13 Search Results

The ATLAS experiment at the Large Hadron Collider explores the use of modern neural networks for a multi-dimensional calibration of its calorimeter signal defined by clusters of topologically connected cells (topo-clusters). The Bayesian neural network (BNN) approach not only yields a continuous and smooth calibration function that improves performance relative to the standard calibration but also provides uncertainties on the calibrated energies for each topo-cluster. The results obtained by using a trained BNN are compared to the standard local hadronic calibration and to a calibration provided by training a deep neural network. The uncertainties predicted by the BNN are interpretedmore » in the context of a fractional contribution to the systematic uncertainties of the trained calibration. They are also compared to uncertainty predictions obtained from an alternative estimator employing repulsive ensembles.« less

The electrochemical conversion of carbon di-/monoxide into commodity chemicals paves a way towards a sustainable society but it also presents one of the great challenges in catalysis. Herein, we present the trends in selectivity towards specific dicarbon oxygenate/hydrocarbon products from carbon monoxide reduction on transition metal catalysts, with special focus on copper. We unveil the distinctive role of electrolyte pH in tuning the dicarbon oxygenate/hydrocarbon selectivity. The understanding is based on density functional theory calculated energetics and microkinetic modeling. We identify the critical reaction steps determining selectivity and relate their transition state energies to two simple descriptors, the carbon andmore » hydroxide binding strengths. The atomistic insight gained enables us to rationalize a number of experimental observations and provides avenues towards the design of selective electrocatalysts for liquid fuel production from carbon di-/monoxide.« less

Despite the apparent simplicity of the hydrogen evolution reaction (HER) and the decades of research into it, controversy remains in the literature regarding the identity of the active site and the competition between the Heyrovsky and Tafel steps. In this work, we use charge-extrapolated ab initio simulations with explicit water in conjunction with mean-field microkinetic modeling to explore the mechanism for HER on both close-packed (111) and stepped (211) transition metals. First, we show that atop H*, beyond a monolayer of hollow H*, is unlikely to play a role in the HER mechanism, given its very positive adsorption energies. Themore » energetics suggests the Volmer–Heyrovsky mechanism to predominate on fcc transition metals under typical operating conditions. Here, we evaluate our theoretical results vs several experimental observations. We show that the Volmer–Heyrovsky mechanism predicts an activity volcano with its peak at a H* binding ΔG_H* ≈ 0 eV, consistent with experiment. In contrast, the Volmer–Tafel volcano shows a broad rate plateau between ΔG_H* ≈ 0 eV and ΔG_H* ≈ – 0.4 eV. We find our theoretical Tafel slopes to be consistent with experimental ones on a range of transition metals. We show that, in line with experimental observations, the introduction of a CO(g) atmosphere shifts the strong binding metals toward the weak binding leg. Our study suggests that the simple thermodynamic approach to HER activity still holds, even when a detailed kinetic picture is considered.« less

Electrochemical reduction of carbon-dioxide/carbon-monoxide (CO₍₂₎R) to fuels and chemicals presents an attractive approach for sustainable chemical synthesis, but it also poses a serious challenge in catalysis. Understanding the key aspects that guide CO₍₂₎R towards value-added multicarbon (C₂₊) products is imperative in designing an efficient catalyst. Herein, we identify the critical steps toward C₂ products on copper through a combination of energetics from density functional theory and micro-kinetic modeling. We elucidate the importance of atomic carbon in directing C₂₊ selectivity and how it introduces surface structural sensitivity on copper catalysts. Overall, this insight enables us to propose two simple thermodynamic descriptorsmore » that effectively identify C₂₊ selectivity on metal catalysts beyond copper and hence it defines an intelligible protocol to screen for materials that selectively catalyze CO₍₂₎ to C₂₊ products.« less

