Accepted Manuscript

Title: Endotoxin removal from aqueous solutions withdimethylamine-functionalized graphene oxide: Modelingstudy and optimization of adsorption parameters

Authors: Fahim Amini Tapouk, Ramin Nabizadeh, SiminNasseri, Alireza Mesdaghinia, Hassan Khorsandi, AmirHossein Mahvi, Elham Gholibegloo, MahmoodAlimohammadi, Mehdi Khoobi

PII: S0304-3894(19)30029-9DOI: https://doi.org/10.1016/j.jhazmat.2019.01.028Reference: HAZMAT 20183

To appear in: Journal of Hazardous Materials

Received date: 9 September 2018Revised date: 10 January 2019Accepted date: 11 January 2019

Please cite this article as: Amini Tapouk F, Nabizadeh R, Nasseri S, Mesdaghinia A,Khorsandi H, Mahvi AH, Gholibegloo E, Alimohammadi M, Khoobi M, Endotoxinremoval from aqueous solutions with dimethylamine-functionalized graphene oxide:Modeling study and optimization of adsorption parameters, Journal of HazardousMaterials (2019), https://doi.org/10.1016/j.jhazmat.2019.01.028

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1

Endotoxin removal from aqueous solutions with dimethylamine-functionalized

graphene oxide: Modeling study and optimization of adsorption parameters

Fahim Amini Tapouk a, Ramin Nabizadeh b,e , Simin Nasseri b,d, Alireza Mesdaghinia b,d, Hassan

Khorsandi f, Amir Hossein Mahvi d, Elham Gholibegloo h, Mahmood Alimohammadi a,b,c,d,*,

Mehdi Khoobi g,h,*

a Department of Environmental Health Engineering, School of Public Health, International Campus, Tehran University of Medical Sciences (IC-

TUMS), Tehran, Iran b Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran c Health Equity Research Center (HERC), Tehran University of Medical Sciences, Tehran, Iran d Center for Water Quality Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran

e Center for Air Pollution Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran f Department of Environmental Health, Urmia University of Medical Sciences, Urmia, Iran g Pharmaceutical Sciences Research Center, The Institute of Pharmaceutical Sciences, Tehran University of Medical Sciences, Tehran 1417614411,

Iran h Department of Pharmaceutical Biomaterials and Medicinal Biomaterials Research Center, Faculty of Pharmacy, Tehran University of Medical

Sciences, Tehran, Iran

* Corresponding author: m_alimohammadi@tums.ac.ir ; m-khoobi@tums.ac.ir

Graphical abstract

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Highlights:

Removal of endotoxins, as a pyrogenic contaminant, from water is very important.

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A novel Graphene oxide (GO)-based adsorbent decorated with dimethylamine (DMA) was

synthesized.

The GO-ECH-DMA sorbents have great influence on endotoxin removal efficiency (> 98%).

The endotoxin was adsorbed with a maximum Langmuir adsorption capacity of 121.47 EUmL-1.

Abstract

Novel graphene oxide (GO)-based adsorbent embedded with epichlorohydrin (ECH) as a coupling agent

and dimethylamine (DMA) as a ligand (GO-ECH-DMA) were prepared and employed for endotoxin

removal from aqueous solutions. The physicochemical properties of nanocomposite were fully

characterized. The model attributed to batch adsorption process was optimized employing response surface

methodology (RSM) via various parameters such as pH, GO-ECH-DMA dosage, and contact time and

endotoxin concentration. The p-value with low probability (<0.00001), determination coefficient (𝑅2 =

0.99) and the non-significant lack of fit (p>0.05) showed a quadratic model with a good fit with experimental

terms. The synergistic effects of the linear term of contact time and GO-ECH-DMA dosage on endotoxin

removal were significant. The optimum condition for endotoxin removal was obtained at pH of 5.52, GO -

ECH-DMA dosage of 21 mgL-1, contact time of 56 min and endotoxin concentration of 51.3 endotoxin units

per milliliter (EUmL-1). The equilibrium was the better explained by Langmuir isotherm with the maximum

monolayer adsorption capacity of 121.47 EUmg-1, while the kinetics of the endotoxin adsorption process was

followed by the pseudo-second-order model. The adsorbent could be recycled with NaOH. The possible mechanisms

of endotoxin adsorption were proposed by hydrogen-bonding, π-π stacking, and electrostatic interaction.

Keywords: Adsorption, Endotoxin, Dimethylamine, Graphene oxide, Modeling, Response -surface

methodology

1. Introduction

Endotoxins, also called lipopolysaccharides (LPSs), are the major component of outer cell wall membranes of Gram-

negative bacteria and some cyanobacteria [1, 2]. Endotoxins are composed of three main parts including the lipid A

as hydrophobic segment, the central part as polysaccharide chains with hydrophilic properties and specific O-antigen

(Fig. 1). The toxicity of endotoxins is related to lipid A, which stimulates macrophage cells and eventually produce

cytokines that have adverse biological effects on human health and mammals [1, 3-6]; while at high concentration,

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pathophysiological symptoms such as diarrhea, fever, hypotension shock and eventually death may be observed [7].

LPSs are released into the environment not only as result of cell multiplication/division but also through cell death [8]

and exposure to it occurs through sources such as drinking water supplies, aspiration of particulate matters in air [9,

10], biological drug products (such as DNA vaccines and proteins) [11], fluids before injection [12], and water used

for kidney hemodialysis [13]. Some medical evidence suggests that the outbreak of fever with unclear medical

symptoms may be due to the presence of endotoxin in water, but there is inadequate information on the risk of

gastrointestinal disease from endotoxin in drinking water [14]. Hindman et al., (1975) reported that the presence of

endotoxin in drinking water coincided with an epidemic of pyrogenic reactions among kidney dialysis patients [15].

However, the World Health Organization is also concerned about the lack of a universal guideline for endotoxin

concentration levels in drinking water [16].

Fig. 1. Modified chemical structure of endotoxin (LPSs) of E. coli O111: B4 [17].

Water sources have different levels of endotoxin, including raw water, which ranges from 18 to 356 EUmL-1 [6];

groundwater, 1 to 200 EUmL-1 [18]; tap water, 60 to 205 EUmL-1 [19] and drinking water from 4 to 119 EUmL-1 [20].

Previous studies on 10 water treatment plants in the U.S showed that the highest amount of endotoxin (500 ngmL -1)

was associated with plant that had only chlorination treatment unit [21]. Zhang Can et al., (2013) reported that drinking

water treatment plant in Beijing, China could only reduce 40% of the endotoxin from raw water [14]. Previous research

studies have shown that conventional oxidation processes for water disinfection using ClO2, Cl2 and O3 were

ineffective for endotoxin destruction [1, 6]. Other conventional oxidation processes for water disinfection not only

decrease but also increase endotoxin levels due to lysis and oxidation of bacterial cell surface [2] and depyrogen

techniques such as dry heat and chemical process are not recommended owing to changes in the chemical nature of

the endotoxin molecules as well as the formation of new by-products [22]. The limitations of the mentioned methods

on the one hand, and the high resistance of endotoxin molecules to pH and temperature (dry sterilization at 250°C for

30 min) [23] on the other hand, led to its removal from biological products and water supplies, which became a major

challenge. Therefore, a high efficiency, low-cost and no risk process for endotoxin removal from water solutions are

needed.

