochar production through hydrothermal carbonization of CS57–60. The D-optimal criteria was advanced in selecting design points in a way that minimizes the variance associated with the estimates of the specified model coefficients thus allowing the identification of optimal processing conditions with fewer independent runs 42. According to the literature, temperature and residence time are the most important factors which affect the HTC process to achieve the expected characteristics of hydrochars for our desired applications (discussed later). This article only investigated the influence of two variables: temperature (T) and reaction time (t). These two variables and their levels are listed in (Table 1). Margins of 200 to 275 C, 30 min to 120 min were used for these two parameters, respectively. According to our optimization, twelve randomized experimental conditions were suggested by the design expert application version 10.0.4.0 and company Stat-Ease, Inc. 2016. In order to avoid hidden effects, the runs were made randomly. The analysis of variance (ANOVA) via DOE was used to identify important terms in the model followed by evaluation of regression model significance on the basis of Fischer (F) test values and probability (Pvalue). Higher values of F and Values of P less than 0.0500 indicates the significance of model while P-values


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greater than 0.1000 shows that the model terms are insignificant. If all the mentioned values plus the R 2 be in reasonable agreement with each other, then it can be concluded that the model is reliable42. The fit of the linear model or the quadratic model to the experimental results were evaluated and finally the most significant model equation according to P-values and R2 was chosen as the equation that defined different output functions: Mass Yield, Carbon Content, O, H, N, S contents, TOC. Multiple regression equations with only significant actual factors were obtained and model graphs were used to predict the response for given levels of each effective parameter as well as their interactions. Results and Discussion The experimental conditions of each run and their corresponding results (carbon, hydrogen, oxygen, sulfur, and nitrogen contents followed by the calculated High Heating Value (HHV), energy densification ratio, energy yield and O/C, H/C ratios for CS and its derived hydrochars) are described in Table 2. These results were obtained to measure the scale of carbonization and energy of hydrochars, respectively. Elemental Composition Appearance transformation of non-gaseous The impacts of temperature and reaction time on the appearance of hydrochar in comparison with raw CS and anthracite coal is demonstrated in Figure 3A. According to this figure, As the operating temperature increased, Visual observations showed the conversion of CS into light-brown, brown and finally to black powdered hydrochars with uniform composition and a nutlike smell 6162. This observation is in significant correlation with the number of double bonds and the conflation of oxygen compounds into the macromolecular network, which is a significant proof of the effective impact of HTC on physical and chemical properties of CS 3061. Besides, it appeared that reaction time has the same effect on the appearance of hydrochar. As reaction time increase from 30 to 120 min, the powder became darker and the uniformity of hydrochar was clearly observed30. Meanwhile, Figure 3B displays the appearance variation of the process filtrate (precursor of soluble) with reaction time and temperature. As time and temperature increased, the filtrates were much darker

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and This trend of

darkness is more sensible as temperature increase from 200 to 275 C compared to reaction time variation. This implied that the HTC reaction was affected more by temperature rather than reaction time1856. ACS Paragon Plus Environment

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Mass Yield The impact of temperature on hydrochar mass yield was investigated through DOE/RSM method and the results are shown in Figure 4A. According to the results, Trends of hydrochar mass yield versus temperature have proved it as an antagonistic factor in the hydrochar yield. As shown in Figure 4A hydrochar mass yield decreased steadily from 62% to 17.36% by elevating the temperature in HTC process from 200 to 275 C18. In contrast, mass yield percentage tended to decrease as reaction time extended but its model is not significant. ANOVA for response surface linear model with F-value of 101.91 and P-value of 0.0001 implies the significance of the linear equation also P-value for temperature is 0.0001 which is less than 0.0500 which indicates that this model term is significant. On the contrary retention time is not a significant term due to its high P-value that is 0.4655 and its effect is not very clear. In the literature, there have been reports of positive, negative, or null effects of retention time on HTC, depending on the used feedstock63. Final developed linear regression equation in terms of coded factors with “Pred R2” of 0.8815 that is in rational agreement with the “Adj R2” of 0.9017 for hydrochar yield versus factor A (temperature) is given: Eq. (2)

%𝑀𝑎𝑠𝑠 𝑌𝑖𝑒𝑙𝑑 = +37.14 − (20.02 ∗ 𝐴)

Predictions about the relative impacts of the factors by comparing their corresponding coefficient can only be achieved by The equation in terms of coded factors as for the equation with uncoded factors, coefficients are adjusted to fit the units of each factor and their intercept is not at the center of the design space, making them unsuitable in determining the relative impacts of factors. A coefficient with only single factor specifies the effect of a particular parameter, on the other hand, the coefficients with two factors specify the effect of the existing interaction between two parameters. Synergetic effects are represented by the positive sign while the negative sign marks the antagonistic effect42. As the reaction temperature increases the amount of obtained hydrochar is reduced and this antagonistic effect can be explained by the intensification of elimination and dehydration processes which is caused by the existing volatile matters being released into the liquid phase at higher temperatures of HTC process and after the KOH activation process that also leads to an increase in the carbon content

3064


. Also, formation of permanent gases

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and lighter organic compounds at the higher reaction temperature, not only reduces the hydrochar yield but also increases carbon’s porosity 3065. Carbon Content According to the results (Table 2), the carbon content in hydrochar highly depends on HTC temperature and the percentage of carbon originally present in the raw feedstock 48. Carbon content increased apparently with an increase in temperature and reaction time 30. For example, Carbon percentage increased from 40/94 in raw CS to 59.84 in H-275-120 which is a 46% increase only after HTC treatment which is in accordance with the results from S. horneri 56. The 3D surface diagram of carbon content versus time and temperature is shown in Figure 4B. The response surface quadratic model with F-value of 90.65 and P-value of 0.0001 proves the significance of the quadratic equation. Also P-values for terms A (temperature), B (time), AB and A2 are 0.0001, 0.0005, 0.0062 and 0.0181 respectively thus these terms can be considered significant. Final quadratic regression equation in terms of coded factors with “Pred R2” of 0.9811 for carbon content versus significant factors is given: %𝐶 = +51.56 + (4.69 ∗ 𝐴) + (1.41 ∗ 𝐵) + (1.22 ∗ 𝐴𝐵) + (1.35 ∗ 𝐴2 )

