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At least 505 records · Page 28

Detailed biomass fast pyrolysis kinetics integrated to computational fluid dynamic (CFD) and discrete element modeling framework: Predicting product yields at the bench-scale

Fast pyrolysis is an intricate process due to the variability and anisotropy of lignocellulosic biomass and the complicated chemistry and physics during conversion in a bubbling fluidized bed reactor (BFBR). The complexity of biomass fast pyrolysis lends itself well to computational fluid dynamics (CFD) and discrete element (DEM) analysis, which promises to reduce experimental time and its associated cost. This work investigated switchgrass fast pyrolysis simulated by computational fluid dynamics coupled with a discrete element method to track individual reacting biomass particles throughout a bench-scale BFBR reactor. We accounted for the fast pyrolysis chemistry through a comprehensive reaction scheme with secondary cracking reactions. We performed a three-step reduction for secondary cracking reactions to convert the full cracking scheme into a reduced scheme easily incorporated into our model. We assessed the impact of operational conditions on the steady-state yields of liquid bio-oil, non-condensable gases (NCG), at 550 °C over a range of fluidization numbers (2 – 6 Umf), reported as a ratio to the minimum fluidization velocity (Umf). At steady-state, the volatile bio-oil yield had a range of 49.3–50.4 wt%. Levoglucosan was the primary volatile component present with 21 wt% of the bio-oil while water was the second largest with 20 wt%. The reduction of the secondary reaction schemes did not appreciably affect the overall yields of switchgrass pyrolysis compared to the full secondary scheme.

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Influence of pilot-fuel mixing on the spatio-temporal progression of two-stage autoignition of diesel-sprays in low-reactivity ambient fuel-air mixture

The spatial and temporal locations of autoignition for direct-injection compression-ignition engines depend on fuel chemistry, temperature, pressure, and mixing trajectories in the fuel jets. Dual-fuel systems can provide insight into both fuel-chemistry and physical effects by varying fuel reactivities and engine operating conditions. In this context, the spatial and temporal progression of two-stage autoignition of a diesel-fuel surrogate, n-heptane, in a lean-premixed charge of synthetic natural-gas (NG) and air is imaged in an optically accessible heavy-duty diesel engine. The lean-premixed charge of NG is prepared by fumigation upstream of the engine intake manifold. Optical diagnostics include high-speed (15kfps) cool-flame chemiluminescence-imaging as an indicator of low-temperature heat-release (LTHR) and OH* chemiluminescence-imaging as an indicator high-temperature heat-release (HTHR). NG prolongs the ignition delay of the pilot fuel and increases the combustion duration. Zero-dimensional chemical-kinetics simulations provide further understanding by replicating a Lagrangian perspective for mixtures evolving along streamlines originating either at the fuel nozzle or in the ambient gas, for which the pilot-fuel concentration is either decreasing or increasing, respectively. The zero-dimensional simulations predict that LTHR initiates most likely on the air streamlines before transitioning to HTHR, either on fuel-streamlines or on air-streamlines in regions of near-constant φ. Due to the relatively short pilot-fuel injection-durations, the transient increase in entrainment near the end of injection (entrainment wave) is important for quickly creating auto-ignitable mixtures. To achieve desired combustion characteristics, e.g., multiple ignition-kernels and favorable combustion phasing and location (e.g., for reducing wall heat-transfer or optimizing charge stratification), adjusting injection parameters could tailor mixing trajectories to offset changes in fuel ignition chemistry.

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Cometary comae

The basis of our knowledge about the structure and composition of a comet nucleus is examined. Such knowledge is inferred from observations of the cometary atmosphere (coma). However, photodissociation, photoionization, and chemistry destroy the mother molecules evaporating from the nucleus. To extract the primary information, the chemical kinetics and the physics of the coma are modeled with a computer and the results are compared with coma observations. The physics and chemistry for a dust free coma are described taking into account energy balance, multi-fluid flow for fast atomic and molecular hydrogen and the bulk fluid, and the transition from a collision dominated inner region to the free molecular flow outer region. Special attention is paid to the molecular data requirements for the current modeld and for extended models which will include solar wind interaction and dust. Such models are an important tool in support of the Giotto mission to Halley's comet, in the analysis and interpretation of coma observations, and in the understanding of the earliest history of the solar system.

