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Investigation of water desalination/purification with molecular dynamics and machine learning techniques

  • Received: 03 September 2022 Revised: 14 October 2022 Accepted: 25 October 2022 Published: 09 November 2022
  • This paper incorporates a number of parameters, such as nanopore size, wall wettability, and electric field strength, to assess their effect on ion removal from nanochannels filled with water. Molecular dynamics simulations are incorporated to monitor the process and a numerical database is created with the results. We show that the movement of ions in water nanochannels under the effect of an electric field is multifactorial. Potential energy regions of various strength are formed inside the nanochannel, and ions are either drifted to the walls and rejected from the solution or form clusters that are trapped inside low potential energy regions. Further computational investigation is made with the incorporation of machine learning techniques that suggest an alternative path to predict the water/ion solution properties. Our test procedure here involves the calculation of diffusion coefficient values and the incorporation of four ML algorithms, for comparison reasons, which exploit MD calculated results and are trained to predict the diffusion coefficient values in cases where no simulation data exist. This two-fold computational approach constitutes a fast and accurate solution that could be adjusted to similar ion separation models for property extraction.

    Citation: Christos Stavrogiannis, Filippos Sofos, Theodoros. E. Karakasidis, Denis Vavougios. Investigation of water desalination/purification with molecular dynamics and machine learning techniques[J]. AIMS Materials Science, 2022, 9(6): 919-938. doi: 10.3934/matersci.2022054

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  • This paper incorporates a number of parameters, such as nanopore size, wall wettability, and electric field strength, to assess their effect on ion removal from nanochannels filled with water. Molecular dynamics simulations are incorporated to monitor the process and a numerical database is created with the results. We show that the movement of ions in water nanochannels under the effect of an electric field is multifactorial. Potential energy regions of various strength are formed inside the nanochannel, and ions are either drifted to the walls and rejected from the solution or form clusters that are trapped inside low potential energy regions. Further computational investigation is made with the incorporation of machine learning techniques that suggest an alternative path to predict the water/ion solution properties. Our test procedure here involves the calculation of diffusion coefficient values and the incorporation of four ML algorithms, for comparison reasons, which exploit MD calculated results and are trained to predict the diffusion coefficient values in cases where no simulation data exist. This two-fold computational approach constitutes a fast and accurate solution that could be adjusted to similar ion separation models for property extraction.



    Most climate change scenarios have shown that different regions and ecosystems are more or less susceptible to rising temperatures, declining snow cover and changing precipitation patterns. River and delta ecosystems have been heavily modified around the world through urbanization, agriculture, damming, channelization, deforestation, mining, industry and fisheries [1]. The changes have been essential for human settlements and development, but have had a dramatic impact on water flows and coastal (terrestrial and maritime) habitats over time [2]. These global changes are expected to be exasperated in the future by climate change, with potential consequences including losses of ecosystem services, economic and social crises and important human migration [3,4].

    It has been shown that predisposition to take up mitigation and adaptation strategies, as well as to support and urge governments to do the same, is often related more to the perceived levels of threats as opposed to real risks [5]. The perception of threat may intensify or diminish depending on psychological, social, institutional and cultural factors. This is strongly related to information transmission mechanisms (direct and indirect communication), personal understanding of causes and effects, past experiences, and cultural beliefs [6]. Environmental risk studies have shown that people draw conclusions about abstract phenomena such as climate change based upon their observed and lived experiences [7]. This may cause people to give more validity to personal experiences over official information sources [8]. Research has shown that climate change concern is often motivated by contextual factors including national prosperity, media coverage, local political action and information sources and by individual factors such as political orientation, education, beliefs, and cultural views [9]. All these aspects contribute to the personal perception of risk, and may increase people's willingness to take action to reduce risks related to climate change and to adapt to new conditions [10]. In order to better apprehend how to address climate change in Europe's Mediterranean deltas, this article focused on three questions: (ⅰ) How do the different populations perceive climate change in their deltas? (ⅱ)What are the main sources of information concerning climate change? and (ⅲ) How do the participants integrate climate changes into their current living conditions?

    Deltas are wetlands that have been formed from accumulations of river-derived sediments adjacent or in close proximity to the source stream [11]. The main natural factors controlling the evolution of deltas are: (ⅰ) size, morphology and geology of the watershed, coastline and sedimentation basin; (ⅱ) climate, precipitation and river discharge and (ⅲ) hydrology, waves, tides and currents. Natural river sediment discharge in the Mediterranean basin is estimated at approximately 1000 million tons per year. Over the last centuries, human activities have greatly impacted these sediment discharges [12]. Massive constructions of reservoirs have caused ~45% of the sediments to be retained behind dams or extracted from river beds for sand and gravel [13]. Problems in sediment balance lead to coastal erosion, creating one of the most important issues along Europe's Mediterranean [13] coasts. These anthropogenic changes have greatly modified the functioning of deltas creating changes in the existing geology of the coastal area with impacts on human populations and biodiversity [14].