Eq. (3)

On the contrary, the only significant factor for carbon recovery rate with P-value of 0.0001 is temperature which had an antagonistic effect on CRR due to more decarboxylation of hydrochars at higher temperatures.63 The linear regression equation model for carbon recovery rate versus A (temperature) with “Pred R2” of 0.8732 is as follows: 𝐶𝑎𝑟𝑏𝑜𝑛 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑦 = +37.73 − (18.41 ∗ 𝐴)

Eq. (4)

Reduction in the CRR can be explained by the loss of carbons that are bound to the surface of the hydrochars as CO and CO2 through the splitting up of some biomass components, such as uronic acid at higher temperatures 63

. As the conversion of biomass to gaseous products becomes more favorable at higher reaction temperatures the

release of unstable and volatile carbon materials into liquid phase will decrease 30. O, H, N, S contents As expected, the elemental composition (Table 2) indicates that the oxygen and hydrogen contents reduced during HTC process by approximately 44.89% which has a positive effect on the combustion properties of hydrochars 64. as shown in Figure 4D (The 3D surface diagram of oxygen content vs time and temperature), the oxygen content decreased from 45/89 in H-200-30 to 35.48 in H-275-120 and the hydrogen content also decreased 11 ACS Paragon Plus Environment

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from 5.75 in H-200-60 to 3.19 in H-275-120 and all the same, H/C and O/C ratios diminished from 1.42 and 0.71 to 0.63 and 0.44, respectively. Final linear regression equation for oxygen content versus its corresponding significant coded factors with “Pred R2” of 0.9811, F-value of 59.21 and P-value of 0.0001 as a proof for the significance of the linear equation with terms A (temperature), B (time), AB with respective P-values of 0.0001, 0.0115 and 0.0228 is given: %𝑂 = +41.75 − (4.13 ∗ 𝐴) − (0.93 ∗ 𝐵) − (1.07 ∗ 𝐴𝐵)

Eq. (5)

The observed antagonistic effect of temperature and time on the oxygen content is attributed to the conversion of more volatile matters through both decarboxylation and dehydration reactions that occurred during HTC 66. The percentages of Nitrogen and Sulfur in CS are 0.8% and 0.53%, respectively.it is obvious that nitrogen content has decreased in hydrochars through degradation of proteins as the major source of Nitrogen because they are degraded above 150 C, also the loss of some surface functional groups containing N and S with volatile matters during the process, can explain this observation 3062. Also as shown in Table 2, As the carbonization temperature increased, The TOC level of liquid product decreased from 1355.21 (mg. L-1) for liquid phase H-275-30 to 1651.51 (mg.L-1) in liquid phase H-200-120. The response surface quadratic model for TOC level with F-value of 6994.35 and P-value of 0.0001 is significant and significant terms, A (temperature), B (time), A2 and B2 with respective P-values of 0.0001, 0.0001, 0.0003 and 0.0011 were considered in the final quadratic regression equation with “Pred R2” of 0.9994 as follows: 𝑇𝑂𝐶 (𝑚𝑔. 𝐿−1 ) = +1502.28 − (111.42 ∗ 𝐴) + (36.28 ∗ 𝐵) + (7.66 ∗ 𝐴2 ) − (6.84 ∗ 𝐵 2 )

Eq. (6)

This reduction in TOC can be explained by partial gasification and decomposition of hemicellulose and cellulose fragments into the gas phase as the carbonization temperature increase 67. Van krevelen diagram In order to visualize the carbonization degree of CS, Van Krevelen diagram was drawn (Figure 5). According to the literature and based on the results, it seems that the effect of dehydration and decarboxylation reactions was more significant during HTC process than demethanation reaction. Therefore, the former reactions can be considered as the essential reaction pathways in HTC of CS and the demethanation pathway can be considered negligible 62. As shown in Figure 5, by prolonging temperature and reaction time from 200 to 275 C and 30 min 12 ACS Paragon Plus Environment

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to 120 min, H/C and O/C ratios changed from 1.94 and 0.23 to 1.84 and 0.33, respectively. Furthermore, it can be observed that the H/C and O/C values follow an almost linear pattern which suggests that HTC process is not affected by simple decarboxylation or dehydration processes 63. In order to compare the properties of hydrochars with four typical coals such as anthracite, bituminous, subbituminous, and lignite, their H/C versus O/C atomic ratios were also plotted in van krevelen diagram. It is apparently observed that hydrochars are approaching the region of lignite. This observation is in adequate agreement with HHV factor of the hydrochars that were around 18/38 MJ.kg-1 that is comparable to the calorific value of lignite (16.3 MJ.kg-1)306263. Optimization Defining the optimal HTC condition in order to find the appropriate hydrochar for further applications through the experimental design can be exceedingly beneficial and even more helpful if the desired hydrochar is achieved at lowest possible reaction temperatures and reaction times resulting in a more cost-effective HTC process 66. On the other hand, chemical activation of the hydrochars leads to low mass yields, therefore, the maximum possible level of mass yield (53.38 %) was chosen for the hydrochars 68. Beside the mentioned parameters, carbon recovery rate and O/C level were planned to be at their highest possible level, (52.66) and (0.69) respectively, to investigate the impact of KOH activation process on the hydrochar with the highest amount of oxygen functional groups 6669. According to the expert design regression equations, as shown in Figure 6, the 3D surface diagram of desirability vs T and t suggests 0.84 desirabilities for point T=207 and t=82. So, H-207-82 was chosen as the optimal hydrochar and the activation process and further analysis were only performed on this sample 70. Surface Morphology FESEM results In order to examine the changes in the morphological structure and physical properties of CS, H-207-82, and A-700-120, their surface morphology was revealed by the FESEM analyses and results are shown in Figure 7. According to this figure, CS demonstrates a common cellular structure of lignocellulosic biomass with a rough surface 67. On the other hand, H-207-82 demonstrates lots of carbon particles and more pores on its rough surface which could be a reliable evidence of appropriate hydrolysis and carbonization of CS 62. ACS Paragon Plus Environment