Huebner, W. F.↗

Recent advances in understanding the role of solvated electrons at the plasma-liquid interface of solution-based gas discharges

The solvated electron is one of the strongest known reducing species. Solution-based glow discharges, in which a gaseous discharge is ignited between a metal electrode and a liquid surface, are an emerging spectrochemical source in analytical atomic emission and mass spectrometry. In other disciplines, the similar setup is called plasma electrolysis and can be used for materials and chemical synthesis. Regardless of its name and application areas, electrons are injected into a solution and the underlying physics and chemistry in these systems is complex. Furthermore, quantitative understanding is necessary in order to maximize performance for chemical and materials applications. In this paper, we summarize the state-of-the-art in plasma-liquid interactions involving solvated electrons, with a particular emphasis on the work by our group, and highlight potential areas of future study to both fill in knowledge gaps and drive applications forward.

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Coupled Cluster Downfolding Methods: the effect of double commutator terms on the accuracy of ground-state energies

Downfolding coupled cluster (CC) techniques have recently been introduced into quantum chemistry as a tool for the dimensionality reduction of the many-body quantum problem. As opposed to earlier formulations in physics and chemistry based on the concept of effective Hamiltonians, the appearance of the downfolded Hamiltonians is a natural consequence of the single-reference exponential parametrization of the wave function. In this paper, we discuss the impact of higher-order terms originating in double commutators. In analogy to previous studies, we consider the case when only one- and two-body interactions are included in the downfolded Hamiltonians. We demonstrate the efficiency of the many-body expansions involving single and double commutators for the unitary extension of the downfolded Hamiltonians on the example of the beryllium atom, and bond-breaking processes in the Li2 and H2O molecules. For the H2O system, we also analyze energies obtained with downfolding procedures as functions of the active space size.

quantum computing, quantum algorithms, electronic ↗

Catalytic Upgrading of Bio-based Furfural to 1,5-Pentanediol: A New Renewable Monomer for the Coatings Industry

This report summarizes the results of a collaborative effort between Oak Ridge National Laboratory (ORNL) and Pyran™ Inc. to utilize modeling capabilities developed by the CCPC (Consortium for Computational Physics and Chemistry) to assist Pyran in scaling up its proprietary process for thermocatalytic conversion of furfural to 1,5 pentanediol (PDO). Pyran’s bio-based PDO is a direct replacement for petroleum-based PDO and 1,6 hexanediol (HDO) currently used in polymers, additives, coatings, adhesives and sealants. The current market is in excess of $1B/yr. According to Pyran, their production process results in 95+% reduction in fossil CO 2 at lower production costs compared to the existing petroleum-based routes for PDO & HDO. Other chemicals based on intermediates from this process have current markets in excess of $10B/yr.

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DFO Computational Modeling Project - Catalytic Upgrading of Bio-based Furfural to 1,5-Pentanediol: A New Renewable Monomer for the Coatings Industry (Final Report)

This report summarizes the results of a collaborative effort between Oak Ridge National Laboratory (ORNL) and Pyran™ Inc. to utilize modeling capabilities developed by the CCPC (Consortium for Computational Physics and Chemistry) to assist Pyran in scaling up its proprietary process for thermocatalytic conversion of furfural to 1,5 pentanediol (PDO). Pyran’s bio-based PDO is a direct replacement for petroleum-based PDO and 1,6 hexanediol (HDO) currently used in polymers, additives, coatings, adhesives and sealants. The current market is in excess of $\$$1B/yr. According to Pyran, their production process results in 95+% reduction in fossil CO 2 at lower production costs compared to the existing petroleum-based routes for PDO & HDO. Other chemicals based on intermediates from this process have current markets in excess of $\$$10B/yr.

36 MATERIALS SCIENCE↗

Triple Excitations in Green’s Function Coupled Cluster Solver for Studies of Strongly Correlated Systems in the Framework of Self-Energy Embedding Theory

Embedding theories became important approaches used for accurate calculations of both molecules and solids. In these theories, a small chosen subset of orbitals is treated with an accurate method, called an impurity solver, capable of describing higher correlation effects. Ideally, such a chosen fragment should contain multiple orbitals responsible for the chemical and physical behavior of the compound. Handling a large number of chosen orbitals presents a very significant challenge for the current generation of solvers used in the physics and chemistry community. Here, we develop a Green’s function coupled cluster singles doubles and triples (GFCCSDT) solver that can be used for a quantitative description in both molecules and solids. This solver allows us to treat orbital spaces that are inaccessible to other accurate solvers. At the same time, GFCCSDT maintains high accuracy of the resulting self-energy. Moreover, in conjunction with the GFCCSD solver, it allows us to test the systematic convergence of computational studies. Developing the CC family of solvers paves the road to fully systematic Green’s function embedding calculations in solids. In this paper, we focus on the investigation of GFCCSDT self-energies for a strongly correlated problem of SrMnO 3 solid. Subsequently, we apply this solver to solid MnO showing that an approximate variant of GFCCSDT is capable of yielding a high accuracy orbital resolved spectral function.

