Analysis of nonconstant area combustion and mixing in ramjet and rocket-ramjet hybrid engines
One-dimensional analysis of variable area mixing and combustion process in supersonic ramjet and rocket-ramjet hybrid engines
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One-dimensional analysis of variable area mixing and combustion process in supersonic ramjet and rocket-ramjet hybrid engines
This document describes the implementation and usage of the Goddard Earth Observing System (GEOS) Hybrid Ensemble-Variational Atmospheric Data Assimilation System (Hybrid EVADAS). Its aim is to provide comprehensive guidance to users of GEOS ADAS interested in experimenting with its hybrid functionalities. The document is also aimed at providing a short summary of the state-of-science in this release of the hybrid system. As explained here, the ensemble data assimilation system (EnADAS) mechanism added to GEOS ADAS to enable hybrid data assimilation applications has been introduced to the pre-existing machinery of GEOS in the most non-intrusive possible way. Only very minor changes have been made to the original scripts controlling GEOS ADAS with the objective of facilitating its usage by both researchers and the GMAO's near-real-time Forward Processing applications. In a hybrid scenario two data assimilation systems run concurrently in a two-way feedback mode such that: the ensemble provides background ensemble perturbations required by the ADAS deterministic (typically high resolution) hybrid analysis; and the deterministic ADAS provides analysis information for recentering of the EnADAS analyses and information necessary to ensure that observation bias correction procedures are consistent between both the deterministic ADAS and the EnADAS. The nonintrusive approach to introducing hybrid capability to GEOS ADAS means, in particular, that previously existing features continue to be available. Thus, not only is this upgraded version of GEOS ADAS capable of supporting new applications such as Hybrid 3D-Var, 3D-EnVar, 4D-EnVar and Hybrid 4D-EnVar, it remains possible to use GEOS ADAS in its traditional 3D-Var mode which has been used in both MERRA and MERRA-2. Furthermore, as described in this document, GEOS ADAS also supports a configuration for exercising a purely ensemble-based assimilation strategy which can be fully decoupled from its variational component. We should point out that Release 1.0 of this document was made available to GMAO in mid-2013, when we introduced Hybrid 3D-Var capability to GEOS ADAS. This initial version of the documentation included a considerably different state-of-science introductory section but many of the same detailed description of the mechanisms of GEOS EnADAS. We are glad to report that a few of the desirable Future Works listed in Release 1.0 have now been added to the present version of GEOS EnADAS. These include the ability to exercise an Ensemble Prediction System that uses the ensemble analyses of GEOS EnADAS and (a very early, but functional version of) a tool to support Ensemble Forecast Sensitivity and Observation Impact applications.
Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum information science have suggested that quantum signal processing (QSP) can enable more powerful signal processing capabilities. However, the developments in QSP have primarily leveraged digital quantum resources, such as discrete-variable (DV) systems like qubits, rather than analog quantum resources, such as continuous-variable (CV) systems like quantum oscillators. Consequently, there remains a gap in understanding how signal processing can be performed on hybrid CV-DV quantum computers. Here we address this gap by developing a new paradigm of mixed analog-digital QSP. We demonstrate the utility of this paradigm by showcasing how it naturally enables analog-digital conversion of quantum signals—specifically, the transfer of states between DV and CV quantum systems. We then show that such quantum analog-digital conversion enables new implementations of quantum algorithms on CV-DV hardware. This is exemplified by realizing the quantum Fourier transform of a state encoded on qubits via the free-evolution of a quantum oscillator, albeit with a runtime exponential in the number of qubits due to information theoretic arguments. Collectively, this work marks a significant step forward in hybrid CV-DV quantum computation, providing a foundation for scalable analog-digital signal processing on quantum processors.
