Alexandre Felten

Irene Suarez-Martinez

Xiaoxing Ke

Gustaaf Van Tendeloo

Jacques Ghijsen

Jean-Jacques Pireaux

Wolgang Drube

Carla Bittencourt

Christopher P Ewels

The Interface between Titanium and Carbon Nanotubes

Keywords: Carbon nanotubes, DFT, Photoemission spectroscopy, Titanium

We study the interface between carbon nanotubes (CNTs) and surface deposited titanium using electron microscopy and photoemission spectroscopy, supported by density functional calculations. Charge transfer from the Ti atoms to the nanotube and carbide formation is observed at the interface which indicates strong interaction. Nevertheless, the presence of oxygen between the Ti and the CNTs significantly weakens the Ti-CNT interaction. Ti atoms at the surface will preferentially bond to oxygenated sites. Potential sources of oxygen impurities are examined, namely oxygen from any residual atmosphere and pre-existing oxygen impurities on the nanotube surface, which we enhance through oxygen plasma surface pre-treatment. Variation in literature data concerning Ohmic contacts between Ti and carbon nanotubes is explained via sample pretreatment and differing vacuum levels, and we suggest improved treatment routes for reliable Schottky barrier free Ti-nanotube contact formation.

Introduction

Carbon nanotubes appear as a good candidate to replace stateof-the-art inlaid copper interconnects in microprocessors. A key step for integration of CNTs in actual devices is the formation of stable and low-resistance ohmic contacts. Experimental results and calculations seem to agree that Ti and Pd are the best candidates for contacts in carbon nanotube based devices [1][2][3][4][5][6][7][8] . They are superior to conventional metals previously used in electronics such as Au, Al, and Pt which have associated high resistance Schottky barriers. Theoretical studies of pure metals on graphite suggest Ti as the best metal for contacts followed by Pd 5 , yet while low resistance Ohmic contacts have been experimentally reported in the case of Ti [1][2][3] , experimental results give Pd as the best choice due to better reliability and reproducibility 2,6 . One of the reasons invoked for this discrepancy is the high chemical reactivity of Ti compared to the other metals 2,6,9 : in realistic systems titanium oxidation occurs. But until now, no chemical study of the Ti/nanotube interface has been carried out in order to understand the phenomenon, nor supporting theoretical calculations.

In this paper, we investigate the growth, electronic structure and chemical composition of Ti atoms on multiwall carbon nanotubes (MWNTs) by transmission electron microscopy (TEM), core levels photoemission spectroscopy (XPS) and density functional calculations.

Results and Discussion

Evaporation of Ti on pristine MWCNTs leads to continuous amorphous coverage of the nanotube surface, even for small amounts of evaporated metal. High resolution TEM images in Figure 1 show that the film is continuous from at least 1 nm coverage; unlike for example Pd which shows isolated particle formation.

Calculations for small Ti clusters confirm the tendency of Ti to wet the carbon surface. A single Ti atom strongly binds to graphene (2.64 eV), with Ti above a hexagon centre with short Ti-C bonds (2.24 Å), in good agreement with previous studies 10 . We have examined a range of 2D and 3D structures for Ti n on graphene (n=1-4). For each cluster size the most stable structure is planar parallel to the graphene (see Figure 2). This is in contrast to Ti 4 in the gas phase where we find the most stable form is tetrahedral, in agreement with previous Ti cluster calculations 11 . A continuous monolayer of epitaxial Ti forms a buckled layer on average 2.0 Å above the graphitic layer, with Ti-C distances of 2.13 Å or 2.39 Å depending on whether the Ti atom lies above C atoms or hexagon centres respectively. In this case our binding energy is 5.43 eV/Ti atom. Our calculated barrier for Ti diffusion on the graphitic surface is 0.75 eV, as compared to ~0.1eV for Au and Pd. Thus while a simple first order Arhennius type equation with the Debye attempt frequency (10 13 Hz) suggests that isolated Au or Pd atoms on the graphitic surface at room temperature will be moving at more than 2×10 11 hops/second, Ti atoms will only be moving at 2 hops/second, i.e. Ti atoms are almost immobile. This is consistent with the Ti coating being amorphous whereas Pd and Au particles are crystalline after deposition 12,13 .

Introducing O 2 strongly modifies the interaction of Ti with the graphitic layer. The two O atoms bind strongly to the single Ti atom (8.59 eV/O 2 , Ti-O bonds of 1.66 Å), which significantly weakens the Ti-C interaction (bonds dilated to 2.60 Å). Essentially the TiO 2 unit becomes molecular and sits above the graphene π-cloud, again in agreement with previous calculations 10 . The presence of oxygen significantly weakens the Ti-C interaction.

The calculations also show strong qualitative variations in charge transfer behaviour. An isolated Ti atom on graphene has a net spin of 2.41µ B , and Mulliken distribution analysis shows a strong net charge transfer from the Ti to the graphene layer resulting in a Ti charge of +0.98e. On addition of oxygen the Ti charge increases to +1.36e, however due to the charge on the oxygen atoms (-0.83e/O) the result is a much weaker net charge transfer in the opposite direction from the graphene to the TiO 2 unit of 0.29e.

Thus we clearly see that the presence of oxygen at the interface between Ti and nanotube critically controls the extent of the Ti-C interaction. Blackstock et al. 14 recently investigated a similar problem at Ti/organic monolayer interfaces. They observed a formation of 1-2 nm thick TiO 2 layer at the interface and attributed it to the vacuum conditions, surface water and oxygen diffusion from the metal oxide substrate. We investigate experimentally the importance of oxygen contamination from two potential sources: residual atmosphere still present in the chamber during Ti evaporation or from oxidized defects present on the nanotube surface.

We first investigate the deposition at ultra-high vacuum of 10 -9 mbar. XPS of pristine nanotubes shows trace oxygen present at less than 1 at%. After the first step of titanium evaporation (sample 1), the Ti 2p 3/2 peak has a binding energy of ~459.0 eV (see Figure 3b), which is characteristic of Ti 4+ present in TiO 2 15,16 . This suggests that titanium atoms first react with any available oxygen to form completely oxidized titanium. As the amount of deposited metal increases, the Ti 2p 3/2 peak evolves into a broad structure due to the presence of Ti in different chemical environments. First, it shows structures ranging from 455 to 460 eV corresponding to oxides with different stoichiometries: peaks at 459.0 eV, 457.6 eV, 456.7 eV and 455.3 eV are reported as TiO 2 , Ti 3 O 5 , Ti 2 O 3 and TiO respectively 15 . Notably with increasing Ti thickness there is a shift in the TiO x peaks towards increasingly oxygen depleted phases, consistent with the presence of a fixed reservoir of oxygen shared by an increasing quantity of Ti. A new peak attributed to Ti atoms bound to carbon progressively appears at lower binding energy (454.8 eV). From sample 5 (10 Å of Ti evaporated), this peak becomes predominant. Finally, for a thick layer of Ti (sample 7), a peak at 453.8 eV is observed corresponding to metallic Ti. This evolution with the thickness is consistent with the theoretical modelling showing a clear preference for Ti to form Ti-O bonds, followed by Ti-C and finally Ti-Ti.