Various methods have been suggested for endotoxin removal from liquids including, ultrafiltration, two-phase

extractions, ion-exchange resins, affinity chromatography, and LPSs affinity interactions; however, these techniques

usually suffer from weak selectivity, high cost and low scale application [8, 24, 25]. Among all the employed methods

for endotoxin removal, adsorption process has attracted more attention owing to its ease of operation [26],

environmental friendliness [27], low cost of operation, high efficacy, easy accessibility and lack of by-products

that possess health effects [12, 28-30].

In comparison with different types of adsorbents including cross-linked cellulose [31], carbon nanotubes [32], N, N-

dimethylaminopropyl acrylamide [5], conducting polymers [33] and activated carbon [34] graphene oxide (GO) was

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considered one of the most interesting adsorbents due to the unique structures, geometry properties, large surface area

(2630 m2g-1) and high fracture strength [35]. These unique physical and chemical characteristics of GO increased its

application as an appropriate adsorbent in various fields of water science such as desalination [36], aromatic pollutants

removal [37, 38] and energy research [39]. Furthermore, due to the available and tunable functional groups of GO as

well as having a hydrophobic center [23], it is able to provide favorable conditions for further functionalization as

reference substrate [40, 41].

Therefore, in this work GO-based adsorbent was synthesized and modified chemically with dimethylamine (DMA)

via epichlorohydrin (ECH) as a spacer to produce a new GO-ECH-DMA nanocomposite for endotoxin adsorption

from aqueous solution (Fig. 2). It has been previously reported that PMMA-5 adsorbent with DMA as a cationic ligand

that contains a hydroxyl group at the β-site on the long alkyl chain can be used for endotoxin adsorption from liquids

[7]. On the premise of this point of view, the GO-ECH-DMA matrix was designed based on the presence of a more

positive charge generated by the amine groups on its surface as well as the negative phosphate groups in the endotoxin

molecules [25]. After complete characterization of the physicochemical properties of the designed adsorbent with

various analytical techniques, the optimization of endotoxin removal with GO-ECH-DMA in the batch system was

performed employing different independent variables including pH, endotoxin concentration, GO-ECH-DMA dosage

and adsorption time to predict the response terms. Optimization of response with the minimum run of experiments,

estimation of the impact of the input variable on response variable, determination of maximum adsorption efficiency,

as well as formulation of regression models were carried out using response surface methodology (RSM) based on

central composite designs (CCD) [42]. CCD-RSM reveals great statistical tools for estimation of the impact of input

control factors on response terms, modeling of the regression equation, as well as the determination of high yield

adsorption to achieve the lowest possible cost, which is not inaccessible in traditional one-factor design [43, 44].

Moreover, the linear forms of adsorption isotherms, kinetics and the mechanism of endotoxin adsorption were

discussed.

2. Materials and Methods

2.1. Materials

QCL-1000™ Endpoint Chromogenic Limulus Amebocyte Lysate (LAL) assay kit for endotoxin detection (US

License No.1775), lipopolysaccharide from Escherichia coli 011: B4 (L2610-MG, 10 EUmL-1 = 1 ngmL-1 ), ECH,

LAL reagent water (LRW) were purchased from Lonza, Inc. Chemical materials such as DMA, H2SO4 with purity >

99%, graphite fine powder with purity > 99.5%, HCl with purity of 37%, KMnO4 with purity > 99%, K2S2O8 with

purity > 99% and P2O5 with purity > 98% were obtained from Merck Ltd Co. Endotoxin-free water (EF water) for all

experiments and other chemical materials were purchased from local chemical companies.

2.2. Depyrogenation

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The materials and equipment in contact with the sample should be free from endotoxin. Consequently, before each

assay, all glass containers were free from endotoxin at 260°C for 3 h, and plastic materials were treated with 33%

hydrogen peroxide rinsed with EF water and finally dried at 80°C for 8 h [45].

2.3. Reconstitution of endotoxin and preparation of stock solution

To prepare the stock solution, the vial of lyophilized (10 mg/vial) endotoxin from E. coli O111: B4 was dissolved in

LAL reagent water (10 mg/2mL, 5×105 EU) based on the manufacturer’s instructions, and the desired concentrations

were prepared.

2.4. Preparation of GO from graphite powder

In this study, for the synthesis of GO, the modified Hummer's technique was employed [46]. Momentarily, 2 g of

graphite fine powder, 46 mL of H2SO4, 1 g of K2S2O8 and 1 g of P2O5 were mixed together for 6 h under ambient

conditions. Then, the products were washed twice with 150 mL of EF water and dried in ambient air for 12 hours. The

dried product was added to 46 mL of H2SO4 at 0.0°C. Under stirring condition and temperatures below 20°C, 6 g of

KMnO4 was slowly added to the mixture. After the temperature reached 35°C, the mixing process was continued for

an extra 2 h; thereafter, 96 mL EF water was added and the mixing was continued for an additional 15 minutes. Finally,

the reaction was completed by adding 4 mL of H2O2 dropwise; this was followed by a change in the color of the

mixture to bright yellow. In order to remove metal ions, the suspension was washed with 10% HCl and repeatedly

washed with EF water. The product was completely dissolved and sonicated at 300 Watts for 1.5 h to produce

exfoliated single sheet GO.

2.5. Synthesis of GO-ECH

Briefly, 300 mg of exfoliated GO was dispersed in 300 mL of EF water. Sonication was performed for half an hour to

achieve a homogeneous suspension. 15 g of NaOH was also added to adjust the pH to 10. To produce cationic groups

on GO layers, 10.125 mL (129 mmol) of ECH was added as a cross-linker between the GO plate and DMA molecules

and the mixing was continued further for 3 h. Thereafter, HCL (3 M) was added to neutralize the reaction and the

product was collected by centrifugation at 14,000 rpm for 10 min. To remove impurities, the product was rinsed four

times with EF water to obtain ECH functionalized GO (GO-ECH) [46].

2.6. Synthesis of GO-ECH-DMA nanocomposite

Initially, 0.3 g of GO-ECH were dispersed in 300 mL of EF water. GO-ECH was fully dispersed by sonicator at 40

°C for 20 min because of the hydrophilic features of the oxygen groups on the surface of GO sheets. After pH

adjustment (pH= 12, NaOH 1.5 M), 17 mL of DMA was added to the suspension. The mixture under magnetic stirring

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was refluxed at 60°C for 3 h. Subsequently, the product was centrifuged at 14000 rpm for 15 min. The product was

rinsed with EF water to remove unreacted agent and impurities. Finally, GO-ECH-DMA nanocomposite as a synthetic

scheme, which is shown in Fig. 2 was obtained [46, 47].

Fig. 2. Schematic preparation of the GO-ECH-DMA nanocomposite.

2.7. Characterization of the prepared adsorbent

In order to determine the morphology, shape and other features of the adsorbents, Field Emission Scanning Electron

Microscope (FE-SEM, Tescan Mira 3-XMU, Czech Republic), X-ray Diffraction (XRD, X’Pert PRO MPD

PANalytical Company, Netherlands, based on “X'Pert High Score Plus” software and Zero diffraction plates

technique), Fourier Transform Infrared Spectroscopy (FT-IR, Tensor 27 Bruker, Germany), Energy Dispersive X-ray

analysis (EDX, PANalytical X'Pert Pro, Netherlands), and zeta potentials analysis of samples (Zetasizer, ZS3600,

Malvern model, UK) were employed.

2.8. Determination of the point of zero charges (pHpzc) of the GO-ECH-DMA

pHpzc as an important parameter is used to evaluate the net surface charge of adsorbent in aqueous solutions. The

procedure was determined according to the reported method [48]. Initially, different pHs (2, 4, 6, 8, 10 and 12) at

volume of 20 mL of NaCl (0.01 M) for each sample was adjusted using 0.1 M HCl or 0.1 M NaOH. Then, 0.05 g of

the GO-ECH-DMA was added to each container and agitated for 48 h. As shown in Fig. 6d, the crossing point of the

initial pH and final pH is called the pHpzc.

