Why copper catalyzes electrochemical reduction of nitrate to ammonia.

Electrochemical reduction of nitrate (NO3RR) has drawn significant attention in the scientific community as an attractive route for ammonia synthesis as well as alleviating environmental concerns for nitrate pollution. To improve the efficiency of this process, the development of catalyst materials that exhibit high activity and selectivity is of paramount importance. Copper and copper-based catalysts have been widely investigated as potential catalyst materials for this reaction both computationally and experimentally. However, less attention has been paid to understanding the reasons behind such high activity and selectivity. Herein, we use Density Functional Theory (DFT) to identify reactivity descriptors guiding the identification of active catalysts for the NO3RR, establish trends in activity, and explain why copper is the most active and selective transition metal for the NO3RR to ammonia among ten different transition metals, namely Au, Ag, Cu, Pt, Pd, Ni, Ir, Rh, Ru, and Co. Furthermore, we assess NO3RR selectivity by taking into account the competition between the NO3RR and the hydrogen evolution reaction. Finally, we propose various approaches for developing highly active catalyst materials for the NO3RR.

Exploring the Effects of Ionic Defects on the Stability of CsPbI3 with a Deep Learning Potential.

Inorganic metal halide perovskites, such as CsPbI3 , have recently drawn extensive attention due to their excellent optical properties and high photoelectric efficiencies. However, the structural instability originating from inherent ionic defects leads to a sharp drop in the photoelectric efficiency, which significantly limits their applications in solar cells. The instability induced by ionic defects remains unresolved due to its complicated reaction process. Herein, to explore the effects of ionic defects on stability, we develop a deep learning potential for a CsPbI3 ternary system based upon density functional theory (DFT) calculated data for large-scale molecular dynamics (MD) simulations. By exploring 2.4 million configurations, of which 7,730 structures are used for the training set, the deep learning potential shows an accuracy approaching DFT-level. Furthermore, MD simulations with a 5,000-atom system and a one nanosecond timeframe are performed to explore the effects of bulk and surface defects on the stability of CsPbI3 . This deep learning potential based MD simulation provides solid evidence together with the derived radial distribution functions, simulated diffraction of X-rays, instability temperature, molecular trajectory, and coordination number for revealing the instability mechanism of CsPbI3 . Among bulk defects, Cs defects have the most significant influence on the stability of CsPbI3 with a defect tolerance concentration of 0.32 %, followed by Pb and I defects. With regards to surface defects, Cs defects have the largest impact on the stability of CsPbI3 when the defect concentration is less than 15 %, whereas Pb defects act play a dominant role for defect concentrations exceeding 20 %. Most importantly, this machine-learning-based MD simulation strategy provides a new avenue to explore the ionic defect effects on the stability of perovskite-like materials, laying a theoretical foundation for the design of stable perovskite materials.

High throughput screening of promising lead-free inorganic halide double perovskites via first-principles calculations.

Perovskite solar cells (PSCs) have been intensively investigated and made great progress due to their high photoelectric conversion efficiency and low production cost. However, poor stability and the toxicity of Pb limit their commercial applications. It is particularly important to search for new non-toxic, high-stability perovskite materials. In this study, 760 Cs2B2+B'2+X6 (X = F, Cl, Br, I) inorganic halide double perovskites are screened based on high-throughput first-principles calculations to obtain an ideal perovskite material. The band gaps of this type of double perovskite are mainly determined by the elements X and B2+, decreasing monotonously with the increase in the atomic number of X (from F to I). We obtain 14 optimal and unreported materials with suitable band gaps as potential alternative materials for Pb-based photovoltaic absorbers in PSCs. This theoretical investigation can provide theoretical guidance for developing novel lead-free PSC materials.

The effect of coordination environment on the kinetic and thermodynamic stability of single-atom iron catalysts.

