Nitrogen Reduction Testing with Real-Time 15 NH 3 Yield Quantification Using Orbital Multiturn Time-of-Flight Mass Spectrometry
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Wastewater is a misplaced resource well suited to recover nutrients, value-added chemicals, energy, and clean water. A photoelectrochemical device is proposed to transform wastewater nitrates to ammonia and nitrous oxide, coupled with water oxidation. Numerical models were developed to quantify the dependence of process efficiencies and nitrogen-removal rates on light absorber band gaps, electrocatalytic kinetic parameters, competing oxygen reduction and hydrogen evolution reactions, and the reacting nitrate species concentrations that affect the mass-transfer limited current densities. With a single light-absorber and state-of-the-art catalysts, optimal solar-to-chemical efficiencies of 7% and 10% and nitrogen-removal rates of 260 and 395 gN m -2 day -1 are predicted for nitrate reduction to ammonia and nitrous oxide, respectively. The influence of competing reactions on the performance depends on the nitrate concentration and band gap of the light absorber modeled. Oxygen reduction is more dominant than hydrogen evolution to compete with the nitrate reduction reaction, but it is mass-transfer limited. Even with kinetic parameters that enhanced the driving forces for the competing reactions, the performance is only minimally affected by these reactions for optimally selected band gaps and nitrate concentrations larger than 100 mM. Here, theoretically predicted peak nitrogen removal rates and specific energy intensities are competitive with reported estimates for electrochemical and Sharon-Anammox processes for ammonia recovery and nitrogen removal, respectively. This result, together with the added benefit of harnessing sunlight to produce value-added products, indicates promise in the photoelectrochemical approach as a tertiary pathway to recover nutrients and energy from wastewater nitrates.
Magnetite concentrates from different parts of the Mesabi Range, exhibiting varying tendencies to encapsulate, were reduced using thermogravimetric analysis (TGA) and a high-temperature confocal scanning laser microscope (CSLM). Gas-phase mass-transfer conditions were intentionally varied by employing two reactors with different geometries: the TGA produced significantly slower reduction, whereas the CSLM setup yielded reduction rates up to 20 times faster under mass-transfer-controlled conditions. A preliminary mechanism is proposed to explain the transition from a porous iron product to a dense encapsulating layer. Encapsulation is interpreted as the outcome of competition between pore creation, driven by the reduction rate, and pore elimination, driven by surface diffusion. When pore formation is insufficient to counteract pore coarsening, a dense iron layer develops and restricts further reduction.
Leveraging the interactions between ionomer and catalyst can increase the performance of proton exchange membrane fuel cells. The impacts of the equivalent weight (EW) of perfluorosulfonic acid–based ionomers on the platinum group metal-free electrode structure and fuel cell performance have not been fully explored. Four membrane electrode assemblies (MEAs) were prepared by using a commercial Fe–N–C catalyst, two perfluorosulfonic acid ionomers with different EWs, that is, Aquivion 720 (A720) and Nafion 1100 (N1100), and two ionomer-to-catalyst (I/C) ratios. The four MEAs were characterized to understand the impact of the ionomer EW and content on the capacitance, proton conductivity, and mass transport on the cathode. The mass transport resistance was measured for the first time using a new oxygen reduction reaction limiting current method enabling to couple the effects of oxygen diffusion with liquid water generation. Low EW ionomer combined with a moderate I/C results in improved performance due to its enhanced proton conductivity. However, when used at high I/C, it can cause severe water flooding at high current density due to the enhanced liquid water uptake, especially at high relative humidity, resulting in lower catalyst utilization and higher mass transport resistance.
