ABSTRACT Due to the complex morphology and small length scales of many fuel cell materials, exper... more ABSTRACT Due to the complex morphology and small length scales of many fuel cell materials, experimental quantification of the key properties of these materials can be expensive and quite difficult to conduct, if not impossible. As a result, modeling efforts become an imperative approach to evaluate the impact of material structure on fuel cell performance. To date, pore-scale modeling approach is widely used to understand the complex materials-performance relationship in these systems. However, the computational complexity of these models often limits simulation to analyze only a small volume of the material of interest. The model domain selected for the pore-scale models is typically chosen randomly from a much larger microstructure dataset. When considering the complex and heterogeneous internal structure of fuel cell materials, it is highly unlikely that this randomly selected volume would accurately reflect the full material structure and related impact on cell performance. The objective of this work is two-fold. The first goal is to develop advanced microstructure analysis tools for direct quantification of the key structural properties of the complex fuel cell materials. The second goal is to develop a new approach for intelligently selecting small representative volume elements (RVEs) from much larger material microstructure datasets, which can be confidently used in pore-scale modeling efforts to obtain reliable results regarding the structure-performance relationship. The diffusion media (DM) in polymer electrolyte fuel cells is chosen for initial demonstration of the approach. The microstructure of a dual-layer DM sample (i.e., a micro-porous layer coated on a macro-DM substrate) is quantified using X-ray computed tomography and dual-beam focused ion beam scanning electron microscopy. Computationally efficient algorithms are developed to extract the key structural parameters (e.g., porosity, surface area, phase connectivity) from measured microstructure datasets of these materials. In particular, two novel microstructure analysis techniques are introduced for the quantification of tortuosity and pore size distribution. Using in-house microstructure analysis tools based on n-point statistics and principal component analysis decomposition, sets of small RVEs that accurately represent salient features of tested fuel cell DM samples are selected from the much larger, full datasets. A detailed validation study is performed to assess the reliability of the presented approach.
Fuel cells efficiently convert chemical energy into electricity, producing a high power density w... more Fuel cells efficiently convert chemical energy into electricity, producing a high power density with low emission of pollutants and, as a result, are a promising power technology for a variety of applications. In particular, polymer-electrolyte fuel cells (PEFCs) are emerging as a compact, lowtemperature alternative to more common solid-oxide fuel cells. PEFCs consist of a polymerelectrolyte membrane (PEM) sandwiched between porous anode and cathode layers. At the anode, H2 molecules are split by a catalyst (typically Pt) thereby releasing ...
Abstract Supercooling of almost any liquid can induce a transition to an amorphous solid phase. T... more Abstract Supercooling of almost any liquid can induce a transition to an amorphous solid phase. This does not appear to be a phase transition in the usual sense—it does not involved sharp discontinuities in any system parameters and does not occur at a well-defined temperature—instead, it is due to a rapid increase in the relaxation time of the material, which prevents it from reaching equilibrium on timescales accessible to experimentation.
Abstract Due to the minute length scales and heterogeneous nature of fuel cell components, experi... more Abstract Due to the minute length scales and heterogeneous nature of fuel cell components, experimental quantification of the key properties of these materials can be expensive and quite difficult to conduct, if not impossible. The objective of this work is to introduce 3-D microstructure analysis tools for “direct” quantification of the key structure-related transport measures of porous fuel cell materials. Two important microstructure analysis tools are presented for the evaluation of tortuosity and void (ie, pore) size distribution.
Pore-scale modeling has become a quite popular tool for evaluating the impact of material structu... more Pore-scale modeling has become a quite popular tool for evaluating the impact of material structure on fuel cell performance. However, the computational complexity of these models often limits simulations to analyze only a small volume of material, which is typically selected randomly from a much larger microstructure dataset.
Abstract The objective of this work is to develop advanced microstructure analysis tools for dire... more Abstract The objective of this work is to develop advanced microstructure analysis tools for direct quantification of the key structural properties of complex fuel cell materials. Computationally efficient algorithms have been developed to extract the key structural parameters from measured microstructure datasets of these materials. In addition to determination of the traditional structural measures (eg, porosity, surface area, phase connectivity), two novel microstructure analysis techniques are introduced for the ...
Abstract The objective of this work is to utilize the recent advances in microstructure quantific... more Abstract The objective of this work is to utilize the recent advances in microstructure quantification to select small volumes (referred to as representative volume elements, or" RVEs") for use in pore scale modeling, which accurately reflect the overall microstructure and transport properties of large fuel cell material datasets. The micro-porous layer (MPL) of polymer electrolyte fuel cells is chosen for demonstration. Focused ion beam scanning electron microscopy is utilized to obtain a 3-D structural dataset for the selected MPL ...
