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At least 757 records · Page 42

NUMERICAL INVESTIGATION OF FUEL PROPERTY EFFECTS ON MIXED-MODE COMBUSTION IN A SPARK-IGNITION ENGINE

In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.

detailed chemical kinetics↗

Defect evolution in Ni and solid-solution alloys of NiFe and NiFeCoCr under ion irradiation at 16 and 300 K

Single-phase concentrated solid-solution alloys (SP-CSAs) have shown unique chemical complexity at the levels of electrons and atoms, and their defect evolution is expected to be different from conventional dilute alloys. Single crystals of Ni, NiFe and NiFeCoCr are chosen as model systems to understand the chemical complexity on defect formation and damage accumulation in SP-CSAs under ion irradiation. The high-quality crystals were irradiated at 16 and 300 K to different ion fluences, to form irradiated region with little to heavy damages. Additionally, the ion-induced damage was determined using Rutherford backscattering spectrometry technique along a channeling direction (RBS/C) and the level of lattice damage in irradiated Ni and SP-CSAs was quantified from Monte Carlo (MC) simulations. The results are interpreted using the Multi Step Damage Accumulation model to reveal material damage accumulation kinetics. Key findings of the study are that in case of room temperature irradiations the damage level measured for complex alloys at the highest irradiation fluence of 2 × 10 15 cm -2 (~3 dpa) is significantly higher than that obtained for pure nickel samples and suggest two-step damage accumulation process with a defect transformation taking place at a fluence of about 1.5 × 10 15 cm -2 . Furthermore, structural and damage kinetic differences clearly imply that, with increasing degree of chemical complexity and high solid-solution strengthening effects from Ni to NiFe and to NiFeCoCr, the enhanced lattice stiffness resists to randomization of atomic configurations and inhibits the growth of extended defects.

36 MATERIALS SCIENCE↗

Production of ice-nucleating particles (INPs) by fast-growing phytoplankton

Sea spray aerosol contains ice-nucleating particles (INPs), which affect the formation and proper ties of clouds. Here, we show that aerosols emitted from fast-growing marine phytoplankton produce effective immersion INPs, which nucleate at temperatures significantly warmer than the atmospheric homogeneous freezing (-38.0 °C) of pure water. Aerosol sampled over phytoplankton cultures grown in a Marine Aerosol Ref erence Tank (MART) induced nucleation and freezing at temperatures as high as -15.0 °C during exponential phytoplankton growth. This was observed in monospecific cultures representative of two major groups of phy toplankton, namely a cyanobacterium (Synechococcus elongatus) and a diatom (Thalassiosira weissflogii). Ice nucleation occurred at colder temperatures (-28.5 °C and below), which were not different from the freezing temperatures of procedural blanks, when the cultures were in the stationary or death phases of growth. Ice nucleation at warmer temperatures was associated with relatively high values of the maximum quantum yield of photosystem II ( Φ PSII ), an indicator of the physiological status of phytoplankton. High values of Φ PSII indicate the presence of cells with efficient photochemistry and greater potential for photosynthesis. For comparison, field measurements in the North Atlantic Ocean showed that high net growth rates of natural phytoplankton assemblages were associated with marine aerosol that acted as effective immersion INPs at relatively warm temperatures. Data were collected over 4 d at a sampling station maintained in the same water mass as the water column stabilized after deep mixing by a storm. Phytoplankton biomass and net phytoplankton growth rate (0.56 d -1 ) were greatest over the 24 h preceding the warmest mean ice nucleation temperature (-25.5 °C). Collectively, our laboratory and field observations indicate that phytoplankton physiological status is a useful predictor of effective INPs and more reliable than biomass or taxonomic affiliation. Ocean regions associated with fast phytoplankton growth, such as the North Atlantic during the annual spring bloom, may be significant sources of atmospheric INPs.