ABSTRACT The Study of H α from Dwarf Emissions (SHαDE) is a high spectral resolution (R = 13 500) H α integral field survey of 69 dwarf galaxies with stellar masses 106 < M⋆ < 109 M⊙. The survey used FLAMES on the ESO Very Large Telescope. SHαDE is designed to study the kinematics and stellar populations of dwarf galaxies using consistent methods applied to massive galaxies and at matching level of detail, connecting these mass ranges in an unbiased way. In this paper, we set out the science goals of SHαDE, describe the sample properties, outline the data reduction, and analysis processes. We investigate the log M⋆–log S0.5 mass–kinematics scaling relation, which has previously shown potential for combining galaxies of all morphologies in a single scaling relation. We extend the scaling relation from massive galaxies to dwarf galaxies, demonstrating this relation is linear down to a stellar mass of M⋆ ∼ 108.6 M⊙. Below this limit, the kinematics of galaxies inside one effective radius appears to be dominated by the internal velocity dispersion limit of the H α-emitting gas, giving a bend in the log M⋆–log S0.5 relation. Replacing stellar mass with total baryonic mass using gas mass estimate reduces the severity but does not remove the linearity limit of the scaling relation. An extrapolation to estimate the galaxies’ dark matter halo masses, yields a log Mh–log S0.5 scaling relation that is free of any bend, has reduced curvature over the whole mass range, and brings galaxies of all masses and morphologies on to the virial relation.
Gas diffusion electrodes (GDEs) have shown promising performance for the electrochemical reduction of CO 2 (CO 2 R). In this study, a resolved, pore scale model of electrochemical reduction of CO 2 within a liquid-filled catalyst layer is developed. Three CO 2 mass transport regimes are identified in which the CO 2 penetration depth is controlled by CO 2 consumption in the electrolyte, CO 2 conversion along the solid-electrolyte double-phase boundaries (DPBs), and CO 2 conversion concentrated around the gas–solid–electrolyte triple-phase boundaries (TPBs). While it is possible for CO 2 R to be localized around the TPBs, in systems with submicron pore radii operating at <1 A cm –2 CO 2 R will be distributed across the DPBs within the catalyst layer. This validates the assumption of pore-scale uniformity implicit in popular, volume-averaged GDE models. Overall, the CO 2 conversion efficiency depends strongly on the governing mass transport regime, and operational-phase diagrams are constructed to guide the catalyst layer design.
Here, to elucidate the impact of local interfaces on mass-transport resistance and overall cell performance of low-loaded proton-exchange-membrane fuel cells (PEMFCs), we present a multiscale modeling framework incorporating a novel modified agglomerate model. The model considers three distinct Pt-electrolyte interfaces: Pt on the carbon surface covered by either ionomer or water film and Pt inside carbon nanopores. Detailed mass-transport voltage-loss breakdowns reveal that coupled agglomerate-interface-scale mass transport dominates the mass-transport loss. The ionomer poisons the exterior-Pt surface through suppressing O 2 adsorption and intrinsic ORR activity, leading to low current-density performance. Conversely, interior-Pt interface enhances the kinetic performance but limits high current-density performance due to its low interfacial permeability. The exterior-Pt/water interface demonstrates superior kinetic performance and mass transport, though its practical implementation requires ensuring proton transport. By coupling the multiscale CL properties with ink parameters, the model identifies an optimal I to C ratio of approximately 0.5, a moderate value where the ionomer content is sufficient to guarantee proton transport without fully covering the Pt surface and forming large agglomeration, thus allowing the utilization of the Pt-water interface and avoiding high mass-transport loss. Overall, the model helps unravel limiting phenomena across different operating regimes and provides routes for optimizing performance.
