Abstract: Although recent studies have advanced the understanding of pyrolyzed
Fe−N−C materials as oxygen reduction reaction (ORR) catalysts, the atomic and
electronic structures of the active sites and their detailed reaction mechanisms still remain unknown. Here, based on first-principles density functional theory (DFT) computations, we discuss the electronic structures of three FeN4 catalytic centers with different local topologies of the surrounding C atoms with a focus on unraveling the mechanism of their ORR activity in acidic electrolytes. Our study brings back a forgotten, synthesized pyridinic Fe−N coordinate to the community’s attention, demonstrating that this catalyst can exhibit excellent activity for promoting direct four-electron ORR through the addition of a fifth ligand such as −NH2, −OH, and −SO4. We also identify sites with good stability properties through the combined use of our DFT calculations and Mössbauer spectroscopy data.

Abstract: Previous studies have shown that positron-annihilation spectroscopy is a highly sensitive probe of the electronic structure and surface composition of ligand-capped semiconductor quantum dots (QDs) embedded in thin films. The nature of the associated positron state, however, whether the positron is confined inside the QDs or localized at their surfaces, has so far remained unresolved. Our positron-annihilation lifetime spectroscopy studies of CdSe QDs reveal the presence of a strong lifetime component in the narrow range of 358–371 ps, indicating abundant trapping and annihilation of positrons at the surfaces of the QDs. Furthermore, our ab initio calculations of the positron wave function and lifetime employing a recent formulation of the weighted density approximation demonstrate the presence of a positron surface state and predict positron lifetimes close to experimental values. Our study thus resolves the long-standing question regarding the nature of the positron state in semiconductor QDs and opens the way to extract quantitative information on surface composition and ligand-surface interactions of colloidal semiconductor QDs through highly sensitive positron-annihilation techniques.

Abstract: Hydrogenotrophic denitrification is a novel and sustainable process for nitrogen removal, which utilizes hydrogen as electron donor, and carbon dioxide as carbon source. Recent studies have shown that nitrous oxide (N2O), a highly undesirable intermediate and potent greenhouse gas, can accumulate during this process. In this work, a new mathematical model is developed to describe nitrogen oxides dynamics, especially N2O, during hydrogenotrophic denitrification for the first time. The model describes electron competition among the four steps of hydrogenotrophic denitrification through decoupling hydrogen oxidation and nitrogen reduction processes using electron carriers, in contrast to the existing models that couple these two processes and also do not consider N2O accumulation. The developed model satisfactorily describes experimental data on nitrogen oxides dynamics obtained from two independent hydrogenotrophic denitrifying cultures under various hydrogen and nitrogen oxides supplying conditions, suggesting the validity and applicability of the model. The results indicated that N2O accumulation would not be intensified under hydrogen limiting conditions, due to the higher electron competition capacity of N2O reduction in comparison to nitrate and nitrite reduction during hydrogenotrophic denitrification. The model is expected to enhance our understanding of the process during hydrogenotrophic denitrification and the ability to predict N2O accumulation.

Abstract: We discuss positron-annihilation lifetimes for a set of illustrative bulk materials within the framework of the weighted-density approximation (WDA). The WDA can correctly describe electron-positron correlations in strongly inhomogeneous systems, such as surfaces, where the applicability of (semi-)local approximations is limited. We analyze the WDA in detail and show that the electrons which cannot screen external charges efficiently, such as the core electrons, cannot be treated accurately via the pair correlation of the homogeneous electron gas. We discuss how this problem can be addressed by reducing the screening in the homogeneous electron gas by adding terms depending on the gradient of the electron density. Further improvements are obtained when core electrons are treated within the LDA and the valence electron using the WDA. Finally, we discuss a semiempirical WDA-based approach in which a sum rule is imposed to reproduce the experimental lifetimes.