Abstract New deposition techniques for amorphous oxide semiconductors compatible with silicon back end of line manufacturing are needed for 3D monolithic integration of thin‐film electronics. Here, three atomic layer deposition (ALD) processes are compared for the fabrication of amorphous zinc tin oxide (ZTO) channels in bottom‐gate, top‐contact n‐channel transistors. As‐deposited ZTO films, made by ALD at 150–200 °C, exhibit semiconducting, enhancement‐mode behavior with electron mobility as high as 13 cm 2 V −1 s −1 , due to a low density of oxygen‐related defects. ZTO deposited at 200 °C using a hybrid thermal‐plasma ALD process with an optimal tin composition of 21%, post‐annealed at 400 °C, shows excellent performance with a record high mobility of 22.1 cm 2 V –1 s –1 and a subthreshold slope of 0.29 V dec –1 . Increasing the deposition temperature and performing post‐deposition anneals at 300–500 °C lead to an increased density of the X‐ray amorphous ZTO film, improving its electrical properties. By optimizing the ZTO active layer thickness and using a high‐ k gate insulator (ALD Al 2 O 3 ), the transistor switching voltage is lowered, enabling electrical compatibility with silicon integrated circuits. This work opens the possibility of monolithic integration of ALD ZTO‐based thin‐film electronics with silicon integrated circuits or onto large‐area flexible substrates.
Relatively robust dynamic covalent interactions have been employed extensively to mediate molecular self-assembly reactions; however, these assembly processes often do not converge to a thermodynamic equilibrium, instead yielding mixtures of kinetically-trapped species. Here, we report a dynamic covalent self-assembly process that mitigates kinetic trapping such that multiple unique oligomers bearing covalently coreactive pendant groups are able to undergo simultaneous, sequence-selective hybridization with their complementary strands to afford biomimetic, in-registry molecular ladders with covalent rungs. Analogous to the thermal cycling commonly employed for nucleic acid melting and annealing, this is achieved by raising and lowering the concentration of a multi-role reagent to effect quantitative dissociation and subsequently catalyze covalent bond rearrangement, affording selective assembly of the oligomeric sequences. The hybridization specificity afforded by this process further enabled information encoded in oligomers to be retrieved through selective hybridization with complementary, mass-labeled sequences.
Quantum nondemolition (QND) measurements of photons is a much pursued endeavor in the field of quantum optics and quantum information processing. Here, we propose a hybrid optoelectromechanical platform that integrates a cavity system with a hybrid electromechanical probe for QND photon counting. Building upon a mechanical-mode-mediated nonperturbative electro-optical dispersive coupling, our protocol performs the QND photon counting measurement by means of the current-voltage characteristics of the probe. In particular, we show that the peak voltage shift of the differential conductance is linearly dependent on the photon occupation number, thus providing a sensitive measure of the photon number, especially in the strong optomechanical coupling regime. Here, given that our proposed hybrid system is compatible with state-of-the-art experimental techniques, we discuss its implementations and anticipate applications in quantum optics and polariton physics.
The global dynamics of the ionized and neutral components in the environment of Io plays an important role in the interaction of Jupiter's corotating magnetospheric plasma with Io. The stationary simulation of this problem was done in the MHD and the electrodynamics approaches. One of the main significant results from the simplified two-fluid model simulations was a production of the structure of the double-peak in the magnetic field signature of the I0 flyby that could not be explained by standard MHD models. In this paper, we develop a method of kinetic ion simulation. This method employs the fluid description for electrons and neutrals whereas for ions multilevel, drift-kinetic and particle, approaches are used. We also take into account charge-exchange and photoionization processes. Our model provides much more accurate description for ion dynamics and allows us to take into account the realistic anisotropic ion distribution that cannot be done in fluid simulations. The first results of such simulation of the dynamics of ions in the Io's environment are discussed in this paper.