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As seen, HTC process raptures raw CS lignocellulosic structure into smaller fragments and brings about the formation of H-207-82 with the observed heterogeneous structure56. As revealed in this figure, KOH activation of H-207-82 resulted in a major morphological transformation between the H-207-82 and A-700-120 including the formation of a well-developed surface with larger individual grains and formation of a more orderly pore structure. Development of mentioned porosities is presumably due to the decomposition of hemicellulose and cellulose by the KOH dehydration effect which breaks the existing C-O-C and C-C bonds in H-207-82(see section 3.4.3) 71. During the pyrolysis of H-207-82, KOH reduces to metallic sodium K, hydrogen gas, and potassium carbonate K2CO3 through the proposed redox reaction as follows: Eq. (7)

6𝐾𝑂𝐻 + 2𝐶 → 2𝐾 + 3𝐻2 + 2𝐾2 𝐶𝑂3

Additionally, the presence of Argon gas at 700 °C further degrades the produced K2CO3 into K, CO, and CO2 allowing more potassium to leach out which leads to the entrapment of more K molecules in pores thus creates pores with Different sizes and the observed shapes between the particles72. BET surface area results For activated carbons containing very narrow microporosity, characterization by N2 adsorption-desorption at 77 K is useless due to the existence of diffusional problems. On the contrary, the CO2 sorption performed at 273 K results in a larger kinetic energy of the CO2 molecules due to the higher adsorption temperature thus avoids the above mentioned diffusional problems52. In consequence, The CO2 adsorption-desorption isotherm and pore size distribution of H-207-82 and A-700-120 were measured and the results are shown in Figure 8. Accordingly, the morphological and structural parameters were also derived from the mentioned isotherms and they are tabulated in Table 3. According to The IUPAC classification, adsorption-desorption isotherm related to H-207-82 that lies at low relative pressures suggests the type I isotherm with the occurrence of a hysteresis loop that proves the presence of some mesoporosity in addition to the expected microporosity73. Brunauer-Emmett-Teller (BET) analysis further showed that H-207-82 has a low specific surface area of 2.6902 (m2.g-1) with the pore size distribution in the range of 15 to 25 nm as shown in Figure 8, the total pore volume of 0.03 (cm3.g-1) and the average pore diameter of 20.294 nm that confirms its mesoporous structure which is consistent with previous researches in biomass-derived hydrochars 265674. As a result, characteristics such as low specific surface area, and ACS Paragon Plus Environment

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low total pore volume limit the potential use of H-207-82 as adsorbents and make the thermal and chemical activation step necessary to improve the hydrochars structure

13

. Remarkably, The corresponding adsorption-

desorption isotherm of A-700-120 as a type IV with the pronounced H4-type hysteresis loop often indicates the presence of well-defined mesoporous and size-homogeneous 1D slit channels beside the narrow slit pores in the micropore region75. SBET, average pore diameter, and total pore volume for A-700-120 were found to be 474.8781 (m2. g-1), 1.3430 (nm), and 0.29 (cm3.g-1) respectively, with the pore size distribution in the range of 0.5 to 2.4 nm which indicates sufficient microporosity76. Further calculations reveal that A-700-120 has a micropore volume of 0.13 (cm3.g-1) that approximately consists 40% of its total pore volume. In contrast to H-207-82, A-700-120 has a higher surface area, higher total pore volume, and well-distributed mesoporous and microporous pores which could be beneficial for the enhancement of adsorption capacity and are comparable with those of other activated hydrochars 77. FT-IR results In order to investigate the surface chemistry of the biomass-derived hydrochar, FT-IR analyses were performed and the spectra of H-207-82 and A-700-120 are presented in Figures 9A and 9B, respectively. As shown in Figure 9A, peaks appeared at 3419, 2919, 1616, 1513, 1426, 1372, 1205, 1160, 1110, 1058 and the zone of 6101000 cm-1 correspond to O-H stretching of alcohol, C-H stretching of alkanes, C=O stretching of aliphatic ketone, C–H stretching of methyl group, C=C stretching of conjugated alkene, aromatic C-C stretching, O-H bending of carboxylic acids, C-O stretching of alcohol, C-O stretching of aliphatic ether, S=O stretching of sulfonate and =C-H bending of alkene 78. According to Islam et.al investigations, the strong peak observed at 1033 cm-1 in H207-82 corresponds to the C-O stretching of the remaining cellulose and hemicellulose in cell walls 7843. During HTC, abundant depletion of hemicelluloses and other water-soluble compounds from the CS leads to the dissolving of the mentioned materials in the reaction media. Thus, all of the observed functional groups on the surface of H-207-82 can be attributed to the remaining cellulose and lignin components in the H-207-82 structure43. After the KOH activation of H-207-82 (As observed in Figure 9B) significant disappearances or shifts in the zone of the functional groups were observed. Production of some new functional groups (as well as removal of 15 ACS Paragon Plus Environment

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the available functional groups) on the A-700-120 surface compared to H-207-82 can be attributed to the nucleophilic effect of KOH which acts as a reducing agent and decomposes residual hemicellulose, cellulose, and lignin 43. As it is observed, after chemical activation, the peaks at 3419, 2919 and 1616 cm-1 shifted to higher frequencies of 3426, 2932 and 1630 cm-1, respectively, whereas the peak at 1426 cm-1 slightly shifted to lower frequencies of 1403 cm-1. According to the literature, continuous dehydration reactions during the activation process can promote the reduction of the peak corresponding to O-H stretching of alcohol (3426 cm-1). Thus this phenomenon can improve the hydrophobicity of the activated carbon (A-700-120) by decreasing the existing hydroxyl and carboxyl contents in A-700-120 79. On the other hand, some new peaks at 1648 cm-1 and a few peaks in the zone of 610-1000 cm-1 (specifically peaks at 1006, 982, 832, 702) were appeared, which could be attributed to C=C stretching and =C-H bending of alkene, respectively. The peaks in the zone of 1030-1330 cm-1 (specifically peaks at 1033, 1058, 1110, 1160, 1205 and 1317 cm-1) were disappeared. As the activation process prolongs, more functional groups will decompose and probably convert to CO2 or CO (gas), which this demonstrates the certain occurrence of a decarboxylation reaction during the activation process 30. Dye Removal experiments As discussed earlier, contact time is the most important variable which affects the dye removal process

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.