54 ENVIRONMENTAL SCIENCES↗

Development of Corrosion- and Erosion-Resistant Coatings for Advanced Ultra-Supercritical Materials

This final report summarized the research efforts and major findings of the Phase I Project “Development of Corrosion- and Erosion-Resistant Coatings for Advanced Ultra-Supercritical Materials”, for the period of October 1, 2019 – Sept. 30, 2021. This project is a collaborative endeavor between Tennessee Tech University, Purdue University, Oak Ridge National Laboratory, Siemens Corporation, and Eastern Plating, LLC, aiming at improving the durability and lifetime of high-pressure (HP) steam turbine blades in advanced ultra-supercritical (A-USC) coal-fired power plants through the development of corrosion/erosion-resistant coatings manufactured via a low-cost electrolytic codeposition process. While Tribaloy alloy T-400C was identified by the U.S. A-USC Materials Consortium as a promising coating composition, further composition optimization is needed to enhance its corrosion and erosion resistance for protecting the A-USC Ni-base turbine components. An integrated computational and experimental approach was employed to optimize coating composition/microstructure and processing parameters. In order to identify candidate coating compositions that could offer balanced properties, thermodynamic calculations were performed to explore the γ+Laves composition space in the Co-Ni-Cr-Mo-Si system with different alloying additions at 600-800 °C. Guided by the calculation results, experimental assessment of selected alloys led to the development of a new generation of Tribaloy compositions with the optimal levels of Cr, Mo and Si, reactive element (e.g., 0.4-0.6 wt.% Y) and other alloying additions. The low-cost and non-line-of-sight electro-codeposition process was employed to deposit a Ni(Co)-CrMoSiY composite coating on commercial Haynes 282 (H282) Ni-base alloy. A diffusion treatment was subsequently applied to convert the composite to the Tribaloy-type coating. Both the codeposition parameters and heat treatment conditions were varied to achieve the desired coating composition, microstructure and phase constituents. In addition, since additive manufacturing (AM) may be an alternative cost-saving option for potential A-USC turbine repair, laser direct deposition was explored to fabricate the H282 alloy with minimal defects. The electro-codeposited Tribaloy coating was also applied to the AM H282 substrate to demonstrate the viability of the coating process in improving the surface finish of AM alloys. Both high-temperature oxidation performance and solid particle erosion (SPE) resistance of model alloys and electro-codeposited coatings were evaluated. About 25 model alloys with various Cr/Mo ratios and reactive element levels, as well as partial substitution of Mo with Nb were evaluated with regard to their oxidation resistance in both air and pure steam at 760-800°C. Compositions based on Ni(Co)-20Cr-18Mo-2.6Si-0.6Y (wt.%) showed significantly improved oxidation resistance over the baseline T400-C. Based on the alloy development results, three generations of new Tribaloy coatings (Gen-1, Gen-2, and Gen-3) with various Mo/Cr contents and Y levels were prepared via electro-codeposition and their microstructure/performance were evaluated. Outstanding air and steam oxidation resistance was achieved for the Gen-2 and Gen-3 coatings. Furthermore, while the SPE resistance of the coatings depended on many factors such as temperature, environment, erodent, velocity and impact angle, the coated samples exhibited similar or better SPE resistance compared to the H282 substrate when magnetite was used as erodent (which is a realistic erodent in A-USC steam turbines). The new Tribaloy coatings also had good long-term compatibility with the H282 alloy substrate. The two large-sized rotating barrels were designed, constructed, and employed to coat dummy HP blades. Uniform coating thickness and microstructure were achieved at various blade locations. Also, a preliminary techno-economic analysis of the proposed coating process was conducted to quantify the cost-effectiveness and to assess the commercial viability of the corrosion- and erosion-resistant coatings. It is estimated that a cost reduction of ~30% could be achieved with the electro-codeposition coating process over the state-of-the-art high velocity oxygen fuel (HVOF) thermal spray. Compared to the leading Tribaloy coating technologies such as HVOF and plasma transfer alloying, electro-codeposition based process has advantages such as low-cost process equipment, uniform deposition even for complex shapes, low levels of contaminants/porosities, reduction of powder waste, and potentially better surface finish and longer turbine service life. The Phase 1 study has demonstrated that it is feasible to develop an electro-codeposited Tribaloy coating with balanced corrosion and erosion properties, even though additional research efforts such as further coating process scale-up and longer-term performance evaluation under realistic A-USC conditions are clearly needed.