The evolution of the C1s spectra with increasing Ti coverage is shown in Figure 3a. At increasing Ti coverage, simultaneously with the appearance of a peak at 281.9 eV associated with the formation of Ti-C bonds, a shoulder on the main C1s peak appears near 285.5 eV. This shoulder is due to charge transfer from the increasing Ti layer to the nanotube. We can analyze this effect further by subtracting from the spectra the contribution of photoelectrons emitted from the inner walls, assuming the layers are electronically isolated, i.e. all charge transfer from the Ti occurs to the outer walls of the CNT 17 . The subtracted spectra are shown in Figure 4. Assuming a rigid band shift, peak displacement to higher energies corresponds to increased charge transfer from Ti to the carbon. The peaks form two distinct families, those at low Ti coverage (samples 1, 2) which are only weakly asymmetric, and those at higher Ti coverage (samples 3-7) which are highly asymmetric with a strong high energy shoulder. This asymmetry has been associated with electronhole pair excitations [START_REF] Hüfner | Photoelectron Spectroscopy: Principles and Applications[END_REF][START_REF] Martensson | [END_REF] : the potential created between the photohole and the remaining electrons after the photoemission induces the promotion of electrons near the Fermi level to empty states just above it. The increased asymmetry is thus consistent with an increase in the DOS associated with charge transfer. The transition from weak to strong charge transfer between samples 2 and 3 corresponds with the first appearance of Ti-C interaction in the Ti 2p spectrum of sample 3 and the end of oxide formation and is in agreement with the calculations showing higher charge transfer for Ti bonded directly to carbon than with oxygen present. We note that for thick Ti films we no longer see any increase in charge transfer in the subtracted C1s spectra, i.e. the top Ti metal does not contribute charge to the underlying nanotube.

In order to investigate the importance of the residual atmosphere, we next deposited a 10 Å layer of Ti under three different pressures: 10 -6 , 10 -7 and 10 -8 mbar, using Au films as the substrate. Figure 5 shows the titanium oxide content in the deposited layers as calculated from a deconvolution of the Ti 2p 3/2 XPS peak area into metal, carbide and oxide components. Oxygen is always present in the titanium film. At 10 -6 mbar, the layer is fully oxidized with a Ti 2p peak showing a large majority of TiO 2 . Improving the vacuum leads to a decrease in the oxide content with a drastic decrease of the TiO 2 peak. At 10 -8 mbar, half of the Ti atoms are oxidized with only 10% forming TiO 2 , the rest forming TiO x (x<2) phases.

Another potential source of oxygen contamination is oxygen containing defects on the nanotube surfaces. In order to investigate the importance of these, we oxygen plasma treated the MWNTs before the Ti is deposited. XPS showed that 15 at% of oxygen is grafted to the nanotube surface using the oxygen plasma treatment. Figure 6a shows the comparison between the C 1s peaks recorded from pristine and oxygen plasma-treated nanotubes. Photoelectrons emitted from carbon atoms in the ''graphite-like'' walls generate the main feature of these spectra at binding energy of 284.3 eV. The chemical modification produced by the plasma treatment is identified by a broad structure peaking at 287.5 eV: it is attributed 20 to photoelectrons emitted from carbon atoms belonging to oxygen groups (hydroxyl, carbonyl and/or carboxyl). The evaporation of titanium was then performed simultaneously on pristine and oxygen plasma treated MWCNTs. Compared to the spectra recorded on pristine nanotubes, similar trends are observed but with some notable differences: (1) sample 3, which showed components due to both Ti-C and Ti-O bonds in the pristine case, now only shows a component due to Ti-O bonds (Figure 7), which is consistent with a larger available reservoir of oxygen ( 2) the C 1s level of functionalized nanotubes shows a peak around 286.7 eV, corresponding to oxygen grafted to carbon during the oxygen plasma treatment. This peak disappears as the amount of Ti increases (Figure 6b); (3) the asymmetry of the C 1s peak is less pronounced compared to non-treated nanotubes. This indicates that due to Ti oxide formation, less charge is transferred to the oxygen treated nanotube than to the pristine one, in agreement with the calculations. For example, at Ti thickness of 2 Å, the FWHM of the C 1s peak after background subtraction is 1.65 eV for pristine MWCNTs and 1.15 eV for the functionalized ones (Figure 6c).

Oxygen plasma treatment under similar conditions induces a variety of defects into the nanotube wall as identifies by XPS 20 , primarily aldehyde/ketones (>C=O) but also ester/carboxyls (-COO-) 21 for longer treatment times. Since there are many possible defect configurations giving rise to these systems, we modelled the behaviour of single Ti atoms in the vicinity of an oxygenated vacancy (VacO 2 ) as the smallest test system, which contains oxygen atoms in both ketone and ether bonded configurations. Several metastable configurations for the addition of a single Ti atom are possible with similar energies, and in all cases the Ti binds strongly (>5 eV), i.e. >3 eV more strongly than to the pristine carbon sheet. Some of the lowest energy configurations involve oxygen atoms scavanged from the vacancy by the Ti atom, however we anticipate the barrier to break the C-O bond will be significant and such configurations will be unobtainable experimentally at room temperature. All other stable configurations involve Ti in the immediate viscinity of the VacO 2 structure, with bonds between the Ti atom and both oxygen and carbon atoms. The high binding energies show that once trapped by an oxygenated surface defect Ti will clearly be immobile at room temperature. The calculations therefore confirm that oxygen plasma induced surface defects will be strong trapping sites for Ti, in agreement with experiment.

Conclusion

The quantity of oxygen present in the initial surface layer crucially controls the Ti-nanotube interaction. Later surface oxygenation of the Ti particle is less important for the contact behaviour. This is because initial Ti deposition preferentially forms Ti-O bonds, strongly reducing the interaction between the Ti and the nanotube. Once there is no oxygen available the remaining Ti forms Ti-C bonds with strong interaction as seen in the large charge transfer.

The quality of the Ti-CNT electrical contact can be determined by the quality of vacuum under which it was formed and the amount of oxygen on the CNT surface i.e. initial CNT purity. These results can explain the wide discrepancy seen in transport behaviour of Ti-nanotube contacts found in the literature.

Although our results suggest ultra-high (10 -9 mbar) vacuums are necessary in order to obtain reproducible low resistance Ohmic Ti-nanotube contact, there may be ways in which lower vacuums could still be used. For example, the nanotubes should have their pre-existing oxygen content minimized via a pre-anneal, preferably once in the chamber. Oxygen contamination from oxide on the Ti source surface and residual gas in the chamber can be minimized by pre-deposition of sacrificial Ti away from the sample. Increasing the sputtering rate may also reduce exposure time to atmospheric oxygen. We emphasize that it is only oxygen at the Ti-nanotube interface which is important; later oxidation of the Ti surface should not affect contact properties.

The theoretical calculations predict mobility for Ti at temperatures not far above room temperature, so gentle surface heating during deposition (up to 100°C) may be sufficient to crystallize the Ti layer under vacuum (however Ti surface mobility is reliant on the absence of oxygen). A crystallized Ti layer should lead to significantly improved contact behaviour, and this is consistent with experimental studies of post-deposition heating which appear to promote TiC formation 22 .

Experimental Section

The samples were prepared using commercially available MWCNT powder synthesized by chemical vapour deposition 23 . Titanium was deposited onto the sample by e-beam evaporation from a Ti rod. The surface rod was cleaned of oxide by pre-sputtering onto a blanking plate. A quartz balance was used to calibrate the Ti evaporation amount. Samples 1-7 correspond respectively to 0.3, 1, 2, 5, 10, 20 and 100 Å nominal amounts of Ti deposition.