The stability of a single-atom catalyst is directly related to its preparation and applications, especially for high-loading single-atom catalysts. Here, the effect of a coordination environment induced by nitrogen (N) atoms coordinated with iron on the kinetic and thermodynamic stabilities of single-atom iron catalysts supported with carbon-based substrates (FeSA/CS) was investigated by density functional theory (DFT) calculations. Five FeSA/CS with different numbers of N atoms were modelled. The kinetic stability was evaluated by analyzing the migration paths of iron atoms and energy barriers. The thermodynamic stability was studied by calculating the adsorption and formation energies. Our results indicated that the coordination environment induced by N can promote the kinetic and thermodynamic stability of FeSA/CS. N atoms on the substrate promote the kinetic stability by raising the energy barrier for iron migration and not only increase the thermodynamic stability, but also contribute to catalyst synthesis. Doping N on the substrate enhances charge transfer between the iron atoms and substrates simultaneously improving the kinetic and thermodynamic stabilities. This theoretical research provides guidance for synthesizing stable and high loading single-atom catalysts by tuning the coordination environment of single-atom elements.

Non-Newtonian rheology in suspension cell cultures significantly impacts bioreactor shear stress quantification.

The fields of regenerative medicine and tissue engineering require large-scale manufacturing of stem cells for both therapy and recombinant protein production, which is often achieved by culturing cells in stirred suspension bioreactors. The rheology of cell suspensions cultured in stirred suspension bioreactors is critical to cell growth and protein production, as elevated exposure to shear stress has been linked to changes in growth kinetics and genetic expression for many common cell types. Currently, little is understood on the rheology of cell suspensions cultured in stirred suspension bioreactors. In this study, we present the impact of three common cell culture parameters, serum content, cell presence, and culture age, on the rheology of a model cell line cultured in stirred suspension bioreactors. The results reveal that cultures containing cells, serum, or combinations thereof are highly shear thinning, whereas conditioned and unconditioned culture medium without serum are both Newtonian. Non-Newtonian viscosity was modeled using a Sisko model, which provided insight on structural mechanisms driving the rheological behavior of these cell suspensions. A comparison of shear stress estimated by using Newtonian and Sisko relationships demonstrated that assuming Newtonian viscosity underpredicts both mean and maximum shear stress in stirred suspension bioreactors. Non-Newtonian viscosity models reported maximum shear stresses exceeding those required to induce changes in genetic expression in common cell types, whereas Newtonian models did not. These findings indicate that traditional shear stress quantification of cell or serum suspensions is inadequate and that shear stress quantification methods based on non-Newtonian viscosity must be developed to accurately quantify shear stress.

Predictive Modeling of Energy and Emissions from Shale Gas Development.

Contributions of individual preproduction activities to overall energy use and greenhouse gas (GHG) emissions during shale gas development are not well understood nor quantified. This paper uses predictive modeling combining the physics of reservoir development operations with depositional attributes of shale gas basins to account for energy requirements and GHG emissions during shale gas well development. We focus on shale gas development from the Montney basin in Canada and account for the energy use during drilling and fluid pumping for reservoir stimulation, in addition to preproduction emissions arising from energy use and potential gas releases during operations. Detailed modeling of activities and events that take place during each stage of development is described. Relative to the hydraulic fracturing activity, we observe significantly higher energy intensity for the well drilling and mud circulation activities. Well completion flowback gas is found to be the predominant potential source of GHG emission. When these results are expressed on an annual basis, consistent with the convention of most climate policy goals and directives, environmental impacts of our growing natural gas economy are better appreciated. Estimated likely GHG emission from new development wells in 2017 in the Montney Formation alone is 2.68 Mt CO2e. However, on a preproduction requirements basis and dependent on mean estimated ultimate recovery (EUR), energy return on invested energy for shale gas from the Montney Formation in Canada is estimated to be about 3400. The approach described here can be reliably extended to areas, globally, where natural gas development is becoming prominent.

Unconventional Heavy Oil Growth and Global Greenhouse Gas Emissions.