    Temperatures in the Mediterranean basin have been estimated as ~1.3 ℃ higher than the end of the 19th century [15]. In addition, low-elevation coastal zones in river deltas are especially exposed to economic and environmental losses due to climate-induced risks from floods, storm surges and salinization of rivers, aquifers and agricultural lands [16]. Delta coastlines are predicted to face unprecedented sea level rise due to global changes, which will in turn increase flooding across the plains and hinder economic activity [17]. The risks to infrastructure and social systems in these deltas require responses in terms of adaptation policies in territorial planning at local, regional, national and international scales [18]. The European Union launched a new strategy on adaptation to climate change in 2013. The strategy includes many different approaches by each member state with a variety of tactics for governance and actions. The objectives are to support the development of national adaptation strategies by member states, to ensure improved decision making through upgraded tools and to mainstream climate change adaptation into European policies [19].

    Past research gathered from different world-wide studies has shown that 90% of the population believes that there has been climate change in the last twenty years and approximately 30% of this group expressed that climate change affected their livelihoods [20]. A recent study in Nigeria by Egbe et al. [21] demonstrated that although the majority of the population believed that climate change is real, there was much less agreement about what if anything should be done to combat these changes. Recent research in Europe has shown similar findings [7,10]. Climate adaptation is primarily tailored towards agricultural production through irrigation and planting crop resistant species [22], yet the responses made by governments and donors do not always impact the most at risk populations [23]. It is important to note that perceptions of climate change vary geographically as a function of demographics and cultural and ideological factors [24]. A multitude of studies have shown that individual-level factors such as demographic variables and political orientation influence perceptions of climate change [25]. For example rural people are often more in tune with the changing aspects of their local situation and have adapted or put in place different coping mechanisms [26]. Climate change is perceived through personal value systems including past experience, knowledge and measuring the individual benefits and costs [27]. In some cases, it may not be important for people to understand or accept climate change, because the proposed mitigation efforts may create sufficient environmental and/or economic benefits to influence uptake [28]. Understanding public perception of climate change and the uptake of adaptation strategies is essential to develop communication strategies [29] and find appropriate and effective actions [9]. Different models such as the Protective Action Decision Model [30] have been proposed to better identify people's responses to environmental disasters. Considering that previous studies have highlighted the importance of focusing on different scales (local, regional and international) to better address the questions of climate change [31,32], this study analyzed the perceptions of climate change in two European Mediterranean deltas in order to identify the similarities and differences at the local scales and to apprehend how to stimulate adaptation strategies at the local and regional scale that may be necessary for the future.

    This study focused on two European Mediterranean deltas (the Camargue or Rhone delta in southern France and Axios delta in Greece (Figure 1)). The two deltas were selected because they share similar ecological habitats and species, and have comparable levels of anthropisation and direct threats (including erosion, flooding, urbanization and pollution) (Table 1). The two deltas are protected under various national protocols and international treaties including the Ramsar Convention for wetlands of international importance. The rivers in the two deltas have been entirely modified over the past centuries. They have constructed dams and protective dykes, forming deltas that rely on human intervention in order to preserve the existing habitats and economic activities [33,34]. The similarities in the two deltas could be used to promote exchanges and best practices between the sites and to learn from successes and failures. At the same time, it is imperative to identify the contextual differences that could prevent these exchanges and the potential for replication.

    Figure 1.  Location of the two European Mediterranean deltas (Camargue and Axios) included in the study on the perceptions of climate change (bold lines indicate the rivers feeding into the delta systems).
    Table 1.  Comparative data of the surface area, population, habitats, protection status, anthropogenic threats and climate change trends and scenarios for the Camargue and Axios delta [4,35,36,37].
    Delta (country) Surface area (ha2) Estimated population Wetland habitats Main anthropogenic threats Protection status Climate change trends and scenarios
    Camargue (France) 85,000 10,000 Sansouires, beaches, dunes, reed beds, marshes, temporary wetlands, lagoons, salty meadows, saline pools and rice fields Intensive agriculture, urbanization, pollution Ramsar site, UNESCO World Heritage site, Natural Regional Park, Natura 2000 site Increased occurrence and intensity of rainfall, decreased hydrological flows, increased temperatures year round
    Axios Delta (Greece) 33,800 44,000 Lagoons, dunes, beaches, salty marshes, sansouires, reed beds, saline pools and rice fields Urbanization, agricultural and industrial pollution Ramsar site, National Park, Natura 2000 site Increased extreme drought, increased extreme temperatures, decreased hydrological flows

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    A total of 395 people participated in the survey through person to person questionnaire deliveries. The sample size was calculated based on the estimated population size in each delta, taking into account the administrative and geographic delta boundaries. Given that no specific demographic data is available for the populations located geographically within the deltas, we used local key informants to estimate population size based on population statistics at municipality levels in each delta. The confidence level was set for 95% with a 7% confidence interval (Table 2).

