Physical parameters of catalyst layers based on Pt/OMC catalyst
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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
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Recently, the mitigation of the greenhouse-gases (GHG) is the important issue to solve climate changes caused by the global warming. According to the international energy agency (IEA) report at 2010 (IEA, 2010), 65% of all GHG emissions can be attributed to energy supply and use. In addition, according to the blue scenario of IEA, all areas will need to reduce the CO2 emission drastically until 2050, when level of CO2 emission should be halved. In a view of energy supply and use, fossil fuels are used mainly in transport and power sectors which generate electricity through multiple steps. Thus, the highly efficient and clean technologies for these sectors are necessary for saving energy and reducing CO2 emission (Pak et al., 2010). Among the alternative means, fuel cell technologies have been attracted because they can transform directly the chemical energy of fuel into electricity and emit clean exhaust gases.
Fuel cells have been developed for a long time since the principle of fuel cell has demonstrated by Sir Groove at 1939, who suggested the “gas battery” (Andujar& Segura, 2009). Initially, fuel cells were seen as an attractive technology for the generation of power due to high theoretical efficiency. However, as the efficiency of other alternative technologies was rapidly being increased, the development of fuel cell became almost negligible during the early of 20th century (Perry &Tuller, 2002). Also, since the interest in fuel cell reoccurred by the “space race” between USA and Russia in the late of 1950s and the first actual power generation system of fuel cell was launched in the Gemini at 1962, many types of fuel cells were developed for many applications and categorized by the electrolyte for use.
Among the various kinds of fuel cells, polymer electrolyte fuel cells (PEFCs) have extensively been developed for transport and distributed-power generation applications due to low emission of GHG and high efficiency compared to the internal combustion engine (ICE) and generators. Thus, PEFC technology is considered as a green technology for energy savings and reduction of GHG emission. As a one part of PEFCs, direct alcohol fuel cell (DAFC), which can use the high energy density of alcohol such as methanol and ethanol that could be produced by using the biomass and corn for carbon neutral cycle or directly using solar energy for artificial photosynthesis, is the most promising fuel cell for mobile and portable applications.
Although the PEFC systems have been developed to its current status through several technical breakthroughs over the years, it is now on initial market stage with the help of government for new and renewable energy policy. To expand the market size or thrive in fuel cell market without external supports, further innovations in the areas of cost and durability are demanded. For this innovation, the understanding and improvement of materials and components for membrane electrode assembly (MEA), which considered as the core of fuel cell system, are very important besides development of fabrication process maximizing the performance with the improved materials for PEFC.
A typical MEA as shown in Fig. 1 consists of a polymer electrolyte membrane (PEM), interposed by two electrodes, cathode and anode, which are composed of catalyst layer (CL) and the gas diffusion layers (GDL), respectively. Usually, a microporous layer (MPL) made from porous carbon materials is located between the CL and the GDL. The total thickness of multilayer of MEA is less than 500 μm (Ramasamy, 2009).
Schematic components of a membrane electrode assembly
The performance of MEA is displayed by the power density (W/cm2), which is the product of current density (A/cm2) and voltage (V), which is totally dependent on the choice of components and materials, especially membrane and catalyst. Thus, the research for increasing the performance of MEA is usually focused on the new materials for membranes and catalysts with enhanced properties. However, to reveal the improved performance of materials in the MEA level, the fabrication processfor MEA should be optimized.
In this chapter, the processes for MEA preparation are reviewed in the section 2 and the optimized performance of MEA using new supported catalysts will be discussed in the sections 3 and 4. Finally, the chapter is closed with conclusions.
Among the components of a MEA, the performance of the MEA is usually dependent on the CL properties and contact interfacial resistance between the CL and membrane according to its preparation technique. The CL has its own set of criteria to fulfil the chemical reaction with complex functionalities and has a three-dimensional porousstructure composed of a network of catalyst particles made of porous carbon supportsand catalytic metal nanoparticles, usually andionomer fragments.
Some common requirements of an idea regarding to CL must have a high electrocatalytic activity for PEFC reactions, a good ionic transport and a high porosity for efficient transport reactant and product (Ramasamy, 2009). Over the years, various slurry formations and coating procedures have been developed for the preparation of CLs in order to realize the better performance of MEA for the commercialization.
One key factor in the preparation of CLs is the selection of solvents to form a homogeneous mixture in the catalyst ink, which was generally made by dispersing the catalyst (supported Pt based catalyst or Pt based black catalyst) with a mixture of Nafionionomer solution, the solvents and deionized (DI) water. Many researchers have mainly studied to focus on the dispersion of catalyst ink formed by ionomer and the catalyst particles. For example, Uchida et al. demonstrated that the further improvement in cell performance could be obtained by using an intermediate dielectric constantsolvents with a range of 3-10 to form a colloidal suspension of Nafion particles in a water-alcohol mixture. Their experimental results were attributed to the higher number of electrochemical interactions between the Nafionionomersand catalysts in the extended reaction interface than those using solvents with a high-dielectric-constant, such as water (Uchida et al., 1998). It is suggested that the selection of highlyviscous glycol for the catalyst ink as a solvent resulted in the higher performance MEAs in which showed low mass-transfer and electrode ionic resistance due to the formation of homogeneous catalyst particles in the catalyst ink (Wilson et al., 1995). Although the homogeneousionomer and the catalyst particles are important for theformation of the slurry ink, the appropriate amount ratio of ionomer to catalyst and fine distribution of the ionomer in the CLsarethe most critical factor, which leads to the minimized electrode resistance and maximized contact of ionomer with catalytic metal nanoparticles.This ratio should be normally optimized for the best formulation of the catalyst ink.
Another key factor in preparation of the CLs is the selection of coating procedures to minimize the roughness factor of the CLs and the contact resistance between the CL and the membrane. The types of coating procedure for preparation of the CLs can be broadly classified into three categories as followings: (1) catalyst coated on electrode (CCE), (2) decal transfer catalyst coated on membrane (DTM) and (3) direct catalyst coated on membrane (DCM).
The CCE method is to form the CL on the GDL as shown in Fig. 2. The catalyst ink was coated onto the MPL in the GDL, andthen the electrode was dried in the vacuum oven at a specific temperature. Finally, the MEAs were assembled by hot pressing the catalystcoated electrodes witha membrane. The CCE method has widely been used in the formation of the large scale mass production of MEAs due to the simple coating process (Frey &Linardi, 2004). The final hot-pressing is indispensable and important process for the higher performance MEA to make a good interfacial contact betweenthe CLs and membrane in the CCE Method. The main parameters of hot-pressing process are the temperature, the pressure and the time. Zhang et al. investigated that the effect of hot-pressing conditions (temperature, pressure and time) on the performance of MEA using the CCE method for the DMFC. The optimized parameters for temperature, pressures and time are 135℃, 80kgf/cm2 and 90s, respectively. The highest power density of MEA is attributed to the lowest contact resistance between the membrane and CL (Zhang et al., 2007). In addition, Therdthianwong et al. tried to find systematically the most significant hot-pressing parameter by designing a full factorial analysis of the three main hot-pressing parameters related to the cell performance (Therdthianwong et al., 2007). In this study, MEA prepared with hot-pressing condition of 100 ºC, 70.3 kgf/cm2 and 120s resulted in the highest power density.
Schematic process of a catalyst coated on electrode (CCE).
Although various conditions for hot-pressing have been employed by researchers in the CCE method, the controlling of hot-pressing temperature to slightly above the glass transition temperature of the membrane might be a critical point to promote good contact within the triple-phase regions of the CL. (Zhang et al., 2007, Tang et al., 2007, Lindermeir et al., 2004). However, the CL prepared in CCE method cannot be effectively transferred to the membrane during the course of hot-pressing theMEA due to the change of the structure in the CL (a distribution of ionomer and porosity) and the dehydration of the membrane, which may lead to an irreversible performance lossof the MEA (Kuver et al., 1994).
The DTM method is to form the CL on the decal substrates as a shown in Fig. 3. The catalyst inks were coated uniformly onto decal blank substrates. The CLs of both electrodes were then transferred from substrates to the membrane by hot pressing under high pressure and temperature for a specific time. The decal substrates can be peeled away from the CCM leaving the CLs fused to membrane, yieldinga three-layer CCM. The GDLs can then be added to theCCM by hot-pressing as mentioned in the previoussection.