Using a pulsed-beam transmission electron microscope, we discover a reduction in damage to methylammonium lead iodide (MAPbI3) as compared to conventional beams delivered at the same dose rates. For rates as low as 0.001 e·Å –2 ·s –1 , we find up to a 17% reduction in damage at a total dose of 10 e·Å –2 . We systematically study the effects of number of electrons in each pulse and the duration between pulse arrival. Damage increases for both, though the number of electrons per pulse has a larger effect. A crossover is identified, where a pulsed beam causes more damage than a conventional one. Although qualitatively similar to previous findings, the degree to which damage is reduced in MAPbI3 is less than that observed for other materials (e.g., C36H74), supporting the hypothesis that the effects are material- and damage-mechanism-dependent. Despite this, the observation here of damage reduction for relatively large electron packets (up to 200 electrons per pulse) suggests that MAPbI3 is in fact less susceptible to irradiation than C36H74, which may be related to reported self-healing effects. This work provides insights into damage processes and durability in hybrid perovskites and also illustrates the viability of using pulsed-beam TEM to explore the associated molecular-level routes to degradation, analogous to laser-accelerated energetic pulsed electron beams and the study of damage to biomolecules, cells, and tissues in radiobiology.
Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations.
Hybrid manufacturing, a combination of additive and subtractive manufacturing capabilities in one system, has recently become a more viable production option across several industries. Although current hybrid manufacturing research covers a broad range of topics, there is a lack of focus on how this new technology impacts both the designer and the operator of hybrid systems. This paper identifies areas of literature across design theory and Industry/Operator 4.0 research efforts and presents a path for applying this research to hybrid manufacturing users. The unique relationship between operator and designer is highlighted as they learn new strategies and develop new intuitive judgements over time to become the first experienced/expert users of hybrid manufacturing. The potential impact of excessive cognitive workload due to the novel combination of processes is discussed. This paper begins a critical discussion about proper knowledge transfer to other hybrid designers and operators, as well as towards efforts of monitoring, inspecting, and automating hybrid manufacturing processes.
Resonant infrared, matrix-assisted pulsed laser evaporation (RIR-MAPLE) is a promising technique for the physical vapor deposition of hybrid organic–inorganic perovskites. The approach already has been used to deposit both three-dimensional and two-dimensional hybrid perovskites with material quality comparable to those synthesized by solution processing. However, the phenomenological mechanisms of hybrid perovskite film formation by RIR-MAPLE have not been articulated. Therefore, this work presents a careful investigation of film formation mechanisms of three-dimensional methylammonium lead halide perovskites by considering the temporal evolution of morphology, crystallinity, and optical properties of films deposited by RIR-MAPLE.
Three different proton conducting polymeric membrane materials (Nafion® 115, Nafion® 212, and sulfonated Diels-Alder polyphenylene [SDAPP]) were evaluated for use in SO 2 -depolarized electrolyzers for the production of hydrogen via the hybrid sulfur cycle. Their performance was measured using different water feed strategies to minimize overpotential losses while maintaining high product acid concentration. Both thin membranes (Nafion® 212 and SDAPP) showed performance superior to that of the thicker Nafion® 115. Here, the SDAPP membrane electrode assembly (MEA) performed well at higher acid concentrations, maintaining low ohmic and kinetic overpotentials. Finally, short-term (100-h) stability tests under constant current conditions showed minimal degradation for the SDAPP and Nafion® 212 MEAs. SDAPP MEA performance approached the targets needed to make the hybrid sulfur cycle a competitive process for hydrogen production (product acid concentration ≥65 wt% H 2 SO 4 at ≤ 0.6-V cell potential and ≥0.5 A-cm –2 current density).
Efficient photovoltaic cells based on thin films of solution-processed 2D Ruddlesden–Popper hybrid perovskites (RPPs) represent an exciting breakthrough due to their enhanced tunability and chemical stability relative to those fabricated from 3D phases. However, reports of efficient charge separation and current collection are in apparent contradiction with the well-known enhancement of the exciton binding energy in multilayered halide perovskites, which should lower the device’s internal quantum efficiency and voltage. This controversy has led to various proposals for the electronic and physical structure of RPP thin films, including phase inhomogeneity as the driving force for exciton dissociation and transport. We address this apparent paradox in high-quality hot-cast RPP films by correlating ultrafast transient absorption spectroscopy with X-ray scattering measurements. We show that a hot-casting fabrication method produces highly phase pure n = 3 (BA) 2 (MA) n-1 Pb n I 3n+1 RPP structures. The high-phase purity and large grain sizes allow us to observe vertical transport of excitons via a diffusive process and allow us to determine that charge separation is primarily driven by dissociation at surface localized subgap electronic states. Furthermore, we analyze the differential absorption kinetics in films of varying thickness to directly determine that the excitonic diffusion constant is ~0.18 cm 2 s –1 . We propose that a surface localized structural distortion, observed using surface selective grazing incidence X-ray scattering measurements, is responsible for the creation of the surface localized defect states. We find that the density and spatial distribution of these defect states is a function of preparation conditions.