Therefore, its impacts on the present dye removal process were studied on six discrete levels (10-20-30-40-50-60 min). The removal of MB was done by two types of CS hydrochar: activated (A-700-120) and non-activated (H207-82) materials. The illustrative results of these investigations are presented in Figure 10. As seen in this figure (Figure 10A), the utilization of H-207-82 as adsorbent lead to a significant color shift to green (30min) and then yellow (60 min) but no removal of MB was observed. In spite of this observation, the A-700-120 adsorbent was able to remove MB from the prepared solution perfectly (Figure 10B). The amount of dye removal for this adsorbent was determined through UV/Vis technique and equation 1, and the results are depicted in Figure 10C. According to this figure, the main part of MB was removed in the first 30 min of contact time with a high rate, and then the amount of dye removal increased slightly reaching 93.4 (mg. g-1) within 60 min. Since the activated material showed a great ability in dye removal compared to the nonACS Paragon Plus Environment

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activated one, it could be deduced that the surface properties of this material play a significant role in the explanation of this phenomenon. Therefore, detailed screening of surface morphology and chemistry of A-700-120 were performed through various techniques (e.g. EDS, FT-IR). Since the presence of metals in MB solution may lead to photocatalytic effects which can be a possible reason for the observed color shift, EDS analysis was performed to investigate the presence of metals in H-207-82 structure and its result is summarized in Figure 11. As depicted in this figure, no significant amount of metal was observed and thus metal presence could not be a suitable explanation for the observed color shifts 80. On the other hand, the main differences between A-700-120 and H-207-82 are probably referred to their surface chemistry (functional groups) and morphology (SBET), which may justify this color shift. As an evidence for the impact of surface chemistry on dye removal process, FT-IR analyses of H-207-82 and A-700-120 after the MB removal process were also performed and According to the results, no significant changes in peaks (strength and frequency) were observed after dye removal process, which could explain that the surface chemical properties of these materials have no or very little effect on MB removal efficiency. On the other hand, H-207-82 has a low surface area (SBET = 2.73 m2. g-1) which limits the adsorption of MB on its surface. Thus, MB cannot be adsorbed/absorbed (physically /chemically) to the surface of H-207-82, therefore, the color shift from blue to yellow still remains an unresolved problem. On the contrary, A-700-120 has a high surface area (SBET = 474.52 m2. g-1) which makes it a potentially susceptible material in adsorption processes. In the case of physisorption of MB on A-700-120, the BET results showed a dramatic decrease in surface area (SBET = 21.1820 m2. g-1) after dye removal process that confirms the physical adsorption of MB on the surface and in the pores of the adsorbent. Based on the above discussion, A-700-120 showed much better performance in MB removal compared to H-20782 as an adsorbent. This better performance is mainly originating from its astonishing porous surface morphology that makes it a good adsorbent for this purpose. Although the conducted efforts in this study could not justify the color shift of MB to green and yellow in the presence of H-207-82, the authors suggest that this phenomenon is probably due to the presence of some impurities in the texture of H-207-82.


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Comparison with previous works Finally, in a comparison with some carbon-based adsorbents, the Activated carbon derived from CS (this project) has the same or even better performance in dye removal. The performances of some adsorbents in MB removal are shown in Table 4. In order to achieve a better comparison between the adsorption capacities of the adsorbents, the adsorption percentage was also calculated and reported in this table. With reference to the results shown in Table 4, the reason for the better performance of the synthesized sample in this work can be related to both porosity and moderately its surface composition. Briefly, the simultaneous clogging of the smaller pores on the rugged surface of A-700-120 by the large molecules of MB can dramatically decrease the specific surface area of A-700-120. The decrease in the BET surface area of the A-700-120 significantly proves the pore filling procedure as one of the key factors in MB adsorption mechanism. Consequently, co-existence of other interactions that are responsible for the adsorption of MB on the surface of A-700-120 are also expected. Nevertheless, decomposition of the oxygen functional groups after the KOH activation clearly limited the number of oxygen groups on the surface of A-700-12081. As discussed earlier in this report, the results of the FT-IR spectra can perfectly prove that the impact of oxygen functional groups on the MB adsorption was negligible. Among the other adsorption mechanism (such as electrostatic interactions, cationic and ionic exchanges, hydrogen bonding formation, n–π electron donor-acceptor interactions) existence of strong π–π interactions between A-700-120 and MB are highly possible, due to the presence of nitrogen groups in the MB structure which act as strong electron acceptors81. With reference to the reports of Huff et al, the addition of oxygen functional groups to the aromatic ring structure of biochar can greatly decrease the adsorption of MB due to the weakened π-π interactions which were responsible for the MB adsorption82. In conclusion, the authors believe that better performance of A-700-120 compared to other samples in literature is due to KOH activation procedure that decomposed the considerable number of oxygen functional groups on the surface of A-700-120 and resulted in higher π-π interactions between the adsorbent and the adsorbate.


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Conclusion In this paper, a novel optimization on the HTC process through DOE/RSM method to produce a solid material (called Hydrochar) with specific properties were performed. The optimization was planned to yield a hydrochar with the maximum CRR, O/C level, and Mass yield. Following the HTC process, carbon content was enhanced in hydrochars and also the oxygen and hydrogen contents decreased. Van Krevelen diagram illustrated that the HTC process was successful to promote the coal rank of raw CS by removing low-grade energy chemicals. It also confirmed that the formations of hydrochar were mainly governed by dehydration and decarboxylation reactions. Also, the DOE/RSM results showed that temperature is the most important variable in HTC process and then H207-82 with the highest estimated CRR, O/C level, and Mass yield was selected for further studies. In the next step, the impact of the KOH activation process on the H-207-82 hydrochar was investigated. According to the results, the activation of hydrochar at 700 °C and 120 min led to a large transformation in surface chemistry and morphology. In contrast with H-207-82, the activated material (called A-700-120) was more porous (SBET= 474.65 m2. g-1), had a raptured texture and has no significant oxygen functional groups on its surface. Finally, the capacity of H-207-82 and A-700-120 in Methylene Blue removal were studied at various contact times. The results indicated that A-700-120 with the higher surface area, lower surface oxygen functional groups (compared to H-207-82) and adsorption capacity of 93.4 (mg. g-1) is much more suitable for MB removal. Besides, an unusual color shift occurred when H-207-82 was used for MB removal. Since EDS and FT-IR analyses were not able to justify this observation, we suggest that some inorganic impurities may have initiated this color shift. Therefore, the authors of this paper suggest a detailed examination to find the reason for this phenomenon in the future.