Here by understanding the surface reactivity of CO, which is a key intermediate during electrochemical CO₂ reduction, is crucial for the development of catalysts that selectively target desired products for the conversion of CO₂ to fuels and chemicals. In this study, a custom-designed electrochemical cell is utilized to investigate planar polycrystalline copper as an electrocatalyst for CO reduction under alkaline conditions. Seven major CO reduction products have been observed including various hydrocarbons and oxygenates which are also common CO₂ reduction products, strongly indicating that CO is a key reaction intermediate for these further-reduced products. A comparison of CO and CO₂more » reduction demonstrates that there is a large decrease in the overpotential for C–C coupled products under CO reduction conditions. The effects of CO partial pressure and electrolyte pH are investigated; we conclude that the aforementioned large potential shift is primarily a pH effect. Thus, alkaline conditions can be used to increase the energy efficiency of CO and CO₂ reduction to C–C coupled products, when these cathode reactions are coupled to the oxygen evolution reaction at the anode. Further analysis of the reaction products reveals common trends in selectivity that indicate both the production of oxygenates and C–C coupled products are favored at lower overpotentials. These selectivity trends are generalized by comparing the results on planar Cu to current state-of-the-art high-surface-area Cu catalysts, which are able to achieve high oxygenate selectivity by operating at the same geometric current density at lower overpotentials. Combined, these findings outline key principles for designing CO and CO₂ electrolyzers that are able to produce valuable C–C coupled products with high energy efficiency.« less

Alkali metal oxides commonly exist as impurities or promoters in syngas conversion catalysts and can significantly influence the activity and selectivity towards higher oxygenate products. In this study, we investigate the effects of sodium oxide on silica-supported Rh catalysts by experimentally introducing different amounts of sodium and monitoring the change in reactivity and CO adsorption behavior. The experimental results combined with density functional theory (DFT) calculations show that sodium selectively blocks step/defect sites on Rh surfaces, leading to reduced activity but higher C₂ oxygenate selectivity. DFT calculations also suggest that sodium present on Rh terrace sites can facilitate CO dissociation,more » potentially increasing C₂ oxygenate production. The overall activity and selectivity toward various products can be changed significantly based on the degree of site blocking by the added sodium.« less

Here, electrocatalytic CO₂ reduction to higher-value hydrocarbons beyond C₁ products is desirable for applications in energy storage, transportation and the chemical industry. Cu catalysts have shown the potential to catalyse C–C coupling for C₂₊ products, but still suffer from low selectivity in water. Here, we use density functional theory to determine the energetics of the initial C–C coupling steps on different Cu facets in CO₂ reduction, and suggest that the Cu(100) and stepped (211) facets favour C₂₊ product formation over Cu(111). To demonstrate this, we report the tuning of facet exposure on Cu foil through the metal ion battery cyclingmore » method. Compared with the polished Cu foil, our 100-cycled Cu nanocube catalyst with exposed (100) facets presents a sixfold improvement in C₂₊ to C₁ product ratio, with a highest C₂₊ Faradaic efficiency of over 60% and H₂ below 20%, and a corresponding C₂₊ current of more than 40 mA cm^–2.« less

The production of liquid fuels and industrial feedstocks from renewable carbon sources is an ongoing scientific challenge. By using atomic layer deposition together with conventional techniques, we synthesize Pt–Co bimetallic catalysts that show improvement for syngas conversion to alcohols. By combining reaction testing, X-ray diffraction, electron microscopy, and in situ infrared spectroscopy experiments, supported by density functional theory calculations, we uncover insights into how Pt modulates the selectivity of Co catalysts. The prepared Pt–Co catalysts demonstrate increased selectivity toward methanol and low molecular weight hydrocarbons as well as a modest increase in selectivity toward higher alcohols. The in situ infraredmore » spectroscopic measurements suggest that these changes in selectivity result from an interplay between linear and bridging carbon monoxide configurations on the catalyst surface.« less

Electrochemical carbon dioxide reduction to fuels presents one of the great challenges in chemistry. Herein we present an understanding of trends in electrocatalytic activity for carbon dioxide reduction over different metal catalysts that rationalize a number of experimental observations including the selectivity with respect to the competing hydrogen evolution reaction. We also identify two design criteria for more active catalysts. The understanding is based on density functional theory calculations of activation energies for electrochemical carbon monoxide reduction as a basis for an electrochemical kinetic model of the process. Furthermore, we develop scaling relations relating transition state energies to the carbonmore » monoxide adsorption energy and determine the optimal value of this descriptor to be very close to that of copper.« less