Here, we study the performance of the hybrid template machine learning photometric redshift (photo- z ) algorithm delight , which uses Gaussian processes, on a subset of the early data release of the Physics of the Accelerating Universe Survey (PAUS). We calibrate the fluxes of the 40 PAUS narrow bands with six broad-band fluxes ( uBVriz ) in the Cosmic Evolution Survey (COSMOS) field using three different methods, including a new method that utilizes the correlation between the apparent size and overall flux of the galaxy. We use a rich set of empirically derived galaxy spectral templates as guides to train the Gaussian process, and we show that our results are competitive with other standard photometric redshift algorithms. delight achieves a photo- z 68th percentile error of σ 68 = 0.0081(1 + z ) without any quality cut for galaxies with i auto < 22.5 as compared to 0.0089(1 + z ) and 0.0202(1 + z ) for the bpz and annz 2 codes, respectively. delight is also shown to produce more accurate probability distribution functions for individual redshift estimates than bpz and annz 2. Common photo- z outliers of delight and bcnz 2 (previously applied to PAUS) are found to be primarily caused by outliers in the narrow-band fluxes, with a small number of cases potentially indicating spectroscopic redshift failures in the reference sample. In the process, we introduce performance metrics derived from the results of bcnz 2 and delight , allowing us to achieve a photo- z quality of σ 68 < 0.0035(1 + z ) at a magnitude of i auto < 22.5 while keeping 50 per cent objects of the galaxy sample.
The growing significance of lignin-first biorefineries, which focus on upgrading the aromatics resulting from lignin depolymerization, presents opportunities for bioproduct synthesis using microbial strains capable of funneling a diverse array of phenolics into a single commodity chemical. In this study, we evaluated a biomass-to-bioproduct pipeline involving the reductive catalytic fractionation (RCF) of poplar biomass followed by biological funneling with a Novosphingobium aromaticivorans strain that produces 2-pyrone-4,6-dicarboxylic acid (PDC), a potential bioplastic precursor. Considering the impact of solvent on RCF reactor operating pressure, and the potential inhibitory effects of solvent on downstream microbial funneling, we performed an analysis of six pure solvents, namely methanol, ethanol, isopropanol, isobutanol, 1,4-dioxane and ethylene glycol, and different variations of their aqueous mixtures comprising 5 to 50 vol% water. For each pure solvent and solvent/water system, we measured phenolic monomer yields in the RCF process and PDC yields from the phenolic monomers. We then developed correlation models that relate phenolic monomer yields from RCF-derived samples to Hansen solubility parameters to determine solvent descriptors that contribute to high yields. Furthermore, we developed an integrated biorefinery system to estimate the minimum selling price (MSP) of PDC and the associated carbon footprint to identify solvent systems with better costs and sustainability metrics. These analyses resulted in the 50 vol% methanol/water system being identified as optimal because it reduces RCF reactor pressure and is compatible with microbial funneling with N. aromaticivorans. This solvent system produced 63 g PDC per kg biomass (264 g PDC per kg lignin) from 85 g phenolic monomers per kg biomass at a reduced reactor pressure of 48 bar (reduced by 26% compared to our previous poplar-to-PDC pipeline). The MSP for this system is $\$$13.98 per kg of purified PDC (carbon footprint of 1.47 kg CO 2 e per kg), which is about 24% lower than a previously described poplar-to-PDC pipeline and 46% lower than a lignin-to-PDC pipeline that used pure methanol as the solvent. The results from this study illustrate improvements that can be made in lignocellulosic biorefineries that are compatible with the hybrid chemical and biological processes needed to gain value from lignin.