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Author contributions AT helped and guided us through the whole experiment, SB designed experiments, performed the operations and wrote the manuscript, MS collected and analyzed data, helped finish the experiments and helped write the manuscript, KK made figures, and helped perform the operations, KB helped analyze data and helped finish the experiments, MA performed the analysis tests.

Acknowledgements Firstly, the authors would like to express their sincere gratitude to Professor Mohammad Reza Ganjali for his immense knowledge as His guidance has helped us visualize our main purpose of this project. The authors would like to acknowledge “The Catalyst and Chemical Reactions” laboratory at the University of Tehran, and our fellow labmates that provided us the opportunity to finish the project. In the end, we are also grateful to Professor Parviz Norouzi for enlightening us the first glance of research.


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Nomenclature Abbreviations Analysis of Variance

ANOVA

Brunauer–Emmett–Teller

BET

Canola Stalk

CS

Carbon Recovery Rate

CRR

Design Of Experiment

DOE

Energy Densification Ratio

EDR

Energy Yield

EY

Energy-dispersive X-ray spectroscopy

EDS

Field Emission Scanning Electron Microscopy

FESEM

Fourier transform infrared

FTIR

High Heating Value

HHV

Hydrothermal Carbonization

HTC

Methylene Blue

MB

Response Surface Methodology

RSM

Total Organic Carbon

TOC

Ultraviolet

UV

Weight Percent

Wt. %

Symbols Fisher's test

F

Temperature

T

Time

t

Volume

V


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References (1)

Sevilla, M.; Fuertes, A. B. Carbon N. Y. 2009, 47 (9), 2281–2289.

(2)

Mohan, D.; Sarswat, A.; Ok, Y. S.; Pittman, C. U. Bioresour. Technol. 2014, 160, 191–202.

(3)

Inoue, S. Carbon N. Y. 2016, 104, 263.

(4)

Liu, J.; Wickramaratne, N. P.; Qiao, S. Z.; Jaroniec, M. Nat. Mater. 2015, 14 (8), 763–774.

(5)

Bartocci, P.; Bidini, G.; Saputo, P.; Fantozzi, F. Chem. Eng. Trans. 2016, 50, 217–222.

(6)

Nugent, P.; Belmabkhout, Y.; Burd, S. D.; Cairns, A. J.; Luebke, R.; Forrest, K.; Pham, T.; Ma, S.; Space, B.; Wojtas, L.; Eddaoudi, M.; Zaworotko, M. J. Nature 2013, 495 (7439), 80–84.

(7)

Abdullah, S. H. Y. S.; Hanapi, N. H. M.; Azid, A.; Umar, R.; Juahir, H.; Khatoon, H.; Endut, A. Renew. Sustain. Energy Rev. 2017, 70, 1040–1051.

(8)

De Volder, M. F. L.; Tawfick, S. H.; Baughman, R. H.; Hart, A. J. Science (80-. ). 2013, 339 (6119), 535– 539.

(9)

Moreno, N.; Caballero, A.; Hernán, L.; Morales, J. Carbon N. Y. 2014, 70, 241–248.

(10)

Xiao, P.-W.; Meng, Q.; Zhao, L.; Li, J.-J.; Wei, Z.; Han, B.-H. Mater. Des. 2017, 129, 164–172.

(11)

Zhang, C.; Kong, R.; Wang, X.; Xu, Y.; Wang, F.; Ren, W.; Wang, Y.; Su, F.; Jiang, J.-X. Carbon N. Y. 2017, 114, 608–618.

(12)

Stolarski, M. J.; Krzyżaniak, M.; Tworkowski, J.; Szczukowski, S.; Niksa, D. Energy 2016, 113, 748–761.

(13)

Hong, S.-M.; Jang, E.; Dysart, A. D.; Pol, V. G.; Lee, K. B. Sci. Rep. 2016, 6 (June), 34590.

(14)

Lu, Y.; Zhu, N.; Yin, F.; Yang, T.; Wu, P.; Dang, Z.; Liu, M.; Wei, X. Biosens. Bioelectron. 2017.

(15)

Liu, C.; Zhang, P.; Zhai, X.; Tian, F.; Li, W.; Yang, J.; Liu, Y.; Wang, H.; Wang, W.; Liu, W. Biomaterials ACS Paragon Plus Environment

22

Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 44

2012, 33 (13), 3604–3613. (16)

Lin, Y.; Ma, X.; Peng, X.; Yu, Z. Bioresour. Technol. 2017, 243, 539–547.

(17)

Nizamuddin, S.; Baloch, H. A.; Griffin, G. J.; Mubarak, N. M.; Bhutto, A. W.; Abro, R.; Mazari, S. A.; Ali, B. S. Renew. Sustain. Energy Rev. 2017, 73 (December 2015), 1289–1299.

(18)

Mäkelä, M.; Benavente, V.; Fullana, A. Appl. Energy 2015, 155, 576–584.

(19)

Adapa, P.; Tabil, L.; Schoenau, G. Biomass and Bioenergy 2011, 35 (1), 549–561.

(20)

Rafatullah, M.; Sulaiman, O.; Hashim, R.; Ahmad, A. J. Hazard. Mater. 2010, 177 (1–3), 70–80.

(21)

Berge, N. D.; Ro, K. S.; Mao, J.; Flora, J. R. V.; Chappell, M. A.; Bae, S. Environ. Sci. Technol. 2011, 45 (13), 5696–5703.