2.9. Batch adsorption study of endotoxin

All of the adsorption experiments and isotherms were carried out in a 25 mL Erlenmeyer flask, under ambient

conditions (24-26°C). The desired dose of the adsorbent was dissolved in a specific amount of EF water briefly and

sonicated at 300 Watts for 30 min. After pH adjustment of the NaOH (0.1 M) and HCl (0.1 M) solutions, the desired

volume of endotoxin was added to the sample. The suspensions were then shaken at 200 rpm for different contact time

based on the experimental design conditions. After the end of the adsorption process, the liquid phase was separated

from the solid phase employing an EMD Millipore Millex™-GP Sterile Syringe Filter. Before each adsorption test,

the exfoliation of GO-ECH-DMA nanocomposite suspension is necessary because the single layer of GO is more

active than the multilayer (non-exfoliated) [49].

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2.10. Endotoxin assay and adsorption experiments

Quantification of endotoxin content in solution was measured employing Endpoint Chromogenic Limulus Amebocyte

Lysate assay kit according to the manufacturer’s instructions (Limulus Amebocyte Lysate (LAL) - QCL-1000TM-US

License NO.1775, Lonza Walkersville, Inc). The endotoxin from E.coli O111: B4 strain was used to prepare standard

stock concentration for all adsorption experiments (10 EUmL-1 = 1 ngmL-1, lot # 072k4093). E.coli O111: B4 strain

was used to determine the calibration curve (Lonza Walkersville, Inc. lot: NO 541111). The sample was initially

mixed with the supplied LAL (50 µl) in free endotoxin well plates of the kit and the chromogenic substrate solution

(100 µl) was then added to the LAL content sample. The endotoxin catalyzed the proenzyme present in the LAL and

formed the enzyme. The enzyme separated the p-nitroaniline (pNA) from a chromogenic substrate and produced the

colorimetric marker with yellow color. The reaction was finally terminated by adding a stop inhibitor (100 µl of 25%

v/v glacial acetic acid) and the free pNA was measured spectrophotometrically at wavelengths (𝜆𝑚𝑎𝑥) of 405-410 nm.

The amounts of endotoxin concentration were computed in comparison with the standard curve in the range of 0.1-

1.0 EUmL-1. All filtered samples were diluted in this range and the adsorbed endotoxin amount, 𝑞𝑒(𝐸𝑈/𝑚𝑔) and

endotoxin removal percentage 𝐸(%) were computed using Eq. (1) and Eq. (2), respectively [47]:

𝑞𝑒(𝐸𝑈𝑚𝑔−1) =(𝐶0−𝐶𝑒)𝑉

𝑊 (1) 𝐸(%) =

(𝐶0−𝐶𝑒)

𝐶0×100 (2)

where qe (EUmg-1) is the endotoxin adsorption capacity at equilibrium time (min), E (%) is the endotoxin removal

percentage, C0 and Ce are initial and equilibrium endotoxin concentration (EUmL-1), respectively. W (mg) is the

weight of adsorbent and V (mL) is the volume of the endotoxin solution.

2.11. Desorption and regeneration experiments

The endotoxin adsorption was carried out at optimum condition. Thereafter, the samples (21 mg) of endotoxin-loaded

GO-ECH-DMA were accurately weighed and transferred into 20 ml of a 0.2 M NaOH solution followed by 30 ml of

2 M sodium chloride solution [5] and shaken for 4 h. Next, the suspension was separated at 14000 rpm for 15 min and

the desorbed endotoxin concentrations in the solution were determined. The separated solid thoroughly rinsed with

EF water, and then dried in an oven at 50°C for reuse. The regenerated GO-ECH-DMA matrix was then applied for

repeated adsorption-desorption cycles as described above to study their recyclability. The desorption capacity and

desorption efficiency were obtained using to the following equations:

Desorption capacity = 𝐶𝑁𝑎𝑉𝑁𝑎

𝑊 (3)

Desorption percentage =𝐶𝑁𝑎𝑉𝑁𝑎

𝑊

𝑞𝑒 × 100 (4)

where 𝐶𝑁𝑎 is endotoxin concentration in NaOH solution at desorption equilibrium (EUmL-1), 𝑉𝑁𝑎 is the volume of

NaOH solution used for desorption (mL), W is the mass of the adsorbent before adsorption of endotoxin (mg), and

qe is the amount of endotoxin adsorbed at equilibrium (EUmg-1).

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2.12. Design of experiments

The purpose of this study was to optimize the operation parameters of endotoxin removal employing central composite

design (CCD) [43] under response surface methodology (RSM) [42, 50] in R version 3.3.2 (2016-10-31). The RSM,

which is a collection of statistical techniques was employed to create an empirical model and investigate the interaction

of operation parameters in endotoxin adsorption, as well as optimize the response variable (y), which is influenced by

several independent variables such as pH (5-9, X1), mass of adsorbent (1-25 mgL-1, X2), contact time (2-60 min, X3)

and endotoxin concentration (10-80 EUmL-1, X4). The maximum values of endotoxin adsorption were considered as

a response of the operation parameters. At the beginning of the processes, the pretest was performed and the range

and central points of all independent variables were determined. A series of experiments called the run order were

carried out, respectively (Table 2). As presented in Table 1, four independent factors (pH (X1), mass of adsorbent (X2),

contact time (X3) and endotoxin concentration (X4) were designed in 5 coded values (-1, -0.5, 0, +0.5, +1) with 34

runs as experimental trials, consisting of 10 replicates in central points, 6 axial points and 18 designed points. The

range and actual level of the independent variable are summarized in Table 1 and coded using the following Eq. (5)

[51]:

Xi =(Xi−X0)

∆Xi (5)

where Xi is a dimensionless coded independent variable, Xi is the actual independent variable and X0 is the center

point value of Xi, and ∆Xi represents the step change values. The condition of the adsorption process including

prediction of the optimum condition for response and interaction between input and output variable is explained by

the following quadratic regression model Eq. (6) [52]:

Y = b0 + ∑ biXi

k

i=1

+ ∑ bii

k

i=1

Xi2 + ∑ ∑ bijXi

k

j=2

k−1

i=1

Xj + C (6)

where Y is the predicted response (removal %), k is the number of independent variables, b0 is the intercept term, bi

is the linear coefficient, bii are quadratic coefficients and bij are interactions coefficients, XiXj are independent

variables and C is the residual (error) factor. To evaluate the significance of the experimental terms as well as the

goodness of fit of the regression model, the ANOVA test was employed.

Table 1

Factors and coded levels of independent variables for endotoxin removal.

Table 2

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CCD design matrix and response obtained by GO-ECH-DMA.

3. Results and Discussion

3.1. Characterization of the GO–ECH–DMA nanocomposite

FTIR spectrum was employed to determine the chemical properties of functional groups in the different steps involved

in the synthesis of the adsorbent. Fig. 3 shows the FTIR spectra of GO (a), GO-ECH (b), GO-ECH-DMA (c) and GO-

ECH-DMA-Endotoxin (d). As depicted in Fig. 3a, the broadband at 3418 cm-1 supported the presence of O-H

stretching vibration. Also, strong adsorption peaks at 1720, 1620 and 1060 cm-1 were attributed to the carboxylic acid

(C=O), C=C and C-O bonds on the surface of GO matrix, respectively [53]. The intensity of the band related to the

C–O at 1060 cm–1 increased after functionalization of GO with ECH, which could probably be due to the new C–O

bonds. In addition, new bands (Fig. 3b) relevant to the C–H stretching vibrations appeared at 2926 cm–1, which could

be attributed to the new aliphatic bonds produced after GO functionalization with ECH [54, 55]. As elucidated in Fig.