The concept of circular economy has been diffused in recent decades to promote economic growth that does not add to the burden on natural resource extraction. Re-X options (e.g., reuse, repair, refurbish, remanufacture, recycle) have been gradually adopted in the product development process and optimized to reduce or eliminate waste and pollution. Although manufacturing incorporating Re-X options can be more environmentally friendly, it involves more sources of uncertainty than traditional manufacturing since the end-of-use products can be collected from multiple origins with various quantities and qualities, and the market demand for both new and remanufactured products cannot be forecasted perfectly. Thus, there is a need to optimize the Re-X policy to alleviate the negative impacts of the higher uncertainty. One option is using the reliability information of new products to estimate the end-of-use conditions and applying multi-stage stochastic optimization to capture multiple demand scenarios. This paper develops a two-stage stochastic optimization model to optimize the quality thresholds for reuse, recycling, and remanufacturing options. Our objective is to minimize the total cost, energy consumption, and environmental impact of producing and providing warranty service for a product family. The model employs reliability information of product components to estimate the warranty service cost and the end-of-use conditions of the returned resources. A case study on a general product family is implemented to illustrate the efficacy of the optimization model. Finally, results show that the two-stage optimization can achieve cost and environmental impact reduction for a hybrid manufacturing and remanufacturing process.
Electrochemical characterizations are performed using thin films and commercial carbon supported platinum and gold catalysts for sulfur dioxide oxidation, the primary electrochemical oxidation reaction in the Hybrid-sulfur (HyS) thermochemical process. Electrochemical evaluation of metal thin films qualitatively confirms the higher activity of Au over Pt, AuPt, Pd, and Ir for the electrochemical oxidation of SO 2 . Ex-situ testing, using rotating disk electrode (RDE), shows an earlier onset potential for Au/C at low sulfuric acid concentrations (C ≤ 3.5 M) and a higher turnover frequency than Pt/C at sulfuric acid concentrations ranging from 3.5 M to 9 M. In-situ electrolysis experiments using low catalyst loadings (0.1 mg Au cm –2 , a factor of ≥5 lower than typical loadings) confirm that Au nanoparticles exhibit higher current densities and greater stability than Pt nanoparticles. This is consistent with the thin film screening studies, which showed higher activity with increasing gold content in AuPt thin films. Here, this work reveals an alternative material to state-of-the-art Pt to lower the energy needs and aid the HyS cycle in reaching the target of $2/kg H 2 set forth by the Department of Energy to achieve economic feasibility of large-scale hydrogen generation.
RNase H enzymes are sequence-nonspecific endonucleases that cleave RNA strands in RNA/DNA hybrid duplexes, an enzymatic process essential in DNA replication and repair in both prokaryotes and eukaryotes. Also, RNase H activity of the reverse transcriptase in human immunodeficiency viruses (HIV-1 and HIV-2) is indispensable for the viral replication cycle. RNase H enzymes play an central role in the development of gene therapies and are targets for novel antivirals. It is therefore of great importance to gain a detailed understanding of the RNase H catalytic mechanism to improve drug design. We utilized Bacillus halodurans RNase H1 (BhRNase H1) to shed light on its function and catalytic mechanism. Room-temperature neutron crystallography of the wild-type and inactive D132N mutant enzymes revealed that E109, belonging to the catalytic DEDD motif, can change its protonation state, allowing us to propose its role in the protonation of the leaving O3′ hydroxyl group of RNA. X-ray crystallography has demonstrated the ability of the RNA/DNA duplex to slide along the protein surface upon metal ion binding at site M A , transforming a product mimic into a Michaelis-like complex, which confirms an essential role of the M A metal ion in catalysis.