Chemical transformation of 2-methyltetrol sulfates (2-MTS), key isoprene-derived secondary organic aerosol (SOA) constituents, through heterogeneous hydroxyl radical ( • OH) oxidation can result in the formation of previously unidentified atmospheric organosulfates (OSs). However, detected OSs cannot fully account for the sulfur content released from reacted 2-MTS, indicating the existence of sulfur in forms other than OSs, such as inorganic sulfates. This work investigated the formation of inorganic sulfates through heterogeneous • OH oxidation of 2-MTS aerosols. Remarkably, high yields of inorganic sulfates, defined as the moles of inorganic sulfates produced per mole of reacted 2-MTS, were observed in the range from 0.48 ± 0.07 to 0.68 ± 0.07. These could be explained by the production of sulfate (SO 4 •- ) and sulfite (SO 3 •- ) radicals through the cleavage of C-O(S) and (C)O-S bonds, followed by aerosol-phase reactions. Additionally, non-sulfated products resulting from bond cleavage were likely volatile and evaporated into gas phase, as evidenced by observed aerosol mass loss (up to 25%) and concurrent size reduction upon oxidation. This investigation highlights the significant transformation of sulfur from its organic to inorganic forms during the heterogeneous oxidation of 2-MTS aerosols, potentially influencing the physicochemical properties and environmental impacts of isoprene-derived SOA.
This study presents steam condensation scaled experiments and semi-empirical models in presence of nitrogen (N)—a noncondensable gas (NCG), simulating air in the reactor containment—to support water-cooled small modular reactors (SMRs) passive containment cooling system (PCCS) design and analysis. Previous experimental studies on PCCS are focused on fixed and smaller tube (mostly 2-in.) geometries and specific test condition variations, bringing challenges with geometric scaling and mismatching with SMR prototypic design. To address these challenges, this study presents steam condensation test dataset obtained from three scaled test sections of 1-, 2-, and 4-in.-diameter steam condensers with an annular/jacket cooling of 2-, 3-, and 6 in.-diameter tubes, respectively. Test data were collected for steam ranges from 58 to 63 kg/hr., and NCG flow of 4.4 to 13.3 kg/hr. Annular cooling water flow was varied to obtain required testing conditions of saturated steam inlet and fully condensed outlet. Axial temperature test data of bulk cooling water, steam and condensate were collected by thermocouples for three test sections and various steam-NCG mixing/testing conditions. A standard data reduction method was adopted—utilizing iterative and nodalized mass and heat transfer calculation—to estimate axial local heat fluxes, heat transfer coefficients (HTCs), condensation rates, film thickness, and Nusselt number. Based on the obtained dataset semi-empirical model results—a ratio of experimental and Nusselt’s theoretical HTC are presented. Such results and findings are supportive of developing scaled-up testing facility, to enable model validations and accelerate next generation of reactors development and deployment
This study presents steam condensation scaled experiments and semi-empirical models in presence of nitrogen--a noncondensable gas (NCG), simulating air in the reactor containment--to support water-cooled small modular reactors (SMRs) passive containment cooling system (PCCS) design and analysis. Previous experimental studies on PCCS are focused on fixed and smaller tube (mostly 2-in.) geometries and specific test condition variations, bringing challenges with geometric scaling and mismatching with SMR prototypic design. To address these challenges, this study presents steam condensation test dataset obtained from three scaled test sections of 1-, 2-, and 4-in.-diameter steam condensers with an annular/jacket cooling of 2-, 3-, and 6 in.-diameter tubes, respectively. Test data were collected for steam ranges from 58 to 63 kg/hr., and NCG flow of 4.4 to 13.3 kg/hr. Annular cooling water flow was varied to obtain required testing conditions of saturated steam inlet and fully condensed outlet. Axial temperature test data of bulk cooling water, steam and condensate were collected by thermocouples for three test sections and various steam-NCG mixing/testing conditions. A standard data reduction method was adopted--utilizing iterative and nodalized mass and heat transfer calculation to estimate axial local heat fluxes, heat transfer coefficients (HTCs), condensation rates, film thickness, and Nusselt number. Based on the obtained dataset semi-empirical model results--a ratio of experimental and Nusselt's theoretical HTC are presented. Such results and findings are supportive of developing scaled-up testing facility, to enable model validations and accelerate next generation of reactors development and deployment.