Enormous global reserves of unconventional heavy oil make it a significant resource for economic growth and energy security; however, its extraction faces many challenges especially on greenhouse gas (GHG) emissions, water consumption, and recently, social acceptability. Here, we question whether it makes sense to extract and use unconventional heavy oil in spite of these externalities. We place unconventional oils (oil sands and oil shale) alongside shale gas, coal, lignite, wood and conventional oil and gas, and compare their energy intensities and life cycle GHG emissions. Our results reveal that oil shale is the most energy intensive fuel among upgraded primary fossil fuel options followed by in situ-produced bitumen from oil sands. Lignite is the most GHG intensive primary fuel followed by oil shale. Based on future world energy demand projections, we estimate that if growth of unconventional heavy oil production continues unabated, the incremental GHG emissions that results from replacing conventional oil with heavy oil would amount to 4-21 Gt-CO2eq GtCO2eq over four decades (2010 by 2050). However, prevailing socio-economic, regional and global energy politics, environmental and technological challenges may limit growth of heavy oil production and thus its GHG emissions contributions to global fossil fuel emissions may be smaller.

Investigation of enhanced geothermal system in the Basal Cambrian Sandstone Unit, Alberta, Canada.

Given the climate challenge, society is seeking low greenhouse gas emission energy sources. In jurisdictions such as Alberta, Canada where power is largely generated through the combustion of natural gas, geothermal offers a compelling option but it remains unclear as to its economic and technical viability. Here, we examine the potential for an enhanced geothermal system in the Basal Cambrian Sandstone Unit in Alberta, Canada. Prior to geothermal operation, hydraulic fracturing is conducted to enhance the permeability of the thermal reservoir. This lowers the pressure drop required for circulating fluids through the system. The results show that the open-loop enhanced geothermal system realizes an energy produced to energy invested ratio from 4 to 9 depending on different operating rate. The results also suggest that applying hydraulic fracturing can accelerate energy harvesting and energy efficiency over the early stages of the process but the greater the injection rate, the smaller is this benefit of hydraulic fracturing stimulation.

Air invasion into three-dimensional foam induces viscous fingering instabilities.

We conducted an experimental investigation to examine the immiscible radial displacement flows of air invading three-dimensional foam in a Hele-Shaw cell. Our study successfully identified three distinct flow regimes. In the initial regime, characterized by relatively low fingertip velocities, the foam underwent a slow displacement through plug flow. During this process, the three-phase contact lines slipped at the cell walls. Notably, we discovered that the air injection pressure exhibited a proportional relationship with the power of the fingertip velocity. This relationship demonstrated excellent agreement with a power law, where the exponent was determined to be 2/3. Transitioning to the second regime, we observed relatively high velocities, resulting in the displacement of the foam as a plug within single layers of foam bubbles. The movement of these bubbles near the cell walls was notably slower. Similar to the first regime, the behavior in this regime also adhered to a power law. In the third regime, which manifested at higher air injection pressures, the development of air fingers occurred through narrow channels. These channels had the potential to isolate the air fingers as they underwent a process of "healing." Furthermore, our results unveiled a significant finding that the width of the air fingers exhibited a continuous scaling with the air injection pressure, irrespective of the flow regimes being observed.

Mass transfer limitations in embryoid bodies during human embryonic stem cell differentiation.

Due to their ability to differentiate into cell types from all the three germ layers and their potential unlimited capacity for expansion, embryonic stem cells have tremendous potential to treat diseases and injuries. Spontaneous differentiation of human embryonic stem cells (hESCs) is influenced by the size of the differentiating embryoid bodies (EBs). To further understand the dynamics between nutrient mass transfer, EB size, and stem cell differentiation, a transient mass diffusion model of a single hESC EB was constructed. The results revealed that the oxygen concentration at the centers of large EBs (400-µm radius) was 50% lower when compared to that in smaller EBs (200-µm radius). In addition, the concentration profile of cytokines within an EB depended strongly on their depletion rate, with higher depletion rates resulting in cytokine concentrations that varied significantly throughout the EB. A comparison of the results of our model with published experimental data reveals a close correlation between the fraction of cells that differentiate to a given lineage and the fraction of cells exposed to different oxygen or cytokine concentrations. This, along with other data from the literature, suggests that diffusive mass transfer influences the differentiation of hESCs within EBs by controlling the spatial distribution of soluble factors. This has important implications for research involving the differentiation of embryonic stem cells in EBs, as well as for bioprocess design and the development of robust differentiation protocols where mass transfer could be altered to control the cell differentiation trajectory.

