Catalyst layer models structure formation

At macroscopic level, the overall relations between structure and performance are strongly affected by the formation of liquid water. Solution of such a model that accounts for these effects provides full relations among structure, properties, and performance, which in turn allow predicting architectures of materials and operating conditions that optimize fuel cell operation. For stationary operation at the macroscopic device level, one can establish material balance equations on the basis of fundamental conservation laws. The general ingredients of a so-called "macrohomogeneous model" of catalyst layer operation include ... 

Matsuura (130) measured the ESR spectra of bismuth molybdate catalysts both before and after reduction of butene. A board signal of high intensity was observed for the y phase of bismuth molybdate. The authors proposed that in the layered Bi2MoOs structure, a (Mo042 ) layer shifts with respect to the nearest layers and causes the formation of Mo-Bi-Mo sites. The results supported the earlier proposed reaction site model, based on adsorption measurements, which consisted of an A site (Bi) and two B sites (Mo). 

This coarse-grained molecular dynamics model helped consolidate the main features of microstructure formation in CLs of PEFCs. These showed that the final microstructure depends on carbon particle choices and ionomer-carbon interactions. While ionomer sidechains are buried inside hydrophilic domains with a weak contact to carbon domains, the ionomer backbones are attached to the surface of carbon agglomerates. The evolving structural characteristics of the catalyst layers (CL) are particularly important for further analysis of transport of protons, electrons, reactant molecules (O2) and water as well as the distribution of electrocatalytic activity at Pt/water interfaces. In principle, such meso-scale simulation studies allow relating of these properties to the selection of solvent, carbon (particle sizes and wettability), catalyst loading, and level of membrane hydration in the catalyst layer. There is still a lack of explicit experimental data with which these results could be compared. Versatile experimental techniques have to be employed to study particle-particle interactions, structural characteristics of phases and interfaces, and phase correlations of carbon, ionomer, and water in pores. 

As described in this chapter, the physieal theory and molecular modeling of catalyst layers provide various tools for relating the global performance metrics to local distributions of physical parameters and to structural details of the complex composite media at the hierarchy of scales from nanoscale to macroscale. The subsisting challenges and recent advances in the major areas of theoretical catalyst layer research include (i) structure and reactivity of catalyst nanoparticles, (ii) selforganization phenomena in catalyst layers at the mesoscopic scale, (iii) effectiveness of current conversion in agglomerates of carbon/Pt, and (iv) interplay of porous structure, liquid water formation, and performance at the macroscopic scale. 

The two-step strategy in the physical modeling of catalyst layer operation is depicted in Figure 3.5. The first step relates structure to the physical properties of the layer, considered as an effective medium. The second step relates these effective properties to electrochemical performance. Relations between structure and performance are complicated by the formation of liquid water, affecting effective properties and performance. Solutions for such a model provide relations between structure, properties, and performance. These relations allow predictions of architectures of materials and operating conditions that optimize catalyst layer and fuel cell operation to be made. 

Simulations of physical properties of realistic Pt/support nanoparticle systems can provide interaction parameters that are used by molecular-level simulations of self-organization in CL inks. Coarse-grained MD studies presented in the section Mesoscale Model of Self-Organization in Catalyst Layer Inks provide vital insights on structure formation. Information on agglomerate formation, pore space morphology, ionomer structure and distribution, and wettability of pores serves as input for parameterizations of structure-dependent physical properties, discussed in the section Effective Catalyst Layer Properties From Percolation Theory. CGMD studies can be applied to study the impact of modifications in chemical properties of materials and ink composition on physical properties and stability of CLs. 

Theoretical and experimental studies of model bimetallic catalysts in recent years have distinguished between thermodynamically stable bulk alloys and so-called near surface alloys. Near surface alloys are materials where the top few surface layers are created in a chemically heterogeneous way, for example, by depositing a monolayer of one metal on top of another metal. These structures are often not the thermodynamic equilibrium states of the material. To give one example, Ni and Pt form an fee bulk solid solution under most (but not all) conditions,73 so if a monolayer of Ni is deposited on Pt and the system comes to equilibrium, all of the deposited Ni will dissolve into the bulk. There is, however, a considerable kinetic barrier to this process, so the near surface alloy of a monolayer on Ni on Pt(lll) is quite stable provided a moderate temperature is used.191 If the deposited monolayer in systems of this type has a tendency to segregate away from the surface, a common near surface alloy structure is the formation of a subsurface layer of the deposited metal.85 The deposition of V on Pd(lll) is one example of this behavior.192... 

Equally fast was the intuition that the formation of stereoselective active sites had to do with specific structural features of the solid catalyst surface, and the consequential decision to investigate its crystal lattice. This rapidly led to the discovery that TiQ3 is polymorphic and that the different modifications can be grouped into two classes, with fibrillar (P) and layered (a, y, 8) structures respectively [7,11,12]. Very recent quantum mechanics (QM) models of the ordered a, p, and y phases [24], in full agreement with... 

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