    Table 2.  Population size and sampling for the deltas involved in the perceptions of climate change study.
    Delta Estimated population* Minimum sample size Actual sample size (n)
    Camargue, France 10,000 192 199
    Axios, Greece 44,000 195 196
    Total 395
    * estimated population was based on demographic information from the different municipalities and key informant interviews.

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    The participants were selected randomly through house to house surveys in each delta. Each hamlet or village in both deltas was visited and the participants were selected by requesting one family member in every third house on a given street to participate. Given the high rates of absenteeism in the Camargue, the survey sample was completed with telephone surveys (20% of the surveyed population). The study was conducted in 2017 and the interviews lasted on average between 20 to 60 minutes per participant.

    The survey questionnaire contained 18 questions with 32 different variables (see the supplementary material). The first section of the questionnaire solicited information on the socio-demographic situation of the participants through nine structured questions (age, gender, professional sector, employment position, geographic identity). This data provided the basic description of the sampled population [38]. The second section sought to identify information sources on climate change ("What are your most important sources of information concerning climate change?"). The third section (4 structured questions) aimed to determine the perception of change in the deltas ("Do you feel that the delta has changed over the last 20 years?", "If yes, what were the most important changes?", "Do you feel that the climate has changed over the last 20 years?" and "If yes, when did you begin to notice a difference?"). We used a 5 point Likert scale (strongly disagree, disagree, don't know, agree and strongly agree) [39] to designate the level of perception of specific changes in the deltas.

    Lastly, at the end of the questionnaire, we had two open ended questions ("What actions have you already made in your home or in your work to adapt to climate change?" and "What actions do you plan to make in the future (at home or at work) to adapt to climate change?") to detect the different adaptation mechanisms that are currently being implemented or that could be implemented in the future.

    Data analysis triangulated qualitative data, standard descriptive statistics and bivariate statistical analysis using R Studio. The qualitative data obtained from open-ended questions in section 4 of the questionnaire was analyzed by coding and grouping similar responses [40]. Standard descriptive statistics were utilized to define the perception of climate and global change in each delta and for the both deltas combined (sections 1, 2 and 3 of the questionnaire). The bivariate statistical analysis (Spearman Test and Principal component analysis) crossed the socio-demographic data (section 1) with the perception of climate change from section 2 of the questionnaire.

    Out of the 395 responses, there was a slight bias for female participants (Females: 56%, Males: 44%) (Table 3). The majority (72% of the participants) were working aged (between 25-64 years) with a marginal participation of retired (18%) and young professionals (10%). Education levels of participants in each delta were significantly different, the Camargue participants claimed higher formal educational levels (49% of the participants from the Camargue completed a University degree compared to 31% in the Axios Delta).

    Table 3.  Socio-demographic information of the sample population for the study of perceptions of climate change in two European Mediterranean deltas.
    Variable Total % Camargue Total % Axios Delta Total %
    Gender Male Female 43 57 44 56 44 56
    Age
    < 18
    18–24
    25–39
    40–64
    65–79
    ≥80
     
    1
    5
    18
    54
    18
    4
     
    0
    14
    24
    48
    10
    4
     
    1
    9
    21
    51
    14
    4
    Education level Primary school
    High school
    Vocational school
    Higher education
    Other
    5
    17
    21
    49
    7
    13
    12
    26
    31
    19
    9
    14
    24
    41
    12

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    Each of the participants identified their three main sources for climate change information and the responses were coded into 15 distinct categories of information sources (Figure 2). Television and radio were the most important information sources in both deltas with 68% of the participants from the Camargue and 57% of the participants from the Axios delta using this source of information. The second most frequently stated information source was newspapers (39% in Camargue and Axios delta). The internet was also identified as an important source of information in the Axios delta (68%) and Camargue (40%). Local, State and Federal government agencies were least cited as sources of information in both deltas.

    Figure 2.  Sources of information on climate change in the Camargue and Axios delta.

    The majority of participants in both deltas (over 75% agreement) perceived that there have been global changes in the delta over the last 20 years, and over 80% agreed that there was climate change (85% agreed in the Camargue, 91% in Axios delta). A large majority of participants (c. 80%) from both deltas expressed agreement "that climate change was a very serious to somewhat serious problem" (Figure 3A) and that "human activity was a contributing factor" for climate change (Figure 3B).

    Figure 3.  A: Perception of "How serious of a problem is climate change" by the participants in the Camargue and Axios delta. B: Perception that "human activity is contributing to climate change" by the participants in the Camargue and Axios delta.