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Electronic Structure of the Complete Series of Gas-Phase Manganese Acetylacetonates by X-ray Absorption Spectroscopy

Metal centers in transition metal–ligand complexes occur in a variety of oxidation states causing their redox activity and therefore making them relevant for applications in physics and chemistry. The electronic state of these complexes can be studied by X-ray absorption spectroscopy, which is, however, due to the complex spectral signature not always straightforward. Here, we study the electronic structure of gas-phase cationic manganese acetylacetonate complexes Mn(acac) 1–3 + using X-ray absorption spectroscopy at the metal center and ligand constituents. The spectra are well reproduced by multiconfigurational wave function theory, time-dependent density functional theory as well as parameterized crystal field and charge transfer multiplet simulations. This enables us to get detailed insights into the electronic structure of ground-state Mn(acac) 1–3 + and extract empirical parameters such as crystal field strength and exchange coupling from X-ray excitation at both the metal and ligand sites. By comparison to X-ray absorption spectra of neutral, solvated Mn(acac) 2,3 complexes, we also show that the effect of coordination on the L 3 excitation energy, routinely used to identify oxidation states, can contribute about 40–50% to the observed shift, which for the current study is 1.9 eV per oxidation state.

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Information-Theoretic Bounds on Quantum Advantage in Machine Learning

We study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments. The experiments depend on an input parameter x and involve execution of a (possibly unknown) quantum process E. Our figure of merit is the number of runs of E required to achieve a desired prediction performance. We consider classical ML models that perform a measurement and record the classical outcome after each run of E, and quantum ML models that can access E coherently to acquire quantum data; the classical or quantum data are then used to predict the outcomes of future experiments. We prove that for any input distribution D(x), a classical ML model can provide accurate predictions on average by accessing E a number of times comparable to the optimal quantum ML model. In contrast, for achieving an accurate prediction on all inputs, we prove that the exponential quantum advantage is possible. For example, to predict the expectations of all Pauli observables in an n-qubit system ρ, classical ML models require 2 Ω(n) copies of ρ, but we present a quantum ML model using only O(n) copies. Our results clarify where the quantum advantage is possible and highlight the potential for classical ML models to address challenging quantum problems in physics and chemistry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Structural and spectroscopic characterization of an einsteinium complex

The transplutonium elements (atomic numbers 95–103) are a group of metals that lie at the edge of the periodic table. As a result, the patterns and trends used to predict and control the physics and chemistry for transition metals, main-group elements and lanthanides are less applicable to transplutonium elements. Furthermore, understanding the properties of these heavy elements has been restricted by their scarcity and radioactivity. This is especially true for einsteinium (Es), the heaviest element on the periodic table that can currently be generated in quantities sufficient to enable classical macroscale studies. Here we characterize a coordination complex of einsteinium, using less than 200 nanograms of 254 Es (with half-life of 275.7(5) days), with an organic hydroxypyridinone-based chelating ligand. X-ray absorption spectroscopic and structural studies are used to determine the energy of the L 3 -edge and a bond distance of einsteinium. Photophysical measurements show antenna sensitization of EsIII luminescence; they also reveal a hypsochromic shift on metal complexation, which had not previously been observed in lower-atomic-number actinide elements. Here, these findings are indicative of an intermediate spin–orbit coupling scheme in which j–j coupling (whereby single-electron orbital angular momentum and spin are first coupled to form a total angular momentum, j) prevails over Russell–Saunders coupling. Together with previous actinide complexation studies, our results highlight the need to continue studying the unusual behaviour of the actinide elements, especially those that are scarce and short-lived.

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Spatially-Resolved Characterization Techniques and Their Implications for Nuclear Debris Formation.

Debris from nuclear tests has a complex formation process and can inform multiple fields of study such as geology, atmospheric science, shock physics, and chemistry under extreme conditions. Macroscopic nuclear debris forms as the result of fireball interaction with surrounding materials (e.g., structural and environmental component), which rapidly undergo melting and vaporization followed by condensation, convective/diffusive mixing, and solidification over the course of seconds. In atmospheric events, some of this material may disperse over long distances, but much of the material is deposited close-in to ground zero, often in multicomponent, partially (or entirely) amorphous debris formations. During the U.S. nuclear testing program, this material was collected and analyzed, particularly for radionuclide composition. Fallout formation models were developed from nuclear test data based on such radionuclide compositional analyses. These models were not just used to understand fallout dispersion (i.e. the spread of radioactivity over geographical regions) but also guide radiochemical interpretations of historical nuclear tests.6 Developments in analytical techniques over the past several decades have made it possible to make new analyses on historical debris, some of which may be more than a half-century old. For example, inductively-coupled plasma mass spectrometry (ICP-MS) has been used to look at the trace elements in glassy fallout material from aboveground nuclear tests (including the Trinity test). Advanced analyses using X-ray absorption allowed for the measurement of oxidation state of fallout constituents, including actinides. The ability to measure trace actinides and their subsequent oxidation state is important to understanding how the surrounding environment may have influenced the resultant fallout composition and may have implications for why certain fractionation trends have been observed. Here we present data from historic nuclear test debris illustrating the power of spatially resolved methods to connect interaction of the near-field environment with the explosion and provide new insights into nuclear debris formation.