3c, comparing GO-ECH-DMA with GO-ECH, the new peaks at 1054, 1115, and 1165 cm−1 were prompted by the C-

N stretching band of amine groups in GO-ECH-DMA adsorbent. An intense vibration in the band at 1619 cm−1

corresponded to N-H deformation vibration of amino groups which have been embedded into the matrix of GO-ECH-

DMA. The results probably revealed that, the cationic DMA have been grafted onto the GO-ECH surface and the GO-

ECH-DMA has been obtained. The FTIR spectrum of GO-ECH-DMA-Endotoxin (Fig. 3d) showed some new sharp

peaks at 1592, 1230 and 1050, which was attributed to N-H (hydrogen bonding), N-O and P-H vibration, respectively

[56, 57]. In addition, the appearance of these strong peaks suggests the successful attachment of endotoxin to GO-

ECH-DMA and removal of endotoxin from aqueous solutions.

Fig. 3. FTIR spectrum of GO (a), GO-ECH (b), GO-ECH-DMA (c), and GO-ECH-DMA-Endotoxin (d).

XRD patterns with peak list of the interlayer structure of GO, GO-ECH, and GO-ECH-DMA nanocomposite are

shown in Fig. 4. The sharp peak at 2θ = 11.002° corresponds to an interlayer spacing of 8.03557 A°, which can be

attributed to the hydrophilic functional groups (carboxylic acid, epoxide and - OH groups) on the surface of GO sheets

(Fig. 4a) [46]. In the XRD pattern of GO-ECH (Fig. 4b), reflection peak with low angle of 2θ = 10.863° (d-spacing

= 8.13763 A°) indicating that the interlayer spacing increased owing to the intercalation of oxygen functional groups

(C–O and C–O–C) of GO with ECH, which ultimately caused the roughness of GO surface. As seen in Fig. 4c, when

GO-ECH was modified with DMA, the diffraction peak at GO-ECH shifted toward a lower angle of 2θ = 8.60° with

an increase in d-spacing =10.27429 A°, which indicates the change in the GO-ECH structures and the successful

formation of GO-ECH-DMA matrix. As seen from the peak list in Fig. 4, other modification process confirming the

insertion of DMA into the GO-ECH layers and formation of GO-ECH-DMA matrix includes the slight changes in d-

spacing for GO-ECH at 2.13141 A° (2θ = 42.37°) and 1.23263 A° (2θ = 77.35°) at angle positions as well as sharp

changes in d-spacing of 4.01296 A° (2θ = 22.13°) and 2.09025 A° (2θ = 43.25°) for GO-ECH-DMA.

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Fig. 4. XRD pattern with peak list of GO (a), GO-ECH (b) and GO-ECH-DMA (c).

Fig. 5 shows the mapping elemental analysis and morphological properties of the GO and GO-ECH-DMA using

EDXA and FE-SEM, respectively. As shown in Fig. 5a, GO seems to be firmly wrinkled with a layered characteristic,

which indicate successful exfoliation of GO during the oxidation process. EDX mapping results also showed the

presence of homogeneous distribution of oxygen and carbon on the surface of GO [58]. As seen in Fig. 5b, after

modification of GO and synthesis of GO-ECH-DMA nanocomposite, heterogeneous rough matrix with 3D layered

structure was clearly observed. The EDX elemental mapping (Fig. 5b) of carbon, oxygen, and nitrogen showed a

heterogeneous distribution of nitrogenous functionalities on GO-ECH-DMA matrix. EDX elemental analysis showed

that 61.44, 11.47 and 27.08% of GO-ECH-DMA weight (W %) is attributable to carbon, nitrogen, and oxygen,

respectively. The loading of a high amount of N on the surface of GO-ECH-DMA matrix in comparison with previous

studies [59] has produced a major concept of adsorption systems in the removal of environmental pollutants.

Fig. 5. FESEM-EDX elemental mapping for GO (a) and GO-ECH-DMA (b).

The zeta potential (ZP) is a physical property of electrostatic potential in colloidal systems [60], as a useful and

efficient technique has been widely employed to measuring the surface charge as well as the surface hydrophobicity

of interfacial layers in the dispersion. The zeta potential of GO (−43.20 mV) and GO-ECH-DMA (+23.45 mV), which

was measured at pH around 6 was shown in Fig 6a-b. As depicted in Fig 6c, GO samples were all highly negatively

charged, ranging from −26 to −65 mV, which indicates that it forms stable colloids due to electrostatic repulsion of

negatively charged of COOH and OH groups, compared to the GO-ECH-DMA sorbent (from +37 to −41 mV) due to

a decrease in oxygen functional groups and the increase of amine functional groups on the surface of matrix. This

result supports the previous study on the ZP value of graphene nanosheets [61]. As can be seen, the values of negative

zeta potential of GO-ECH-DMA decreases when pH is lowered, approaching a pHpzc of sorbent at about pH 6.7 (Fig.

6d). Moreover, our findings suggest that the cationic DMA ligands are covalently grafted onto the GO-ECH-DMA

surface. Hence, it is hypothesized that the positively charged cationic ligands of DMA could act as the anchor sites

for adsorption of endotoxin molecules, followed by the electrostatic attraction between GO-ECH-DMA and lipid

A phosphate groups of endotoxin molecules.

Fig. 6. Zeta potential of GO (a) and GO-ECH-DMA (b) at high and low pH values in the range of pH 3 to 10 (c) and pHpzc of GO-ECH-DMA (d).

3.2. Regression model and statistical analysis

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The RSM employed as a set of the statistical method has some advantages, including saving time, availability of raw

materials and reduction in the number of experiments [62]. The efficiency of the models and the prediction of a

relationship between variable data were evaluated using analysis of variance (ANOVA). The quadratic regression

model for prediction of the effects of independent variables on the response was obtained as follows Eq. (7):

y = 69.90−27.58X1 + 10.92X2 + 18.08X3−20.75X4+2.25X1X2+4.24 X1X3−3.25 X1X4

−2.25 X2X3+10.25 X2X4+9.25 X3X4+0.06 X12−8.94 X2

2−3.44X32−3.44X4

2 (7)

The negative and positive signs in front of the independent variables equation show an antagonistic and synergistic

effect of variable values on the response terms, respectively. As can be seen from Table 4, the GO-ECH-DMA dosage

(𝑋2) and contact time (𝑋3) had synergistic effects on response prediction with p-values of 6.928×10-12 and 7.595×10-

16, respectively. The highest synergistic effect is related to contact time (𝑋3). The pH (𝑋1) and endotoxin concentration

(𝑋4) had an antagonistic effect on the quadratic model with p-values of 2.2×10-16 and 2.2×10-16, respectively. However,

the linear terms of independent variables based on synergistic effect were as follows: contact time (𝑋3)> GO-ECH-

DMA dose (𝑋2)> endotoxin concentration (𝑋4)> pH (𝑋1) values.