(22)

Ashori, A.; Hamzeh, Y.; Azadeh, E.; Izadyar, S.; Layeghi, M.; Mirfatahi Niaraki, M. S. J. Wood Chem. Technol. 2012, 32 (4), 328–341.

(23)

Xu, R.; Xiao, S.; Yuan, J.; Zhao, A. Bioresour. Technol. 2011, 102 (22), 10293–10298.

(24)

Tong, X.; Xu, R. J. Environ. Sci. 2013, 25 (4), 652–658.

(25)

Gallezot, P. Chem. Soc. Rev. 2012, 41 (4), 1538–1558.

(26)

Hu, B. B.; Wang, K.; Wu, L.; Yu, S.; Antonietti, M.; Titirici, M. 2010, 813–828.

(27)

Titirici, M.-M.; Antonietti, M. Chem. Soc. Rev. 2010, 39 (1), 103–116.

(28)

Titirici, M.-M.; White, R. J.; Falco, C.; Sevilla, M. Energy Environ. Sci. 2012, 5 (5), 6796.

(29)

Fangming Jin. Application of Hydrothermal Reactions to Biomass Conversion; Springer Berlin Heidelberg, 2014.

(30)

Lin, Y.; Ma, X.; Peng, X.; Yu, Z. Energy and Fuels 2016, 30 (9), 7746–7754. ACS Paragon Plus Environment

23

Page 25 of 44

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

(31)

Mau, V.; Quance, J.; Posmanik, R.; Gross, A. Bioresour. Technol. 2016, 219, 632–642.

(32)

Ghanim, B. M.; Kwapinski, W.; Leahy, J. J. Bioresour. Technol. 2017, 238, 78–85.

(33)

Kim, D.-W.; Kil, H.-S.; Nakabayashi, K.; Yoon, S.-H.; Miyawaki, J. Carbon N. Y. 2017, 114, 98–105.

(34)

Jain, A.; Aravindan, V.; Jayaraman, S.; Kumar, P. S.; Balasubramanian, R.; Ramakrishna, S.; Madhavi, S.; Srinivasan, M. P. Sci. Rep. 2013, 3, 3002.

(35)

Yin, J.; Pei, M.; He, Y.; Du, Y.; Guo, W.; Wang, L. Rsc Adv. 2015, 5 (109), 89839–89847.

(36)

Alatalo, S.-M.; Mäkilä, E.; Repo, E.; Heinonen, M.; Salonen, J.; Kukk, E.; Sillanpää, M.; Titirici, M.-M. Green Chem. 2015, 1137–1146.

(37)

Huanlei Wang Alireza Kohandehghan, Zhi Li, Kai Cui, Xuehai Tan, Tyler James Stephenson, Cecil K. King’ondu, Chris M. B. Holt, Brian C. Olsen, Jin Kwon Tak, Don Harfield, Anthony O. Anyia, and David Mitlin, Z. X. Acsnano 2013, No. 6, 5131–5141.

(38)

Zhou, M.; Pu, F.; Wang, Z.; Guan, S. Carbon N. Y. 2014, 68, 185–194.

(39)

Saleh, T. A.; Rachman, I. B.; Ali, S. A. Sci. Rep. 2017, 7 (1), 4573.

(40)

Pang, J.; Fu, F.; Ding, Z.; Lu, J.; Li, N.; Tang, B. J. Taiwan Inst. Chem. Eng. 2017, 77, 168–176.

(41)

Sari, A. A.; Amriani, F.; Muryanto, M.; Triwulandari, E.; Sudiyani, Y.; Barlianti, V.; Lotulung, P. D. N.; Hadibarata, T. J. Taiwan Inst. Chem. Eng. 2017, 77, 236–243.

(42)

Montgomery, D. C. Design and Analysis of Experiments Eighth Edition; Wiley, cop., 2012; Vol. 2.

(43)

Islam, M. A.; Tan, I. A. W.; Benhouria, A.; Asif, M.; Hameed, B. H. Chem. Eng. J. 2015, 270, 187–195.

(44)

Islam, M. A.; Sabar, S.; Benhouria, A.; Khanday, W. A.; Asif, M.; Hameed, B. H. J. Taiwan Inst. Chem. Eng. 2017, 74, 96–104.

(45)

Sevilla, M.; Fuertes, A. B. Energy Environ. Sci. 2011, 4 (5), 1765–1771. ACS Paragon Plus Environment

24

Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 44

(46)

Norouzi, O.; Jafarian, S.; Safari, F.; Tavasoli, A.; Nejati, B. Bioresour. Technol. 2016, 219, 643–651.

(47)

Guangzhi, Y.; Jinyu, Y.; Yuhua, Y.; Zhihong, T.; DengGuang, Y.; Junhe, Y. RSC Adv. 2017, 7 (7), 4152– 4160.

(48)

Reza, M. T.; Andert, J.; Wirth, B.; Busch, D.; Pielert, J.; Lynam, J. G.; Mumme, J. Appl. Bioenergy 2014, 1 (1), 11–29.

(49)

Zhang, X.; Zhang, L.; Li, A. J. Environ. Manage. 2017, 201, 52–62.

(50)

Afolabi, O. O. D.; Sohail, M.; Thomas, C. L. P. Energy 2017, 134, 74–89.

(51)

Song, T.; Liao, J. M.; Xiao, J.; Shen, L. H. Xinxing Tan Cailiao/New Carbon Mater. 2015, 30 (2), 156– 166.

(52)

Lozano-Castell, D.; Cazorla-Amors, D.; Linares-Solano, A. Carbon N. Y. 2004, 42 (7), 1231–1236.

(53)

Han, S.; Liu, K.; Hu, L.; Teng, F.; Yu, P.; Zhu, Y. Sci. Rep. 2017, 7 (January), 43599.

(54)

Islam, M. A.; Benhouria, A.; Asif, M.; Hameed, B. H. J. Taiwan Inst. Chem. Eng. 2015, 52, 57–64.

(55)

Liu, J.; Li, E.; You, X.; Hu, C.; Huang, Q. Sci. Rep. 2016, No. June, 38450.