For the oxygen plasma pre-treated samples, the plasma treatment was carried out for MWCNTs on the carbon film support in order to avoid dispersion and post-treatment contamination. The plasma chamber is described elsewhere 24 . The treatment was performed inside the plasma glow discharge for 60 seconds with gas pressure of 0.1 Torr at 15 W 20 . TEM using a JEOL 3000F microscope operated at 300 kV was used to follow the metal deposition for increasing metal evaporated amounts. MWCNT produced by arc-discharge 25 were used for the TEM imaging. The MWCNT powder was dispersed in ethanol, and a drop of the solution was deposited on a lacey carbon film supported by a copper grid.

XPS measurements of the C 1s and Ti 2p core levels were performed at Hasylab at beamline BW2 using a photon energy of 3300 eV. The overall resolution of the system (source + analyzer) was 0.6 eV

26

. The Au 4f 7/2 peak at 84.00 eV, recorded on a gold sample reference was used for calibration of the binding energy scale. In order to check for any possible photon energy drift in the measurements, reference spectra were recorded before and after each core level data set recorded on all samples. To perform the XPS measurements, the MWCNT powder was pressed on a conductive adhesive tape suitable for ultra high vacuum. The thickness and the homogeneity of the CNT layer were checked to assure no interference of the tape on the measurements. From Figure 3 (inset) it can be seen that a porous CNT-film is formed. Additional XPS measurements reported in Figure 5 were performed using an SSI-100 spectrometer at a photon energy of 1486.6 eV. were used. Atom-centered Gaussian basis functions are used to construct the many-electron wave function with angular momenta up to l=2. Electronic level occupation was obtained using a Fermi occupation function with kT=0.04 eV. In the energetic analysis that follows, binding energies are defined as the difference in energy between the relaxed combined system and the isolated perfect graphite sheet and a single isolated metal atom unless stated otherwise. The diffusion barrier for Ti was determined by constraining the system symmetry and was confirmed as a saddle point by subsequent symmetry breaking and structural optimization which led to the ground state structure.

Density Functional calculation

27 , 28 within

 2728 the Local Density Approximation are carried out on a 8×8 supercell of graphene, i.e. a monolayer of 128 carbon atoms. Fully spin polarized single k-point calculations were geometrically optimized from multiple possible starting structures. Hartwigsen, Goedecker and Hutter (HGH) pseudopotentials 29

Figure 1 .

 1 Figure 1. HRTEM micrographs of (a) pristine MWCNTs, (b) 10 Å of Ti on pristine MWCNTs and (c) 10 Å of Pd on pristine MWCNTs . Scale bars are 10 nm long

Figure 2 .Figure 3 .

 23 Figure 2. Top and side view of the DFT optimized structures of one to four Ti atoms on graphene

Figure 4 .Figure 5 .Figure 6 .

 456 Figure 4. Subtracted XPS C 1s level of Ti decorated pristine nanotubes. The red, green, blue, cyan and magenta curves correspond respectively to sample 1, 2, 3, 4, 5. The C 1s level of pristine nanotube is shown for comparison (dotted curve).

Figure 7 .

 7 Figure 7. Evolution of Ti 2p core levels for increasing coverage of titanium on oxygen plasma treated MWCNTs

-Page No. The Interface between Titanium and Carbon Nanotubes Title

  Table of Contents (Please choose one layout)

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	ARTICLES
	Alexandre Felten, Irene Suarez-
	Martinez, Xiaoxing Ke, Gustaaf Van
	Tendeloo, Jacques Ghijsen, Jean-
	Jacques Pireaux, Wolgang Drube, Carla
	Bittencour ] and Christopher P. Ewels
	Page No.

Acknowledgements

This work is financially supported by the Belgian Program on Interuniversity Attraction Pole (PAI 6/08), ARC-UMH , by the EU FP6 project STREP "nano2hybrids", Reference 003311 and by DESY and the European Commission under contract RII3-CT 2004-506008 (IASFS). JG is a research associate of NFSR (Belgium).


Linh Duy Nguyen

Mohamed Ayman Kammoun

Minh Quang Bui

Philippe Sistat

André Deratani
email: andre.deratani@umontpellier.fr

François Zaviska

Optimization of a hybrid process combining Nanofiltration and Electrodialysis for the treatment of surface water in the Mekong Delta region

Keywords: Desalination, pesticide removal, hybrid process, optimization, experimental design method

The coastal area of the Mekong Delta is facing a huge problem of water supply quality due to pesticide (intensive agriculture) and salinity (sea water intrusion) contamination. Their simultaneous presence makes this water complex and requires advanced water treatment processes in order to meet the Vietnamese Guideline for drinking water quality. The objective of this work is to develop an efficient surface water treatment based on electrodialysis and nanofiltration technologies. The approach consists in using electrodialysis in a first stage for salinity removal to improve, in the second stage, the performance of nanofiltration for the

Introduction

Access to safe drinking water is one of the most important challenges facing the world today, especially in the rural area of Mekong Delta, Vietnam [START_REF] Grady | Who is being left behind? An analysis of improved drinking water and basic sanitation access in the Vietnamese Mekong Delta[END_REF]. The Mekong Delta region is famous for its abundant surface water resource from an interlacing network of rivers and canals [START_REF] Renaud | The Mekong Delta System[END_REF][START_REF] Whitehead | Water quality modelling of the Mekong River basin: Climate change and socioeconomics drive flow and nutrient flux changes to the Mekong Delta[END_REF]. Water quality in the main river channels is generally good since pollutants and contaminants are often diluted due to the enormous volumes of water. However, the surface water sources to which rural people have direct access for daily use come from smaller tributaries and canals near their homes. They contain a significantly higher concentration of pollutants and contaminants [START_REF] Ly | Surface water quality in canals in An Giang province, Viet Nam, from 2009 to 2016[END_REF][START_REF] Minh | Effects of multi-dike protection systems on surface water quality in the Vietnamese Mekong Delta[END_REF].

Pesticide pollution in the Mekong delta is due to the co-occurrence of recently used pesticides. Their residues were detected and frequently exceed the guideline concentrations in many rivers and canals. It has been reported [START_REF] Carvalho | Agrochemical and polychlorobyphenyl (PCB) residues in the Mekong River delta, Vietnam[END_REF] that the concentration of diazinon, and fenotrothion were from 0.003 to 0.043 µg/L in canal water samples near rice field. A study conducted in the two provinces of Can Tho and Dong Thap [START_REF] Pham | Pesticide management and their residues in sediments and surface and drinking water in the Mekong Delta, Vietnam[END_REF] has revealed the presence of commonly used pesticide residues at high concentration in the irrigation canals. In particular, isoprothiolane was detected in 100 % of the samples with the maximum concentration of 11.24 µg/L, followed by fenobucarb in 90.8 % of the samples with concentration ranging from 0.02 to 1.43 µg/L. Other pesticides with a high frequency in the sample analyzed were pretilachlor (68.9 %), buprofezin (58.7 %), fipronil (48.5 %) and propiconazole (45.9 %). The presence of these pesticides in canal waters in An Giang Province has also been reported with over 80 % of the samples containing more than five pesticides simultaneously and 95 % of samples exceeding the EC guideline value for concentration of total pesticides in drinking water (0.5 µg/L) [START_REF] Chau | Pesticide pollution of multiple drinking water sources in the Mekong Delta, Vietnam: evidence from two provinces[END_REF]. Based on the data presented above, the three most frequently detected pesticides were fenobucarb (an insecticide), isoprothiolane (a fungicide) and pretilachlor (an herbicide). These molecules were chosen for this study as representative of the pesticides that can be found in the surface waters of the Mekong Delta.