The results of the statistical significance of polynomial model and ANOVA techniques are shown in Table 4 and Table

3, respectively. The non-significant model lack-of-fit of 0.085 relative to the pure error and p-values of less than 0.05

revealed that the model was significant at 95% confidence level suggesting that the quadratic model was valid for

endotoxin removal using GO-ECH-DMA sorbent. The interaction effects of independent variables (𝑋1: 𝑋3) on

response were insignificant (p-values = 0.02955). The coefficient of determination is usually expressed as a percentage

and represents the data points that fall on the linear model formed by the regression equation. The values of 𝑅2 for the

model's suitability are very important. Previous studies [51] have suggested that the values of 𝑅2 should be at least

0.80 for the goodness of fit of the model. In this study, 𝑅2 = 0.9919, which means that a 99.5% variation in

independent variable values could be explained by response terms and that the regression model will fit the

independent variables. The difference between 𝑅2 and 𝑅Adj2 was 0.0035, which showed that the model was highly

significant. Fig. 7 shows the actual and predicted values for endotoxin removal by GO-ECH-DMA. It is quite obvious

that there was a good correlation between the predicted and experimental responses with 𝑅2 of 0.9934. The polynomial

equation has also revealed the good fit of the model terms. Results showed that among two-way interaction terms of

(𝑋1−4), as well as quadratic terms of (𝑋1−42 ) with p-values < 0.05, except for(X1: X4),(X1: X2),(X2: X3) and X1

2 with p-

values > 0.05, other terms had a significant effect on the polynomial Eq. (7).

Table 3

ANOVA results of the reduced quadratic model for endotoxin adsorption onto GO-ECH-DM.

Table 4

The output of the quadratic model for endotoxin adsorption using GO-ECH-DM.

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Fig. 7. Observed vs. predicted values plot of endotoxin adsorption percentage by GO-ECH-DMA.

3.3. Analysis of adsorption variables by 3D contour plotting and response surface

Contour plots or three-dimensional (3D) surface response is a visual technique for determining the interactions

between the independent and response variables [63]. Significant graphical interactions of primary developed model

parameters for endotoxin removal are graphically shown in Fig. 8 (a) to (e). In each plot, two input variables were

kept constant while other independent variables were varied on the x-y grid within the desired range, and the

interaction among them was estimated by response visualized curvature lines.

3.3.1. The combined effect of GO-ECH-DMA dosage and pH on the endotoxin removal

The pH of the solution is an effective parameter for endotoxin adsorption by GO-ECH-DMA sorbent. The performance

of pH on adsorption is dependent on ionization of endotoxin molecule and the protonation and deprotonation of the

different functional groups on sorbent matrix [64-66]. As shown in Fig. 8a, by fixing endotoxin concentration and

time at 45 EUmL-1 and 31 min, respectively, the endotoxin adsorption percentage (EAP) by GO-ECH-DMA reached

maximum at dosage of 15 to 22 mgL-1 and pH value of 5.5; the minimum percentage of endotoxin adsorption (30%)

was obtained at pH 9 and dosage of less than 5 mgL-1. A similar result was reported for endotoxin adsorption using

aminated cationic ligands [24, 25]. The decrease in EAP with an increase in pHs higher than pHZPC can be attributed

to the formation of the repulsion force between the negatively charged phosphorylated endotoxin and functional

groups on the adsorbent surface [64].

3.3.2. The combined effect of pH and contact time on the endotoxin removal

The interaction effect of initial contact time with pH is shown in Fig. 8b, while the GO-ECH-DMA dosage and

endotoxin concentration were kept constant at 13 mgL-1 and 45 EUmL-1, respectively. As can be seen, there was no

change in EAP with pH in the range of 5.5 to 5 at time 30 to 55 min. The phenomena might be associated with the

high molecular mass of endotoxin [8], which requires much contact time to reach the adsorbent matrix and occupy the

available binding sites on the GO-ECH-DMA matrix. Consequently, there was no significant change in EAP in the

range of contact time of 30 to 55 min.

3.3.3. The combined effect of GO-ECH-DMA dosage and contact time on the endotoxin removal

Fig. 8c shows the dependence of EAP on GO-ECH-DMA dosage and contact time. By fixing endotoxin concentration

and initial pH at 45 EUmL-1 and 7, respectively the maximum EAP was observed at 17 to 22 dosage mgL-1 within 45

to 55 min. As previously reported, the endotoxin removal activity increased with increase in Ag3-DMA-L-lysine

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dosage [67]. It was observed that EAP increased with an increase in GO-ECH-DMA dosage from 5 to 20 mgL-1 and

contact time from 10 to 40 min; then, became relatively constant. The increase in EAP at high GO-ECH-DMA dosages

can be attributed to the increase in available aminated cationic adsorptive sites [62]. In addition, when the dosage of

GO-ECH-DMA was around 20 mgL-1, the EAP was approximately completed and no significant increase in its values

was observed.

3.3.4. The combined effect of GO-ECH-DMA dosage and endotoxin concentration on the endotoxin removal

The interaction effects of GO-ECH-DMA dosage and initial endotoxin concentration on the endotoxin removal is

shown in Fig. 8d. The pH and contact time were fixed at 7 and 31 min, respectively. As seen, the EAP in endotoxin

concentration in the range of 10 to 15 EUmL-1 increased with increase in the dosage of GO-ECH-DMA from 5 to 18

mgL-1 and then decreased. This situation was ascribed to desorption of endotoxin molecules after adsorption

equilibrium. At low GO-ECH-DMA dosage and high endotoxin concentration, the EAP attained the minimum values

(20%).

3.3.5. Combined effect of endotoxin concentration and contact time on the endotoxin removal

Fig. 8e shows the combined effect of endotoxin concentration and contact time on the endotoxin removal. The GO-

ECH-DMA dosage and pH values were kept constant at 13 mgL-1 and 7, respectively. As seen, the EAP increased

with decrease in endotoxin concentration and increase in contact time. In this condition, the optimum area for

endotoxin concentration and contact time for EAP were in the range of 10-15 EUmL-1 and 30-50 min, respectively.

The EAP attained a minimum value at low contact time and high endotoxin concentration. This situation was attributed

to the high molecular mass of endotoxin, which takes time to get to the adsorbent surface [8].

Fig. 8. The 3D contour plots of the independent variable and percentage endotoxin removal: pH and GO-ECH-DMA dosage (a); time and pH (b);

time and GO-ECH-DMA dosage (c); GO-ECH-DMA dosage and endotoxin concentration (d); time and endotoxin concentration (e).

3.4. Experimental isotherm study

The adsorption isotherm models were applied to fit the experimental data and also are important for explaining

adsorption systems and designing the liquid-solid phase characteristics. The fitting of adsorption systems to different

isotherm models has a major role to better understanding and designing the adsorption process. In this work, for further

understanding the adsorbate–adsorbent interactions and simulation of endotoxin adsorption systems, experimental

equilibrium data were analyzed using the various most adsorption models such as Langmuir [44], Freundlich [68],

and Dubinin Radushkevich (D-R) isotherms [69, 70]. The Linear form of these isotherm models was examined based

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on the following equations. Based on the monolayer, homogeneous and uniform energy on an adsorbent surface, the

Langmuir isotherm model is represented as (Eq. 8).

1

qe=

1

qmax+

1

qmaxKLCe (8)

where Ce (EUmL-1) is the equilibrium concentration of endotoxin in solution, KL (mLEU-1) is Langmuir constant

related to adsorption energy, qe and qmax are the amounts of endotoxin (EUmg-1) adsorbed by GO-ECH-DMA at

equilibrium and the maximum adsorption capacity (EUmg-1), respectively.

The Freundlich adsorption model is an empirical term that can be employed in multilayer adsorption on the

heterogeneous matrix surface and linear form of the model is as follows Eq. (9) [71]:

logqe = logKF + 1

nlogCe (9)

where 1/n and KF (EUmg −1. mLEU−1)1

n⁄ are Freundlich constants, which indicates the favorability of the adsorption

process and adsorption capacity, respectively. The n and KF are constant terms which depend on the nature of adsorbed

substance and adsorbent.