Abstract: The mobilization of arsenic (As) in aquatic environment (groundwater) can cause severe environmental and healthy issues. To develop remediation strategies, we proposed a comprehensive mathematical model to describe the As removal in a arsenite (As (III)) oxidizing and ferrous iron (Fe (II)) oxidizing denitrifying granular biofilm system. In the model framework, the growth-linked microbial oxidation of As (III) and Fe (II) was coupled to chemolithotrophic denitrification of one-step reduction of nitrate to nitrogen gas. Meanwhile, the precipitation of ferric iron (Fe (III)) and adsorption of arsenate (As (V)) onto the biogenic Fe (III) (hydr)oxides were also considered. The model was calibrated by comparing the model predictions against experimental data from batch experiments. The validity of the model was further demonstrated through testing against long-term experimental results from five independent bioreactors with different reactor configurations and operational conditions. Modeling results revealed that the granule size would exert a limited impact on arsenic and iron removal. Nevertheless, their removal efficiencies increased rapidly with the increase of hydraulic retention time (HRT) from 1 h to 12 h, but became independent of HRT as it further increased. The established model framework enables interpretation of a range of experimental observations on As and Fe removal and helps to identify the optimal conditions for enhanced arsenic remediation. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: Nitrate contamination of groundwater has been recognized as a significant environmental problem world widely. Sulfur-driven mixotrophic denitrification has been demonstrated as a promising groundwater treatment process, which though plays an important role in nitrous oxide (N2O) emissions, significantly contributing to the overall carbon footprint of the system. However, the current process optimizations only focus on nitrate removal and excess sulfate control, with the N2O emission being ignored. In this work, an integrated mathematical model was proposed to evaluate the N2O emission as well as the excess sulfate production and carbon source utilization in sulfur-driven mixotrophic denitrification process. In this model, autotrophic and heterotrophic denitrifiers use their corresponding electron donors (sulfur and organic matter, respectively) to reduce nitrate to nitrogen gas, with each modeled as three-step denitrification (NO3 to N-2 via NO2 and N2O) driven by sulfur or organic matter to describe all potential N2O accumulation steps. The developed model, employing model parameters previously reported in literature, was successfully validated using N2O and sulfate data from two mixotrophic denitrification systems with different initial conditions. Modeling results revealed substantial N2O accumulation due to the relatively low autotrophic N2O reduction activity as compared to heterotrophic N2O reduction activity, explaining the observation that higher carbon source addition resulted in lower N2O accumulation in sulfur-driven mixotrophic denitrifying system. Based on the validated model, optimizations of the overall system performance were carried out. Application of the model to simulate long-term operations of sulfur-driven mixotrophic denitrification process indicates that longer sludge retention time reduces N2O emission due to better retention of active biomass. High-level total nitrogen removal with significant N2O emission mitigation, appropriate excess sulfate control and maximized COD utilization can be achieved simultaneously through controlling the influent nitrate and COD concentrations. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: Sustainable wastewater treatment has been attracting increasing attentions over the past decades. However, the production of nitrous oxide (N2O), a potent GHG, from the energy-efficient granule-based autotrophic nitrogen removal is largely unknown. This study applied a previously established N2O model, which incorporated two N2O production pathways by ammonia-oxidizing bacteria (AOB) (AOB denitrification and the hydroxylamine (NH2OH) oxidation). The two-pathway model was used to describe N2O production from a granule-based partial nitritation (PN) reactor and provide insights into the N2O distribution inside granules. The model was evaluated by comparing simulation results with N2O monitoring profiles as well as isotopic measurement data from the PN reactor. The model demonstrated its good predictive ability against N2O dynamics and provided useful information about the shift of N2O production pathways inside granules for the first time. The simulation results indicated that the increase of oxygen concentration and granule size would significantly enhance N2O production. The results further revealed a linear relationship between N2O production and ammonia oxidation rate (AOR) (R-2 = 0.99) under the conditions of varying oxygen levels and granule diameters, suggesting that bulk oxygen and granule size may exert an indirect effect on N2O production by causing a change in AOR.

Abstract: The trapping of positrons at the surface of a material can be exploited to study quite selectively the surface properties of the latter by means of positron annihilation spectroscopy techniques. To support these, it is desirable to be able to theoretically predict the existence of such positronic surface states and to describe their annihilation characteristics with core or valence surface electrons in a reliable way. Here, we build on the well-developed first-principles techniques for the study of positrons in bulk solids as well as on previous models for surfaces, and investigate two schemes that can improve the theoretical description of the interaction of positrons with surfaces. One is based on supplementing the local-density correlation potential with the corrugated image potential at the surface, and the other is based on the weighted-density approximation to correlation. We discuss our results for topological insulators, graphene layers, and quantum dots, with emphasis on the information that can be directly related to experiment. We also discuss some open theoretical problems that should be addressed by future research.

Abstract: Positrons can be trapped in localized states at the surface of a material, and thus quite selectively interact with core or valence surface electrons. Hence, advanced surface positron spectroscopy techniques can present the ideal tools to study a topological insulator, where surface states play a fundamental role. We analyze the problem of a positron at a TI surface, assuming that it is a weakly physisorbed positronium (Ps) atom. To determine if the surface of interest in a material can sustain such a physisorption, an accurate description of the underlying van der Waals (vdW) interaction is essential. We have developed a first-principles parameterfree method, based on the density functional theory, to extract key parameters determining the vdW interaction potential between a Ps atom and the surface of a given material. The method has been successfully applied to quartz and preliminary results on Bi2Te2Se indicate the existence of a positron surface state. We discuss the robustness of our predictions versus the most relevant approximations involved in our approach.