Before being used, rural people treat surface water by a basic method such as removing sediments with aluminium sulphate, followed by boiling. These procedures make the water appearance "cleaner", but they pose a potential threat to human health. It has been proved that boiling can remove most pathogens in water, but can actually increase the concentration of pesticides present [START_REF] Pham | Pesticide management and their residues in sediments and surface and drinking water in the Mekong Delta, Vietnam[END_REF]. In addition, some pesticides have also been detected at concentrations above the European Commission's guideline values for drinking water in some purchased bottled water, which is generally considered safer water, [START_REF] Chau | Pesticide pollution of multiple drinking water sources in the Mekong Delta, Vietnam: evidence from two provinces[END_REF]. Thus, more effective water treatment methods need to be implemented at the household level in Mekong Delta rural area.

Accordingly, the integration of two different membranes technologies, namely electrodialysis (ED) and nanofiltration (NF), has been proposed to treat surface water in the coastal area of the Mekong Delta [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF]. This original combination seems to be well suited for the treatment of complex water containing biological pollution, high salinity and a high concentration of pesticides. On one hand, NF is probably the most polyvalent membrane separation technique, which is characterized by a very high efficiency for the removal of biological compound, organic and inorganic compounds removal at a reasonable operating cost. NF is a membrane pressure driven process where pollutants are retained by both steric and electrostatic repulsion (Donnan) effect. Many applications for the treatment of water containing organic pollutants can be found in literature, such as the removal of pesticides and other micropollutants [START_REF] Miralles-Cuevas | Removal of pharmaceuticals from MWTP effluent by nanofiltration and solar photo-Fenton using two different iron complexes at neutral pH[END_REF][START_REF] Nghiem | Removal of natural hormones by nanofiltration membranes: Measurements, modeling, and mechanisms[END_REF][START_REF] Ormad | Pesticides removal in the process of drinking water production[END_REF][START_REF] Park | Chapter 6 -Attenuation of contaminants of emerging concerns by nanofiltration membrane: rejection mechanism and application in water reuse[END_REF][START_REF] Vergili | Application of nanofiltration for the removal of carbamazepine, diclofenac and ibuprofen from drinking water sources[END_REF][START_REF] Wang | A review of advances in EDCs and PhACs removal by nanofiltration: Mechanisms, impact factors and the influence of organic matter[END_REF], and that of pesticides and salts or inorganic pollutants at the same time [START_REF] Košutić | Removal of arsenic and pesticides from drinking water by nanofiltration membranes[END_REF][START_REF] Nikbakht Fini | The effect of water matrix, feed concentration and recovery on the rejection of pesticides using NF/RO membranes in water treatment[END_REF][START_REF] Qiu | Polycyclic aromatic hydrocarbons (PAHs) in the water column and sediment core of Deep Bay, South China[END_REF][START_REF] Sarkar | Potable water production from pesticide contaminated surface water-A membrane based approach[END_REF][START_REF] Thanuttamavong | Rejection characteristics of organic and inorganic pollutants by ultra low-pressure nanofiltration of surface water for drinking water treatment[END_REF][START_REF] Van Der Bruggen | Application of nanofiltration for removal of pesticides, nitrate and hardness from ground water: rejection properties and economic evaluation[END_REF].

Concerning more specifically the removal of pesticides by NF, the rejection efficiency strongly depends on the membrane characteristic (membrane cut-off, materials, hydrophilicity, electrical charge…), the nature of the pesticide molecule (size, hydration radius, electrical charge, steric configuration, hydrophilicity…) and also on the presence/concentration of other compounds such as salts and organic matter. In particular, it has been proven that salinity has a strong negative impact on organic micropollutant retention [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF][START_REF] Plakas | Membrane retention of herbicides from single and multisolute media: The effect of ionic environment[END_REF][START_REF] Ren | Influence of inorganic salt on retention of ibuprofen by nanofiltration[END_REF][START_REF] Zhang | Removal of bisphenol A by a nanofiltration membrane in view of drinking water production[END_REF]. This effect has been explained by pore swelling, decrease of solute hydrodynamic radius (Stokes radius), possibly due to partial dehydration, or a combination of the above [START_REF] Ren | Influence of inorganic salt on retention of ibuprofen by nanofiltration[END_REF][START_REF] Teixeira | The role of membrane charge on nanofiltration performance[END_REF][START_REF] Zhang | Removal of bisphenol A by a nanofiltration membrane in view of drinking water production[END_REF][START_REF] Zhao | Effects of inorganic electrolytes on zeta potentials of ceramic microfiltration membranes[END_REF]. On the other hand, ED can easily remove salinity by extracting ions through ion exchange membranes placed in an electrical field. Compared to other desalination membrane technologies based on pressure or thermal action, ED targets ions instead of the solvent. Therefore, ED is more energy efficient for treating water with salinity below 6 g/L [START_REF] Al-Karaghouli | Energy consumption and water production cost of conventional and renewable-energy-powered desalination processes[END_REF][START_REF] Patel | Energy Efficiency of Electro-Driven Brackish Water Desalination: Electrodialysis Significantly Outperforms Membrane Capacitive Deionization[END_REF] and much more flexible in terms of treatment. Indeed, the desalination rate can be adapted by simply adjusting the electrical charge and the hydraulic retention time. However, this technology cannot remove pesticides, as most of these substances are neutral and cannot be transported through the membrane by electrical force.

In a previous work [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF], the feasibility of the hybrid process coupling ED and NF for the treatment of surface water in the coastal area of Mekong Delta has been evaluated. In this context, ED has been proposed as a pre-desalination step during the dry season in order to improve the retention efficiency of pesticides in the subsequent NF stage and also to enhance the overall salinity retention. It was found that a tight NF membrane such as NF90 leads to produced water with a quality complying with the VN guideline for drinking water. As previously mentioned, the specific energy consumption of ED varies greatly with the quantity of salt to be extracted, whereas that of NF depends on the conversion rate. In order to develop an energy-efficient system in the context of an implementation in the rural area of the Mekong Delta, it is critical to optimize the energy consumption of both stages ED and NF.

The present report aims at proposing clues for optimizing the overall performance of the ED -NF integrated system in terms of pollutant removal and energy consumption for treatment of matrices as complex as surface water in the Mekong Delta. The challenge in optimizing the hybrid ED-NF process is that the performance of the first stage significantly affects the efficiency of the second stage and then the cost of the overall process. For example, if the salinity of the feed water was not sufficiently removed by ED, the pesticide removal capacity by NF would be remarkably reduced due to the swelling effect of the membrane pores [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF]. Otherwise, the energy consumption of ED would increase, if the TDS concentration of the diluted compartment continued to decrease. Thus, each operation parameter in the two stages is influenced by the others. In other words, the hybrid system is a non-linear system, in which the outputs must involve not only the relationship with single parameters, but also the interaction or combination between the parameters. The biggest problem in the application of non-linear methods to solve such systems arises from the often extreme sensitivity to noise (experimental measurement uncertainties) and the difficulty in choosing a good non-linear fitting function in the absence of a suitable physical model. Linear methods are more robust, less sensitive to noise, simpler to implement, and can lead to reasonable predictions for quantities by getting the trends right, although finer details may be lost by using a linear method for an inherently nonlinear system Therefore, in order to determine the best compromise between removal efficiency and energy consumption, a multi-variable analysis based on response surface design was used to optimize the whole ED -NF system. Experimental design methodology (RSM) is a statistical tool than can be used to accurately assess the effect of the main parameters affecting each step as well as the interactions between the parameters of the entire hybrid process [START_REF] Mäkelä | Experimental design and response surface methodology in energy applications: A tutorial review[END_REF].