Real time monitoring of biofilm development under flow conditions in porous media.

Biofilm growth can impact the effectiveness of industrial processes that involve porous media. To better understand and characterize how biofilms develop and affect hydraulic properties in porous media, both spatial and temporal development of biofilms under flow conditions was investigated in a translucent porous medium by using Pseudomonas fluorescens HK44, a bacterial strain genetically engineered to luminesce in the presence of an induction agent. Real-time visualization of luminescent biofilm growth patterns under constant pressure conditions was captured using a CCD camera. Images obtained over 8 days revealed that variations in bioluminescence intensity could be correlated to biofilm cell density and hydraulic conductivity. These results were used to develop a real-time imaging method to study the dynamic behavior of biofilm evolution in a porous medium, thereby providing a new tool to investigate the impact of biological fouling in porous media under flow conditions.

A descriptor for the structural stability of organic-inorganic hybrid perovskites based on binding mechanism in electronic structure.

The poor stability of organic-inorganic hybrid perovskites hinders its commercial application, which motivates a need for greater theoretical insight into its binding mechanism. To date, the binding mode of organic cation and anion inside organic-inorganic hybrid perovskites is still unclear and even contradictory. Therefore, in this work based on density functional theory (DFT), the binding mechanism between organic cation and anion was systematically investigated through electronic structure analysis including an examination of the electronic localization function (ELF), electron density difference (EDD), reduced density gradient (RDG), and energy decomposition analysis (EDA). The binding strength is mainly determined by Coulomb effect and orbital polarization. Based on the above analysis, a novel 2D linear regression descriptor that Eb = - 9.75Q2/R0 + 0.00053 V∙EHL - 6.11 with coefficient of determination R2 = 0.88 was proposed to evaluate the binding strength (the units for Q, R0, V, and EHL are |e|, Å, bohr3, and eV, respectively), revealing that larger Coulomb effect (Q2/R0), smaller volume of perovskite (V), and narrower energy difference (EHL) between the lowest unoccupied molecular orbital (LUMO) of organic cation and the highest occupied molecular orbital (HOMO) of anion correspond to the stronger binding strength, which guides the design of highly stable organic-inorganic hybrid perovskites.

A novel Fe-Co double-atom catalyst with high low-temperature activity and strong water-resistant for O3 decomposition: A theoretical exploration.

Developing catalysts with high activity, durability, and water resistance for ozone decomposition is crucial to regulate the pollution of ozone in the troposphere, especially in indoor air. To overcome the shortcomings of metal oxide catalysts with respect to their durability and water resistance, Fe-Co double-atom catalyst (DAC) is proposed as a novel catalyst for ozone decomposition. Here, through a systematic study using density functional theory (DFT) calculations and microkinetic modeling, the adsorption and catalytic decomposition of O3 on Fe-Co DAC have been examined based on adsorption configuration, orbital hybridization, and electron transfer. Based on Eley-Rideal (E-R) and Langmuir-Hinshelwood (L-H) reaction mechanisms, the mechanisms of ozone decomposition on Fe-Co DAC were explored by analyzing reaction paths and energy variations. To confirm the water-resistant of Fe-Co DAC, competitive adsorption behavior between O3 and dominant environmental gases was discussed through ab initio molecular dynamic (AIMD) simulation. The dominant reaction mechanism of ozone decomposition is L-H and the rate-determining step is the desorption of the first oxygen molecule from the surface of Fe-Co DAC which has an energy barrier of 0.78 eV. Due to this relatively low energy barrier and high turnover frequency (TOF), the optimal operation window of catalytic O3 decomposition on Fe-Co DAC is <500 K suggesting that catalytic decomposition of O3 on Fe-Co DAC can occur at room temperature. This theoretical study provides new insights for designing novel catalysts for ozone decomposition and fundamental guidance for subsequent experimental research.