Tang et al. reported that the DTM method could show a better utilization of catalystsand a superior formation of the ionomer network compared to the CCE method, which are allbeneficial for improving the performance and long-term durabilityof the MEA for the DMFC due to a low interfacial resistancebetween the CL and polymer membrane, a thinnercatalyst layer with a lower mass transfer resistance,and a bettercontact among the electrode components (Tang et al., 2007). However, the process of the DTM method seems to be more complex than CCE method and impossible to control the porosity and the thickness of the CLs due to the dehydration of the membrane during the decal transfer and, it has a possibility of sintering of the catalytic nanoparticles (Song et al., 2005). Furthermore, the ionomersegregation is likely to occur onto the outsideof the CL during the transfer step of the CLs from the decal substrates to Na+-Nafion membrane with high hot-pressing temperature in order to increase the transfer ratio of the CL into the membrane (Xie et al., 2004). Recently, a breaking layer composed of carbon powder andNafionionomeron the CLs was suggested by two groups to overcome those problems, that is, the CLwas sandwiched between the inner thin carbon and theouter ionomer layers (Park et al., 2008, Cho et al., 2010). However, the additional layer could generate a further resistance to proton and mass transports, which may lead to an irreversible performance lossof the MEA. The DTM method must be improved further for the commercialization of MEA.
Schematic process of a decal transfer catalyst coated on membrane (DTM)
The DCM method is to form the CL directly onto the membrane as shown in Fig. 4. The DCM method is more simple andefficient than indirect coating process, DTM method and has no risk of uneven and incomplete transfer of catalyst in the CL. Furthermore, it also produces a higher MEA performance than the DTM method due to an easier controllability of the CL thickness as well as a better ionic connection between the CLs and the membrane resulted from a strong attachment of the solvent on the membrane. However, the direct coating of catalyst slurry onto the membrane has a critical problem that the membrane has a
Schematic process of a direct catalyst coated on membrane (DCM)
high tendency to swell or wrinkle with a contact of many solvents in the catalyst slurries, which could give rise to the deformation of the CL by fast volume changes of the membrane.
It could cause the membrane and the CLto be deformed by fast volume changes. Therefore, swelling control of the membrane is very importantin the DCM method for the highquality MEA fabrication. To minimize such dimensional changes during the catalyst coating process, many researchers have tried to prevent the membrane from swelling during the coating process. For example, Park et al. suggested a process byemploying a pre-swollen Nafion membrane. They soaked the Nafion membrane in EG and sprayed the catalyst slurry onto the pre-swollenmembrane. Thus, the prepared MEA showed improvementover a commercially available MEA due to the reduction of a stressproblem of membranes by the pre-swelling process (Park et al., 2010). Shao et al. prepared MEA using direct spray deposition of the catalyst ink into Nafion 212 membrane with the aid of a hot-plate at 150 ºC, whose condition could decrease the swelling and wrinkling of the Nafion membrane due to the solvent gasification before being absorbed into the Nafion membrane (Shao et al. 2001). Also, in case of our lab, an innovative process preventing the swelling from the solvents by holding a membrane on a porous vacuum plate is developed, which is an efficient way for realizing a high precision in catalyst loading with high reproducibility (You et al. 2010). Considering the CL design, the selection of good solvents and DCM method as a coating process could offer a more efficient and attractiveway for high quality and high performance of MEAs.
One parameter in MEA design to improve the performance of DMFCs is to increase the catalyst utilization and electrochemical surface area (ESA) of the electrodes byincreasingthe level of gas access, proton access and electron access to the reaction sites. Hence, the structures of CLs where the electrochemical reactions occur should be optimized for maximizing thetriple-phase boundaries. In addition, minimizingaresistance between the catalyst and ionomer in the CL, as well as the interfacial resistance between the electrolyte and the CLare essential in MEA structure. Furthermore, the resistance of the electrolyte membrane itself should be minimized.
Another parameter in MEA design is the control of porosity to maximize their active surface area of catalyst in the electrodes. During DMFC operation, complex flow of reactants and reaction products exists in the porous space of CL. The pores in cathode should allow oxygen to reach the catalyst surface and support efficient transport of water to prevent flooding of the layer. One method achieving a good balance of fuel transport capability with effective product removal is the addition of pore-forming materials into the CL.They help tailor the CL morphology and pore structure to meet the above-mentioned requirements, thereby decreasing the transport resistance.
Considering the above-mentioned issues in the CL design, the optimized design of CLs must have the lowest resistance between the membrane and CL, the properdistance of proton conductor from the catalyst and the optimum porosity of the catalyst layer. The DCM method with the catalyst slurry composed of EG and pore forming agent is investigated to optimize the structure of CLsby parameters for hot-pressing such as temperature and pressure.
All investigated MEAs in this section were prepared with the hydrocarbon membrane (the conductivity and thickness of the membrane was 0.06 S/cm and 32 μm, respectively) and the SGL 25 BC for GDLs of both electrodes.Pt-Ru black (HiSpec 6000, Johnson Matthey) and Pt black (HiSpec 1000, Johnson Matthey) were used as the anode and cathode catalyst, respectively.Catalyst inks, consisting of black catalysts, Nafion solution, DI water, MgSO4, and EG with weight ratios of 0.288: 0.18: 0.155: 0.058: 0.36 for the anode and 0.241: 0.151: 0.12: 0.036: 0.452 for the cathode, respectively, were well dispersed using high speed rotating equipment (conditioning mixer, AR-500) for 10min.
For the preparation of CLsusing the DCM, the anode inks were coated uniformly onto one side of the electrolyte membrane directly, which was held on a vacuum plate with 32 mm× 32 mm mask films to prevent dimensionalchange of the membrane. The coated membrane was then dried for 24h in a vacuum oven at 120ºC after removing the mask. The cathode catalyst ink wasapplied to the opposite side of the anode-catalyst coated membrane in the same manner. The catalyst loading for both electrodes was 5 mg/cm2 and the active area of the MEAs was 10 cm2.
Hot-pressing after direct coating of CL was performed at three different temperatures (140, 150, and 160ºC)and pressures (0.1, 0.2, and 0.3 tonf/cm2) for 10 min to control the porosity and contact resistance of the CLs.And then, The CCM prepared was pre-treated in a solution containing 1M methanol and 1M sulfuric acid at 95ºC for 4h.Finally, the MEAs werefabricated by placing GDLs onto the corresponding sides of the CCM by hot-pressing at the 125ºC and 0.1tonf/cm2for 3min.
The performance of the MEA under the DMFC condition was measured by fuel cell testing system (Won-A Tech) using single cell hardware with an active area of 10 cm2. A 1M aqueous methanol solution was fed to the anode side at a flow rate of 0.25 ml/min∙A. Dry air was supplied to the cathode side at a flow rate of 45 ml/min∙A under ambient pressure. The cell performance was measured at 60ºC and operated in potentiostatic mode at a voltage of 0.45V for 4 h each day. The polarization curves of the MEAs were recorded at the end of the procedure at a constant voltage.
Electrochemical impedance spectroscopy (EIS) of the MEAs were measured at a current of 220 mA/cm2 using an electrochemical analysis instrument (VMP2) in the frequency range from 100 kHz to 0.1 Hz with 10 points per decade at 60 ºC. The amplitude of the sinusoidal current signal was 10 mA. To separate the anode and cathode impedance, the cathode side was supplied with a continuous supply of hydrogen, which would function as a dynamic hydrogen reference (DHE) and counter electrode.
The effect of the hot-pressing conditions (temperature and pressure) on the MEA performance for DMFC was investigated to decrease the reaction transfer resistance through the extended catalyst and ionomer interface in the electrode and to increase the interfacial bonding through the strong formation of a proton conducting ionomer network between the CL and membrane. Fig. 5(a) shows the power densities at 0.45V of the MEAs from the CCMs prepared by the DCM at various hot-pressing temperatures under the same pressing pressure (0.2tonf/cm2). The performance of the MEA produced at a hot-pressing temperature of 150ºCwas higher than that of the MEA produced at 140 and 160ºC, respectively.