However, such a methodology may require a large number of experiments depending on the number of parameters involved. A specific approach was developed in order to minimize the number of experiments while maintaining a sufficient degree of information for accurate experimental modelling. Based on the developed models, an optimization was carried out taking into account the efficiency in terms of desalination rate and pesticide removal as well as the operating cost (energy consumption and membrane surface area). The optimal conditions determined by the modeling were then validated experimentally.

Materials and methods

Chemicals

All pesticides, organic solvents and inorganic salts used in this study were obtained from Sigma Aldrich at the analytical grade. Stock solutions of the pesticides isoprothiolane, fenobucarb and pretilachlor were prepared in acetonitrile/water (50:50) at a concentration of 1000 mg/L and stored at 4 °C. Milli-Q water (at 18 MΩ.cm -1 ) was used for the whole experiment.

Synthetic Mekong Delta surface water

Ion composition of the synthetic Mekong Delta solution is shown in Table 1. These ion concentrations correspond with their concentration at median values in the Mekong Delta surface water in coastal areas during the dry season [START_REF] Nguyen | Current status of surface water in the Mekong Delta, Vietnam: Threats for drinking water supply and treatment technologies[END_REF]. The pesticide concentrations in the synthetic solution were 300, 300 and 1000 ppb for fenobucarb, isoprothiolane and pretilachlor, respectively. These concentrations were chosen based on the instrument limit detection, so that pesticide residues in the permeate could be determined with enough accuracy, even if removal values are greater than 95%. The pH of the solution was 5.9 -6.2.

Membranes selection

In the ED stage, the PC-SK and PC-SA membranes (PCA GmbH, Germany) were chosen as cation and anion exchange membranes, respectively, while in the NF stage, NF90 (Dow-Filmtech, DuPont Water Solutions, USA) was used. The latter membrane was selected to achieve the best compromise in terms of salinity rejection, pesticide rejection and permeability [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF].

Pesticide and ions analysis

Pesticide concentration was determined by direct injection liquid chromatography with tandem mass spectrometry method (DI-LC/MS/MS) by using Waters instruments (Wythenshawe, Manchester, UK). The analytical conditions and the detection limit were described in a previous study [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF].

The ion concentration was determined by ion chromatography (ICS-900, Dionex) and the conductivity was measured by a conductivity meter (Cond 315i, WTW).

ED -NF integrated membrane experiments

The membrane set-up and the operating procedures were similar to those used in a previous report [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF].

ED stage

The ED experiments were carried out on a PCCell ED 64-004 cell (PCA GmbH, Heusweiler, Germany) with 7 pieces of the PC-SA and 8 pieces of the PC-SK and a pair of electrodes made of Pt/Ir-coated titanium. The active membrane area was 64 cm 2 . Flow paths of the diluate stream (referred to as ED permeate in this study) and concentrate stream were formed by plastic spacers between the membranes with width of 0.5 mm and their flow rate were maintained at 0.5 L/min. Initial concentrate stream was filled with 0.8 L synthetic solution.

One liter of Na2SO4 0.2 mol/L solution was used as the electrode rinsing solution with flow rate maintained at 1.0 L/min.

ED operating conditions for ED, including applied voltage (V), which is controlled at a constant value during each experiment, permeate volume (L) and processing time (min), were setup for each experiment in the Box Behnken design.

NF stage

The NF stage was carried out in an NF pilot equipped with an Osmonics Sepa CF II cell (Sterlitech Corp., Kent, WA). The NF90 membrane coupons of 140 cm 2 surface area were rinsed and conditioned at 15 bar during 1 hour inside the NF pilot before being used. Then, the tank of the NF pilot was filled with 5 L of feed solution and the experiment was performed. The NF operating conditions such as applied pressure (bar), feed concentration (mg/L) and NF processing time (min) were setup for each experiment in the Box Behnken design. The feed solution temperature was kept constant at 25.0 ± 0.5 °C. The membrane rejection R was calculated from the pesticide concentration in the feed solution and the permeate according to equation 1:

= 1 - × 100 (1)
where Cp and Cf are the concentration of pesticides (mg/L) in the permeate and the feed solution, respectively.

Energy consumption calculation

In this study, one of the important parameters for evaluating process efficiency is energy consumption.

The specific energy consumption (SEC) often used to characterize the energy cost of the NF process is the energy (from pump) needed to produce one cubic meter of permeate at the desired water recovery. SECNF of the pump in kWh/m 3 is calculated by equation 2:

= ∆ (2)
where ∆P is the trans-membrane pressure (bar); η is the pump efficiency, assumed to be 0.8 in this study; γ is the water recovery by the process and equals the ratio of the volume of the permeate and the feed obtained after each experiment.

In the ED process, the electrical energy is consumed by the ED cell and the solution circulation pumps. In this study, only the energy consumed by the ED cell was taken into account, assuming that the consumption of pumps contributed negligibly to the overall energy consumption under the operating conditions.

The specific energy consumption of the ED cell (SECED, in kWh/m 3 ) for the transfer of ions is the definite integral of the voltage and current with respect to time t, as follows:

= (3)
In fact, ED was carried out at constant voltage in this work. Based on the experimental data of the total voltage and current recorded at time t, the specific energy consumption of the stack can then be calculated using equation 4:

= (4)

Optimization of the ED -NF coupled process with the Box-Behnken experimental design

It has been pointed out previously that the performances of these two processes are interconnected. The extent to which the first stage removes salts, will inevitably influence the efficiency of the second stage and the cost of the entire process. Therefore, a compromise must be found between these two processes. At which desalination rate should ED be carried out in order to provide a sufficient pesticide removal in NF step and sufficient overall desalination rate to satisfy the VN guideline at a reasonable cost? To answer this question, a specific Response Surface Methodology (RSM) was applied: the Box Behnken Design (BBD) [START_REF] Myers | Response Surface Methodology: Product and Process Optimization Using Designed Experiments[END_REF]. Using this methodology, the process can be described (by modeling) taking into account the interaction between the parameters. Moreover, a precise optimization can be achieved using the developed mathematical model considering both the efficiency and the cost of treatment. Box and Behnken have developed a family of efficient three-level designs for fitting second-order response surface methodologies [START_REF] Myers | Response Surface Methodology: Product and Process Optimization Using Designed Experiments[END_REF]. The methodology of design is interesting and quite creative. The class of design is based on the construction of the balanced incomplete block designs. In the BBD, each pair of factors is linked in a 2 2 factorial (scaling ± 1) while the other ones remain fixed at the center of the experimental region investigated. Five experiments in the center of the domain are also required in order to determine the experimental error (pure error) which could be compared with the lack of fit, the error attributed to the inadequacy of the developed models. The number of assays (Na) required can be calculated using equation 5:

! " = (2 % × & × (& -1) 2 ⁄ ) + 5 (5)
where n is the number of variables. It has to be noted that the number of experiments is at the "power" of the number of parameters.

In this study, only the main parameters affecting ED and NF were considered such as applied voltage, product volume and treatment time for the ED stage and applied pressure, feed concentration and operating time for the NF stage.

However, the ED and NF processes are linked since the NF feed solution corresponds to the ED permeate. Then, a total of 5 parameters should be taken into account for the entire hybrid process, which would lead to a large number of experiments (Na = 45). Therefore, in order to limit the number of experiments, these two processes were study (modeling) independently, first the ED stage then the NF stage. The ED results were used to define the experimental region of the NF process. Once the mathematical models for each process were validated, another Box Behnken matrix was developed coupling the two processes. In that case, the responses of this matrix were not experimentally recorded but rather extracted from the two previously validated models. In addition to reduce the number of experiments, such strategy is a step by step method allowing adjustment in case of unsuitable results (out of the scope of this study).