A Sulfur-Tolerant MOF-Based Single-Atom Fe Catalyst for Efficient Oxidation of NO and Hg0.

Catalytic oxidation of NO and Hg0 is a crucial step to eliminate multiple pollutants from emissions from coal-fired power plants. However, traditional catalysts exhibit low catalytic activity and poor sulfur resistance due to low activation ability and poor adsorption selectivity. Herein, a single-atom Fe decorated N-doped carbon catalyst (Fe1 -N4 -C), with abundant Fe1 -N4 sites, based on a Fe-doped metal-organic framework is developed to oxidize NO and Hg0 . The results demonstrate that the Fe1 -N4 -C has ultrahigh catalytic activity for oxidizing NO and Hg0 at low and room temperature. More importantly, Fe1 -N4 -C exhibits robust sulfur resistance as it preferably adsorbs reactants over sulfur oxides, which has never been achieved before with traditional catalysts. Furthermore, SO2 boosts the catalytic oxidation of NO over Fe1 -N4 -C through accelerating the circulation of active sites. Density functional theory calculations reveal that the Fe1 -N4 active sites result in a low energy barrier and high adsorption selectivity, providing detailed molecular-level understanding for its excellent catalytic performance. This is the first report on NO and Hg0 oxidation over single-atom catalysts with strong sulfur tolerance. The outcomes demonstrate that single-atom catalysts are promising candidates for catalytic oxidation of NO and Hg0 enabling cleaner coal-fired power plant operations.

A new approach to model the spatiotemporal development of biofilm phase in porous media.

Bacteria can exist within biofilms that are attached to the solid matrix of a porous medium. Under certain conditions, the biomass can fully occupy the pore space leading to reduced hydraulic conductivity and mass transport. Here, by treating biofilm as a growing, high-viscosity phase, a novel macroscopic approach to model biofilm spatial expansion and its corresponding effects on porous medium hydraulic properties is presented. The separate yet coupled flow of the water and biofilm phases is handled by using relative permeability curves that allow for biofilm movement within the porous medium and bioclogging effects. Fluid flow is governed by Darcy's law and component transport is set by the convection-diffusion equation reaction terms for each component. Here, the system of governing equations is solved by using a commercial multiphase flow reservoir simulator, which is used to validate the model against published laboratory experiments. A comparison of the model and experimental observations reveal that the model provides a reasonable means to predict biomass development in the porous medium. The results reveal that coupled flow of water and movement of biofilm, as described by relative permeability curves, is complex and has a large impact on the development of biomass and consequent bioclogging in the porous medium.

Methane activation on dual-atom catalysts supported on graphene.

Dual-atom Fe catalysts supported by three nitrogen atom doped graphene (Fe-TM/GP, where TM = Ti, V, Cr, Mn, Fe, Co, Ni, and Cu) are explored for methane adsorption and activation. The addition of the second metal significantly tunes the properties of the catalysts. The main factor influencing methane adsorption is electron transfer. The second metal promotes methane adsorption by altering the electronic properties such as the band structure and charge transfer. A volcano-shaped relationship is found between the absolute value of adsorption energy and energy barrier at the heteroatom Fe-TM/GP. Fe-Ni/GP has the lowest energy barrier. Heteroatom Fe-TM/GP has a lower energy barrier than Fe-Fe/GP.

Release of sugars and fatty acids from heavy oil biodegradation by common hydrolytic enzymes.

In response to recent advances in understanding relating to the remarkable persistence of soil organic matter during burial and diagenesis, we examine the extent to which bitumen compositionally reflects the soil organic matter from which it was derived. Through a simple set of experiments, exposure of bitumen to lipase and cellulase, two enzymes effective in the biodegradation of soil organic matter, resulted in the release of glycerin, palmitic and oleic fatty acids from lipase digestion in addition to the release of glucose, alkylphenols and acyclic polyols from fermentation with cellulase, consistent with the products expected these enzymes. These results are significant in that they suggest that heavy oils are more similar to their soil precursor than previously thought, that biodegradation of bitumen can be accelerated using common over the counter enzymes in aerobic conditions and that heavy oils, which are 1000 times more abundant than coal, can release similar biomolecules as those generated in bioreactor culture or biomass harvest, using two of the most abundantly produced enzymes presently available.