Electrochemical impedance spectroscopy (EIS) and differential scanning calorimetry (DSC) were performed to elucidate the effect of the hot-pressing temperature on the DMFC MEA performance. Firstly, in EIS analysis, the reaction transfer resistance of the anode, cathode, and the total showed similar values regardless of the hot-pressing temperature, as shown in Fig. 5 (b). Thisindicates that the pressing temperature for CLsisnot related to the reaction transfer resistancebetween catalyst and ionomer, and pore structure but is associated with changes in theinterfacial propertiesby the strong bonding between the CL and membrane. Secondly, Fig.5 (c) shows the DSC analysis of the hydrocarbon membrane. The exothermic process was observed at 150°C, which corresponds to the glass transition temperature (Tg) of the hydrocarbon membrane. At an appropriate temperature, such as 150°C, side chain movement brings the -SO3H group out of the bulk to the surface to decrease the surface energy (Liang et al., 2006, Guan et al., 2006, Robertson et al., 2003). This might give rise to intimate bonding between the hydrocarbon membrane and CL resulting in the enhanced proton conductivity. Therefore, the optimum hot-pressing temperature contributes to the significant increase in the MEA performance.
Effect of hot pressing temperature for the CCM prepared by direct coating on (a) power density of MEA and (b) reaction (rxn) transfer resistance from electrochemical impedance spectroscopy (EIS) and (c) DSC analysis of hydrocarbon membrane.
Fig.6 (a) shows the power densities at 0.45V and reaction transfer resistances of the MEA using CCM produced by the DCM under various hot-pressing pressures under the sametemperature of 150ºC. The increase of hot-pressing pressure for the CCM to approximately 0.225tonf/cm2resulted in significantly improved MEA performance with power density up to 107mW/cm2 at 0.45V and 60ºC. This might be attributed to the decreased reaction transfer resistance by the improved proton conduction and oxygen transport through the well-connected network of the CLs in the MEA. However, further increases in the hot-pressing pressure led to a decrease in the performance of MEA owing to the destroyed microstructures of the CL by excessive pressing.
This supposewasconfirmed by EIS analysis of the MEAs. Fig. 6 (b) shows the effect of the hot-pressing pressure for the CCM prepared by DCM on the reaction transfer resistance.The cathode reaction transfer resistance increased as both CLs were further compressedby increasing the hot-pressing pressure, whereas the anode reaction transfer resistancedecreased, even though the thickness of both CLs have decreased. Generally, the thickness of both porous CLs decreases with increasing of density (decreased porosity) as the pressing pressure increases to fabricate the CCM. The dense anode CL may increase the methanol utilization efficiency with the decreasing of the methanol crossover, resulting in the decreased the anode reaction transfer resistance. This phenomenon might be that because the dense anode CL serves as an additional resistance against methanol crossover (Mao et al., 2007, Liu et al., 2006, Park et al., 2008). In contrast, the thick microstructure (high porosity) for the cathode CL is essential for transporting reactant gas effectively from the GDL to CL and for eliminating the water produced by the electrochemical reaction from the CL to GDL (Liu & Wang, 2006, Wei et al., 2002, Song et al., 2005). Therefore, the hot-pressing pressure for the CCM showed the lowest total reaction transfer resistanceat 0.2tonf/cm2 and resulted in the highest power densityof the MEA produced by the DCM.It was suggested that the hot-pressing condition has a significant effect on the electrochemical performance of MEAs, particularly in the reaction transfer resistance.
Effect of hot-pressing pressure for the CCM prepared (a) power density of MEA and (b) reaction (rxn) transfer resistance from EIS.
The magnesium sulphate (MgSO4) was chosen as a pore forming agent for the preparation of the cathode CL. TheMgSO4 is widely used as a drying agent due to its hygroscopic properties (readily absorbs water from the air).Hence, it can be easily removed in the CL by boiling the CCM at DI water after DCM process. The vacant sites in the CL by resulted from removed MgSO4 may play a role as pores. In addition, compared to that of insoluble pore forming agents (e.g. Li2CO3) (Tucker et al., 2005), the addition of soluble MgSO4 could form more uniform pore distributions with smaller pore size (approximately 3 nm as a shown in Fig. 7 (b)) in the CL by the homogeneous catalyst inks, since the solubility of MgSO4 was superior in catalyst ink mixtures composed of the water, EG, ionomers and catalysts.
Fig. 7 (a) shows the effect of the pore forming agent (MgSO4) loading in the CL on the power density of the MEA by the DCM. As it can be seen, the addition of MgSO4in the catalyst slurry from 0wt% to 30 wt% led to an increase in power density of MEAs at 0.45V. This might be due to the higher degree of catalyst utilization and increase in active ESA because more pores that had formed by the MgSO4 contributed to thesupply of air to the catalytic active sites effectively to produce the required amount of power,and eliminate the water produced by the electrochemical reaction. Moreover, the effect of the cathode reaction transfer resistance by the addition of MgSO4 showed an opposite trend to the result of the cell performance as shown in Fig. 7 (a). However, further increasing of MgSO4 showed an increase of cathode reaction transfer resistance due to the destroyed microstructures of the weaken CL mechanically by excessive porous structure. Furthermore, the resistance for the proton transport to and from the active sites increased with increasing distance between catalysts and ionomers at the CL. Therefore, the pores generated by the MgSO4 mightbe an effective channel for air transport inside the CL.In addition, increased pore volumes are expected to enhance rapid mass-transfer near the catalyst surface providing open diffusion paths for the water produced from the CL. Furthermore, the enhanced oxygen supply increased the rate of oxygen reduction because the charge transfer reaction is a function of the reactant concentration.
Effect of MgSO4 amount in the catalyst layer of CCM prepared on (a) power density and cathode reaction transfer resistance and (b) pore size distribution of catalyst layer.
In this section, the adoption of new supported catalyst (Pt/OMC) consisted of novel ordered mesoporous carbon (OMC) support and highlydispersedPt to the cathode catalyst layer of the MEA for DMFC is presented as an example of optimization of properties such as catalystloading, ionomer concentration and porosity in the electrode (Kim et al., 2008). The Pt/OMC catalysts have been developed in our lab over several years for the DMFC, which is based on the novel OMC supports having very high surface area and ordered array of mesopores inside the particles (Chang et al., 2007, He et al., 2010, Joo et al., 2009., Lee et al., 2009, Pak et al., 2009).
A balance between proton conduction path and mass transport via pore structures of catalyst layer was investigated by changing an amount of ionomer and compressing the MEA with hot press. The performance of MEA as a function of voltage was measured to determine the optimized the conditions for catalyst layer, which governs the power density. Furthermore, the performance of MEA with optimized Pt/OMC catalyst layer was compared to that of unsupported Pt black catalyst layer to prove the possibility for decreasing the Pt amount in the cathode without loss of power density for DMFC.
The SEM and TEM images of ordered mesoporous silica (OMS), which is the hard-template for OMC, and OMC were displayed in the Fig 8. As observed in Fig. 8, the OMS is composed of 200 – 300 nm particles and OMC has similar particle morphology and size, which indicates that the nano-replication (Joo et al., 2001) of OMS into OMC is successfully occurred and the removal of OMS to generate the pore inside of the OMC did not alter the apparent morphology of OMC. The TEM image from OMS (Fig. 8 (b)) shows that the uniform mesopores are hexagonally well-arranged in the particle. For the OMC, the TEM image display that the pores and the walls of OMS are inverted to the carbon-nanorod and mesopore of OMC, respectively. The low angle X-ray diffraction (XRD) patterns (refer to Joo et al., 2006) of OMS and OMC showed three, well resolved peaks corresponding to (1 0 0), (1 1 0) and (2 0 0) diffractions of hexagonal p6mm symmetry. The unit cell dimension of OMS and OMC, estimated from the (1 0 0) diffraction was 12.0 and 11.0 nm, respectively. The OMC has a slightly compressed unit cell because of the structural shrinkage of carbon frameworks during the high temperature carbonization (Jun et al., 2000).
SEM and TEM images of (a, b) OMS and (c, d) OMC, respectively.
The pore structures of OMS and OMC were further characterized by using the nitrogen adsorption and desorption isotherms (Joo et al., 2006). The corresponding pore size distribution estimated from the adsorption branch by BJH method for OMS and OMC samples. The OMS template showed typical Type IV isotherm with H1 hysteresis. The sharp increase of nitrogen uptake in the adsorption branch in the partial pressure of 0.8–0.9 indicates that the mesopore of OMS has uniform distribution through the particles. The BET surface area of OMS template is451m2/gand pore volume is 1.27 cm3/g, while the porediameter calculated from the adsorption branch of isothermsis 12.2 nm. The nitrogen isotherms of OMC sample exhibited similar shapes, where capillary condensationoccurred in the partial pressure range of 0.4–0.6.The BET surface area of OMCsample is884 m2/gand pore volume is 0.86 cm3/g, while the porediameter is 4.0 nm.