Self-supported nanocolumnar Pt:Ni thin films (TFs) with varying Pt:Ni atomic ratios and Pt mass loadings were produced on a microporous layer (MPL)-like surface composed of carbon particles by high pressure sputtering and examined as oxygen reduction reaction (ORR) electrocatalysts for polymer electrolyte membrane fuel cells. Cauliflower-like microstructures were observed from scanning electron microscopy imaging. Various Pt:Ni atomic ratios were obtained by simply changing the relative deposition power between Pt and Ni source and investigated by X-ray diffraction and quartz crystal microbalance analysis. Additionally, electrochemical characterization of the Pt:Ni-TF/MPL-like-layer/glassy-carbon samples was conducted through benchtop cyclic voltammetry and rotating disk electrode measurements. The electrochemically active surface area (ECSA) was found to be between 22–42 m 2 g -1 for different Pt:Ni atomic ratios. Lower Pt mass loadings exhibited a higher ECSA and the catalytic activity of all Pt:Ni ratios increased with the increase in Pt mass loading. The ORR activity of the Pt:Ni-TFs increased in the order of 3:1 < 1:1 < 1:3 with exhibiting a specific activity of 1781 μA cm -2 and mass activity of 0.66 A mg -1 for the Ni-rich film with 1:3 ratio. The catalytic performance of Pt:Ni-TFs were higher than traditional high surface area carbon supported Pt nanoparticles, elemental Pt nanorods, and Pt-Ni nanorods.
During large-scale, outdoor algal biomass growth, production strain(s) are subject to attack by pathogens, predators, and non-productive competitors, compromising the biomass yield. The project team at UCSD developed and demonstrated the effectiveness of Volatile Organic Compound, VOC, analysis via mass spectrometry (MS) as an early detection system for the presence of production algal ponds infection. The MS detection can then trigger high-resolution melt analysis (HRMA) and enhanced quantitative PCR (qPCR) to identify predatory or pathogenic species precisely. This study gathered the foundational data informing how wholly automated systems monitor the health of production ponds. By detecting the presence of low molecular weight VOCs in the air space above ponds, the instrument was able to mimic “sniffing” the health of the algae pond. This early warning system will be free growers from time-consuming and costly regular surveillance of ponds with the current techniques, such as qPCR and flow-cam assays, which are slower, less sensitive, and not easily fully automated, resulting in increased production efficiency through the reduction of crop loss. This project demonstrated that Chemical Ionization Mass Spectrometry, CIMS, could serve as a real-time monitor of ponds health tracking up to 100 different VOCs simultaneously for continuous periods up to 60 days without interruption, signaling infection within an algal crop 24 to 36 hours prior to techniques such as qPCR and microscopy. While mass spectrometry is an expensive tool, this simple VOC sampling system proved not only to be sensitive and robust but could to multiplexed to monitor several ponds, lowering the overall cost serially. This technology demonstrated a reduction in biomass production cost by approximately 50% compared to growers not employing any detection methodology.
In the face of a warming planet, steps must be taken to reduce the greenhouse gas emissions (GHG) associated with our building industry, which is a significant contributor to global emissions. Large, prefabricated wood elements such as mass timber panels (MTP) have great potential to achieve these reductions as they help displace high-embodied‑carbon materials like concrete and steel. Furthermore, storing the wood's biogenic carbon in buildings benefits the climate because it delays the eventual release of the carbon into the atmosphere. While these climate impacts have been assessed for the construction phase of mass timber buildings, relatively few life cycle assessment (LCA) studies have evaluated the climate impacts for the buildings' end-of-life (EOL) phase. This research estimates the climate impacts of four EOL scenarios for MTP: reusing as MTP, recycling into particleboard, incinerating, and landfilling. Using dynamic radiative forcing modeling and factoring in temporal GHG emissions and biogenic carbon storage, the global warming potential impacts are calculated for construction, deconstruction, and EOL processing of hybrid mass timber buildings in the U.S. Pacific Northwest for 160 years (GWP 160 ). The 160-year temporal scale used in this paper is an arbitrary scale, with the first 80 years being the assumed life of the building, followed by a series of reuse, recycle, or disposal scenarios over the second 80 years of that temporal scale. Of the four EOL scenarios considered in this paper, the ‘reuse’ scenario has the lowest net GWP 160 impact (calculated by summing the GWP 160 and carbon storage benefits, i.e., GWP$^{bioCS}_{160}$ ), emerging as a climate-preferred scenario, followed by ‘landfill’, ‘incinerate’, and ‘recycle’ scenarios. The lower net GWP 160 impact associated with the reuse scenario is due to the low fossil carbon emissions during EOL processing, as well as the biogenic carbon storage benefits. The results of this study also highlight the importance of efficient reuse and recycling strategies for wood in MTP.