    The statistical analysis showed significantly positive correlations in the Axios delta for the degree of severity of climate change (0.42) and that climate change is caused by humans (0.19). On the contrary, in the Camargue, there were significant negative correlations for the degree of severity (-0.4) and that climate change is caused by humans (-0.1).

    The participants conveyed that climate change could be felt in a variety of ways in their deltas. Participants from both deltas highlighted that the "temperatures are warmer" (73%), "dry seasons are longer" (57%), and "summer months are longer and hotter" (49%) (Figure 4).

    Figure 4.  Perceived "changes due to climate change" as expressed by the participants in the Camargue and Axios delta.

    The responses to the open-ended question "What changes have you made to adapt to climate change" were coded into 15 categories: changes in construction (including using improved materials/techniques), changes in transportation (including reducing displacements, using alternative types of transport, improved vehicles and carpooling), changes in eating habits (including buying more local products, respecting seasonality of products, eating less meat), organic (choosing to produce or buy organic products), recycling (plastics, paper, glass and reusing objects), energy conservation (including using led bulbs, using renewable energies), water conservation (including using less water for the household), favor the local economy (buying local products), agricultural changes (including reduced tilling, using rain water for irrigation, changing crop varieties), solar power (installation of solar panels for heating water and electricity), compost (using compost techniques or chickens to reduce food wastes), conservation (engaging in some type of nature conservation activity), not polluting (disposing of wastes appropriately and trying to reduce consumption), awareness raising and nothing (Figure 5).

    Figure 5.  "Changes in practice" by participants in the Camargue and Axios delta in response to climate change.

    The participants in both deltas shared similar responses to changes in practices, favoring activities such as conserving energy (24% in Camargue and 20% in Axios delta), recycling (15% in Camargue and 29% in Axios delta), and changes in constructions/infrastructure (13% in Camargue and 11% in Axios delta). The Camargue participants also highlighted altering their transportation methods (10%) while water conservation (13%) was more frequently expressed in the Axios delta. In the open ended question "what actions do you plan to take", there was no clear action that the participants planned to make in the future in either delta. There was however a general agreement that local and national governments should enhance their responsibility by putting in place policy and implementing mitigation actions for climate change.

    It is important to understand people's perceptions about climate change because it could potentially increase the public's willingness to make changes and to accept public policy measures [9]. Similar to Kim and Wolinsky-Nahmias [41], we found that public concern about climate change is very high in both surveyed deltas. This supports previous research indicating that inhabitants of coastal zones are highly informed and concerned about climate change [10] and shows an increase in concern from former studies in southern Europe [42]. The similarity in perception at a regional European Mediterranean scale is conform with previous work by Poortingua et al. [25] demonstrating the importance of regional analysis at a European scale. In addition, we showed that the participants in both deltas perceived that climate change was caused by human activities. Yet as Lee et al. [43] point out, concern is not the only factor that could lead to change or policy implementation. Substantial progress in climate change mitigation necessitates public support of climate change policies. Public support and eventually behavior change is especially relevant as it could have possible economic costs and potentially reduce living standards. Considering the multitude of factors that contribute to the acceptance of mitigation measures and the likelihood to make concrete changes, it is important to understand the barriers existing at the local scale. The barriers often associated with environmental behavior change are lack of knowledge, existing or previous behaviors, lack of incentives (external and internal) and insufficient feedback on change [44]. These barriers need to be taken into account in order to increase mitigation acceptance and uptake.

    Similar to climate change trends and scenarios from previous scientific studies [4,45,46], the participants noted increased temperatures (in spring, summer or year around) and decreases in hydrological flows and/or precipitation. However, the participants did not identify increased intensity of rainfall in the Camargue or increase in extreme temperatures in the Axios delta. This is contrary to previous studies on perceptions of extreme weather events where participants tended to remember extreme events and relate them to climate change [47]. Despite the lack of reference made to extreme weather (temperatures or precipitation), the participants' perceptions were in line with scientific trends which could indicate higher levels of knowledge about climate change and reduce this barrier, inciting environmental behavioral changes.

    There seems to be a common confusion in both deltas between climate adaptation and climate mitigation. Climate adaption is the change(s) made in response to the actual or anticipated impacts of climate change whereas climate mitigation is the action(s) aimed at reducing climate change [48]. The only identified climate adaptations that were declared in our survey were concerning agricultural changes and changes in construction (in both the Camargue and Axios delta). The other declared changes were mitigation actions, with energy conservation and recycling being the most important activities. These results coincide with the national and international policy focusing on mitigation over climate adaptation [48].