The D-R isotherm as an empirical model has been effectively used to express the change in energy on the structure

of the sorbent in both homogeneous and heterogeneous surfaces. Linearized the D-R isotherm equation is described

as Eq. (10):

Lnqe = Lnqmax − βε2 (10)

where β is the D-R isotherm constant for adsorption energy (mol2·J-2) and ε is the Polanyi potential, which is

illustrated as Eq. (11):

ε = RTLn (1 +1

Ce) (11)

where T is the temperature in Kelvin (K) and R is gas constant (8.3145 J.mol-1.K-1) and E value as free adsorption

energy (Kj.mol-1) is explained as follows Eq. (12):

E =1

√2β (12)

The results of the experimental data obtained from Fig. 9 are summarized in Table 5. As can be seen, the correlation

coefficients were well fitted with Langmuir isotherm model (R2 = 0.981) compared to the Freundlich model (𝑅2 =

0.933) and D–R isotherms (𝑅2 = 0.886) because active sites were uniformly distributed on the GO-ECH-DMA

surface. The result indicating that the adsorption process occurred at the cationic functional groups on the surface of

the GO-ECH-DMA, which was described as homogeneous monolayer surface. The result showed that, the maximum

singular layer adsorption capacities (qmax) for endotoxin and 1/n (slope value) were 121.47 EUmg-1 and 0.36 at

optimum conditions, respectively. In addition, the high value of n parameter in Freundlich's isotherm indicates the

presence of high energy sites for endotoxin adsorption on the adsorbent surface and 1/n value below one implies a

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chemisorption nature [72] of the endotoxin removal by the GO-ECH-DMA. However, the modeling results

summarized in Table 5, demonstrated that the D-R isotherm showed also fit the experimental adsorption values. The

qe (EUmg-1) of endotoxin adsorption with different adsorbents are given in Table 6. As shown, the GO-ECH-DMA

has a high adsorbent capacity of endotoxin compared to other adsorbents, but the Silica gel (Silan-Histidin) [24] with

high uptake capacity is still an attractive adsorbent. This high adsorption capacity clarified that GO-ECH-DMA is an

applicable matrix for endotoxin adsorption from aqueous solution.

Table 5

Isotherm parameters for adsorption of endotoxin onto GO-ECH-DMA.

Fig. 9. Endotoxin adsorption isotherm models by GO-ECH-DMA matrix.

Table 6

Comparison of various adsorbents for endotoxin (LPSs) adsorption.

3.5. Adsorption kinetics

Adsorption is a surface-based physicochemical phenomenon that involves the mass transfer of a solute from liquid

phase to an adsorbent’s surface [73, 74]. Kinetics provides important information about the mechanism of endotoxin

adsorption onto GO-ECH-DMA, which was necessary to evaluate the adsorption rate of adsorbent and control the

residual contact time step of the whole adsorption process. In this study, to analyze the kinetics of endotoxin onto GO-

ECH-DMA, the pseudo-first-order, pseudo-second-order, and intra-particle diffusion models were investigated. The

linear forms of these models are respectively as Eq. (13, 14, and 15) [69]:

Log(𝑞𝑒−𝑞𝑡 ) = Log𝑞𝑒 −K1

2.303. 𝑡 (13)

𝑡

𝑞𝑡 =

1

𝐾2𝑞𝑒2 +

1

𝑞𝑒. 𝑡 (14)

𝑞𝑡 = 𝐾𝑝 . 𝑡0.5 + 𝐶 (15)

Where qe and qt endotoxin adsorption capacity (EUmg-1) at equilibrium and at time t (min) respectively; 𝐾1 is the

rate constant of first-order adsorption (min-1); 𝐾2 is the rate constant of pseudo-second-order adsorption kinetic

equation (mg.(EUmin)-1); 𝐾𝑝 is an intraparticle diffusion rate constant (EU.(mg-1.min-0.5)). The value of intercept

factor C indicates the mechanism of the adsorption to be either quite complex (C ≠ 0) or adsorption kinetics is only

controlled by intraparticle diffusion (C = 0). In the present study, as depicted from Fig 10 c, the C value is always a

non-zero (C = 64.12 ± 5.84) revealing that the adsorption process is not controlled only by intraparticle diffusion but

involves complex mechanism pathway. Kinetics parameters of endotoxin adsorbed on GO-ECH-DMA by the pseudo-

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first-order, pseudo-second-order, and intra-particle diffusion models were summarized in Table 7 and shown in Fig.

10. It was found that the adsorption kinetics of endotoxin seems to obey both kinetic models of pseudo-second-

order (𝑅2 = 0.988) and intra-particle diffusion models (𝑅2 = 0.916). In addition, the pseudo-second-order model

seems fits the data better than others. Pseudo-second-order kinetic model assumes that the chemisorption process may

be the rate-limiting step in adsorption processes. As shown in Fig. 10a, the correlation coefficients (𝑅2) for the pseudo-

first-order kinetic model was values were relatively small (0.888) and the experimental (qe, exp = 50.40 EUmg-1) values

not well fit the calculated values obtained from the optimum condition (qe, oc = 119.7 EUmg-1). According to the

pseudo-second order kinetic model, the qe calculated was very close to the values of the optimum ones.

Fig. 10. Endotoxin adsorption kinetic models by GO-ECH-DMA matrix.

Table 7

Parameters of Kinetic models for endotoxin adsorption onto GO-ECH-DMA matrix.

3.6. Adsorption capacity of unmodified graphene oxide (GO)

To assess the influence of GO on the endotoxin removal, adsorption experiments were designed under optimum

conditions. Results showed that, by fixing optimum conditions there was a weak reduction (41%) in the amount of

endotoxin adsorbed onto the GO compared to GO-ECHDMA nanocomposite (0.98%). The minimum (25%) and

maximum (48%) percentage of endotoxin adsorption were obtained at pH 9 and 4, respectively. The low endotoxin

adsorption ability of the GO can be mainly attributed to the following factors: The isoelectric point of endotoxin and

pHzpc of GO are about 1.3 [75] and 3.04 [76], respectively. The -COOH groups from GO are changed to -COO- at

higher pHzpc, which is unfavorable for the adsorption of endotoxin onto the GO single layer. The electrostatic

repulsion between partially phosphorylated endotoxin molecules and oxygen functional groups could also prevent the

adsorption of endotoxin onto the GO. In addition, these factors simultaneously affect the ionic interaction between

endotoxin and the GO and lead to the occurrence of minimum adsorption toward endotoxin at a particular pH for GO

matrix.

3.7. Recycling and desorption of GO-ECH-DMA nanocomposite

Desorption and regeneration of an adsorbent was the most important items for the design and practical application of

cyclic adsorption processes. The effect of reuse times on the adsorption capacity of GO-ECH-DMA for endotoxin was

shown in Fig. 11. As can be seen, the adsorption capacity of the regenerated GO-ECH-DMA decreased during the

subsequent recycles. A desorption efficiencies of endotoxin onto GO-ECH-DMA at five cycle are 96.63 %, 91.59 %,

88.23 %, 84.87%, and 84.03 %, respectively. The results showed that, compared to the initial adsorption, the

adsorption capability of GO-ECH-DMA decreased only after the 5th cycle to approximately 15.59 %. This

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phenomenon can be attributed to a reduction in endotoxin binding sites after each desorption step [77]. The GO-HCH-

DMA can be reused as adsorbents five times during their adsorption/desorption cycles with a no significant loss in the

adsorption capacity for endotoxin removal from aqueous solution.