20 FOSSIL-FUELED POWER PLANTS↗

Copper availability governs nitrous oxide accumulation in wetland soils and stream sediments

Denitrification is microbially-mediated through enzymes containing metal cofactors. Laboratory studies of pure cultures have highlighted that the availability of Cu, required for the multicopper enzyme nitrous oxide reductase, can limit N2O reduction. However, in natural aquatic systems, such as wetlands and hyporheic zones in stream beds, the role of Cu in controlling denitrification remains incompletely understood. In this study, we collected soils and sediments from three natural environments -- riparian wetlands, marsh wetlands, and a stream -- to investigate their nitrogen species transformation activity at background Cu levels and different supplemented Cu loadings. All of the systems contained solid-phase associated Cu below or around geological levels (40 - 280 nmol g-1) and exhibited low dissolved Cu (3-50 nM), which made them appropriate sites for evaluating the effect of limited Cu availability on denitrification. In laboratory incubation experiments, high concentrations of N2O accumulated in all microcosms lacking Cu amendment except for one stream sediment sample. With Cu added to provide dissolved concentrations at trace levels (10-300 nM), reduction rate of N2O to N 2 in the wetland soils and stream sediments was enhanced. A kinetic model could account for the trends in nitrogen species by combining the reactions for microbial reduction of NO 3 - to NO 2 -/N 2 O/N 2 and abiotic reduction of NO 2 - to N 2 . The model revealed that the rate of N 2 O to N 2 conversion increased significantly in the presence of Cu. For riparian wetland soils and stream sediments, the kinetic model also suggested that overall denitrification is driven by abiotic reduction of NO2- in the presence of inorganic electron donors. This study demonstrated that natural aquatic systems containing Cu at concentrations less than or equal to crustal abundances may display incomplete reduction of N 2 O to N 2 that would cause N 2 O accumulation and release to the atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CLPNets: Coupled Lie–Poisson neural networks for multi-part Hamiltonian systems with symmetries

To accurately compute data-based prediction of Hamiltonian systems, it is essential to utilize methods that preserve the structure of the equations over time. We consider a particularly challenging case of systems with interacting parts that do not reduce to pure momentum evolution. Such systems are essential in scientific computations, such as discretization of a continuum elastic rod, which can be viewed as the group of rotations and translations $SE(3)$. The evolution involves not only the momenta but also the relative positions and orientations of the particles. The presence of Lie group-valued elements, such as relative positions and orientations, poses a problem for applying previously derived methods for data-based computing. We develop a novel method of data-based computation and complete phase space learning of such systems. We follow the original framework of SympNets (Jin et al., 2020) and LPNets (Eldred et al., 2024), building the neural network from phase space mappings that preserve the Lie–Poisson structure. We derive a novel system of mappings that are built into neural networks describing the evolution of such systems. We call such networks Coupled Lie–Poisson Neural Networks, or CLPNets. We consider increasingly complex examples for the applications of CLPNets, starting with the rotation of two rigid bodies about a common axis, progressing to the free rotation of two rigid bodies, and finally to the evolution of two connected and interacting $SE(3)$ components, describing the discretization of an elastic rod into two elements. Our method preserves all Casimir invariants to machine precision, preserves energy to high accuracy, and shows good resistance to the curse of dimensionality, requiring only a few thousand data points for all cases studied (three to eighteen dimensions). Additionally, the method is highly economical in memory requirements, requiring only about 200 parameters for the most complex case considered.

Data-based modeling↗

Probing topological phase transitions using high-harmonic generation

We report the prediction and realization of topological insulators have sparked great interest in experimental approaches to the classification of materials. The phase transition between non-trivial and trivial topological states is important, not only for basic materials science but also for next-generation technology, such as dissipation-free electronics. It is therefore crucial to develop advanced probes that are suitable for a wide range of samples and environments. Here we demonstrate that circularly polarized laser-field-driven high-harmonic generation is distinctly sensitive to the non-trivial and trivial topological phases in the prototypical three-dimensional topological insulator bismuth selenide. The phase transition is chemically initiated by reducing the spin–orbit interaction strength through the substitution of bismuth with indium atoms. We find strikingly different high-harmonic responses of trivial and non-trivial topological surface states that manifest themselves as a conversion efficiency and elliptical dichroism that depend both on the driving laser ellipticity and the crystal orientation. The origins of the anomalous high-harmonic response are corroborated by calculations using the semiconductor optical Bloch equations with pairs of surface and bulk bands. As a purely optical approach, this method offers sensitivity to the electronic structure of the material, including its nonlinear response, and is compatible with a wide range of samples and sample environments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Compression behavior of dense H 2 -He mixtures up to 160 GPa

