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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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.

Nanoparticle localization in blood vessels: dependence on fluid shear stress, flow disturbances, and flow-induced changes in endothelial physiology.

Nanoparticles in the bloodstream are subjected to complex fluid forces as they move through the curves and branches of healthy or tumor vasculature. While nanoparticles are known to preferentially accumulate in angiogenic vessels, little is known about the flow conditions in these vessels and how these conditions may influence localization. Here, we report a methodology which combines confocal imaging of nanoparticle-injected transgenic zebrafish embryos, 3D modeling of the vasculature, particle mapping, and computational fluid dynamics, to quantitatively assess the effects of fluid forces on nanoparticle distribution in vivo. Six-fold lower accumulation was found in zebrafish arteries compared to the lower velocity veins. Nanoparticle localization varied inversely with shear stress. Highest accumulation was present in regions of disturbed flow found at branch points and curvatures in the vasculature. To further investigate cell-particle association under flow, human endothelial cells were exposed to nanoparticles under hemodynamic conditions typically found in human vessels. Physiological adaptations of endothelial cells to 20 hours of flow enhanced nanoparticle accumulation in regions of disturbed flow. Overall our results suggest that fluid shear stress magnitude, flow disturbances, and flow-induced changes in endothelial physiology modulate nanoparticle localization in angiogenic vessels.

Identification of Nanocellulose Retention Characteristics in Porous Media.

The application of nanotechnology to the petroleum industry has sparked recent interest in increasing oil recovery, while reducing environmental impact. Nanocellulose is an emerging nanoparticle that is derived from trees or waste stream from wood and fiber industries. Thus, it is taken from a renewable and sustainable source, and could therefore serve as a good alternative to current Enhanced Oil Recovery (EOR) technologies. However, before nanocellulose can be applied as an EOR technique, further understanding of its transport behavior and retention in porous media is required. The research documented in this paper examines retention mechanisms that occur during nanocellulose transport. In a series of experiments, nanocellulose particles dispersed in brine were injected into sandpacks and Berea sandstone cores. The resulting retention and permeability reduction were measured. The experimental parameters that were varied include sand grain size, nanocellulose type, salinity, and flow rate. Under low salinity conditions, the dominant retention mechanism was adsorption and when salinity was increased, the dominant retention mechanism shifted towards log-jamming. Retention and permeability reduction increased as grain size decreased, which results from increased straining of nanocellulose aggregates. In addition, each type of nanocellulose was found to have significantly different transport properties. Experiments with Berea sandstone cores indicate that some pore volume was inaccessible to the nanocellulose. As a general trend, the larger the size of aggregates in bulk solution, the greater the observed retention and permeability reduction. Salinity was found to be the most important parameter affecting transport. Increased salinity caused additional aggregation, which led to increased straining and filter cake formation. Higher flow rates were found to reduce retention and permeability reduction. Increased velocity was accompanied by an increase in shear, which is believed to promote breakdown of nanocellulose aggregates.

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.

Co-immobilization of cellulase and lysozyme on amino-functionalized magnetic nanoparticles: An activity-tunable biocatalyst for extraction of lipids from microalgae.

An activity-tunable biocatalyst for Nannochloropsis sp. cell-walls degradation was prepared by co-immobilization of cellulase and lysozyme on the surface of amino-functionalized magnetic nanoparticles (MNPs) employing glutaraldehyde. The competition between cellulase and lysozyme during immobilization was caused by the limited active sites of the MNPs. The maximum recovery of activities (cellulase: 78.9% and lysozyme: 69.6%) were achieved due to synergistic effects during dual-enzyme co-immobilization. The thermal stability in terms of half-life of the co-immobilized enzymes was three times higher than that in free form and had higher catalytic efficiency for hydrolysis of cell walls. Moreover, the co-immobilized enzymes showed greater thermal stability and wider pH tolerance than free enzymes under harsh conditions. Furthermore, the co-immobilized enzymes retained up to 60% of the residual activity after being recycled 6 times. This study provides a feasible approach for the industrialization of enzyme during cell-walls disruption and lipids extraction from Nannochloropsis sp.

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.

Impact of biofilm on bacterial transport and deposition in porous media.

Laboratory scale experiments were conducted to obtain insights into factors that influence bacterial transport and deposition in porous media. According to colloidal filtration theory, the removal efficiency of a filter medium is characterized by two main factors: collision efficiency and sticking efficiency. In the case of bacterial transport in porous media, bacteria attached to a solid surface can establish a thin layer of biofilm by excreting extracellular polymeric substances which can significantly influence both of these factors in a porous medium, and thus, affect the overall removal efficiency of the filter medium. However, such polymeric interactions in bacterial adhesion are not well understood and a method to calculate polymeric interactions is not yet available. Here, to determine how the migration of bacteria flowing within a porous medium is affected by the presence of surface-associated extracellular polymeric substances previously produced and deposited by the same bacterial species, a commonly used colloidal filtration model was applied to study transport and deposition of Pseudomonas fluorescens in small-scale columns packed with clean and biofilm coated glass beads. Bacterial recoveries were monitored in column effluents and used to quantify biofilm interactions and sticking efficiencies of the biofilm coated packed-beds. The results indicated that, under identical hydraulic conditions, the sticking efficiencies in packed-beds were improved consistently by 36% when covered by biofilm.