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Sulfur mass loading of the atmosphere from volcanic eruptions: Calibration of the ice core record on basis of sulfate aerosol deposition in polar regions from the 1982 El Chichon eruption

Major volcanic eruptions disperse large quantities of sulfur compound throughout the Earth's atmosphere. The sulfuric acid aerosols resulting from such eruptions are scavenged by snow within the polar regions and appear in polar ice cores as elevated acidity layers. Glacio-chemical studies of ice cores can, thus, provide a record of past volcanism, as well as the means for understanding the fate of volcanic sulfur in the atmosphere. The primary objectives of this project are to study the chemistry and physical properties of volcanic fallout in a Greenland Ice Core in order to evaluate the impact of the volcanic gases on the atmospheric chemistry and the total atmospheric mass of volcanic aerosols emitted by major volcanic eruptions. We propose to compare the ice core record to other atmospheric records performed during the last 10 years to investigate transport and deposition of volcanic materials.

Sigurdsson, Haraldur↗

Vibronic mixing enables ultrafast energy flow in light-harvesting complex II

Since the discovery of quantum beats in the two-dimensional electronic spectra of photosynthetic pigment-protein complexes over a decade ago, the origin and mechanistic function of these beats in photosynthetic light-harvesting has been extensively debated. The current consensus is that these long-lived oscillatory features likely result from electronic-vibrational mixing, however, it remains uncertain if such mixing significantly influences energy transport. Here, we examine the interplay between the electronic and nuclear degrees of freedom (DoF) during the excitation energy transfer (EET) dynamics of light-harvesting complex II (LHCII) with two-dimensional electronic-vibrational spectroscopy. Particularly, we show the involvement of the nuclear DoF during EET through the participation of higher-lying vibronic chlorophyll states and assign observed oscillatory features to specific EET pathways, demonstrating a significant step in mapping evolution from energy to physical space. These frequencies correspond to known vibrational modes of chlorophyll, suggesting that electronic-vibrational mixing facilitates rapid EET over moderately size energy gaps.

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A reflection on lithium-ion battery cathode chemistry

Abstract Lithium-ion batteries have aided the portable electronics revolution for nearly three decades. They are now enabling vehicle electrification and beginning to enter the utility industry. The emergence and dominance of lithium-ion batteries are due to their higher energy density compared to other rechargeable battery systems, enabled by the design and development of high-energy density electrode materials. Basic science research, involving solid-state chemistry and physics, has been at the center of this endeavor, particularly during the 1970s and 1980s. With the award of the 2019 Nobel Prize in Chemistry to the development of lithium-ion batteries, it is enlightening to look back at the evolution of the cathode chemistry that made the modern lithium-ion technology feasible. This review article provides a reflection on how fundamental studies have facilitated the discovery, optimization, and rational design of three major categories of oxide cathodes for lithium-ion batteries, and a personal perspective on the future of this important area.

Science & Technology - Other Topics↗

Carbon clusters formed from shocked benzene

Abstract Benzene (C 6 H 6 ), while stable under ambient conditions, can become chemically reactive at high pressures and temperatures, such as under shock loading conditions. Here, we report in situ x-ray diffraction and small angle x-ray scattering measurements of liquid benzene shocked to 55 GPa, capturing the morphology and crystalline structure of the shock-driven reaction products at nanosecond timescales. The shock-driven chemical reactions in benzene observed using coherent XFEL x-rays were a complex mixture of products composed of carbon and hydrocarbon allotropes. In contrast to the conventional description of diamond, methane and hydrogen formation, our present results indicate that benzene’s shock-driven reaction products consist of layered sheet-like hydrocarbon structures and nanosized carbon clusters with mixed sp 2 - sp 3 hybridized bonding. Implications of these findings range from guiding shock synthesis of novel compounds to the fundamentals of carbon transport in planetary physics.

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