We have studied the compression behavior of H 2 -He mixtures in comparison with pure H 2 and He using powder synchrotron x-ray diffraction and present the pressure-volume (PV) compression data of H 2 -He mixtures to 160 GPa. The results indicate that both H 2 and He in H 2 -He mixtures remain in hcp to the maximum pressure studied, yet develop a substantial level of lattice distortion in the (100) plane, most profound in He-rich solids and below 66 GPa. The measured PV data also indicate softening of He (or H 2 )-rich lattice upon increasing the level of the guest H 2 (or He) concentration. We suggest that the observed softening and lattice distortion are due to a substitutional incorporation of H2 (guest) molecules into the basal plane of hcp-He (host) lattice and, thereby, reflect the miscibility between H 2 and He in H 2 -He mixtures. Interestingly, solid He exhibits a lesser degree of preferred orientation in H2-He mixtures than in pure He, likely due to the presence of solid H 2 disturbing the crystalline ordering of He-rich solids. Finally, the present PV compression data of H 2 -rich and He-rich solids to 160 GPa deviate from those of pure H 2 and pure He above ~70 and 45 GPa respectively, providing new constraints for development of the EOS for H 2 -He mixtures for planetary models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Disorder-dependent slopes of the upper critical field in nodal and nodeless superconductors

In this work we study the slopes of the upper critical field S = ∂H c2 /∂T at the superconducting transition temperature T c in anisotropic superconductors with transport (nonmagnetic) scattering employing the Ginzburg-Landau theory, developed for this case by Pokrovsky and Pokrovsky [Phys. Rev. B 54, 13275 (1996)]. We find unexpected behavior of the slopes for a d -wave superconductor and, in a more general case, of materials with line nodes in the order parameter. Specifically, the presence of line nodes causes S to decrease with increasing nonmagnetic scattering parameter P = ℏ/2πT c0 τ (T c0 is for the clean limit, τ is the scattering time), unlike the nodeless case where the slope increases. In a pure d -wave case, the slope changes from decreasing to increasing when the scattering parameter approaches P ≈ 0.91 P crit , where P crit ≈ 0.28, at which T c → 0, which implies the existence of a “gapless” state in d -wave superconductors with transport scattering in the interval, 0.91 P crit < P < P crit . Furthermore, we consider the mixed (s + d)-wave order parameter with four nodes on a cylindrical Fermi surface when the d part is dominant, or no nodes at all when the s-wave phase dominates. We find that the presence of nodes causes the slope S(P) to decrease initially with increasing P, whereas in the nodeless state, S(P) monotonically increases. Therefore, relatively straightforward measurements of the disorder dependence of the slope of H c2 at T c can help distinguish between nodal and nodeless order parameters, which is particularly useful for quickly assessing newly discovered superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Pretreatments for the continuous production of pyrolytic sugar from lignocellulosic biomass

Fast pyrolysis of lignocellulosic biomass yields little sugar or anhydrosugars compared to pyrolysis of pure polysaccharides because naturally abundant alkali and alkaline earth metals (AAEM) in biomass catalyze the fragmentation of pyranose and furanose rings. Sugar yields can be increased dramatically by pretreating the biomass with sulfuric acid prior to pyrolysis, which passivates the catalytic activity of the metals by converting them into thermally stable salts. However, depolymerization of lignin in biomass also depends on the catalytic activity of AAEM. Thus, passivating AAEM has the unintended consequence of slowing the rate of depolymerization and volatilization of lignin, resulting in a transient melt phase that agglomerates and can foul pyrolysis reactors. Here, to overcome this problem, various non-alkali metal sulfates were tested as replacements for sulfuric acid. Iron in the form of ferrous sulfate proved the most effective in depolymerizing lignin without fragmenting pyranose rings. Conventional nitrogen-blown pyrolysis of ferrous sulfate pretreated corn stover achieved WHSV of 4 h –1 compared to only 0.6 h –1 for acid pretreated corn stover. Autothermal (air-blown) pyrolysis of ferrous sulfate pretreated corn stover showed even more dramatic improvement, increasing WHSV from 1 h –1 to 10 h –1 compared to acid pretreated corn stover under autothermal operation. Fermentable sugar yields from the pyrolysis of corn stover increased from 0.9 wt% to 11.8 wt% on a biomass basis, a 13-fold increase as a result of the ferrous sulfate pretreatment. These advantages combine to increase volumetric sugar productivity from 62 g L –1 h –1 for conventional pyrolysis of untreated corn stover to 2041 g L –1 h –1 for autothermal pyrolysis of ferrous sulfate treated corn stover.