    Despite the fact that the majority of the participants claimed to undertake some type of adaptation actions, the actions were limited. The limited action could be in part due to implicatory denial when people minimize the moral, psychological or political implications of an action [49]. The phenomenon of climate change might be acknowledged, but the way that it is perceived can cause the participants to assume that their individual action may not be useful or that the situation is so far advanced that no action needs to be taken [50]. Bain et al. [28] suggest that it is necessary to move beyond knowledge and acceptance of climate change to emphasize two co-benefit types: development (including economic and scientific advancement) and benevolence (focusing on morals and caring communities). These co-benefits are likely to work across scales to motivate public, private and financial engagements to address climate change. Our study suggests that although the participants perceive that climate change is important and that they are undertaking some activities to adapt to these changes, it is important that more political action be taken at a local and regional scale to overcome the barriers inhibiting further actions. Given the heterogeneity in climate change adaptation and climate change mitigation, it could be valuable to correlate these current changes with political and economic climate change strategies in each site. This information could increase our understanding of why certain activities are more common in some areas (such as changes in transportation in the Camargue and water conservation in the Axios delta) and could provide insight into the motivating factors invoking further changes.

    Considering that the participants in our study are already convinced that climate change is real and that it is human induced, it becomes imperative that communication strategies for climate change mitigation take on a new framing. Baumer et al. [51] suggest interventions that focus on frame-invoking words may encourage new reflection and increase policy action. In order for these messages to be effective, they must be transmitted by appropriate information sources [52]. Given that the most cited information sources in both deltas was based on mass media combining a large range of individual sources (different television and radio stations and internet sites), the quality and content of the messages are quite diverse and could have an impact on the acceptance or rejection of different measures [53]. A site specific approach entailing the use of trusted information sources along with adapted communication tools [52,54] is strongly recommended in order to increase efficacy and to incite behavioral changes and practices. The results of our study show that governmental organizations (local, regional and national) are the least used information sources in both deltas. This is a significant barrier to successful climate change mitigation and adaptation. Most climate change policies need public support and more governmental communication using a range of strategies is recommended to increase mitigation and adaptation policy acceptance [55]. This support will be more likely if the strategies for climate change are adapted to the unique differences across cultures and nationalities [10].

    There have been some findings that indicate that higher education and socio-economic status give people an increased sense of control and decreases their risk perceptions; however, similar to van der Linden [56] our study did not find any correlation between age, education and risk perceptions of climate change. Our study supports previous research [25,44,57] indicating that although there are many commonalities concerning climate change and climate change perceptions, the socio-cultural factors of specific sites are extremely important to understand in order to promote more effective mitigation efforts and uptake. Using an interdisciplinary approach integrating environmental, communication and psychological methods could be a step forward to improving climate change mitigation and acceptance in the future [58].

    This study has demonstrated many similarities related to the perception of climate change in two European Mediterranean deltas. There was an overwhelming perception that climate change is happening and the change is attributed to human causes. The perceptions of climate change coincide with most scientific climate change scenarios, demonstrating a high level of awareness about climate change by the local population. Despite this recognition, the local populations in the surveyed deltas have taken little action to adapt to or mitigate against climate change. We recommend that future studies be implemented researching action uptake and behavioral changes related to climate change by triangulating political science, communication and ecological methods. This information could increase our understanding of why certain activities are more common in some areas and could provide insight into the motivating factors invoking further changes. In order to better prepare the future, it is important that climate change adaptation messages move beyond global trends and scenario planning in order to focus on climate change mitigation and adaptation measures that are customized to each local context. This change in methods requires the development of new and site specific communication that effectively encourages actions and policy acceptance. Given that the information channels are different in each local context; it is imperative that the messages are transmitted through trusted information sources specific to each site. The role of local, regional and national governments as information providers is currently underutilized in both deltas. In order to make the transition from climate change policy to climate change actions, the government institutions should use an interdisciplinary approach to improve their communication strategies in order to increase policy uptake and acceptance in the future.

    This study was funded by the Foundation Tour du Valat, Foundation Pro-Valat and Provence Alpes Côte d'Azur Région. We would like to thank Parul Rishi for her reflections on the methodology of the study. We would also like to acknowledge Styliani Anagnostou and Sultana Tsompanoglou, guards of the Management Authority, for conducting the survey in the Axios delta and Loïc Willm for his help with the graphics.

    All authors declare no conflicts of interest in this paper.