Fig. 11. Relationship between the reuse times and the endotoxin adsorption capacity of the GO-ECH-DMA nanocomposite.

3.8. Adsorption mechanism

Endotoxins are amphipathic molecules and consist of two parts of polar hydrophilic polysaccharide chain and non-

polar hydrophobic fatty acid head (Lipid A) which are linked to the net negative charge of phosphate groups [45]. As

previously reported [45] this characteristic of endotoxin supports the idea that ionic bonding plays an imperative role

in the chemical reaction between GO-ECH-aminated cationic groups and lipid A phosphate groups [78]. Due to the

high volume and weight (1 × 106 to 20 × 106 Dalton, Da) of the endotoxin molecules [33], functional groups on the

surface of the adsorbent without a linker were unable to sufficiently bond to endotoxin molecule [7]. As seen in Fig.

2, to surmount this problem, one carbon length was produced between the cationic ligand and the hydroxyl group of

alkyl chains (R-C(OH) H2CH3CH2-Amino-group) using the ECH as a cross-linker. The electrostatic interaction,

hydrophobic interactions, and hydrogen bonding for endotoxin adsorption with cationic ligands have been described

in various studies [7, 25, 64] and dimethylamine as cationic ligand for endotoxin removal was also applied by Yuan

et al. [7]. From these results, we can infer that the possible mechanisms of endotoxin adsorption onto GO-ECH-DMA

are predominantly as follows (Fig. 12): Initial formation of H bond between the hydrogen atoms from phosphorylated

groups of endotoxin and an oxygen atom from OH groups of alkyl chains of GO-ECH-DMA, and secondary reactions

induced by electrostatic interaction from a net positive charge of (−HN+(R)2) amine end groups on GO-ECH-DMA

surface and an oxygen atom of phosphate groups [7, 24], and hydrophobic interactions (π-π stacking) or physical

adsorption between alkane chain of nonpolar lipid A [79] and surface of GO-ECH-DMA. In addition, all of these

processes precipitate a strong reaction between the endotoxin molecule and GO-ECH-DMA matrix [17].

Fig. 12. The dominant mechanism of the endotoxin removal from liquid phase using GO-ECH-DMA sorbent at pH< pHzpc.

4. Conclusion

A novel adsorbent of GO-ECH-DMA matrix was successfully synthesized and employed for bacterial endotoxin

removal from aqueous solutions. XRD, FE-SEM, EDX and FTIR analyses confirmed the surface of GO-ECH

modified by DMA. A quadratic model showed the good fit of operation variables (actual vs. predicted data) with the

coefficient of determination values (R-squared: 0.9919, Adjusted R-squared: 0.9884). RSM under CCD was employed

for independent variables to evaluate the relation between operating factors and adsorption capacity. Contour plots or

3D surface was used to determine the optimum response. Through response surface analysis obtained from the

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quadratic model, pH (𝑋1) and endotoxin concentration (𝑋4) were found to have an antagonistic effect on endotoxin

adsorption. The optimum operation variables to attain maximum endotoxin adsorption (>98%) were obtained using

pH 5.52, 21 mgL-1 GO-HCH-DMA dosage, 56 min contact time and 51.3 EUmL-1 endotoxin concentration (10 EUmL-

1 = 1 ngmL-1) and under these circumstances equilibrium endotoxin adsorption was reached in 119.7 EUmg-1. Due to

the homogeneous distribution of active site on the adsorbent surface, the experimental data fitted well with the

Langmuir isotherm model (R2 = 0.98) than the Freundlich isotherm (R2 = 0.93). The results showed that endotoxin

was removed at a maximum Langmuir adsorption capacity of 121.47 EUmg-1. In addition, it was found that the

pseudo-second-order model successfully explained the adsorption kinetics of endotoxin, as compared to other models.

The GO-HCH-DMA can be regenerated five times during their adsorption-desorption cycles with a no significant loss

in the adsorption capacity. The most favorable pH value for endotoxin adsorption from aqueous solution was above

its isoelectric point (pIen) and below the pHpzc = 6.8 of the GO-HCH-DMA. The electrostatic interaction, hydrogen

bonding, and hydrophobic interaction played an important role in the endotoxin adsorption on GO-ECH-DMA

adsorbent. This study seeks to explain new insights for application of cationic GO-ECH-DMA adsorbent as an

economical, efficacious and environmentally friendly material for drinking water supplies, pharmaceutical industry,

and hemodialysis water treatment system.

Acknowledgments

This study is based on the Ph.D thesis of the first author. The authors like to acknowledge the Department of

Environmental Engineering of the School of Public Health of International Campus of Tehran University of Medical

Sciences (IC-TUMS), (Grant No. 95-03-103-32699) for their financial support.

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Fig. 1. Modified chemical structure of endotoxin (LPSs) of E. coli O111: B4 [17].

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Fig. 2. Schematic preparation of the GO-ECH-DMA nanocomposite.

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Fig. 3. FTIR spectrum of GO (a), GO-ECH (b), GO-ECH-DMA (c), and GO-ECH-DMA-Endotoxin (d).

4000 3000 2000 1000

20

30

40

50

60

70

80

90

100

110

1620

1720

(a)

Tra

nsm

itta

nce

(a.

u)

3418

1720

1620

1385 1060

4000 3000 2000 1000 0

20

30

40

50

60

70

80

90

100

110

1041

2926

(b)

3417

1389

4000 3000 2000 1000 0

20

30

40

50

60

70

80

90

100

110

+

+

(c)

Tra

nsm

itta

nce

(a.

u)

Wavenumbers cm−1

1054

1115

1165

1247

1383

1616

4000 3000 2000 1000 0

20

30

40

50

60

70

80

90

100

110

-+

(d)

Wavenumbers cm−1

15923428

1845

1230

1050

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Fig. 4. XRD pattern with peak list of GO (a), GO-ECH (b), and GO-ECH-DMA (c).

0 10 20 30 40 50 60 70 80

0.00

1.10k

2.20k

3.30k

4.40k

0.00

5.40k

10.80k

16.20k

0.00

5.20k

10.40k

15.60k

+

Position [02 Teta] (Copper(Cu))

(c)

Co

un

tsC

ou

nts

Co

un

ts

+

(b)

(a)

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Fig. 5. FESEM-EDX elemental mapping for GO (a), and GO-ECH-DMA (b).

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Fig. 6. Zeta potential of GO (a) and GO-ECH-DMA (b) at high and low pH values in the range of pH 3 to 10 (c) and

pHpzc of GO-ECH-DMA (d).

(a) (b)

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Fig. 7. Observed vs. predicted values plot of endotoxin adsorption percentage by GO-ECH-DMA.

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Fig. 8. The 3D contour plots of the independent variable and percentage endotoxin removal: pH and GO-ECH-

DMA dosage (a); time and pH (b); time and GO-ECH-DMA dosage (c); GO-ECH-DMA dosage and endotoxin

concentration (d); time and endotoxin concentration (e).

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Fig. 9. Endotoxin adsorption isotherm models by GO-ECH-DMA matrix.

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Fig. 10. Endotoxin adsorption kinetic models by GO-ECH-DMA matrix.

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Fig. 11. Relationship between the reuse times and the endotoxin adsorption capacity of the GO-ECH-DMA

nanocomposite.

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Fig. 12. The dominant mechanism of the endotoxin removal from liquid phase using GO-ECH-DMA sorbent at pH<

pHzpc.

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Table 1 Factors and coded levels of independent variables for endotoxin removal.