09 BIOMASS FUELS↗

Nondegenerate Noise-Resilient Superconducting Qubit

We propose a superconducting qubit based on engineering the first and second harmonics of the Josephson energy and phase relation 𝐸 𝐽⁢1 ⁢cos 𝜑 and 𝐸 𝐽⁢2 ⁢cos 2⁢𝜑. By constructing a circuit such that 𝐸 𝐽⁢2 is negative and |𝐸 𝐽⁢1 | ≪ |𝐸 𝐽⁢2 |, we create a periodic potential with two nondegenerate minima. The qubit, which we dub “harmonium,” is formed from the lowest-energy states of each minimum. Bit-flip protection of the qubit arises due to the localization of each qubit state to their respective minima, while phase-flip protection can be understood by considering the circuit within the Born-Oppenheimer approximation. We demonstrate with time-domain simulations that single- and two-qubit gates can be performed in approximately 100 ns. Finally, we compute the qubit coherence times using numerical diagonalization of the complete circuit in conjunction with state-of-the-art noise models. We estimate out-of-manifold heating times on the order of milliseconds, which can be treated as erasure errors using conventional dispersive readout. We estimate pure-dephasing times on the order of many tens of milliseconds, and bit-flip times on the order of seconds.

quantum error correction↗

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗

Encapsulation of Nanoparticle Organic Hybrid Materials within Electrospun Hydrophobic Polymer/Ceramic Fibers for Enhanced CO 2 Capture

Liquid-like nanoparticle organic hybrid materials (NOHMs) consisting of a silica core with ionically grafted branched polyethyleneimine chains (referred to as NIPEI) are encapsulated within submicron-scale polyacrylonitrile (PAN)/polymer-derived-ceramic electrospun fibers. The addition of a room-temperature curable, liquid-phase organopolysilazane (OPSZ) ceramic precursor to the PAN/NOHM solution enhances the internal dispersion of NOHMs and forms a thin ceramic sheath layer on the fiber exterior, shielding the hydrophilic NIPEI to produce near-superhydrophobic non-woven fiber mats with contact angles exceeding 140°. 60:40 loadings of NOHMs to PAN/OPSZ can be reliably achieved with low OPSZ percentages required, and up to 4:1 NOHM:polymer loadings are possible before losing hydrophobicity. These fibers demonstrate up to ≈2 mmol CO 2 g -1 fiber capture capacities in a pure CO 2 atmosphere through the nonwoven fibrous networks and the permeability of the OPSZ shell. In conclusion, the hybrid fibers additionally show enhanced capture kinetics under pure CO 2 and 400 ppm CO 2 conditions, indicating their promising application as a direct air capture platform.

36 MATERIALS SCIENCE↗

Mechanistic insights into the catalytic methanol steam reforming performance of Cu/ZrO 2 catalysts by in situ and operando studies

Here, we assessed the catalytic properties of the Cu/ZrO 2 interface in methanol and formaldehyde steam reforming (MSR and FSR) on powder catalysts by using a comparative approach with respect to the influence of the ZrO 2 polymorph support structure (monoclinic (m-)ZrO 2 vs. tetragonal (t-)ZrO 2 ), its synthesis routine and the choice of the precursor material on the CO 2 selectivity. Our studies reveal that ZrO 2 exhibits a pronounced versatility as a support material and its catalytic properties depend most strongly on its surface properties governed by its synthesis, especially by the choice of the Zr precursor. The way of combining the support with copper introduces an additional layer of complexity, but its influence on the MSR performance is limited to a modification of the conditions provided by the ZrO 2 support. Exploiting the comparative approach regarding the Cu-ZrO 2 catalysts in FSR and MSR – including the pure support materials – in combination with in situ Fourier transform infrared (FT-IR) spectroscopy shows that the CO observed in MSR on Cu/m-ZrO 2 can be attributed to a spillover of formaldehyde to the support. Side reactions of m-ZrO 2 are suppressed at lower temperatures due to its lack of highly reactive sites, resulting in a CO 2 -selective MSR performance. In Cu/t-ZrO 2 , however, the amount of CO is higher and a combination of a formaldehyde spillover to the support and a Cu-ZrO 2 phase boundary yielding CO leads to the lower CO 2 selectivity of these samples. An elevated number of defects and reactive Lewis acidic and Brønsted basic centers of t-ZrO 2 explains this increased activity towards side reactions in contrast to Cu/m-ZrO 2 catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗

Reentrant superconductivity through a quantum Lifshitz transition in twisted trilayer graphene