(56)

Xu, Q.; Qian, Q.; Quek, A.; Ai, N.; Zeng, G.; Wang, J. 2013.

(57)

Ba-Abbad, M. M.; Kadhum, A. A. H.; Mohamad, A. B.; Takriff, M. S.; Sopian, K. J. Ind. Eng. Chem. 2013, 19 (1), 99–105.

(58)

Shafeeyan, M. S.; Wan Daud, W. M. A.; Houshmand, A.; Arami-Niya, A. Fuel 2012, 94, 465–472.

(59)

Wu, J.; Zhang, H.; Oturan, N.; Wang, Y.; Chen, L.; Oturan, M. A. Chemosphere 2012, 87 (6), 614–620.

(60)

Kuram, E.; Ozcelik, B.; Bayramoglu, M.; Demirbas, E.; Simsek, B. T. J. Clean. Prod. 2013, 42, 159–166.

(61)

Poerschmann, J.; Weiner, B.; Woszidlo, S.; Koehler, R.; Kopinke, F. D. Chemosphere 2015, 119, 682– ACS Paragon Plus Environment

25

Page 27 of 44

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

689. (62)

He, C.; Giannis, A.; Wang, J. Appl. Energy 2013, 111, 257–266.

(63)

Sabio, E.; Román, S.; Ledesma, B. Waste Manag. 2016, 47, 122–132.

(64)

Liu, Z.; Quek, A.; Hoekman, S. K.; Balasubramanian, R. Fuel 2013, 103, 943–949.

(65)

Hao, W.; Björkman, E.; Lilliestråle, M.; Hedin, N. Appl. Energy 2013, 112, 526–532.

(66)

Nizamuddin, S.; Mubarak, N. M.; Tiripathi, M.; Jayakumar, N. S.; Sahu, J. N.; Ganesan, P. Fuel 2016, 163, 88–97.

(67)

Gao, P.; Zhou, Y.; Meng, F.; Zhang, Y.; Liu, Z.; Zhang, W.; Xue, G. Energy 2016, 97, 238–245.

(68)

Sermyagina, E.; Saari, J.; Kaikko, J.; Vakkilainen, E. J. Anal. Appl. Pyrolysis 2015, 113, 551–556.

(69)

Liu, T.; Li, Y.; Peng, N.; Lang, Q.; Xia, Y.; Gai, C.; Zheng, Q.; Liu, Z. J. Environ. Manage. 2017, 197, 151–158.

(70)

Chabbi, A.; Yallese, M. A.; Meddour, I.; Nouioua, M.; Mabrouki, T.; Girardin, F. Measurement 2017, 95, 99–115.

(71)

Islam, M. A.; Ahmed, M. J.; Khanday, W. A.; Asif, M.; Hameed, B. H. Ecotoxicol. Environ. Saf. 2017, 138 (August 2016), 279–285.

(72)

Zequine, C.; Ranaweera, C. K.; Wang, Z.; Singh, S.; Tripathi, P.; Srivastava, O. N.; Gupta, B. K.; Ramasamy, K.; Kahol, P. K.; Dvornic, P. R.; Gupta, R. K. Sci. Rep. 2016, 6 (August), 31704.

(73)

Qin, T.; Song, M.; Jiang, K.; Zhou, J.; Zhuang, W.; Chen, Y.; Liu, D.; Chen, X.; Ying, H.; Wu, J. RSC Adv. 2017, 7 (59), 37112–37121.

(74)

Wei, L.; Sevilla, M.; Fuertes, A. B.; Mokaya, R.; Yushin, G. Adv. Energy Mater. 2011, 1 (3), 356–361.

(75)

Liu, J.; Lei, J.; He, J.; Deng, L.; Wang, L.; Fan, K.; Rong, L. Sci. Rep. 2015, 5 (1), 11327. ACS Paragon Plus Environment

26

Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 28 of 44

(76)

X.L. Zhang, L.P. Cheng, X.P. Wu, Y.Z. Tang, Y. C. W. J. Environ. Sci. 2015, 33, 97–105.

(77)

Gu, X.; Wang, Y.; Lai, C.; Qiu, J.; Li, S.; Hou, Y.; Martens, W.; Mahmood, N.; Zhang, S. Nano Res. 2014, 8 (1), 129–139.

(78)

Xu, R. kou; Xiao, S. cheng; Yuan, J. hua; Zhao, A. zhen. Bioresour. Technol. 2011, 102 (22), 10293– 10298.

(79)

Zhao, P.; Shen, Y.; Ge, S.; Chen, Z.; Yoshikawa, K. Appl. Energy 2014, 131, 345–367.

(80)

Wang, W.; Feng, J.; Ye, Y.; Lyu, F.; Liu, Y.; Guo, J.; Yin, Y. Nano Lett. 2017, 17 (2), 755–761.

(81)

Tran, H. N.; Wang, Y. F.; You, S. J.; Chao, H. P. J. Environ. Manage. 2017, 188, 322–336.

(82)

D.Huff, Matthew; W.Lee, J. J. Environ. Manage. 2016, 165, 17–21.

(83)

Tan, I. A. W.; Ahmad, A. L.; Hameed, B. H. Desalination 2008, 225 (1), 13–28.

(84)

Hameed, B. H.; Ahmad, A. L.; Latiff, K. N. A. Dye. Pigment. 2007, 75 (1), 143–149.

(85)

Marrakchi, F.; Ahmed, M. J.; Khanday, W. A.; Asif, M.; Hameed, B. H. Int. J. Biol. Macromol. 2017, 98, 233–239.

(86)

Ahmed, M. J.; Theydan, S. K. Powder Technol. 2012, 229, 237–245.

(87)

Altıntıg, E.; Altundag, H.; Tuzen, M.; Sarı, A. Chem. Eng. Res. Des. 2017, 122, 151–163.