    [1] Abraham J, Vasu KS, Williams CD, et al. (2017) Tunable sieving of ions using graphene oxide membranes. Nat Nanotechnol 12: 546–550. https://doi.org/10.1038/nnano.2017.21 doi: 10.1038/nnano.2017.21
    [2] Padmavathy N, Behera SS, Pathan S, et al. (2019) Interlocked graphene oxide provides narrow channels for effective water desalination through forward osmosis. ACS Appl Mater Interfaces 11: 7566–7575. https://doi.org/10.1021/acsami.8b20598 doi: 10.1021/acsami.8b20598
    [3] Yang T, Lin H, Loh KP, et al. (2019) Fundamental transport mechanisms and advancements of graphene oxide membranes for molecular separation. Chem Mater 31: 1829–1846. https://doi.org/10.1021/acs.chemmater.8b03820 doi: 10.1021/acs.chemmater.8b03820
    [4] Landon J, Gao X, Omosebi A, et al. (2019) Progress and outlook for capacitive deionization technology. Curr Opin Chem Eng 25: 1–8. https://doi.org/10.1016/j.coche.2019.06.006 doi: 10.1016/j.coche.2019.06.006
    [5] Barbosa GD, Liu X, Bara JE, et al. (2021) High-salinity brine desalination with amine-based temperature swing solvent extraction: A molecular dynamics study. J Mol Liq 341: 117359. https://doi.org/10.1016/j.molliq.2021.117359 doi: 10.1016/j.molliq.2021.117359
    [6] Mahmoud A, Nassef E, Salah H, et al. (2020) Use of hydrazide derivative of poly methylacrylate for the removal of cupric ions from solutions. AIMS Mater Sci 7: 420–430. https://doi.org/10.3934/matersci.2020.4.420 doi: 10.3934/matersci.2020.4.420
    [7] Yang F, He Y, Rosentsvit L, et al. (2021) Flow-electrode capacitive deionization: A review and new perspectives. Water Res 200: 117222. https://doi.org/10.1016/j.watres.2021.117222 doi: 10.1016/j.watres.2021.117222
    [8] Muscatello J, Jaeger F, Matar OK, et al. (2016) Optimizing water transport through graphene-based membranes: Insights from nonequilibrium molecular dynamics. ACS Appl Mater Interfaces 8: 12330–12336. https://doi.org/10.1021/acsami.5b12112 doi: 10.1021/acsami.5b12112
    [9] Cohen-Tanugi D, Lin L-C, Grossman JC (2016) Multilayer nanoporous graphene membranes for water desalination. Nano Lett 16: 1027–1033. https://doi.org/10.1021/acs.nanolett.5b04089 doi: 10.1021/acs.nanolett.5b04089
    [10] Giri AK, Cordeiro MNDS (2021) Heavy metal ion separation from industrial wastewater using stacked graphene Membranes: A molecular dynamics simulation study. J Mol Liq 338: 116688. https://doi.org/10.1016/j.molliq.2021.116688 doi: 10.1016/j.molliq.2021.116688
    [11] Yu Y, Tan R, Ding H (2020) Controlling ion transport in a C2N-based nanochannel with tunable interlayer spacing. Phys Chem Chem Phys 22: 16855–16861. https://doi.org/10.1039/D0CP02993A doi: 10.1039/D0CP02993A
    [12] Shao C, Zhao Y, Qu L (2020) Tunable graphene systems for water desalination. ChemNanoMat 6: 1028–1048. https://doi.org/10.1002/cnma.202000041 doi: 10.1002/cnma.202000041
    [13] Abdullah N, Yusof N, Ismail AF, et al. (2021) Insights into metal-organic frameworks-integrated membranes for desalination process: A review. Desalination 500: 114867. https://doi.org/10.1016/j.desal.2020.114867 doi: 10.1016/j.desal.2020.114867
    [14] Presumido PH, Primo A, Vilar VJP, et al. (2021) Large area continuous multilayer graphene membrane for water desalination. Chem Eng J 413: 127510. https://doi.org/10.1016/j.cej.2020.127510 doi: 10.1016/j.cej.2020.127510
    [15] Hinds BJ, Chopra N, Rantell T, et al. (2004) Aligned multiwalled carbon nanotube membranes. Science 303: 62-65. https://doi.org/10.1126/science.1092048 doi: 10.1126/science.1092048
    [16] Agrawal KV, Shimizu S, Drahushuk LW, et al. (2016) Observation of extreme phase transition temperatures of water confined inside isolated carbon nanotubes. Nat Nanotechnol 12: 267–273. https://doi.org/10.1038/nnano.2016.254 doi: 10.1038/nnano.2016.254
    [17] Hou D, Qiao G, Wang P (2021) Molecular dynamics study on water and ions transport mechanism in nanometer channel of 13X zeolite. Chem Eng J 420: 129975. https://doi.org/10.1016/j.cej.2021.129975 doi: 10.1016/j.cej.2021.129975