A working method for estimating dynamic shear velocity in the montney formation.

In this paper, we present a customized method for estimating sonic shear velocity (Vs) from compressional velocity (Vp) logs in the Montney Formation, in wells lacking dipole sonic data. Following a multi-scenario analysis that comprised of assessing empirical Vs estimation relations [including lithology, porosity (Ø), and volume of clay (Vsh)-based Vs estimation techniques], bivariate statistics, and machine learning, we found that the Greenberg & Castagna (1992) shale lithology constants yield Vs log estimates that best match the measured Montney Formation Vs in our study area, with a regional correlation coefficient of 0.8. We have therefore customized the Vs estimation method in our study to use the Greenberg & Castagna (1992) shale lithology constants. Our working method: •Improves the efficacy of Vs log estimation from Vp logs in the study area•Demonstrates the importance of calibrating empirical relations for Vs estimation to a specific formation, and•Provides a more accurate complementary Vs log dataset for subsequent regional reservoir characterization studies.

Using computational fluid dynamics (CFD) modeling to understand murine embryonic stem cell aggregate size and pluripotency distributions in stirred suspension bioreactors.

Computational fluid dynamics (CFD) modeling can be applied to understand hydrodynamics in stirred suspension bioreactors, which can in turn affect cell viability, proliferation, pluripotency and differentiation. In this study, we developed a CFD model to determine the effects of average shear rates and turbulent eddies on the formation and growth of murine embryonic stem cell aggregates. We found a correlation between average eddy size and aggregate size, which depended on bioreactor agitation rates. By relating these computational and biological variables, CFD modeling can predict optimal agitation rates to grow embryonic stem cell aggregates in stirred suspension bioreactors. To examine the effect of hydrodynamics on pluripotency, mESCs cultured in bioreactors under various agitation rates were tested for SSEA-1, Sox-2, and Nanog expression. Cells maintained a minimum of 95% positive expression with no change in the intensity distribution pattern between the different bioreactor conditions. This indicates that the average level of pluripotency marker expression is independent of changes in the hydrodynamic profile and resulting aggregate size distribution. The findings here can be further extended to other cell types that grow as aggregates in stirred suspension bioreactors and offer important insights necessary to realize cell therapies.

Comparison of Electronic and Physicochemical Properties between Imidazolium-Based and Pyridinium-Based Ionic Liquids.

To compare 1-butyl-3-methylimidazolium ([BMIM]+)- and 1-butyl-3-methylpyridinium ([BMPy]+)-based ionic liquids (ILs) and investigate the influence of intramolecular and intermolecular interactions on physicochemical properties, a systematic study was performed on the electronic structures and physicochemical properties of [BMIM]+ tetrafluoroborate ([BMIM][BF4]), [BMIM]+ hexafluorophosphate ([BMIM][PF6]), [BMIM]+ hydrogen sulfate ([BMIM][HSO4]), [BMIM]+ methylsulfate ([BMIM][MSO4]), [BMIM]+ ethylsulfate ([BMIM][ESO4]), [BMPy]+ tetrafluoroborate ([BMPy][BF4]), [BMPy]+ hexafluorophosphate ([BMPy][PF6]), [BMPy]+ hydrogen sulfate ([BMPy][HSO4]), [BMPy]+ methylsulfate ([BMPy][MSO4]), and [BMPy]+ ethylsulfate ([BMPy][ESO4]) using density functional theory and molecular dynamics simulation. The results reveal that aggregation behavior exists in [HSO4]-- and [ESO4]--based ILs, and the differences between their densities and self-diffusion coefficients are smaller when there is an aggregation effect in ILs. A dimer is formed by two strong hydrogen bonds between two [HSO4]- anions in [HSO4]-based ILs, and the existence of hydrogen bonds in ILs increases density and decreases the self-diffusion coefficient. The intermolecular interaction strength of [BMIM]+-based ILs is stronger than that of [BMPy]+-based ILs.