The unique structural characteristics of OMCs make themsuitable as catalyst supports for DMFC application as mentioned earlier. For example, the high surface area of OMC, compared with theconventional carbon blacks such as Vulcan XC-72R and KetjenBlack, can provide sufficient surface functional groups oranchoring sites for the nucleation and growth of metal nanoparticles,thus metal catalysts can be prepared on OMC with highdispersion. Further, uniform mesopore structure of OMC wouldfacilitate the diffusion of reactive molecules for electrochemicalreactions.
Pt nanoparticles were supported on the OMC by incipient wetness impregnationof the Pt precursor (H2PtCl6 xH2O) in acetonesolutioninto the pores of OMC support and subsequent reduction under H2 flow. The total loadingof Pt was controlled as high as 60 wt%, because an electrocatalystfor DMFC application requires very high metalloading (Chang et al., 2007). The TEM image of Pt/OMC (Fig. 9(a)) indicates thatPt nanoparticles are uniformly scattered on the carbon nanorod of OMC.The average particles size determined from the TEM image is 2.85 nm.The XRD patterns for 60 wt% Pt/OMC presentedin Fig. 9(b) showed distinct peaks at around 39.8º, 46.3º and 67.5º,corresponding to the (11 1), (2 0 0) and (2 2 0) planes of a face-centeredcubic structure, respectively. The crystalline size ofthe Pt nanoparticle estimated by the Scherrer equation is2.86 nm,which is matched well with the value obtained from TEM analysis.
a) TEM image and (b) XRD pattern for Pt/OMC catalyst.
To realize the adoption of Pt/OMC in the cathode catalyst layer for DMFC, the effect of the ionomer contents (18, 30 and 45 % compared to the Pt/OMC) and process parameter (compressed vs. uncompressed) were investigated on the morphology of electrode and performance of MEA at 70 ºC as summarized in the Table 1. The catalyst ink was sprayed directly on to a Nafion 115 membraneto form the so-called CCM. Themembrane was held on a vacuum plate to prevent dimensionalchange of the membrane during the direct coating of the ink. Thecathode catalyst ink was coated on one side of the membrane followedby drying at 60 ºC under vacuum for 2 h. On the uncoatedside of the cathode-coated membrane, the anode catalyst ink wasapplied in the same manner.As a reference,the catalyst layer based on unsupported Ptblack catalyst (JohnsonMatthey, HiSpec® 1000) at a loading level of 6mg/cm2 was alsoprepared. The geometric area of the catalyst layers was 25 cm2. In order to produce a catalyst layer with lower porosity, thecathode-coatedmembranes were compressed at 30MPa and at135 ºC for 5min before the subsequent anode coating was performed.As a diffusion layer, 35 BC (SGL, Germany) was used forboth the cathode and the anode. The MEAswere prepared by hot pressingthe CCM and two diffusion layers at 125 ºC and 51MPa. Themorphology of the catalyst layers was observed by SEM.
Catalyst Layer | Amount of Pt(mg/cm2) | Ionomer content(%) | Compression |
CL18-U | 2.39 | 18 | X |
CL18-C | 2.39 | 18 | O |
CL30-U | 2.64 | 30 | X |
CL30-C | 2.64 | 30 | O |
CL45-U | 2.39 | 45 | X |
CL45-C | 2.39 | 45 | O |
Physical parameters of catalyst layers based on Pt/OMC catalyst
The thicknessof the uncompressed catalyst layers (CL18-U, CL30-U and CL45-U) is 70, 128 and 132μm, respectively, forcorresponding ionomer contents of 18, 30 and 45 % and the thickness of the compressed catalyst layers (CL18-C, CL30-C and CL45-C) is found to be 64, 53 and 48% of the pristine thickness for ionomer amount of 18, 30 and 45%, respectively. In the case of ionomer amount of 12%, the strength of catalyst layer is not enough to adhere on the GDL, which could be attributed that the ionomer content is not enough to bind Pt/OMC catalysts effectively. The ionomer contents become more than 12% and the catalyst layer showed acceptable mechanical strength.
The apparent shape of the Pt/OMC-based catalyst layers wasobserved by SEM, as displayed in Fig. 10 for representative examples (CL18-U and CL18-C). These are featured bythe formation of agglomerates of the Pt/OMC and ionomer and of the pores between these agglomerates. The agglomerate size is in therange of 200–1000 nm. Considering the size of the primary OMC (200–300 nm) particle as shown in Fig. 8, several Pt/OMC particles are included in theagglomerate. The change of ionomeramount did not cause the appreciable changes in the size of the agglomerates in the catalyst layers. For the uncompressedcatalyst layers, the porosity appears to be larger at higherionomer contents.
After compression, densification of the catalystlayer is observed. On the other hand, the size of the agglomerates islittle affected by the compression, as shown in Fig. 10. This indicatesthat macropores between the agglomerates are reduced during thecompression process. The compressed catalyst layers do not differin their pore structures.
RepresnetativeSEM images with different magnification of (a, b)CL18-U and (c, d) CL18-C.
Fig. 11 showed polarization curves obtained after five day activation at 70 ºC. Among the MEA, CL18U-C case showed the highest power density of 104.2 mW/cm2 at 0.45 V. Theoperating voltage of DMFC MEA was chosen based on the balance between powerdensity and energy efficiency. Operation at lower voltage generateshigh power density, and thus size reduction of the stack is possible.On the other hand, energy efficiency decreases on lowering thevoltage, which requires a larger fuel tank for a given energy consumption. To maximize the system efficiency, an operating voltage of 0.45V is chosen for DMFC usually. Dry air and 1Maqueous methanol solution were used as feedstocks for the cathode and the anode, respectively. As shown in Fig. 11, uncompressed MEAs show higher performance at 0.45 V than that of compressed MEAs with same amount of ionomer in the catalyst layer. The variation of the ionomer amount results in a more pronounced effect on the power density than compression of catalyst layer, which is consistent with a result reported earlier in the literature (Frey and Linardi, 2004). As the catalyst layer compressed, the layer becomes more compact, which reduced the mass transport in the catalyst layer. However, the proton conductivity in the catalyst layer should be increased with compression, which was confirmed by the analysis of impedance (Kim et al., 2008).
Polarization curves for MEAs based on Pt/OMC at 70 ºC (cathode feed: air, anode feed: 1M CH3OH).
Thus, the decrease in power density with the compression indicates that mass transport is more important than the proton conductivity (ionic transport) for the Pt/OMC based cathode. A similar finding was reported for a PtRu/C supported catalyst in the previous paper, which suggested the compaction of the anode catalyst layer led to a decrease in performance by 23% due to increased mass transport (Zhang et al., 2006).
For both the uncompressed and compressed MEAs,the gap of power density increases with reducing in the ionomer contentabove 150mA/cm2. Below 150mA/cm2, however, the differenceis less pronounced, where the power density of CL45-U becomes comparable to that of CL18-U.The large difference in power densitiesat high current densities indicates a considerable mass-transportlimitation at higher ionomeramount.When conventional Pt-supported carbon is used, there is anoptimum value of ionomer content in the catalyst layer to obtainthe best performance. Even though the existence of an optimumat lower ionomer content is expected for a Pt/OMC-basedcatalyst layer, it is not possible to confirm this because the mechanicalintegrity of the catalyst layer is not sufficient as mentioned earlier in this section. An improvement in the formation of thethree-dimensional network of the ionomer phase which providesmechanical integrity is needed to confirm the existence of an optimumat lower content of ionomer.
The polarization behaviour of a CL18-U catalyst layer at aloading level of 2mg/cm2 and a catalyst layer based on Ptblackcatalyst at a loading of 6mg/cm2 is compared at Fig. 12. The thicknessof the catalyst layer for the CL18-U and Pt-black catalystsis 70 and 45μm, respectively. The MEAs have identical components,except the cathode catalyst layer. The CL18-U catalyst delivershigher power at high voltages (>0.4 V) and lower power density atlow voltages (<0.4 V) than the Ptblack-based cathode. Since catalyticactivity governs the electrochemical reaction rate at the highvoltages (activation region), the higher power density for Pt/OMCindicates that 2mg/cm2 of Pt/OMC gives higher catalytic activitythan 6mg/cm2 of Ptblack catalyst, which is of practical importance. Withthe introduction of an OMC support, the Pt loading in the cathodecan be reduced to one-third of Ptblack-based catalyst layer,without any negative effect on power performance, and thiswouldsignificantly contribute to cost reduction of MEAs. The lower powerdensity for the Pt/OMC catalyst layer at high-current density indicatesthat the mass-transport limitation is greater than that for thePtblack-based catalyst layer.