    [18] Liu Y, Cheng Z, Song M, et al. (2021) Molecular dynamics simulation-directed rational design of nanoporous graphitic carbon nitride membranes for water desalination. J Membrane Sci 620: 118869. https://doi.org/10.1016/j.memsci.2020.118869 doi: 10.1016/j.memsci.2020.118869
    [19] Zhao Y, Huang D, Su J, et al. (2020) Coupled transport of water and ions through graphene nanochannels. J Phys Chem C 124: 17320–17330. https://doi.org/10.1021/acs.jpcc.0c04158 doi: 10.1021/acs.jpcc.0c04158
    [20] Chen L, Wang SY, Xiang X, et al. (2020) Mechanism of surface nanostructure changing wettability: A molecular dynamics simulation. Comput Mater Sci 171: 109223. https://doi.org/10.1016/j.commatsci.2019.109223 doi: 10.1016/j.commatsci.2019.109223
    [21] Mahmood A, Chen S, Chen L, et al. (2020) Spontaneous propulsion of a water nanodroplet induced by a wettability gradient: A molecular dynamics simulation study. Phys Chem Chem Phys 22: 4805-4814. https://doi.org/10.1039/C9CP06718C doi: 10.1039/C9CP06718C
    [22] Ranathunga DTS, Shamir A, Dai X, et al. (2020) Molecular dynamics simulations of water condensation on surfaces with tunable wettability. Langmuir 36: 7383-7391. https://doi.org/10.1021/acs.langmuir.0c00915 doi: 10.1021/acs.langmuir.0c00915
    [23] De Luca S, Todd BD, Hansen JS, et al. (2013) Electropumping of water with rotating electric fields. J Chem Phys 138: 154712. https://doi.org/10.1063/1.4801033 doi: 10.1063/1.4801033
    [24] Kazemi AS, Nataj ZE, Abdi Y, et al. (2021) Tuning wettability and surface order of MWCNTs by functionalization for water desalination. Desalination 508: 115049. https://doi.org/10.1016/j.desal.2021.115049 doi: 10.1016/j.desal.2021.115049
    [25] Giri AK, Teixeira F, Cordeiro MNDS (2019) Salt separation from water using graphene oxide nanochannels: A molecular dynamics simulation study. Desalination 460: 1–14. https://doi.org/10.1016/j.desal.2019.02.014 doi: 10.1016/j.desal.2019.02.014
    [26] Zong D, Yang Z, Duan Y (2017) Wettability of a nano-droplet in an electric field: A molecular dynamics study. Appl Therm Eng 122: 71–79. https://doi.org/10.1016/j.applthermaleng.2017.04.064 doi: 10.1016/j.applthermaleng.2017.04.064
    [27] Bruus H (2008) Theoretical Microfluidics, Oxford, New York: Oxford University Press.
    [28] Bartzis V, Sarris IE (2020) A theoretical model for salt ion drift due to electric field suitable to seawater desalination. Desalination 473: 114163. https://doi.org/10.1016/j.desal.2019.114163 doi: 10.1016/j.desal.2019.114163
    [29] Bartzis V, Ninos G, Sarris IE (2022) Water purification from heavy metals due to electric field ion drift. Water 14: 2372. https://doi.org/10.3390/w14152372 doi: 10.3390/w14152372
    [30] Sofos F (2021) A water/ion separation device: Theoretical and numerical investigation. Appl Sci 11: 8548. https://doi.org/10.3390/app11188548 doi: 10.3390/app11188548
    [31] Sofos F, Karakasidis T, Sarris IE (2020) Molecular dynamics simulations of ion drift in nanochannel water flow. Nanomaterials 10: 2373. https://doi.org/10.3390/nano10122373 doi: 10.3390/nano10122373
    [32] Kandezi MK, Lakmehsari MS, Matta CF (2020) Electric field assisted desalination of water using B- and N-doped-graphene sheets: A non-equilibrium molecular dynamics study. J Mol Liq 302: 112574. https://doi.org/10.1016/j.molliq.2020.112574 doi: 10.1016/j.molliq.2020.112574
    [33] Lynch CI, Rao S, Sansom MSP (2020) Water in nanopores and biological channels: A molecular simulation perspective. Chem Rev 120: 10298–10335. https://doi.org/10.1021/acs.chemrev.9b00830 doi: 10.1021/acs.chemrev.9b00830
    [34] Steinhauser MO (2017) Multiscale modeling, coarse-graining and shock wave computer simulations in materials science. AIMS Mater Sci 4: 1319–1357. https://doi.org/10.3934/matersci.2017.6.1319 doi: 10.3934/matersci.2017.6.1319
    [35] Huang DM, Cottin-Bizonne C, Ybert C, et al. (2008) Aqueous electrolytes near hydrophobic surfaces: Dynamic effects of ion specificity and hydrodynamic slip. Langmuir 24: 1442–1450. https://doi.org/10.1021/la7021787 doi: 10.1021/la7021787
    [36] Bonthuis DJ, Horinek D, Bocquet L, et al. (2009) Electrohydraulic power conversion in planar nanochannels. Phys Rev Lett 103: 144503. https://doi.org/10.1103/PhysRevLett.103.144503 doi: 10.1103/PhysRevLett.103.144503