ABSTRACT Due to the complex morphology and small length scales of many fuel cell materials, exper... more ABSTRACT Due to the complex morphology and small length scales of many fuel cell materials, experimental quantification of the key properties of these materials can be expensive and quite difficult to conduct, if not impossible. As a result, modeling efforts become an imperative approach to evaluate the impact of material structure on fuel cell performance. To date, pore-scale modeling approach is widely used to understand the complex materials-performance relationship in these systems. However, the computational complexity of these models often limits simulation to analyze only a small volume of the material of interest. The model domain selected for the pore-scale models is typically chosen randomly from a much larger microstructure dataset. When considering the complex and heterogeneous internal structure of fuel cell materials, it is highly unlikely that this randomly selected volume would accurately reflect the full material structure and related impact on cell performance. The objective of this work is two-fold. The first goal is to develop advanced microstructure analysis tools for direct quantification of the key structural properties of the complex fuel cell materials. The second goal is to develop a new approach for intelligently selecting small representative volume elements (RVEs) from much larger material microstructure datasets, which can be confidently used in pore-scale modeling efforts to obtain reliable results regarding the structure-performance relationship. The diffusion media (DM) in polymer electrolyte fuel cells is chosen for initial demonstration of the approach. The microstructure of a dual-layer DM sample (i.e., a micro-porous layer coated on a macro-DM substrate) is quantified using X-ray computed tomography and dual-beam focused ion beam scanning electron microscopy. Computationally efficient algorithms are developed to extract the key structural parameters (e.g., porosity, surface area, phase connectivity) from measured microstructure datasets of these materials. In particular, two novel microstructure analysis techniques are introduced for the quantification of tortuosity and pore size distribution. Using in-house microstructure analysis tools based on n-point statistics and principal component analysis decomposition, sets of small RVEs that accurately represent salient features of tested fuel cell DM samples are selected from the much larger, full datasets. A detailed validation study is performed to assess the reliability of the presented approach.
Fuel cells efficiently convert chemical energy into electricity, producing a high power density w... more Fuel cells efficiently convert chemical energy into electricity, producing a high power density with low emission of pollutants and, as a result, are a promising power technology for a variety of applications. In particular, polymer-electrolyte fuel cells (PEFCs) are emerging as a compact, lowtemperature alternative to more common solid-oxide fuel cells. PEFCs consist of a polymerelectrolyte membrane (PEM) sandwiched between porous anode and cathode layers. At the anode, H2 molecules are split by a catalyst (typically Pt) thereby releasing ...
Abstract Supercooling of almost any liquid can induce a transition to an amorphous solid phase. T... more Abstract Supercooling of almost any liquid can induce a transition to an amorphous solid phase. This does not appear to be a phase transition in the usual sense—it does not involved sharp discontinuities in any system parameters and does not occur at a well-defined temperature—instead, it is due to a rapid increase in the relaxation time of the material, which prevents it from reaching equilibrium on timescales accessible to experimentation.
Abstract Due to the minute length scales and heterogeneous nature of fuel cell components, experi... more Abstract Due to the minute length scales and heterogeneous nature of fuel cell components, experimental quantification of the key properties of these materials can be expensive and quite difficult to conduct, if not impossible. The objective of this work is to introduce 3-D microstructure analysis tools for “direct” quantification of the key structure-related transport measures of porous fuel cell materials. Two important microstructure analysis tools are presented for the evaluation of tortuosity and void (ie, pore) size distribution.
Pore-scale modeling has become a quite popular tool for evaluating the impact of material structu... more Pore-scale modeling has become a quite popular tool for evaluating the impact of material structure on fuel cell performance. However, the computational complexity of these models often limits simulations to analyze only a small volume of material, which is typically selected randomly from a much larger microstructure dataset.
Abstract The objective of this work is to develop advanced microstructure analysis tools for dire... more Abstract The objective of this work is to develop advanced microstructure analysis tools for direct quantification of the key structural properties of complex fuel cell materials. Computationally efficient algorithms have been developed to extract the key structural parameters from measured microstructure datasets of these materials. In addition to determination of the traditional structural measures (eg, porosity, surface area, phase connectivity), two novel microstructure analysis techniques are introduced for the ...
Abstract The objective of this work is to utilize the recent advances in microstructure quantific... more Abstract The objective of this work is to utilize the recent advances in microstructure quantification to select small volumes (referred to as representative volume elements, or" RVEs") for use in pore scale modeling, which accurately reflect the overall microstructure and transport properties of large fuel cell material datasets. The micro-porous layer (MPL) of polymer electrolyte fuel cells is chosen for demonstration. Focused ion beam scanning electron microscopy is utilized to obtain a 3-D structural dataset for the selected MPL ...
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