Photocatalysts are conceptually simple reaction units where nanoscale semiconductors integrated with catalysts drive a pair of redox reactions on illumination. However, the proximity of reaction sites performing cathodic and anodic reactions poses dire challenges to realize large light-to-fuel conversion efficiencies. In this study, a powerful, yet straightforward, equivalent-circuit detail-balance modeling framework is developed and applied to evaluate the performance of photocatalytic systems featuring multiple light absorbers. Specifically, low bandgap iridium-doped strontium titanate is modeled as a Z-scheme photocatalyst to achieve desirable hydrogen evolution and iron-based redox shuttle oxidation reactions. Our model has unique capabilities to simulate competing redox reactions and address mass-transfer limitations. In a significant departure from state-of-the-art circuit models, our study develops tools to perform load-line analyses by incorporating a net electrochemical load curve that includes both desired and competing redox reactions. Consequently, reaction selectivity is predicted from equivalent circuit models for photocatalytic and photoelectrochemical systems. Our investigation into ensembles comprised of multiple, semi-transparent light absorbers reveals their potential to outperform a single, optically thick light absorber, particularly when operated under mass-transfer-limited conditions. However, this outcome hinges on minimizing mass-transfer rates of select redox species to prevent undesired reactions of hydrogen oxidation and/or redox shuttle reduction. Our findings demonstrate that reaction selectivity can be achieved by tuning asymmetry in redox species mass-transfer even with perfectly symmetric electrocatalytic charge-transfer coefficients. The influences of various kinetic, mass-transfer, and thermodynamic parameters are explored to offer crucial insights for synthesis of the next-generation of photocatalysts and selective coatings, and reactor designs.
In the present study, the multiphase volume distribution problem, where there can be an arbitrary number of phases, is addressed using a consistent and conservative volume distribution algorithm. The proposed algorithm satisfies the summation constraint, the conservation constraint, and the consistency of reduction. The first application of the volume distribution algorithm is to determine the Lagrange multipliers in multiphase Phase-Field models that enforce the mass conservation, and a multiphase conservative Allen-Cahn model that satisfies the consistency of reduction is developed. A corresponding consistent and conservative numerical scheme is developed for the model. The multiphase conservative Allen-Cahn model has a better ability than the multiphase Cahn-Hilliard model to preserve under-resolved structures. The second application is to develop a numerical procedure, called the boundedness mapping, to map the order parameters, obtained numerically from a multiphase model, into their physical interval, and at the same time to preserve the physical properties of the order parameters. Along with the consistent and conservative schemes for the multiphase Phase-Field models, the numerical solutions of the order parameters are reduction consistent, conservative, and bounded, which are theoretically analyzed and numerically validated. Then, the multiphase Phase-Field models are coupled with the momentum equation by satisfying the consistency of mass conservation and the consistency of mass and momentum transport, thanks to the consistent formulation. Finally, it is demonstrated that the proposed model and scheme converge to the sharp-interface solution and are capable of capturing the complicated multiphase dynamics even when there is a large density and/or viscosity ratio.