The experimental region investigated for both ED and NF processes and the coded values are

shown in Table 2. The experimental data were analyzed using Design-Expert 8 software including ANOVA in order to obtain the interactions between the process variables and to evaluate the accuracy/correctness of the mathematical model. As mentioned above, three input parameters, including voltage (X1), permeate volume (X2) and treatment time (X3), were taken into account in the case of ED for the modeling. Water recovery (Y1), TDS concentration of the diluted compartment (Y2) and SECED (Y3) were recorded as responses. For the NF stage, the input parameters were applied pressure (X4), TDS concentration (X5) and treatment time (X6). Similarly, water recovery (Y4), permeate TDS concentration (Y5) and SECNF (Y6) were recorded as responses with the addition of pesticide removal (Y7). For the ED stage, the water recovery (Y1) was calculated by the ratio between the ED permeate volume (X2, in L) and the total volume of the synthetic solution used in the permeate (X2) and concentrated tanks (Vc, in L) as shown in Equation 6.

+ , = -. -. /01 (6)
For the NF stage, the water recovery (Y4) was calculated based on the feed volume (Vf, equal to 5 L) and the permeate (Vp, in L) obtained after a batch experiment according to Equation 7:

+ 2 = 0 0 (7)
The total water recovery of the coupled ED -NF process is then equal to:

+ 3 = + , × + 2 (8)

Energy consumption calculation

In the ED process, the energy consumption comes mainly from the electrical energy required by the stack (Equation 4). The SECED (Y3) is therefore inversely proportional to the volume of permeate produced (X2, in L):

+ = 4 -. -5 6 (9)
where the definite integral of current with respect to time from the beginning of experiment (t0 = 0) to the treatment time as mentioned in Table 2 (t = X3, in min).

In the NF process, the specific energy consumption (Y6) was calculated according to Equation 2. Thus, the overall specific energy consumption of the integrated process (Y10) is equal to the sum of specific energy consumption of the two stages:

Y10 = Y6 + Y3 (10)

Results and discussion

A feasibility study of an innovative process for treating surface water in the Mekong Delta containing both high salinity and pesticides has been previously conducted [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF]. Only one NF stage is not able to reject pesticides to the level necessary to meet the Vietnamese guideline for drinking water when the salinity is too high. For this reason, it has been proposed to couple NF with a pre-desalination stage by ED ensuring about 50% of salt removal. As a result, a permeate water complying with the Vietnamese guideline for drinking water was produced with a recovery in the range of 30-50% depending on the initial salinity.

In addition, the specific energy consumption of the NF stage could be reduced due to the lower salinity of the input water. By contrast, the energy consumption of the ED stage is heavily dependent on the quantity of salt to be removed. Therefore, the crucial issue for the feasibility and perspective of ED-NF hybridization is the optimization of the obtained performance in terms of quality and recovery with respect to the consumed energy in each stage. In order to determine the best compromise, a response surface design was used.

Electrodialysis process modeling

In this section, ED process is described using a BBD design. The data, including natural levels, design, and responses values, are shown in Table S1.

The experimental design consisted of 12 experiments, where each pair of factors is linked in a 2 2 factorial (assays 1-12) plus five additional assays conducted at the center of the experimental region investigated (assays 13-17). Water recovery depends exclusively on the permeate volume and was varied from 50 to 75% (model not shown). Under these conditions, the experimental TDS concentration (Y2) in the ED permeate ranged from 322 to 4287 ppm, corresponding to a desalination efficiency varying from 94.6% to 28.6%. On the other hand, the corresponding calculated SECED (Y3) ranged from about 3.87 to 0.60 kWh/m 3 .

The regression models for Y2 and Y3 can be expressed (in terms of coded variables) by the following second-order polynomial equations:

+ % =
The coefficients of the polynomial model (quadratic model) were calculated using the Design-Expert® V11 program software. Their respective weights presented in Figure S1 (Appendix A) show that X2 (permeate volume) is the most prominent factors affecting ED desalination (Y2) followed by the treatment time (X3) and the applied voltage (X1). Concerning SECED (Y3), the applied voltage (X1) is the most relevant parameter, which is logical because it is a square effect factor on this response (according to the Ohm's law, intensity is proportional to voltage). Obviously, the processing time (X3) is also a very important factor impacting the energy consumption as well as the permeate volume (X2). Considering the interactions between the different parameters, voltage and treatment time interact significantly with each other (X1X3) on the desalination efficiency, since the amount of salt transported from the permeate compartment to the concentrate compartment is governed by the electrical charge which is simply the product of current intensity (consequence of the voltage) and time. The same interaction can be observed in the Y3 modelling (energy consumption) because the dissipated power is the product of the electrical charge and the voltage. There is also a strong interaction between voltage and permeate volume, X1X2 on energy consumption. This can be explained by the fact that during the ED process, the overall resistivity of the system increases with the treatment time (due to the decrease in salinity of the permeate compartment) leading to a decrease of the resulting intensity. The reduction in conductivity is related to both treatment time and permeate volume. The smaller the permeate volume, the larger the drop in intensity (lower overall electrical charge). This phenomenon is even more pronounced when the desalination rate is high, that is when the treatment time is longer. In other words, at constant voltage (potentiostatic mode), the lower the permeate TDS concentration, the lower the applied electrical charge and the slower the desalination rate. Under such operating conditions (constant voltage), the desalination rate is self-limited contrary to the case of the galvanostatic operating mode.

The analysis of variance (ANOVA) of regression parameters of the predicted response surface quadratic models for the two Y2 and Y3 outputs shows that both models have a high Fisher coefficient value (F value) and a low probability value (Pr >F < 0.0001) indicating that they are significant (Table 3). Correlation coefficient (R 2 = 0.9895 for Y2 and R 2 = 0.9944 for Y3)

indicate that only ~ 1 % of the total variation could not be explained by the empirical model.

It can be noted that according to [START_REF] Joglekar | Product excellence through design of experiments[END_REF], a good model fit should have an R 2 value of at least 0.80. Figure 1 and Figure 2 show the 3D contour plot for Y2 and Y3 respectively with the corresponding correlation between actual values versus predicted values. For both responses, the experimental (actual) values fit very well with the predicted values, which demonstrates a very good adequacy of the models. From the 3D contour plot of Y2, it can be observed that the effect of the treatment time is accentuated at high voltage and vice versa (X1X3 interaction).

Likewise, the strong interaction between the applied voltage and the permeate volume (X1X2) can be easily observed in the 3D contour plot of Y3 (Figure 2). A). Table 4 shows the analysis of variance (ANOVA) of the regression parameters of the predicted quadratic response surface models for the NF stage : water recovery (Y4), TDS permeate concentration (Y5), SECNF (Y6) and pesticide removal (Y7). All four model equations are significant with negligible lack of fit. The regression coefficients R 2 are above 97%

(except for Y7) with a quite closed value of adjusted R 2 and predicted R 2 . The model equation for Y7 is not as accurate as the other models (R 2 = 0.864) but remains valid and significant (J [START_REF] Joglekar | Product excellence through design of experiments[END_REF]. This observation can be easily explained. In fact, the small lack of adjustment was attributed to the narrow range of the obtained experimental values (approaching the analytical error) and also because only one parameter, the TDS concentration, significantly impacts the pesticide rejection. Indeed, TDS concentration has a very strong impact on pesticide removal and affects the responses (Y7) with a contribution over 99%, which is in agreement with the previous observation [START_REF] Nguyen | Desalination and removal of pesticides from surface water in Mekong Delta by coupling nanofiltration and electrodialysis[END_REF].