Comparison of polarization curves at 70 ◦C of MEA with the cathode from Pt/OMC catalyst (2 mg/cm2) andunsupported Ptblack catalyst (6mg/cm2) (cathode feed: air, anode feed: 1M CH3OH).
In this chapter, the fabrication processes for the electrode for MEA was briefly reviewed ina view of optimization of process parameter and application of new supported catalyst. The processes were catalyst coated on the electrode (CCE), decal transfer catalyst coated on membrane (DTM) and direct catalyst coated on membrane (DCM) methods. Among the three processes, the optimization of DCM method for DMFC MEA was presented as an example. The temperature and pressure were the main parameter which should be adjusted for maximizing the performance of MEA using hydrocarbon membrane. The effect of pore generation by pore forming agent on the performance was discussed. In addition, the application of new Pt/OMC catalyst for DMFC MEA was demonstrated by controlling the amount of ionomer and compression of catalyst layer. The application of Pt/OMC catalyst resulted in the decrease of the amount of Pt in the cathode from 6 mg/cm2 for Pt black catalyst to 2 mg/cm2 using Pt/OMC without lost the performance.
Navigation in ports, canals and waterways must be safeguarded by maintenance dredging to remove sediments deposited by tide, river flows and currents. In order to keep ports and waterways accessible, this non-contaminated sediment is typically dredged by a trailing suction hopper dredger (TSHD) and reallocated at sea [1].
Maintenance dredging of sediment deposits can be highly expensive and inefficient as it must be done on a regular basis. Therefore, port authorities seek tailor-made solutions to reduce the costs and at the same time guarantee safe navigation in ports and waterways. Over the last decades, a number of strategies for port maintenance have been tested by port and governmental authorities. Maintenance dredging can be optimized by techniques to avoid or reduce sedimentation, such as optimization of port design, current deflecting walls, see [2], or by designing a sedimentation trap to focus sediment deposition in order to make reallocation easier and to reduce sediment deposition in other port areas [3].
Once dredging has conducted, typical strategies for dredged sediment management are either based on the concepts of keeping sediment in the water system or bringing sediment on land (see Figure 1). The former is generally considered as the most cost-effective strategy. However, the latter can be utilized for beneficial re-use of dredged sediment, thus better embedded into a circular economy.
Types of port maintenance methods which are based on the dredging methods keeping sediment in water or bringing dredged material on land.
It is a well-known fact that in major sea ports fine-grained sediment deposits are routinely reallocated from the port area either further away downstream from the dredged area or directly to the sea depending on the return flow of from the reallocation locations. The choice in reallocation area often consists of finding a balance between minimizing sediment return flows back into the harbor and transport distance and costs. Often, the reallocation of dredged sediment is combined with sediment management within a building with nature concept [4]. These reallocation projects are mainly focused on the reallocation of fine-grained sediment for land creation or improvement, wild habitat restoration, shore nourishment and marsh or wetland development [5, 6, 7].
In contrast to reallocation of sediment, conditioning is used for port maintenance with the assumption that the sediment stays in the port area. The goal of conditioning the sediment is to create navigable conditions in waterways while keeping the sediment in place. In this case, the nautical bottom concept is often applied for navigation through mud [8, 9, 10]. One of the examples for applying sediment conditioning for port maintenance is in the Port of Emden. The sediment first dredged and then conditioned by reducing the strength of dredged sediment in the dredging vessel [8]. The created fluid mud is then pumped back to the port mouth creating a weak navigable fluid mud layer. If the transport of fluid mud towards the river equals the import of suspended mud by exchange flows, a dynamic equilibrium is achieved without residual import, hence dredging.
These techniques do not apply to contaminated dredged sediment which is either stored in confined disposal facilities [1, 11] or processed in sediment treatment facilities [12, 13]. The latter technology uses mechanical treatment to prepare the sediment for further beneficial re-use options. Recently, mechanical treatment is also used for non-contaminated sediment as dredged sediment is being recognized as a resource. The treated material can be used as a constructional component for building and re-enforcement of infrastructure [14, 15].
Water injection dredging (WID) can be used as a tool for both reallocation and conditioning of the deposited sediment. The efficiency of this dredging method has been recognized over the past 30 years. However, the successful application of WID can be only achieved by combining technical approaches with knowledge of the system where WID is to be applied. Particularly, the following key questions have to be answered in order to understand better the impact of WID on reallocation and conditioning of cohesive sediment:
What type of sediment is to be relocated or conditioned by WID?
What are the hydrodynamic conditions and bathymetry in the WID area?
How fluidized sediment is distributed in port basins after WID?
How far and where is the WID-induced plume transported after WID?
What is the impact of WID on near-surface turbidity and how is this influenced by operational parameters?
What criteria for navigation can be used in WID-conditioned areas?
The goal of this chapter is to provide an overview of the developed knowledge and tools that can be used for addressing the abovementioned questions. In addition, recently-developed numerical modeling, field and laboratory experiments can provide the necessary information for optimizing WID and defining the boundary conditions for its application. Finally, the recent findings on navigable conditions in ports and waterways, where WID is used for conditioning the sediment and keeping fluid mud in place, are discussed.
The principle of the water injection process is based on fluidization of deposited sediment by a water jet (see Figure 2). Water injection is performed by injecting large volumes of water (approx. 12,000 m3/h) under relatively low pressure (approx. 1-1.5 bar) from water jet nozzles, that are distributed over an equal distance on the jet [16, 17]. The injected water penetrates the cavities between the individual sediment particles weakening the forces between them and destroying the formed structure of the bed. The water-sediment mixture forms a fluid mud layer of about 0.5-3 m thickness right above the bed. Most investigations show that the sediment material hardly mixes into the upper water volume, and sediment transport of the fluidized mud layer remained predominantly close to the bottom [18, 19].
Phases of WID: I. water injection and fluidization; II. Transition zone, where a density flow is created; III. Transport of the density flow. Adapted from [
A sketch of WID performed in a navigational channel with a bed mainly consisting of fine-grained cohesive sediment is shown in Figure 3. The near bed fluidized sediment deposit generates a gravity driven density flow up to few meters high, transporting the sediment in a horizontal direction as a result of the density difference [17, 20, 21, 22]. This density flow can be described as a homogeneous suspension layer with a solid concentration of up to 200 g/l. Since the density between the fluid mud layer and the surrounding water body is different, fluid mud sets in motion under the action of natural hydrodynamic processes. Thus, WID is different from agitation dredging in which sediment is deliberately mixed over the full water column and then transported in horizontal direction as a passive plume by the ambient currents resulting in a less environmental-friendly outcomes.
Illustration of WID performed in a navigational channel during the ebb tide. a) Initial conditions for WID. b) Fluidization of deposited sediment during WID. c) WID-induced fluid mud layer. d) Final result after WID in case WID is conducted for sediment reallocation purposes.
The velocity of fluidized sediment is reported in the range between 0.3 m/s and 1 m/s [16, 21, 22]. Based on the hydrodynamic conditions in a port basin, WID-conditioned sediment can either settle over time in a low-energy area or be transported by means of gravity currents to deeper areas such as sediment traps [3].
Different transport distances from a few hundred meters to a few kilometers are reported for fluidized sediment [19, 21, 22, 23]. Natural transport of coarse-grained sandy sediment is substantially shorter. Therefore, the sediment composition of the bottom can be altered by WID operations. Fine-grained sediment can be generally more easily fluidized than coarse-grained material and has better transport properties. Since the fine grain fraction is transported away sooner and further than the coarse grain fraction, over time the particle size distribution of the sediment bed can be segregated as a result of dredging. Therefore, the coarse-grained component increases as a result of WID operations.
The effectiveness of the WID process can be influenced by various factors. The direction, velocity and achieved transport distances of the fluidized layer depend on the interaction of different physical forces. The important influencing factors are sediment composition and characteristics, WID operation characteristics, resulting density of the fluidized layer, bathymetry and natural currents and bed shear stresses in the WID area. The efficiency of the process is also influenced by the bathymetry of the dredging area and the prevailing natural currents. Productivity is generally increased when WID can be carried out so that fluid mud can flow with a natural gradient from higher to lower-lying bathymetry.