    [37] Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J Comput Phys 117: 1–19. https://doi.org/10.1006/jcph.1995.1039 doi: 10.1006/jcph.1995.1039
    [38] Karniadakis G, Beşkök A, Aluru NR (2005) Microflows and Nanoflows: Fundamentals and Simulation, Springer.
    [39] Dimiduk DM, Holm EA, Niezgoda SR (2018) Perspectives on the impact of machine learning. deep learning, and artificial intelligence on materials, processes, and structures engineering. Integr Mater Manuf I 7: 157–172. https://doi.org/10.1007/s40192-018-0117-8 doi: 10.1007/s40192-018-0117-8
    [40] Sofos F, Stavrogiannis C, Exarchou-Kouveli KK, et al. (2022) Current trends in fluid research in the era of artificial intelligence: A review. Fluids 7: 116. https://doi.org/10.3390/fluids7030116 doi: 10.3390/fluids7030116
    [41] Abbaspour M, Akbarzadeh H, Jorabchi MN, et al. (2022) Investigation of doped carbon nanotubes on desalination process using molecular dynamics simulations. J Mol Liq 348: 118040. https://doi.org/10.1016/j.molliq.2021.118040 doi: 10.1016/j.molliq.2021.118040
    [42] Voronov RS, Papavassiliou DV, Lee LL (2006) Boundary slip and wetting properties of interfaces: Correlation of the contact angle with the slip length. J Chem Phys 124: 204701. https://doi.org/10.1063/1.2194019 doi: 10.1063/1.2194019
    [43] Ibrar I, Yadav S, Braytee A, et al. (2022) Evaluation of machine learning algorithms to predict internal concentration polarization in forward osmosis. J Membrane Sci 646: 120257. https://doi.org/10.1016/j.memsci.2022.120257 doi: 10.1016/j.memsci.2022.120257
    [44] Odabaşı Ç, Dologlu P, Gülmez F, et al. (2022) Investigation of the factors affecting reverse osmosis membrane performance using machine-learning techniques. Comput Chem Eng 159: 107669. https://doi.org/10.1016/j.compchemeng.2022.107669 doi: 10.1016/j.compchemeng.2022.107669
    [45] Salari K, Zarafshan P, Khashehchi M, et al. (2022) Modeling and predicting of water production by capacitive deionization method using artificial neural networks. Desalination 540: 115992. https://doi.org/10.1016/j.desal.2022.115992 doi: 10.1016/j.desal.2022.115992
    [46] Yin G, Alazzawi FJI, Bokov D, et al. (2022) Multiple machine learning models for prediction of CO2 solubility in potassium and sodium based amino acid salt solutions. Arab J Chem 15: 103608. https://doi.org/10.1016/j.arabjc.2021.103608 doi: 10.1016/j.arabjc.2021.103608
    [47] Sofos F, Karakasidis TE, Liakopoulos A (2012) Surface wettability effects on flow in rough wall nanochannels. Microfluid Nanofluid 12: 25–31. https://doi.org/10.1007/s10404-011-0845-y doi: 10.1007/s10404-011-0845-y
    [48] Jiang H, Müller-Plathe F, Panagiotopoulos AZ (2017) Contact angles from Young's equation in molecular dynamics simulations. J Chem Phys 147: 84708. https://doi.org/10.1063/1.4994088 doi: 10.1063/1.4994088
    [49] Jorgensen WL, Chandrasekhar J, Madura JD, et al. (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79: 926–935. https://doi.org/10.1063/1.445869 doi: 10.1063/1.445869
    [50] Bagheri M, Akbari A, Mirbagheri SA (2019) Advanced control of membrane fouling in filtration systems using artificial intelligence and machine learning techniques: A critical review. Process Saf Environ 123: 229–252. https://doi.org/10.1016/j.psep.2019.01.013 doi: 10.1016/j.psep.2019.01.013
    [51] Behnam P, Faegh M, Khiadani M (2022) A review on state-of-the-art applications of data-driven methods in desalination systems. Desalination 532: 115744. https://doi.org/10.1016/j.desal.2022.115744 doi: 10.1016/j.desal.2022.115744
    [52] Bratko D, Daub CD, Leung K, et al. (2007) Effect of field direction on electrowetting in a nanopore. J Am Chem Soc 129: 2504–2510. https://doi.org/10.1021/ja0659370 doi: 10.1021/ja0659370
    [53] Yeo CSH, Xie Q, Wang X, et al. (2020) Understanding and optimization of thin film nanocomposite membranes for reverse osmosis with machine learning. J Membrane Sci 606: 118135. https://doi.org/10.1016/j.memsci.2020.118135 doi: 10.1016/j.memsci.2020.118135
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