Monte Carlo simulation of a solvated ionic polymer with cluster morphology

Matthews, Jessica L.; Lada, Emily K.; Weiland, Lisa Mauck; Smith, Ralph C.; Leo, Donald J.

doi:10.1088/0964-1726/15/1/048

Cited by 18 publications

(10 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The details of the statistical fitting methods applied to the development of various P(r) expressions for the same distribution of r values are discussed in [30]. Provided here is a brief overview of the cubic spline and Johnson Bounded methods.…”

Section: Discussionmentioning

confidence: 99%

“…[22]). However, it has been hypothesized that reasonable estimations for the above noted limitations are possible so long as an appropriate statistical approach is first employed [30,34], where the authors consider various statistical fitting methodologies as they relate to stiffness predictions for solvated ionomers. RIS theory is applied in a manner analogous to the particle inclusion works [25][26][27] where inclusion volumes are now taken to be clusters.…”

Section: Cross-sectional View Of a Typical Ipmc With Il-mentioning

confidence: 99%

“…Whereas a typical value for n in the chemical structure of Nafion is approximately 7, there is in fact variability in this value. To account for this variation, n is sampled from a discrete probability distribution with a minimum of 5, a maximum of 11, and a mean of approximately 7 [30].…”

Section: Simulation Model For Estimating Chain Lengthmentioning

confidence: 99%

“…The grid size is selected to accommodate the longest anticipated, fully extended backbone. Two cluster distribution schemes have been considered as detailed in the preliminary works [30,34]. The first relies directly on the simplified model of Hsu and Gierke [12] where the clusters are uniformly distributed on a square grid analogous to the cubic crystalline structure.…”

Section: Simulation Model For Estimating Chain Lengthmentioning

confidence: 99%

See 3 more Smart Citations

Application of Monte Carlo Simulations to Hydrated Nafion Stiffness Predictions

et al. 2005

View full text Add to dashboard Cite

Application of Rotational Isomeric State (RIS) theory to the prediction of Young’s modulus of a solvated ionomer is considered. RIS theory directly addresses polymer chain conformation as it relates to mechanical response trends. Successful adaptation of this methodology to the prediction of elastic moduli would thus provide a powerful tool for guiding ionomer fabrication. The Mark-Curro Monte Carlo methodology is applied to generate a statistically valid number of end-to-end chain lengths via RIS theory for a solvated Nafion case. The distribution of chain lengths is then fitted to a Probability Density Function by the Johnson Bounded distribution method. The fitting parameters, as they relate to the model predictions and physical structure of the polymer, are studied so that a means to extend RIS theory to the reliable prediction of ionomer stiffness may be identified.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Cross-sectional View Of a Typical Ipmc With Il-mentioning

confidence: 99%

Section: Simulation Model For Estimating Chain Lengthmentioning

confidence: 99%

Section: Simulation Model For Estimating Chain Lengthmentioning

confidence: 99%

See 2 more Smart Citations

Application of Monte Carlo Simulations to Hydrated Nafion Stiffness Predictions

et al. 2005

View full text Add to dashboard Cite

show abstract

“…By increasing the capacitance of IPMC, more than 2 percent strain can be achieved They also employed a Monte Carlo style approach to study the effects of pendant chain stiffness and charge balance of the equilibrium state of a single cluster in ionic polymer (Weiland and Leo, 2005b). Matthews et al (2006) presented a multiscale modeling approach for the prediction of material stiffness of Nafion polymer. The simulation model was developed by combination of traditional rotational isomeric state theory and Monte Carlo method.…”

Section: Experimental Study and Physical Modelingmentioning

confidence: 99%

Actuation characteristics and applications of piezoelectric materials and ionic polymer-metal composites