In this study, experimental studies using mass spectroscopy, thermogravimetric analysis, in situ X-ray diffraction (XRD), and theoretical density functional theory calculations were carried out to investigate the mechanism of methane partial oxidation over a CaFe 2 O 4 oxygen carrier. The XRD analysis revealed the formation of the calcium ferrite phases during methane reduction occurred in the sequence CaFe 2 O 4 →CaFe 3 O 5 + Ca 2 Fe 2 O 5 →FeO + Fe + CaO→Fe + CaO. Each of these phases was modeled using periodic density functional theory to study the activity of these phases for the reactivity with CH 4 , CO, and H 2 along with the adsorbed surface species to help elucidate the effect that phase changes during reduction have on the chemical looping products CO and H 2 . Mass spectroscopic analysis revealed the formation of H 2 O and CO 2 occurred prior to the formation of CO and H 2 , and these products may be due to the removal of lattice oxygen bound in the discrete primary phase, which contributes to a small portion (~16%) of the total transferable oxygen in the solid. The density functional theory (DFT) results suggest that the gaseous CO and H 2 are not thermodynamically favorable to react with the Ca 2 Fe 2 O 5 where the release of CO and H 2 led to an increase in selectivity for these products. The DFT results suggest that some of the adsorbed atomic hydrogen combined to form adsorbed H 2 and then gaseous H 2 on the CaFe 2 O 4 surface, while the carbon deposition and some adsorbed atomic hydrogen react to form the CaFe 3 O 5 and Ca 2 Fe 2 O 5 phases simultaneously. DFT simulations suggest that both the gaseous H 2 and adsorbed atomic H are less thermodynamically favorable to drive the deep reduction of Ca 2 Fe 2 O 5 to CaO and Fe0. The deep reduction of the calcium ferrite therefore favors the generation of syngas products (CO and H 2 ) through mechanisms of methane dehydrogenation and selective oxidation of carbon to CO. The significant difference in mechanisms for partial oxidation of methane to syngas with the CaFe 2 O 4 carrier can be correlated to the differences in the oxide phases present during the reduction process, concentration of oxygen species, and bonding in the lattice structure.
Polymer-electrolyte membrane (PEM) fuel-cells are one of the most promising energy conversion technologies for renewable clean energy applications. A major challenge preventing the widespread use and commercialization of PEM fuel cells is achieving high performance with low-loadings of platinum group metal (PGM) catalysts. One of the factors driving performance limitations in the cell is the mass transport losses within the cathode catalyst layers (CCL) due to sluggish oxygen-reduction reactions occurring at the platinum-ionomer interface. Any resistance to transport of these ionic and gaseous species within the CCL results in mass-transport limitations and performance losses, especially at high current densities. It is known that mass-transport losses increase with reduced platinum loading, thereby creating a performance-cost tradeoff for fuel cells. A viable solution to reduce the transport resistances in the catalyst layers is to create new ionomers that can provide good ion and oxygen transport needed to accomplish high-performing fuel cell catalysts. Using this approach Tetramer Technologies and LBNL propose improved fuel-cell catalyst ionomers based on Tetramers proprietary polymer chemistry.
This study demonstrates an atomic composition manipulation on Pt–Ni nano-octahedra to enhance their electrocatalytic performance. By selectively extracting Ni atoms from the {111} facets of the Pt–Ni nano-octahedra using gaseous carbon monoxide at an elevated temperature, a Pt-rich shell is formed, resulting in an ~2 atomic layer Pt-skin. The surface-engineered octahedral nanocatalyst exhibits a significant enhancement in both mass activity (~1.8-fold) and specific activity (~2.2-fold) toward the oxygen reduction reaction compared with its unmodified counterpart. After 20,000 potential cycles of durability tests, the surface-etched Pt–Ni nano-octahedral sample shows a mass activity of 1.50 A/mg Pt , exceeding the initial mass activity of the unetched counterpart (1.40 A/mg Pt ) and outperforming the benchmark Pt/C (0.18 A/mg Pt ) by a factor of 8. DFT calculations predict this improvement with the Pt surface layers and support these experimental observations. Therefore, this surface-engineering protocol provides a promising strategy for developing novel electrocatalysts with improved catalytic features.