A series of recent experiments has demonstrated robust superconductivity in magic-angle twisted trilayer graphene (TTG). In particular, a recent work by Cao et al. [Nature (London) 595, 526 (2021)] studies the behavior of the superconductor in an in-plane magnetic field and an out-of-plane displacement field, finding that the superconductor is unlikely to have purely spin-singlet pairing. Herein, this work also finds that at high magnetic fields and a smaller range of dopings and displacement fields, the superconductor undergoes a transition to a distinct field-induced superconducting state. Inspired by these results, we develop an understanding of the superconductivity in TTG using a combination of phenomenological reasoning and microscopic theory. We describe the role that an in-plane field plays in TTG, and we use this understanding to argue that the reentrant transition may be associated with a quantum Lifshitz phase transition, with the high-field phase possessing finite-momentum pairing. We argue that the superconductor is likely to involve a superposition of singlet and triplet pairing, and we describe the structure of the normal state. We also draw lessons for twisted bilayer graphene (TBG), and we explain the differences in the phenomenology with TTG despite their close microscopic relationship. We propose that a singlet-triplet superposition is realized in the TBG superconductor as well, and that the ν = –2 correlated insulator may be a time-reversal protected Z 2 topological insulator obtained through spontaneous spin symmetry breaking.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Role of copper in nitrous oxide accumulation in wetland soils from Illinois and South Carolina and stream sediments from Tennessee

Denitrification is microbially-mediated through enzymes containing metal cofactors. Laboratory studies of pure cultures have highlighted that the availability of copper (Cu), required for the multicopper enzyme nitrous oxide reductase, can limit nitrous oxide (N2O) reduction. However, in natural aquatic systems, such as wetlands and hyporheic zones in stream beds, the role of Cu in controlling denitrification remains incompletely understood. In this study, we collected soils and sediments from three natural environments -- riparian wetlands, marsh wetlands, and a stream -- to investigate their nitrogen species transformation activity at background Cu levels and different supplemented Cu loadings. All of the systems contained solid-phase associated Cu below or around geological levels (40–280 nmol g-1) and exhibited low dissolved Cu (3–50 nM), which made them appropriate sites for evaluating the effect of limited Cu availability on denitrification.The dataset contains the variation in the nutrient (nitrate (NO3-), nitrite (NO2-), and ammonium (NH4+)) and N2O concentrations during the incubation experiments to evaluate the effect of Cu. We have also reported the variation in metal concentrations (Cu, iron(Fe) and manganese (Mn)) and dissolved organic carbon (DOC) concentrations during the incubations. The parameters obtained using a kinetic model to quantitatively report the effect of Cu on nitrogen species conversion in natural aquatic systems are also added in the dataset. The dataset also contains the labile concentration of Cu estimated using a speciation model in MINTEQ. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units.Our study suggests that high concentrations of N2O accumulated in all microcosms lacking Cu amendment except for one stream sediment sample. With Cu added to provide dissolved concentrations at trace levels (10–300 nM), the reduction rate of N2O to N2 in the wetland soils and stream sediments was enhanced. A kinetic model could account for the trends in nitrogen species by combining the reactions for microbial reduction of NO3- to NO2-/N2O/N2 and abiotic reduction of NO2 to nitrogen (N2_. The model revealed that the rate of N2O to N2 conversion increased significantly in the presence of Cu. For riparian wetland soils and stream sediments, the kinetic model also suggested that overall denitrification is driven by abiotic reduction of NO2- in the presence of inorganic electron donors. This study demonstrated that natural aquatic systems containing Cu at concentrations less than or equal to crustal abundances may display incomplete reduction of N2O to N2 that would cause N2O accumulation and release to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗

A numerical study of an atomizing jet in a resonant acoustic field

By applying state-of-the-art, high-fidelity methods for compressible multiphase flows, this work features a parametric study of a turbulent liquid jet atomizing under the influence of standing acoustic waves with five different amplitude values. We perform these simulations in a semi-periodic domain to isolate interactions between acoustic and atomization processes and to emulate a pure liquid fuel spray placed at the pressure node of a resonant acoustic field. Characterization of the flow includes measurements of the mean dimensions, droplet number, and surface area of the liquid distribution, alongside qualitative depictions of the interface evolution, breakup events, and hydrodynamic fields. As acoustic forcing is provided to the flow, the added energy provokes atomization when shear would otherwise be insufficient for breakup. The magnitude of the forcing determines the rate of droplet production, which accelerates as the evolving liquid surface modifies the induced motion of the gas phase. At the nodal plane, the acoustic field produces an organizing effect on the liquid structures.

42 ENGINEERING↗