Concerning water recovery (Y4), the most influential factor is the pressure applied (X4), closely followed by the salinity of the NF feed solution (X5,). These two parameters have antagonist influence on the water flow rate because they are related to the effective driving force and thus strongly affect the water recovery (for a given treatment time) (equation 7).

Hence, these two parameters are interrelated, which can be observed by the strong interaction X1X2 in the Y4 model. andX6), the TDS concentration in the permeate is therefore mainly related to the feed concentration (X5) (the higher the feed concentration the higher the permeate concentration will be). Hence, this parameter has a huge impact on the response (Y5), which has the consequence of mitigating strongly, in the model, the effect of the two others parameters.

Pressure (X4) has the effect of increasing both water flux (increase in driving force) and solute flux (increase of concentration polarization and concentration factor). However, the dilution effect due to an increased water flux is predominant leading to an increase in overall retention with rising pressure (X4 has a negative effect on Y5). Similarly, treatment time (X6) determines the concentration factor (water recovery) but also leads to an increase of the salinity gradient between the feed and the permeate side.

The salinity gradient decreases salt retention, so X6 has a positive effect on the response Y5.

Finally, SECNF is mainly influenced by both salinity (X5) and treatment time (X6). Salinity decreases the effective driving force (increase of osmotic pressure) leading to a water flux decline (at the identical pressure) and thus positively impacts the SECNF value. In another respect, it was pointed out previously that the longer the treatment time, the higher the water recovery and consequently the lower the SECNF. Moreover, as pressure and initial salt concentration determine the effective driving force, it is normal to observe a strong interaction between these 2 parameters.

the hybrid ED/NF system SEC (Y10). In addition, since the two processes are interrelated, interactions between the parameters of the two processes can also be observed especially in the case of Y8 where cross coefficients between X2 and X3 of the ED stage and X5 and X6 have a significant influence. The optimization of the overall hybrid process was carried out by applying specific criteria in order to comply the Vietnamese regulations (QCVN 01-1:2018/BYT, 2018) regarding the concentration of pesticides, sodium and chloride while minimizing the operating cost (energy consumption and membrane surface area) and the investment cost (ED cells and NF membrane modules).

The criteria selected for the optimization of the entire hybrid system are the following:

(1) The TDS removal should be maximized (importance 3/5)

(2) The overall water recovery should be maximized (importance 3/5)

(3) The overall SEC should be minimized (importance 3/5) (4) Chloride and sodium concentrations (Y11 and Y12) have to be in the range of 50 to 250 ppm.

Moreover, in a more forward-looking perspective of system scaling up, it is necessary to take into account in addition to the energy consumption, the investment and operating costs related to the number of ED cells and the membrane surface area for each process (ED and NF). This dimensioning aspect is directly related to the hydraulic retention time (HRT) which is, in this case, dependent on the treatment time of each process. As a consequence, a fifth criterion was chosen corresponding to the system dimensioning:

(5) Minimization of the processing time for both ED and NF (importance 1/5).

It has to be noted that these criteria were selected in order to obtain a cost-effective hybrid process but it could be modified to adjust the configuration and the operating conditions more precisely according to the local constraints such as footprint, energy cost, membrane availability…. Based on the five criteria defined above, the Design Expert V11 software proposed the best solution (Table 5) in terms of desirability (best compromise to satisfy the applied criteria) with a value close to 80%.

The experiments carried out under the optimal conditions deduced from the modeling gave experimental results in good agreement with the predictions allowing to validate this optimization approach. It can be seen that the desalination rate is higher than expected in the ED stage, implying an overconsumption of energy, and that the conversion rate is lower in the NF stage, probably due to the uncertainty of the pressure measurement related to the gauge used (± 0.1 bar). In addition, the multivariable-linear analysis used for this non-linear system can lead to small deviations between the predicted and experimental values, as mentioned above.

Nevertheless, the observed deviations are acceptable with values of about 8% and 10% on overall productivity (Y8) and specific energy consumption (Y10), respectively. Correlatively, water was produced with a better quality due to higher rejection of salts and lower conversion rate during the ED and the NF stages, respectively. S5). Table 6 summarizes the experimental ionic composition of the feed and permeates at each stage of the hybrid ED/NF system. Since monovalent ions constitute the majority ions in the feed, they dominate the TDS rejection rate. The rejection of about 90% observed for monovalent ions by the NF90 membrane is in agreement with the values found in the literature [START_REF] Kammoun | Nanofiltration performance prediction for brackish water desalination: Case study of Tunisian groundwater[END_REF]. The near quantitative rejection of sulfate ions in the NF stage counterbalances the low removal of these ions in the ED stage, demonstrating the complementarity of the two processes.

Table 6

Experimental ionic composition of the feed and permeates at each stage of the hybrid process. Overall desalination rate 95.4

Chloride

The experimental validation showed that the desalination rate reached about 95% for the overall hybrid system. Operating conditions achieved a salinity of less than 3.5 g/L after the ED stage, which is low enough for the subsequent NF treatment to meet Vietnamese guidelines for sodium and chloride concentration and to remove about 99% of total pesticides.

During the dry season in 2020, the saline intrusion, with a salinity rate of 4 g/L can move up to 50 -130 km from the river mouth inside the delta [START_REF] Loc | Intensifying saline water intrusion and drought in the Mekong Delta: From physical evidence to policy outlooks[END_REF]. More generally, it forms a wide strip of land whose salinity is between 1 and 10 g/L from January to April making the surface water undrinkable [START_REF] Ly | Surface water quality in canals in An Giang province, Viet Nam, from 2009 to 2016[END_REF][START_REF] Whitehead | Water quality modelling of the Mekong River basin: Climate change and socioeconomics drive flow and nutrient flux changes to the Mekong Delta[END_REF]]. In fact, salinity varies with peaks during the months of February and March depending on the tide amplitude and the river discharge [START_REF] Tuan | Flood and salinity management in the Mekong Delta, Vietnam[END_REF]. When the salinity is below about 3 g/L, a single stage with a tight NF membrane (like NF90) [START_REF] Kammoun | Nanofiltration performance prediction for brackish water desalination: Case study of Tunisian groundwater[END_REF] is sufficient to obtain drinking water that meets the Vietnamese standards in terms of both desalination and pesticide removal. Beyond this value, ED/NF integration in a hybrid process becomes necessary.

However, as can be seen in Table 5, the ED desalination stage contributes predominantly to the energy consumption of the hybrid system in the case studied (TDS of about 5 g/L). This contribution strongly depends on the amount of salt to be removed in order for the NF stage to effectively remove pesticides: the greater this amount, the higher the energy consumption of ED. This hybrid process will therefore become prohibitively expensive if salinity is very high (in coastal areas for example) or if salinity peaks of high intensity occur and last for a long time.

