RESUMEN
In electrocatalysis, mechanistic analysis of reaction rate data often relies on the linearization of relatively simple rate equations; this is the basis for typical Tafel and reactant order dependence analyses. However, for more complex reaction phenomena, such as surface coverage effects or mixed control, these common linearization strategies will yield incomplete or uninterpretable results. Cohesive kinetic analysis, which is often used in thermocatalysis and involves quantitative model fitting for data collected over a wide range of reaction conditions, requires more data but also provides a more robust strategy for interrogating reaction mechanisms. In this work, we report a robotic system that improves the experimental workflow for collecting electrochemical rate data by automating sequential testing of up to 10 electrochemical cells, where each cell can have a different electrode, electrolyte, gas-phase reactant composition, and applied voltage. We used this system to investigate the mechanism of carbon dioxide electroreduction to carbon monoxide at several immobilized metal tetrapyrroles. Specifically, at cobalt phthalocyanine (CoPc), cobalt tetraphenylporphyrin (CoTPP), and iron phthalocyanine (FePc), we see signatures of complex reaction mechanisms, where observed bicarbonate and CO2 order dependences change with applied potential. We illustrate how phenomena such as electrolyte poisoning and potential-dependent degrees of rate control can explain the observed kinetic behaviors. Our mechanistic analysis suggests that CoPc and CoTPP share a similar reaction mechanism, akin to one previously proposed, whereas the mechanism for FePc likely involves a species later in the catalytic cycle as the most abundant reactive intermediate. Our study illustrates that complex reaction mechanisms that are not amenable to common Tafel and order dependence analyses may be quite prevalent across this class of immobilized metal tetrapyrrole electrocatalysts.
RESUMEN
We present the results of molecular dynamics simulations of a nanoscale electrochemical cell. The simulations include an aqueous electrolyte solution with varying ionic strength (i.e., concentrations ranging from 0-4 M) between a pair of metallic electrodes held at constant potential difference. We analyze these simulations by computing the electrostatic potential profile of the electric double-layer region and find it to be nearly independent of ionic concentration, in stark contrast to the predictions of standard continuum-based theories. We attribute this lack of concentration dependence to the molecular influences of water molecules at the electrode-solution interface. These influences include the molecular manifestation of water's dielectric response, which tends to drown out the comparatively weak screening requirement of the ions. To support our analysis, we decompose water's interfacial response into three primary contributions: molecular layering, intrinsic (zero-field) orientational polarization, and the dipolar dielectric response.
RESUMEN
The Tafel slope is a key parameter often quoted to characterize the efficacy of an electrochemical catalyst. In this paper, we develop a Bayesian data analysis approach to estimate the Tafel slope from experimentally-measured current-voltage data. Our approach obviates the human intervention required by current literature practice for Tafel estimation, and provides robust, distributional uncertainty estimates. Using synthetic data, we illustrate how data insufficiency can unknowingly influence current fitting approaches, and how our approach allays these concerns. We apply our approach to conduct a comprehensive re-analysis of data from the CO2 reduction literature. This analysis reveals no systematic preference for Tafel slopes to cluster around certain "cardinal values" (e.g. 60 or 120 mV/decade). We hypothesize several plausible physical explanations for this observation, and discuss the implications of our finding for mechanistic analysis in electrochemical kinetic investigations.
RESUMEN
In this manuscript, we examine the role of image charge effects on the electrostatic potential fluctuations experienced by ionic species in the vicinity of an electrode surface. We combine simulation and theory to quantify these fluctuations and how they vary with distance from the electrode surface. We observe that the potential distribution narrows significantly for species within a few electrolyte screening lengths of the electrode. We attribute this narrowing to the effects of image charge fluctuations originating from the polarization response of the electrode. We show that the physical consequences of these image charge effects can be captured in the context of a simple analytical field theory with anti-symmetric boundary conditions. We contextualize these results by discussing their implications for rates of Marcus-like outer-sphere interfacial electron transfer.
RESUMEN
With the availability of nanoparticles with controlled size and shape, there has been renewed interest in the mechanical properties of polymer/nanoparticle blends. Despite the large number of theoretical studies, the effect of branching for nanofillers tens of nanometers in size on the elastic stiffness of these composite materials has received limited attention. Here, we examine the Young's modulus of nanocomposites based on a common block copolymer (BCP) blended with linear nanorods and nanoscale tetrapod Quantum Dots (tQDs), in electrospun fibers and thin films. We use a phenomenological lattice spring model (LSM) as a guide in understanding the changes in the Young's modulus of such composites as a function of filler shape. Reasonable agreement is achieved between the LSM and the experimental results for both nanoparticle shapes--with only a few key physical assumptions in both films and fibers--providing insight into the design of new nanocomposites and assisting in the development of a qualitative mechanistic understanding of their properties. The tQDs impart the greatest improvements, enhancing the Young's modulus by a factor of 2.5 at 20 wt.%. This is 1.5 times higher than identical composites containing nanorods. An unexpected finding from the simulations is that both the orientation of the nanoscale filler and the orientation of X-type covalent bonds at the nanoparticle-ligand interface are important for optimizing the mechanical properties of the nanocomposites. The tQD provides an orientational optimization of the interfacial and filler bonds arising from its three-dimensional branched shape unseen before in nanocomposites with inorganic nanofillers.