Zhang¹

View full text Add to dashboard Cite

Smart materials are a special class of materials which have abilities to change their physical properties in response to environmental stimuli. One of the important groups of smart materials is electro-active material (EAM) which responds to external electric potentials. Based on the working mechanism, the EAM can be further divided into two groups, i.e., electronic EAMs which rely on internal electrostatic forces for their actuation and ionic EAMs which depend on ion transportation and interaction for their actuation. Piezoelectric material and ionic polymer-metal composite (IPMC) are typical electronic EAM and ionic EAM, respectively. Piezoelectric materials, when subject to a mechanical force, will become electrically polarized. Tension and compression generate voltages of opposite polarity, and in proportion to the applied force. Conversely, when piezoelectric materials are subject to an electric field parallel to the polarization direction, they will expand or contract according to the polarity of the field, and in proportion to the strength of the field. The two effects are labeled as direct and converse piezoelectric effect and they are the basis for piezoelectric materials as sensors and actuators. Similar to piezoelectric materials, the IPMCs can also respond to electric and mechanical excitations. Instead of extension and contraction as piezoelectric materials, the IPMCs undergo transverse bending motion under an applied electric potential on the electrodes. On the other hand, the IPMCs can generate a measurable electric potential when it is subject to an imposed deformation. Thus, the IPMCs can also serve as sensors and actuators. The two types of smart materials, each has its own characteristics, can be employed for different applications in biomedical engineering. The objective of this research is to study the actuation characteristics of piezoelectric materials and IPMCs and explore the possibility of using the two types of materials for biomedical applications.

show abstract

Physical Modeling of Fuel Cells and their Components

Eikerling

Kornyshev

Kulikovsky

2007

Encyclopedia of Electrochemistry

View full text Add to dashboard Cite

This chapter presents an overview of the status of physical modeling of polymer‐electrolyte fuel cells (PEFCs), the understanding gained from modeling and its impact on optimization of the operation regime and new cell design. It begins with the physical theory of proton transport in polymer‐electrolyte membranes (PEMs). This comprises microscopic aspects of the elementary act of proton transfer in aqueous environments, their realization in a single water‐filled pore and the statistical geometry of the pore network. Based on these fundamental properties, electroosmosis and different models of water backflow under fuel cell operation conditions are discussed. The resulting water‐content profiles and current–voltage performance are compared with experimental data. The diffusion model of water backflow perceives the membrane as a solution of water in a polymer host, while the hydraulic permeation model rests on the idea of a swelling porous structure, inside of which the proton and water transport take place. An important result is the critical current density, at which water content near the anode drops below the percolation threshold for water network proton conductance. Next, theories of performance and structure of composite catalyst layers are presented, mainly focusing on the cathode as an eminent example. They account for the transport of feed gas, protons and electrons, as well as for the reaction at the membrane/catalyst interface, and result in a “phase diagram”, which suggests an optimum thickness of the layer, subject to the basic parameters and the target current density. The relation between the structure and performance, rationalized using the concepts of the percolation theory, paves the way for an optimum composition of the layer. A similar theory of the complex impedance connects the composite structure and ac response. This gives a tool for determining the catalyst layer parameters. With this background we move toward 3D effects in the cell. The approach rests on a quasi‐three‐dimensional (Q3D) model of the stack element. The fuel cell stack is a two‐scale system. The small and large scales are determined, respectively, by membrane‐electrode assembly (MEA) thickness and by the length of the feed channel. The fully 3D model of the stack element is split into a 2D model of a cell cross section (internal model) and a 1D model of the feed flow along the channel (channel model). The two models are coupled via the local current density along the channel and the overall solution is obtained by iterations. The model is designed to investigate the interplay of small‐ and large‐scale processes in PEFC/DMFC. It results in distributions of gas concentrations, proton and electron currents, and reaction rates in a cell cross section, perpendicular to a long meander‐like channel, that is, it gives a functional “map of a cell”. Model equations and numerical procedures are discussed. The results of simulations are shown for the stack modules of the gas‐feed DMFC and hydrogen–oxygen PEFC. A simplified theory of “along‐the‐channel” feed gas consumption, important for understanding the cell starvation effect is surveyed and compared with simulations and experiments. The message of the model results is summarized and discussed in the sequence of the rising potential for improving PEFC/DMFC design and operation.

show abstract

Monte Carlo simulation of a solvated ionic polymer with cluster morphology

Cited by 18 publications

References 27 publications

Application of Monte Carlo Simulations to Hydrated Nafion Stiffness Predictions

Application of Monte Carlo Simulations to Hydrated Nafion Stiffness Predictions

Actuation characteristics and applications of piezoelectric materials and ionic polymer-metal composites

Physical Modeling of Fuel Cells and their Components

Contact Info

Product

Resources

About