Five membrane-electrode assemblies (MEAs) with different average sizes of platinum (Pt) nanoparticles (2.2, 3.5, 5.0, 6.7, and 11.3 nm) in the cathode were analyzed before and after potential cycling (0.6 to 1.0 V, 50 mV/s) by transmission electron microscopy. Cathodes loaded with 2.2 and 3.5 nm catalyst nanoparticles exhibit the following changes during electrochemical cycling: (i) substantial broadening of the size distribution relative to the initial size distribution, (ii) presence of coalesced particles within the electrode, and (iii) precipitation of submicron-sized particles with complex shapes within the membrane. In contrast, cathodes loaded with 5.0, 6.7, and 11.3 nm size catalyst nanoparticles are significantly less prone to the aforementioned effects. As a result, the electrochemically active surface area (ECA) of MEA cathodes loaded with 2.2 and 3.5 nm nanoparticle catalysts degrades dramatically within 1000 cycles of operation, while the electrochemically active surface area of MEA cathodes loaded with 5.0, 6.7, and 11.3 nm nanoparticle catalysts appears to be stable even after 10 000 cycles. The loss in MEA performance for cathodes loaded with 2.2 and 3.5 nm nanoparticle catalysts appears to be due to the loss in electrochemically active surface area concomitant with the observed morphological changes in these nanoparticle catalysts.

The evolution of Pt nanoparticle cathode electrocatalyst size distribution in a polymer electrolyte membrane fuel cell (PEMFC) was followed during accelerated stress tests using in-operando anomalous small-angle X-ray scattering (ASAXS). This evolution was compared to that observed in an aqueous electrolyte environment using stagnant electrolyte, flowing electrolyte, and flowing electrolyte at elevated temperature to reveal the different degradation trends in the PEMFC and aqueous environments and to determine the relevance of aqueous measurements to

The durability of carbon supported PtCo-alloy based nanoparticle catalysts play a key role in the longevity of proton-exchange membrane fuel cells (PEMFC) in electric vehicle applications. To improve its durability, it is important to understand and mitigate the various factors that cause PtCo-based cathode catalyst layers (CCL) to lose performance over time. These factors include i) electrochemical surface area (ECSA) loss, ii) specific activity loss, iii) H+/O2-transport changes and iv) Co2+ contamination effects. We use a catalyst-specific accelerated stress test (AST) voltage cycling protocol to compare the durability of Pt and PtCo catalysts at similar average nanoparticle size and distribution. Our studies indicate that while Pt and PtCo nanoparticle catalysts suffer from similar magnitudes of electrochemical surface area (ECSA) losses, PtCo catalyst shows a significantly larger cell voltage loss at high current densities upon durability testing. The distinctive factor causing the large cell voltage loss of PtCo catalyst appears to be the secondary effects of the leached Co2+ cations that contaminate the electrode ionomer. A 1D performance model has been used to quantify the cell voltage losses arising from various factors causing degradation of the membrane electrode assembly (MEA).

Transmission electron microscopy (TEM) represents a unique and powerful modality for capturing spatial features of nanoparticles, such as size and shape. However, poor statistics arise as a key obstacle, due to the challenge in accurately and automatically segmenting nanoparticles in TEM micrographs. Towards remedying this deficit, we introduce an automatic particle picking device that is based on the concept of variance hybridized mean local thresholding. Validation of this new segmentation model is accomplished by applying a program written in Matlab to a database of 150 bright field TEM micrographs containing approximately 2,000 nanoparticles. We compare the results to global thresholding, local thresholding, and manual segmentation. It is found that this novel automatic particle picking device reduces false positives and false negatives significantly, while increasing the number of individual particles picked on regions of particle overlap.

Proton exchange membrane fuel cells (PEMFCs) are promising energy conversion devices due to their high efficiency, high energy density and low operation conditions. Pt nanoparticles are widely used as the catalysts in cathode and anode for the half cell reactions. However, the durability of Pt nanoparticles still remains the most significant obstacle for large scale application of PEMFCs, especially in the cathode. In general, a significant decrease in electrochemical surface area (ECA) is observed.In this work, five membrane electrode assemblies (MEAs) with platinum (Pt) nanoparticles of different average sizes (2.2, 3.5, 5.0, 6.7, and 11.3 nm) in the cathode were analyzed before and after potential cycling (0.6 to 1.0 V, 50 mV/s). MEAs with 2.2nm and 3.5nm show significant growth in mean particle sizes after 10,000 potential cycles, while the other samples do not (Fig.1a).To understand the aforementioned particle growth, we need to consider the following possible mechanisms: (i) modified electrochemical Ostwald ripening (MEOR), (ii) platinum dissolution and re-precipitation inside the membrane and (iii) particle migration and coalescence. As MEOR is an isotropic process, a comparison of the particle size distributions (PSDs) of spherical particles and PSDs of all the particles indicates that this mechanism plays a significant role in the degradation of 2.2nm and 3.5nm samples, but not in the other samples (Fig.1b). Re-precipitated particles in the membrane are found among almost all the samples (Figure 2a-e), but their amount is minor comparing to the particles in the cathode, which reveals that re-precipitation plays an insignificant role in the degradation of PEMFCs. In terms of coalescence there are three plausible mechanisms: (i) particles migrate and coalescence, (ii) particles in proximity grow in size due to MEOR and make contact and (iii) soluble Pt species re-precipitate to bridge two particles followed by MEOR (Figure 3a). In any case, coalesced particles occur among all samples, although the 2.2nm sample shows the highest extent of coalescence (Fig.3b). However, as the carbon support exhibits a convoluted 3D structure, as shown by in-situ tomography (Fig. 3c,d), it is difficult for particles to coalesce through a migration mechanism.In summary, Pt dissolution seems to be the controlling mechanism for degradation, as it assists the MEOR process and two plausible mechanisms of coalescence. Thus, reducing Pt dissolution is essential to prevent ECA loss and catalyst performance degradation.