Factors (Independent variables) Unit Coded levels

-1 -0.5 0 0.5 1

Actual variable ranges

pH (X1) 5 6 7 8 9

Adsorbents (X2) mgL-1 1 7 13 19 25

Time (X3) min 2 16.5 31 45.5 60

Endotoxin concentration (X4) EUmL-1 10 27.6 45 62.5 80

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Table 2 CCD design matrix and response obtained by GO-ECH-DMA.

Run

order

Coded level of variables

Response endotoxin

Removal %

Run

order

Coded level of variables

Response endotoxin

Removal %

X1 X2 X3 X4 Observed Predicted X1 X2 X3 X4 Observed Predicted

1 -0.5 -0.5 -0.5 -0.5 83 80.75 18 0 0 0 0 69 69.90

2 -0.5 -0.5 0.5 0.5 74 73.58 19 0.5 -0.5 0.5 -0.5 69 68.25

3 0.5 -0.5 -0.5 0.5 24 19.42 20 -0.5 0.5 0.5 -0.5 95 96.75

4 0.5 0.5 0.5 0.5 60 61.42 21 0 0 0 0 69 69.90

5 0 0 0 0 70 69.90 22 0 0 0 0 70 69.90

6 -0.5 0.5 0.5 0.5 89 87.38 23 0 0 0 -1 88 87.21

7 0.5 -0.5 -0.5 -0.5 50 51.55 24 0 -1 0 0 48 50.04

8 0.5 0.5 -0.5 0.5 38 37.72 25 0 0 0 1 44 45.71

9 0.5 0.5 -0.5 -0.5 60 59.59 26 -1 0 0 0 87 93.45

10 0.5 0.5 0.5 -0.5 73 74.05 27 0 0 0 0 70 69.90

11 0.5 -0.5 0.5 0.5 45 45.38 28 0 0 0 0 69 69.90

12 0 0 0 0 71 69.90 29 0 0 0 0 70 69.90

13 0 0 0 0 72 69.90 30 0 1 0 0 71 71.88

14 -0.5 0.5 -0.5 0.5 68 67.92 31 1 0 0 0 44 42.38

15 -0.5 -0.5 -0.5 0.5 53 51.88 32 0 0 -1 0 46 48.38

16 -0.5 -0.5 0.5 -0.5 96 93.21 33 0 0 1 0 77 75.54

17 -0.5 0.5 -0.5 -0.5 87 87.38 34 0 0 0 0 68 69.90

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Table 3

ANOVA results of the reduced quadratic model for endotoxin adsorption onto GO-ECH-DM.

Response: Removal

Model formula Df Sum Sq Mean Sq F value Pr(>F) Judgment

First-order response (X1, X2, X3, X4) 4 9825.50 2456.37 683.34 < 2.2×10-16 Highly significant

Two-way interactions (X1, X3) 1 18.10 18.06 5.02 0.03493 significant

Two-way interactions (X2, X4) 1 105.10 105.06 29.23 1.71×10-05 Highly significant

Two-way interactions (X3, X4) 1 85.60 85.56 23.80 6.30×10-05 Highly significant

Pure quadratic response (X2, X3, X4) 3 192.70 64.22 17.87 3.29×10-06 Highly significant

Residuals 23 82.70 3.59

Lack of fit 14 65.80 4.70 2.50 0.085 Non-significant

Pure error 9 16.90 1.88 0.035

Multiple R-squared: 0.9919, Adjusted R-squared: 0.9884, F-statistic: 284.5 on 10 and 23 DF, p-value: < 2.2×10-16

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Table 4 The output of the quadratic model for endotoxin adsorption using GO-ECH-DM.

Model parameters Parameter

estimate

Estimate Std.

Error t- value p-value Judgment

(Intercept) 69.90 0.57 122.38 < 2.2×10-16 Highly significant

𝑋1 (pH) -27.58 0.74 -37.41 < 2.2×10-16 significant

𝑋2 (GO-ECH-DMA dosage) 10.92 0.74 14.80 6.928×10-12 Highly significant

𝑋3 (contact time) 18.08 0.74 24.52 7.595×10-16 Highly significant

𝑋4 (endotoxin concentration) -20.75 0.74 -28.14 < 2.2×10-16 Highly significant

𝑋1: 𝑋2 2.25 1.81 1.25 0.22801

𝑋1: 𝑋3 4.25 1.81 2.35 0.02955 significant

𝑋1: 𝑋4 -3.25 1.81 -1.80 0.08786

𝑋2: 𝑋3 -2.25 1.81 -1.25 0.22801

𝑋2: 𝑋4 10.25 1.81 5.68 1.802×10-05 Highly significant

𝑋3: 𝑋4 9.25 1.81 5.12 6.068×10-05 Highly significant

X12 0.06 1.30 0.04 0.96463

X22 -8.94 1.30 -6.89 1.437×10-06 Highly significant

X32 -3.44 1.30 -2.65 0.01577 significant

X42 -3.44 1.30 -2.65 0.01577 significant

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Table 5 Isotherm parameters for adsorption of endotoxin onto GO-ECH-DMA.

Isotherms The model of

adsorption Straight form Parameters

Langmuir qe =qmaxKLCe

1 + KLCe

1

qe

=1

qmax

+1

qmaxKLCe

qmax(EUmg-1) 121.47

KL(mLEU-1) 0.307

R2 0.981

Freundlich qe = KFCe

1n⁄ logqe = logKF +

1

nlogCe

KF(EUmg −1. mLEU−1)1

n⁄ 3119

n (Dimensionless) 2.71

R2 0.933

D-R qe = qmax. exp ( − βε2) Lnqe = Lnqmax − βε2

qmax(EUmg-1) 84.71

β (Dimensionless) 2.4×10-7

R2 0.886

Endotoxin concentration = 10-80 EUmL-1; mass of sorbent = 21mgL-1; pH value = 5.5; volume of endotoxin solution = 50 mL; ambient

temperature = 24°C; adsorption time = 2h.

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Table 6

Comparison of various adsorbents for endotoxin (LPSs) adsorption.

Sorbent matrix qe (EUmg-1) Endotoxin removal percentage

(E %)

Reference

Silica gel (Silan-Histidin) 1.2 mgg-1 = 12000 EUmg-1* Higher than 90% [24]

Polymethyl methacrylate (PMMA-dimethylamine) 73.78 EUµmol-1 ligand 83.8% [7]

Cross-linked cellulose microspheres (CL-CMs) 3605 EUg-1 = 3.605 EUmg-1 More than 70% [31]

Ag3- hexamethylendiamine -L-lysine 152.17 EUg-1 = 0.15217 EUmg-1 73.6% [67]

Aminoalkylagarose-L-phenylalanine (His) 292.41 EUg-1 = 0.29241 EUmg-1 37.1% [47]

GO-ECH-DMA 121.47 EUmg-1 >98% This study

*10 EUmL-1 = 1 ngmL-1

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Table 7

Parameters of Kinetic models for endotoxin adsorption onto GO-ECH-DMA matrix.

Pseudo-first-order Pseudo-second-order Intra-particle diffusion

qe

(EUmg-1) K1

(min-1) R2 qe

(EUmg-1) K1

(mg.(EU.min)-1) R2 Kp

(EU.(mg-1.min-0.5))

R2

50.40 0.0291 0.888 117.07 0.0019 0.988 6.0274 0.916

Endotoxin concentration = 51.3 EUmL-1; mass of sorbent = 21 mg-l; pH value = 5.5; volume of endotoxin solution = 50 mL; ambient temperature

= 24°C; adsorption time = 2h.

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