The composition and strength of the sediment are also essential for fluidization process. Although it is reported that WID has been also performed for removing coarse-grained sandy sediment and even consolidated soils [16, 21, 22], the best efficiency of WID has been achieved by fluidizing fine-grained sediment deposits. In [20] WID productions are reported in the order of a few thousand m3/h for very fine-grained sediments and in the order of a few hundred m3/h for coarser sediments.
The operational parameters for execution of WID are playing an important role for WID. The determining factors are the nozzles diameter, the flow velocity of the water from the jet, jet penetration, the forward movement of the jet pipe, and the distance between the jet nozzle and the surface of the sediment [24]. A WID operator can find the optimal combination of the aforementioned factors to achieve the maximum production of loosened material. However, not only the mass flux of loosened material should be optimized, but also the initial density, layer height and velocity. A thin but dense layer with little initial momentum will hardly spread, whereas a thick, diluted layer with high velocity will quickly mix with ambient water, with negative consequences for turbidity and focus of sedimentation footprint.
WID is generally considered as a relatively low-cost process [3, 25]. As the fluidized sediment is transported in the form of a density flow on the bed and is not distributed throughout the entire water column, WID is also characterized by a high level of environmental compatibility competing to traditional port maintenance dredging [3, 18]. Recently, it was also shown that WID is more CO2 efficient than the regular TSHD maintenance because WID requires less fuel consumption than TSHD. All these aspects suggest that WID can be more attractive tool for port maintenance.
In recent years, different tools have been developed for optimizing WID processes and better prediction of sediment plume movement during WID. Numerical modeling tools can be used for estimating sediment dynamics in ports and waterways after WID.
Mid-field modeling is often used for calculating the sediment footprint on the areas up to about 1 km away from WID. The obtained knowledge on sedimentation can help to better design WID operations including real bathymetry of a navigational channel. Existing and hypothetical infrastructure can be included in mid-field modeling allowing for testing of WID in combination with sediment transport steering management solutions such as sediment traps, sills and current-deflection walls.
Far-field modeling evaluates the impact of WID on the scale of the entire port or estuary area. This kind of modeling is used for estimating WID reallocation strategies of sediment from the port basins to the sea and for assessing return flows. Simulations can demonstrate the transport of the WID plume during different phases of the tide and the impact of river and sea conditions. Based on the obtained information, the authorities can decide if conducting WID for reallocation purposes is effective in the port.
Mid-field modeling is carried out by two distinct models: a Lagrangian 1DV model and a 3D CFD model (TUDflow3D). The Lagrangian 1DV model is a rapid assessment tool which can be used for rather uniform bathymetry and slowly varying flows while neglecting lateral spreading. When these assumptions are not valid the more sophisticated 3D CFD model TUDflow3D can be used which includes lateral spreading and simulates a WID density current in three dimensions. TUDflow3D needs much more simulation time as the Lagrangian 1DV model.
The Lagrangian 1DV approach allows us to follow the development of the fluidized layer flow along a user-defined trajectory using a moving frame of reference. The 1DV model determines the thickness and the density (or the sediment concentration) of the fluidized mud layer and correlates these properties to the hydrodynamics in the water column and the slope of the bed. Additionally, it determines the sedimentation flux on the bed. For an equal initial momentum of the fluidized mud layer, the layer will flow further along a downward slope than along a flat bed. In general, the results of 1DV modeling can be used for a better planning of WID.
Figures 4 and 5 illustrate an example of utility of the 1DV model for water injection dredging. In both figures, the left panel shows the distribution of the sediment concentration and the height of the fluidized mud layer along the slope. The right panel shows the flow velocity of the fluidized mud layer. Figure 4 shows the simulation of WID for an initial WID plume height of 2 m and Figure 5 shows the results of WID for an initial WID plume height of 3 m. Both cases start with an initial sediment concentration of 170 kg/m3 and 0.7 m/s flow velocity. It can be seen that a higher fluidized mud layer travels faster and reaches a higher internal velocity.
1DV results for initial WID plume height of 2 m.
1DV result for initial WID plume height of 3 m.
WID density-driven plumes can be also simulated in 3D by the CFD model TUDflow3D [26, 27]. Originally, TUDflow3D has been developed for accurate near field simulations of Trailing Suction Hopper Dredger overflow plumes on real scale. It has also been used for MFE (Mass Flow Excavation) plumes, deep sea mining tailing plumes and salinity driven density flows. TUDflow3D can supplement the 1DV model for complex situations in which the simplifications of the 1DV model make application impossible. TUDflow3D is fully 3D with variable density taken into account in all three dimensions (not just in the vertical), non-hydrostatic pressure and turbulence captured by either the accurate LES (Large Eddy Simulation) approach or by a faster RANS (Reynolds Averaged Navier Stokes) approach.
An instantaneous snapshot of the modeled density current is shown in Figure 6. The individual turbulent eddies and whirls resolved on the grid in LES are clearly visible. Comparison for time averaged velocity and Suspended Sediment Concentration (SSC) profiles with measured ones is given in Figure 7. Here, different manners of capturing turbulence are compared. In addition to LES with the WALE sub-grid-scale model, the RANS with Realizable K-Epsilon model and Realizable K-Epsilon model with reduced eddy viscosity near the bed are tested. In the latter the eddy viscosity near the bed is adjusted, effectively reduced, to correspond to the correct amount of bed shear stress. The results show that this adjustment improves the Realizable K-Epsilon results for this flow. The vertical SSC profile and layer thickness of the density current is captured very well in the CFD LES model and the velocity profiles are captured reasonably well with a small overprediction of the near bed velocity. The Realizable K-Epsilon results with adjusted near bed viscosity are considerably better as the default Realizable K-Epsilon results.
Instantaneous LES snapshot of 3D contour (top) of a turbidity current and SSC at a vertical slice through the center of the turbidity current (bottom).
Comparison modeled time averaged velocity and SSC profiles with 3 different turbulence settings (LES; realizable K-epsilon and realizable K-epsilon with reduced near bed viscosity) and measurements from [
An example a of application of TUDflow3D for WID is given in Figure 8. In this CFD run a WID works along a 300 m track which it has done 6 times in a row. The CFD model uses the real bathymetry of the port. The resulting WID plume is shown in brown and the bathymetry is illustrated as a gray surface. At the moment of this image the WID has just finished the 6th time along the black dashed track of 300 m long. In this example the WID plume flows down the sloping bed in lateral direction under influence of gravity. A top view of the bathymetry is shown in Figure 9.
Example of TUDflow3d simulation: Plume distribution from WID action along black dashed line.
Example of TUDflow3D simulation: Implementing bathymetry in a CFD domain.
A comparison of TUDflow3D and the Lagrangian 1DV model for WID in a lateral confined situation without bed-slope is shown in Figure 10. For this simulation, the following initial conditions were applied: initial WID layer thickens of 2 m, 170 kg/m3 and 0.7 m/s inflow (resulting in an influx of 238 kg/s). The example shows the simulated vertical velocity profiles and density profiles at different distances from the WID. The model also calculates the sedimentation flux out of the WID density current. The results of the 1DV model and full 3D CFD are close to each other for this case. For cases where the assumptions of the Lagrangian 1DV model (neglecting lateral spreading and slowly varying flow conditions) hold it is much faster as the more sophisticated TUDflow3D model and in other cases it is advised to use a 3D near field model like TUDflow3D.
Comparison of CFD model TUDflow3D and 1Dv simulations for WID in a lateral confined situation. TUDflow3D is compared for two different turbulence settings (LES; realizable K-epsilon).
Sediment dynamics and specifically, the siltation of mud, in ports is of great interest to those responsible for the maintenance of ports, harbors and access channels around the world. The amount of siltation determines the frequency and volume of maintenance dredging needed to maintain navigable depth. In order to understand sediment dynamics in the system, in particular the processes responsible for suspended mud and fluid mud transport, a range of spatial and temporal scales must be analyzed. A numerical model is an ideal tool with which to investigate both the transport, deposition, and potential resuspension of a WID plume. Such a model was developed, using Delft3D, for the Rhine Meuse Delta in the Netherlands, in order to calculate both background fine sediment dynamics in the Port of Rotterdam and the transportation of a fluid mud layer after a WID operation.