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Table Captions Table 1. Control Factors and Their Levels Used in This Experiment Table 2. Ultimate Analysis of CS and Its Derived Hydrochars Table 3. Textural properties of H-207-82 and A-700-120 Table 4. Dye Adsorption capacity of various adsorbents Figure Captions Figure 1. Schematic of Reactor system. A) Molten salt bath, B) stainless-steel pipe reactor, C) electrical heater, D) High-pressure valve, E) Low-pressure valve, F) Low-pressure gauge, G) High-pressure gauge, H) Mixer, I) ktype thermocouple, J) Water bath, K) Temperature controller, L) Flowmeter, and M) Argon gas cylinder Figure 2. Temporal variation of the pressure inside the reactor. Figure 3. Appearance of (A) raw CS and hydrochars, (B) process filtrate obtained at different HTC conditions Figure 4. The 3D surface diagram of (A) Mass yield, (B) Carbon content, (C) CRR, and (D) Oxygen vs temperature vs time. Figure 5. Van Krevelen diagram of raw CS and hydrochar. Figure 6. Operation Desirability vs temperature vs time Figure 7. FESEM image of CS, H-207-82, and A-700-120 Figure 8. CO2 sorption isotherms and the related pore size distribution (inset) of H-207-82 and A-700-120 Figure 9. FT-IR spectrum of (A) H-207-82, and (B) A-700-120 Figure 10. Impact of (A) H-207-82, (B) A-700-120 on MB removal at various contact times and (C) MB adsorption capacity of A-700-120 versus contact time Figure 11. EDS spectrum of H-207-82 ACS Paragon Plus Environment

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Table 1

Sample

Row

Temperature (°C)

Reaction Tim (min)

5

1

200

30

4

2

225

30

7

3

250

30

10

4

275

30

6

5

200

60

9

6

225

60

8

7

250

60

11

8

275

60

3

9

200

120

2

10

225

120

1

11

250

120

12

12

275

120


29

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Energy & Fuels

Table 2

Elemental Analysis (%) Samples

Mass Yield (%)

CRR (%)

C

H

N

S

O

H/C

O/C

CS

N.Ca

N.C

40.94

5.52

0.80

0.53

52.21

1.60

0.95

H-200-30

54.33

63.87

48.13

5.74

0.24

0

45.89

1.42

H-225-30

42.66

43.35

48.91

5.37

1.50

0.74

43.48

H-250-30

35.00

36.93

51.61

5.09

1.19

0.80

H-275-30

19.33

20.73

55.36

3.95

0.88

H-200-60

62.00

54.35

48.53

5.75

H-225-60

45.66

46.25

49.16

H-250-60

27.66

29.74

H-275-60

17.66

H-200-120

HHV

TOC

EDR

EY %

14.04

N.C

N.C

N.Mb

0.71

17.65

1.25

68.28

1577.44

1.30

0.66

17.78

1.26

54.03

1497.55

41.31

1.17

0.60

18.62

1.32

46.41

1423.47

0

39.81

0.85

0.53

18.41

1.31

25.34

1355.20

0.38

0.10

45.24

1.41

0.69

17.90

1.27

79.02

1607.70

5.20

0.91

0.42

44.31

1.26

0.67

17.48

1.24

56.86

1527.81

52.85

4.92

0.65

0.55

41.03

1.10

0.58

18.82

1.34

37.08

1453.74

18.78

56.20

3.75

0.97

1.10

37.98

0.79

0.50

18.78

1.33

23.62

1385.47

57.00

49.13

48.45

5.53

0.59

0.28

45.15

1.36

0.69

17.58

1.25

71.38

1651.50

H-225-120

46.00

47.92

50.48

5.17

0.23

0

44.12

1.22

0.65

17.88

1.27

58.58

1571.61

H-250-120

17.33

19.33

56.31

4.77

0.40

0.10

38.42

1.00

0.51

20.11

1.43

24.82

1497.53

H-275-120

21.00

22.31

59.84

3.19

0.75

0.74

35.48

0.63

0.44

19.54

1.39

29.22

1429.27

a

(Mj.kg−1)

(mg.L-1)

Not Calculated, b Not Measured


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Table 3

Sample

a

SBET (m2.g-1)

Total Pore Volume

Micropore Volumea

(cm3.g-1)

(cm3.g -1)

Average Pore Diameter (nm)

H-207-82

2.69

0.03



20.29

A-700-120

474.87

0.29

0.13

1.34

Calculated by non local density functional theory (NLDFT) model


31

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Energy & Fuels

Table 4

Adsorbent

pH

Dosage

Initial concentration

Adsorption capacity (mg.g-1)

Adsorption (%)

Ref.

Oil palm shellbased AC

6.5

0.1 mg/100 mL

50–500 mg.L-1

243.90

60.97

Tan et al. (2008)83



0.1 mg/100 mL

100–500 mg.L-1

294.14

58.82

11

1 g/L

25–400 mg.L-1

121.45

30.36

Marrakchi et al. (2017)85

255.30

28.36

Theydan and Ahmed (2012)86

Rattan sawdustbased AC Chitosan flakesbased AC

N.A

Hameed et al. (2007)84

Ferric AC (FAC)

7

0.5 g/L

acorn shell-based AC

4

0.05 g/100 mL

50–250 mg.L-1

303

78.09

Altıntıg et al. (2017)87

Fe loaded acorn shellbased AC

4

0.05 g/100 mL

50–250 mg.L-1

357.10

92.03

Altıntıg et al. (2017)87

A-700-120

7

0.1 g/250 mL

100 mg.L-1

93.40

93.40

This Study

50–450

mg.L-1

 Not Announced


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33

Figure 1

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Figure 2


34

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35

Figure 3

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Figure 4


36

Energy & Fuels

Figure 5

1/8 H-225-30

1/6

H-200-60

H-200-30 Raw Canola

1/4

H-250-60

1/2

H/C

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Sub-Bituminous

1

H-200-120

Lignite H-250-120

H-225-60 H-250-30

0/8 0/6

Decarboxylation

H-275-30

Bituminous H-275-120

0/4

H-225-120

H-275-60

Anthracite

0/2

Dehydration Demethanation

0 0

0/2

0/4

0/6 O/C

0/8


1

1/2

37

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Figure 6


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Figure 7

Canola Stalk

H-207-82


A-700-120

39

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Figure 8


40

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41

Figure 9

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Figure 10


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43

Figure 11

and Microporous Canola Stalk-Derived Hydrothermal Carbon via

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