Conclusion

The complexity of Mekong Delta surface waters due to the simultaneous presence of high levels of pesticides and salinity requires the use of advanced treatment techniques such as membrane technologies to secure the water supply for the living population in the rural areas of the Delta. In this work, a hybrid process was developed combining ED as a preliminary treatment to reduce salinity and NF for the removal of pesticides and residual salinity. The

Figure 1 a

 1 Figure 1

Figure 2 a

 2 Figure 2

Table 1

 1 Ion composition (mg/L) of the synthetic salt solution

	Ion composition	Na +	Mg 2+	Ca 2+	Cl -	SO4 2-	TDS
	Concentration (mg/L)	1721	258	59	3197	459	5693

Table 2

 2 Box Behnken Matrix: Experimental range and levels of independent variables for ED and NF processes expressed in coded (Xi) and real values (Ui)

		Coded	Factor (Ui)	Experimental field
		variables (Xi)		Minimum	Maximum	U	i	,	0	i U Δ
				value (-1)	value (+1)
		X1	U1 : Applied Voltage (V)	6	10	8			2
	ED	X2	U2 : Permeate volume (L)	0.8	2.4	1.6			0.8

Table 3

 3 ANOVA for TDS concentration in ED permeate (Y2) and SECED (Y3)

	Source		Analysis of Variance (ANOVA)
		df	Sum of Square Mean of Square	F value	Pr>F
	ANOVA results of Y2	R 2 = 0.9895 ; adjusted R 2 = 0.9832 ; predicted R 2 = 0.9756
	Model	6	1.983E+07	3.305E+06	157.44	< 0.0001
	Residual	10	2.099E+05	20990.51
	Lack of Fit	6	69163.48	11527.25	0.3276	0.8923
	Pure error	4	1.407E+05	35185.40
	ANOVA results of Y3	R 2 = 0.9944 ; adjusted R 2 = 0.9901 ; predicted R 2 = 0.9701
	Model	8	12.14	1.52	187.66	< 0.0001
	Residual	8	0.0647	0.0081
	Lack of Fit	4	0.0487	0.0122	3.04	0.1532
	Pure error	4	0.0160	0.0040

Table 5

 5 Predicted and experimental responses obtained from the optimal conditions deduced from the modeling.

			ED				NF
	Optimal parameters	X1	X2	X3		X4		X5
		9 V	2.4 L	27.1 min	11.1 bar		4.38 h
			ED				NF
		Y1	Y2	Y3	Y4	Y5	Y6	Y7
	Responses	(YED)	TDS ED permeate	SECED	(YNF)	TDS removal	SECNF	pesticide removal
		%	mg/L	kWh.m -3	%	%	kWh.m -3	%
	Predicted	75	3382	1.36	72	90.4	0.53	96
	Experimental	75	3233	1.56	66	91.9	0.57	> 99
				ED -NF hybrid system
		Y8	Y9		Y10	Y11	Y12
	Responses	(Ytot)	removal) (total TDS		(total SEC)	[Cl -]	[Na + ]
		%	%		kWh.m -3	mg/L	mg/L
	Predicted	54	94.5		1.89	186	114
	Experimental	50	95.4		2.13	158	100
	Desirability				78.5%
	The evolution of conductivity during the ED stage and of conductivity and permeate flux
	during the NF stage are presented in Appendix A (Figures S4 and

Institute of Environmental Technology, Vietnam Academy of Science and Technology (IET-VAST), Hanoi, Vietnam.

Acknowledgment

The authors are grateful for the financial support of this work provided in part by the Vietnamese government (VIED-Vietnam International Education Development-Project 911) by the University of Science and Technology of Hanoi (USTH) and Campus France (Linh Duy Nguyen's grant).

Nanofiltration process modeling

The NF stage was described using the same BBD approach. The applied pressure (X4), the TDS concentration in the ED permeate (X5) and the treatment time (X6) were considered as the main parameters of this study. Similarly, the water recovery (Y4), the TDS concentration in the NF permeate (Y5) and the SECNF (Y6) were recorded as responses with in addition the pesticide removal (Y7). The data, including natural levels, design, and responses values for the NF process, are shown in Table S2. Based on the experimental input matrix, the water recovery (Y4) varies from 26.6 to 86.1% (mean at 63.5%), the TDS concentration (Y5) which is the result of the two processes (ED + NF) varies from 22.3 to 541.3 ppm (mean at 155.9 ppm), and SECNF (Y6) from 0.304 to 0.912 kWh.m -3 (mean at 0.156 kWh.m -3 ). Regarding the pesticide removal (Y7), it was calculated from the mean of the three pesticides (fenobucarb, isoprothiolane and pretilachlor). Whatever the experimental condition, the concentration of isoprothiolane is below the detection limit corresponding to a rejection of more than 99.5%.

Fenobucarb and pretilachlor follow the same trend with a retention ranging from 89 to 99.9%.

The regression models for Y4, Y5, Y6 and Y7 can then be expressed (in terms of coded variables) by the following equations:

Coupling the ED and NF process: optimization

The objective of this section is to describe using modeling the entire hybrid system combining ED and NF in order to optimize the process in term of efficiency (salt and pesticide removal)

and energy cost. Based on the models developed in the previous section for both ED and NF, another experimental matrix was realized coupling the two stages. As mentioned above, the experimental data of this matrix are deduced from the previously developed models for each stage, considering for each experiment that the ED permeate is subsequently treated by NF.

The same parameters and ranges were taken into account except for the NF feed concentration which is the results (outlet) of the ED stage. The ED-NF Box Behnken matrix including experimental condition and results is provided in Appendix A (Table S3).

Additional responses were included, such as the overall water recovery (Y8), TDS removal (Y9) and specific energy consumption (Y10). Y8 and Y9 are the product of the water recovery (Equation 8) and TDS removal of each stage respectively whereas the total specific energy consumption (Y10) is the sum of SECED and SECNF (Equation 10). In addition, since sodium and chloride are the majority ions (due to sea water intrusion), their concentrations could exceed the Vietnamese regulations and should be considered as responses for the optimization (Y11 and Y12 for chloride and sodium respectively).

+

Because these models were developed based on the results predicted from the previous validated models (for each process independently), they can be considered significant. The respective values of coefficients in Equations 17-21 presented in Figure S3 (Appendix A)

show that the treatment time (X6) and feed TDS (X5) of the NF stage are predominant factors for water recovery (Y8) while the applied voltage (X1), permeate volume (X2) and treatment time (X3) of the ED stage are the predominant factors for total TDS removal (Y8), and residual chloride (Y11) and sodium (Y12) ions in the purified water. As expected, SECED (Y3) dominates efficiency of pesticide removal by NF is highly dependent on the TDS concentration and thus on the performance of the preliminary ED stage. This study highlighted the following points:

• By using a specific surface response methodology, modeling of the entire hybrid system can be performed in terms of water quality (overall desalination and pesticide removal) and energy consumption.

• The experimental operating conditions resulting from the modeling confirmed the predicted performance of the coupled ED/NF system with water quality in compliance with Vietnamese regulations and a maximum deviation of about 8% and 10% on the conversion rate and energy consumption, respectively.

• It should be noted that the models developed using the experimental design methodology are only relevant to the experimental domain explored.

• Future works may consist of verifying the optimized conditions of the ED/NF process by applying it to real surface waters of the Mekong Delta. On the other hand, the integration of photovoltaic solar panels could make it possible to obtain an ecofriendly and autonomous system operating at low energy costs.

Such a treatment strategy could be a safe and reliable solution to provide drinking water during the dry season for remote population living in the Mekong Delta. This could also benefit many other agricultural and coastal area regions in the world where dry and rainy season become more and more pronounced due to climate change, resulting in severe drought and seawater intrusion.

Declaration of competing interest

The authors declare that they have no known competing financial interest or personal relationship that could have appeared to influence the work reported in this paper.

Graphical abstract

Optimization of a hybrid process combining Nanofiltration and Electrodialysis for the treatment of surface water in the Mekong Delta region

Linh Duy Nguyen 1,2 , Mohamed Ayman Kamoun 1 , Minh Quang Bui 2 , Philippe Sistat 1 , André Deratani 1 , François Zaviska 1