Deltares’ open source software Delft3D is a flexible, integrated modeling framework which simulates two and three-dimensional flow, waves, sediment transport and morphology (as well as dredging and dumping) on a time-scale of days to decades. The sediment transport module includes both suspended and bed/total load transport processes for an arbitrary number of cohesive and non-cohesive sediment fractions. It can keep track of the bed composition to build up a stratigraphic record. The suspended load solver is connected to the 2D or 3D advection–diffusion solver of the hydrodynamic module and importantly for fluid-mud simulations, density feedback can also occur.
For this work, a Delft3D model of the entire Rhine Meuse Estuary was setup. Hydrodynamic conditions were simulated for a full month, including wave effects. This hydrodynamic model is then used to force the sediment transport model. Background sediment concentrations are included in the model using three sediment fractions to represent the appropriate range of coarser and finer fractions. Once natural dynamics regarding sediment transport and sediment deposition in the different ports was captured, a range of WID tests could be undertaken. The parameters derived for different WID production rates in the mid-field modeling (described in Section 3.1) are used to define the initial conditions for the WID plume in the far-field model. Numerical experiments could then be performed such as simulating where the WID plume is transported to, the amount of return flow into different parts of the port and the amount of mixing that occurs throughout the water column. Vertical mixing may result in elevated turbidity levels near the surface, which should remain within the environmental limits. The model is also used to investigate the optimum location for sediment traps to capture the WID high density plume.
Horizontal near bed plume spreading, WID starts 1 h before HW with a production rate of 500 kg/s.
Horizontal near bed plume spreading, WID starts 1 h before LW with a production rate of 500 kg/s.
The plume disperses in a distinct way between the simulation starting before high water (HW) compared to a start at low water (LW). Figure 11 shows that the plume is predominantly dispersed in the seaward direction with the outgoing tide. For WID, this would be the most preferable conditions because in this way the suspended sediment will be relocated from the area where WID is conducted offshore. However, after approximately six hours the flow is reversed, and the plume is pushed in the landward direction.
Figure 12 show the initial plume dispersion for the simulations in which sediment is released just before LW. The dispersion of the plume in the first 2 hours of the simulations is similar to the experiment with WID release just before HW. However, between four and eight hours a predominant landward plume dispersion is observed. After the flow reversal, it is observed that the plume starts to disperse in the seaward direction. A continuation of the landward spreading is observed in the channel because of the predominant landward flood directed current.
The far-field modeling illustrates the importance of the hydrodynamic conditions during WID. This knowledge can help to choose the most-efficient strategy for WID in ports and waterways with mud layers. The most efficient strategy is not only related to optimizing the sedimentation footprint, but also to minimizing vertical mixing and the contribution of WID to turbidity higher up in the water column. By choosing operational parameters wisely and executing WID operations only during favorable hydrodynamic conditions demands on sedimentation footprint and turbidity are more easily met.
In low-energy regions or in a tidal area of the port, WID-induced sediment can form a fluid mud layer that remains in the port area. The thickness of WID-induced fluid mud layer is often larger than the thickness of original mud layer resulting in a reduced draft for the incoming vessels. In this case, WID is often combined with the nautical bottom approach defined by PIANC for navigation. According to PIANC, ‘The nautical bottom is the level where physical characteristics of the bottom reach a critical limit beyond which contact with a ship’s keel causes either damage or unacceptable effects on controllability and manoeuvrability’ [10, 29]. The nautical bottom allows to use the fluid mud in estimates of under keel clearance (UKC) that the vessels can navigate in the port areas with no unacceptable effects on controllability and maneuvering of the vessels. If accepted by the port authorities, the nautical bottom approach is used for navigation through mud in ports and waterways with fluid mud layers.
Generally, the density of the top sediment layer is used for defining the nautical bottom (see Figure 13). The level, where the density of sediment is lower than 1.2 t/m3, is widely accepted for navigation in ports. Ports in Rotterdam, Zeebrugge, Bordeaux, Saint-Nazaire, Bristol, Bangkok, Tianjin have successfully adapted the density criterium for navigation [29, 30]. However, the Port of Emden relies on the rheological properties rather than density of the sediment for defining the nautical bottom. The yield stress of the top sediment layer gives an indication if the sediment is navigable or not. The sediment with yield stress lower than 100 Pa is considered navigable. The choice of the nautical bottom criterium is related to the conditioning of sediment, that the Port of Emden has been conducting for port maintenance.
Illustration of the nautical bottom concept with the density of 1.2 t/m3.
The knowledge on in-situ density or rheological properties of the top sediment layer are necessary for implementing the nautical bottom approach. There are in-situ tools that can provide an information about vertical profiles of density and strength in water-mud column. The in-situ devices Rheotune, Graviprobe and DensX have been intensively tested for the nautical bottom approach over last years [3, 29, 31].
An example of in-situ measurement of density and yield stress provided by Rheotune is shown in Figure 14. The measurements are conducted in a sediment trap that was filled with WID-induced fluid mud during day 1. The development of density and yield stress of WID-induced sediment has been observed for the period of 3 months. The in-situ devices can naturally provide only 1D vertical profiles. However, the thickness of mud layer can be defined from the profiles if the critical value for physical parameters is defined.
Density and yield stress profiles measured by Rheotune.
In the example given in Figure 15, the critical value for the density is chosen as 1.2 t/m3 providing the density-based nautical bottom shown in red line. In this case, the SILAS software is used for matching the density given by Rheotune (shown by vertical blue line in Figure 15) to the seismic data of 38 kHz. The measurements are conducted 7, 21 and 42 days after WID.
Development of the density-based nautical bottom after WID. Red line shows the level, where the density of sediment is equal to 1.2 t/m3.
The development of WID-induced mud layer be also estimated with the numerical code solving the Gibson Eq. [33]. For instance, settling and consolidation of fluid mud can be predicted by matching the measured data to the model output. Figure 16 shows the comparison of 1DV model and measured data during consolidation of WID-induced fluid mud layer. The model’s output is the density of mud and the water mud interface as a function of time, that can be correlated to measured densities and multibeam data, respectively. The latter can typically provide a reliable water-mud interface for WID operations. For instance, Figure 17 shows the development of water-mud interface before, during and after WID in the Calandkanaal.
Estimating consolidation of fluidized mud layer after WID. Left panel shows development of water - fluidized mud interface as well as fluidized mud – Consolidated bed interface. Right panel show model predictions (solid lines) and in-situ measurements (symbols) of densities in water-mud vertical column.
Multibeam measurements indicating water-mud interface before WID (reference), during WID (day 1) and after WID (day 7 - day 42) in the Calandkanaal.
Vertical density profiles are shown in the right panel of Figure 16. The density measurements can be done by different penetrometers [3, 31, 32], in this case the densities are measured by DensX. It can be observed that the measured density profiles show a good resemblance with the results of numerical modeling [31, 32]. Thus, the combination of the model with the in-situ measurements can potentially be used for predicting the development of the nautical bottom in time.
An example of the application of PIANC’s nautical bottom approach after WID in the Port of Rotterdam is shown in Figure 18. The standard multibeam echosounder survey indicated the bathymetry that corresponds to the water-mud level. However, the WID-induced fluid mud has relatively low densities (<1200 kg/m3) and weak strength (<100 Pa). Therefore, the nautical bottom approach can be applied. Adapting either a density-based (1200 kg/m3) or yield stress-based (100 Pa) criterium for the nautical bottom results in an additional 1.5 and 2 m of navigable depth, respectively. 20 days after WID, these differences are reduced. However, the yield stress-based nautical bottom still shows an advantage of about 0.5 m of extra navigable depth.
An example of applying the nautical bottom approach after WID [
Water injection dredging is a widely applicable dredging method. The efficiency of the method for maintaining ports and waterways is generally high. WID operational parameters, knowledge of sediment properties, boundary and hydrodynamic conditions of the maintained area can greatly increase the efficacy of the water injection process. The most important parameters and factors influencing the performance of WID are the following: WID operational parameters (diameter of nozzles, flow velocity from the nozzle, stand-off distance of the jet, trailing speed of the WID vessel), sediment properties (grain size distribution, shear strength, density, oxygen consumption potential and sediment quality), boundary conditions of the maintained area (bathymetry, slope angle, embankments), hydrodynamics conditions (direction and velocity of tidal currents, existing density currents and salinity gradients).
Apart from the operational parameters, other factors and conditions that can increase the performance of WID are site-specific. Currently, the literature on research investigations into WID operational parameters is scarce. Therefore, there is a need for further systematic laboratory investigations for exploring the most-efficient WID operational parameters, which can further maximize the WID production rates in the field.
Sediment properties in the proposed area for WID can be studied before conducting WID. Typically, sediment samples are collected for laboratory analysis. The shear strength and density of sediment are linked to WID operational parameters (such as flow velocity) during the WID fluidization processes. The literature on investigations of sediment properties while testing varying WID operational parameters is very limited. Predominantly, WID is applied in the area with no-contaminated sediment. Therefore, the knowledge of the quality of sediment in the WID area is important.
The geometry of the WID area should be taken into account for planning and execution of WID operations in port and waterways. Bathymetric charts, which, will provide the information about deeper areas in the WID location, which are typically filled in with fluid mud after WID. Furthermore, bathymetric charts will indicate the slopes in the WID area, which can be also used for transporting the fluidized mud more efficiently.
Hydrodynamic conditions in the WID area should be taken into account when determining the final fate of fluid mud generated by WID, whether WID is used for the transport or conditioning of mud. For the transport of mud, the knowledge of the direction of the natural current and current velocities can help to minimize the spread of the WID-induced fluid mud deeper into the port area and maximize the transport of the sediment from the port area. For the conditioning of mud, the hydrodynamic conditions can potentially provide an indication whether fluid mud starts to settle in the allocated area or is transported to other locations of the port. Salinity gradients and local density currents can influence the density currents by damping the velocity of WID-induced fluid mud, thus decreasing production rates in the WID-area.
This chapter focusses on presenting an overview of developed knowledge for WID. In particular, new insights gained using a combination of in-situ monitoring and numerical modeling. The research focusea on fluid mud behavior and transport, but also the resulting sediment plume. Both mechanisms are important and depend on the surrounding hydrodynamic conditions. Mid-field modeling was used to investigate the WID plume flow and deposition behavior up to 1 km away from the WID dredger. The WID-induced fluid mud layer thickness and WID production estimates were used as input in to the far-field model. The far-field model was used to determine where the WID-induced plume traveled under different tidal and discharge conditions, how much deposited back in the harbors and how much was flushed out to sea with the ebb tide. The model was also used to test different disposal locations to reduce return flow.
Key factors and parameters influencing the efficiency of WID have been identified from the available literature and discussed further. The modeling tools presented in the chapter can potentially help to analyze the sediment properties, boundary conditions and hydrodynamic conditions in the WID area and in the entire port area. However, more experimental research is needed for defining the most-efficient set of operational parameters. Particularly, the knowledge on linking WID operational parameters with sediment properties for maximizing production rates is very scarce.
By combining measurements from the field, laboratory experiments on fluid mud properties, with a state-of-the-art modeling approach, new insights were gained on the best approach for implementing WID as a maintenance dredging strategy. In addition due to more efficient maintenance, reduction of costs, CO2 emissions and additional environmental impacts is achieved during the application of these techniques.
The work in this study is funded by the Port of Rotterdam and by Topconsortium voor Kennis en Innovatie (TKI) Deltatechnologie subsidy. The research is carried out within the framework of the MUDNET academic network https://www.tudelft.nl/mudnet/
The authors declare no conflict of interest.
water injection dredging trailing suction hopper dredger Reynolds averaged Navier Stokes suspended sediment concentration Large Eddy Simulation Mass Flow Excavation high water low water World Association for Waterborne Transport Infrastructure under keel clearance
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The choice of available treatments depends on tumor characteristics such as biomarkers, tumor size, metastatic disease, ligands, and antigen or endocrine receptor expression. Combined with surgical resection, chemotherapy and radiation remain the first line of treatment for patients with cancer. Even with these treatments, however, cancer continues to have high fatality rates and current therapeutic modalities have yet to significantly improve the often dismal prognosis of this disease. Nanotechnology is a highly focused approach, which may provide more effective and less toxic treatment when compared to chemotherapy. This area of research has emerged as cancer treatment in the form of new drugs and has reached promising results in preclinical and clinical trials proving its value as a potential tumor therapy.",book:{id:"5431",slug:"breast-cancer-from-biology-to-medicine",title:"Breast Cancer",fullTitle:"Breast Cancer - From Biology to Medicine"},signatures:"Márcia Rocha, Natalia Chaves and Sônia Báo",authors:[{id:"147895",title:"Dr.",name:"Sônia Nair",middleName:null,surname:"Báo",slug:"sonia-nair-bao",fullName:"Sônia Nair Báo"},{id:"190527",title:"MSc.",name:"Natalia",middleName:null,surname:"Chaves",slug:"natalia-chaves",fullName:"Natalia Chaves"},{id:"190529",title:"MSc.",name:"Marcia",middleName:null,surname:"Oliveira Da Rocha",slug:"marcia-oliveira-da-rocha",fullName:"Marcia Oliveira Da Rocha"}]}],mostDownloadedChaptersLast30Days:[{id:"53856",title:"Early-Stage Progression of Breast Cancer",slug:"early-stage-progression-of-breast-cancer",totalDownloads:1684,totalCrossrefCites:4,totalDimensionsCites:4,abstract:"Breast cancer can be defined as a group of diseases with heterogeneous origins, molecular profiles and behaviors characterized by uncontrolled proliferation of cells within the mammary tissue. Around one in eight women in the US will develop breast cancer in their lifetime, making it the second most frequently diagnosed cancer behind skin cancer [1]. In 2015, an estimated 231,840 cases of invasive carcinoma were diagnosed, and over 40,000 deaths were caused by breast cancer which accounts for almost 7% of all cancer mortality each year. In 2015, 60,290 cases of in situ breast cancer were diagnosed, representing over 14% of all new cancer cases among women and men. The steep increase in diagnosis of early‐stage breast cancer over the past 10 years is believed to be a result of more frequent mammography. However, since over half of these in situ lesions will not progress to invasive breast cancer, controversies have arisen about approaches to treatment and prevention of progression of early‐stage in situ breast cancer. Understanding the mechanisms of transition of normal breast to in situ pre‐neoplastic lesions and invasive breast cancer is currently a major focus of breast cancer research with implications for preventive and clinical management of breast cancer. In this review, we give an overview of current knowledge on the molecular and pathological changes that occur during early‐stage progression of breast cancer and describe some of the current models that are used to study this process.",book:{id:"5431",slug:"breast-cancer-from-biology-to-medicine",title:"Breast Cancer",fullTitle:"Breast Cancer - From Biology to Medicine"},signatures:"William Kietzman, Anna T. 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TN, HER2+ tumors in postmenopausal women were of higher grade, showing lymph node and lymphovascular invasion with poor prognosis in all case series. However, the ER+/PR−/HER2+ subgroup had the lowest survival rates in 2- and 5-year follow-ups. Comparison between the ER+PR+HER2+ and ER+PR−HER2− subgroups showed that HER2− status is an indicator of improved prognosis in long-term follow-up. Single hormone receptor (HR)(+) status, particularly HER2(−) cases, was in between the favorable and poor survival subgroups. The ER−, PR−, and HER2+ properties were found to be risk factors for frequent recurrences. In this chapter, breast cancer subtypes are compared with each other. Results from different studies highlight the importance of ER/PR/HER2 receptor variations in the choice of treatment and prognosis of breast cancer.",book:{id:"5431",slug:"breast-cancer-from-biology-to-medicine",title:"Breast Cancer",fullTitle:"Breast Cancer - From Biology to Medicine"},signatures:"Nilufer Bulut",authors:[{id:"189255",title:"Associate Prof.",name:"Nilufer",middleName:null,surname:"Bulut",slug:"nilufer-bulut",fullName:"Nilufer Bulut"}]},{id:"42313",title:"HER2-Driven Carcinogenesis: New Mouse Models for Novel Immunotherapies",slug:"her2-driven-carcinogenesis-new-mouse-models-for-novel-immunotherapies",totalDownloads:4490,totalCrossrefCites:2,totalDimensionsCites:2,abstract:null,book:{id:"2883",slug:"oncogene-and-cancer-from-bench-to-clinic",title:"Oncogene and Cancer",fullTitle:"Oncogene and Cancer - From Bench to Clinic"},signatures:"Cristina Marchini, Lucia Pietrella, Cristina Kalogris, Chiara Garulli, Federico Gabrielli, Elena Quaglino, Manuela Iezzi, Serenella M. 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