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At least 1,297 records · Page 72

Phase Transition and Liquid-like Superionic Conduction in Ag 2 S

Superionic conductivity in certain polymorphs of Ag 2 S has inspired numerous concepts for materials applications, but the relationship between the structure and the mobility of silver ions remains poorly explored. In this paper, we report ab initio molecular dynamics simulations for low- (acanthite) and high-temperature (argentite) Ag 2 S polymorphs that reveal the dynamical processes, giving rise to the superionic behavior in the latter. Similarities between their sulfur sublattices enable simulations of silver ion diffusivities and pathways on essentially an equal footing. For the higher temperature polymorph, calculated temperature-dependent mean square displacements and activation energies by the nudged elastic band method show good correspondence with expectations from the experiment. In the superionic state, silver atoms diffuse in a liquid-like behavior with no preferred diffusion pathways, within the relatively stable body-centered cubic sulfur framework. Conversely, conduction in acanthite appears to depend more on the mobilities of electronic charge carriers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Highly Selective Electrocatalytic Reduction of CO 2 into Methane on Cu–Bi Nanoalloys

Methane (CH 4 ), the main component of natural gas, is one of the most valuable products facilitating energy storage via electricity conversion. However, the poor selectivity and high overpotential for CH 4 formation with metallic Cu catalysts prevent realistic applications. Introducing a second element to tune the electronic state of Cu has been widely used as an effective method to improve catalytic performance, but achieving high selectivity and activity toward CH 4 remains challenging. Here, we successfully synthesized Cu–Bi NPs, which exhibit a CH 4 Faradaic efficiency (FE) as high as 70.6% at -1.2 V versus reversible hydrogen electrode (RHE). The FE of Cu–Bi NPs has increased by approximately 25-fold compared with that of Cu NPs. DFT calculations showed that alloying Cu with Bi significantly decreases the formation energy of *COH formation, the rate-determining step, which explains the improved performance. Further analysis showed that Cu that has been partially oxidized because of electron withdrawal by Bi is the most possible active site.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The physical chemistry of solar fuels catalysis

The demonstration of effective light-driven electrochemical water splitting at the surface of a TiO 2 electrode in the seminal 1972 Honda–Fujishima publication spurred global research efforts to understand this effect and design advanced systems for solar H 2 generation from water as a carbon-free and sustainable fuel. In the 50+ years since that discovery, research investigating approaches toward the catalytic generation of the so-called “solar fuels,” i.e., not only H 2 from water but also CO 2 reduction products and NH 3 from N 2 , has expanded dramatically in scope and scale. The development of new experimental and computational methods and construction and commissioning of large-scale facilities have paved the way for important insights into the machinery of natural photosynthesis, leading to a greater understanding of the complexity of light-to-chemical energy conversion with an exquisite temporal and spatial resolution. Finally, these studies have provided the foundation for biologically inspired molecular and hybrid designs with the goal to promote the photochemical steps critical to solar fuels generation while avoiding unproductive or unnecessary pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Reinforcement Learning Approach to Augment Conventional PID Control in Nuclear Power Plant Transient Operation

The ability of nuclear reactors to operate their power conversion cycles more flexibly will enhance their value to energy grids with variable pricing. Current nuclear control systems are typically classical controllers that are often based on proportional-integral-derivative (PID) control. This paper presents a method of augmenting the existing PID control for difficult transient operations in nuclear power plants using a reinforcement learning–derived feedforward signal applied in real time. The agents, which are trained on a test thermal load-following problem, are designed to improve steam generator outlet temperature control for a range of fast load-following scenarios covering ramp rates from 9%/min to 15%/min. Several reinforcement learning algorithms were initially investigated for the training of the feedforward agents with deep Q-learning (DQN) and proximal policy optimization (PPO) networks, which were found to be the most promising. The DQN controllers utilize discrete actions, giving them a better disturbance rejection at steady state but inconsistent response to initial temperature deviations. In contrast, PPO-trained agents, which take continuous actions except for a dead zone around zero, were shown to have the best combination of high disturbance rejection at steady state and good tracking of the desired temperature value. The ability of the PPO agent was also examined, with the average time of decision making found to be on the order of 1 ms. The fault properties of the controller under the loss of the reinforcement learning agent feedforward signal were also examined. The controller showed strong performance in situations of “no-signal” faults. but was less good at handling “stuck-at” faults, where the feedforward signal remains at a set value. In both cases, however, the PID was able to successfully maintain stability, eventually returning the system to a steady state. It is hoped that this work will allow for the proposed control architecture to be examined for more difficult control problems such that it may eventually be used to adapt existing nuclear plants for more aggressive load-following on grids of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Tetraquarks made of sufficiently unequal-mass heavy quarks are bound in QCD

Tetraquarks, bound states composed of two quarks and two antiquarks, have been the subject of intense study but are challenging to understand from first principles. We apply variational and Green’s function Monte Carlo methods to compute tetraquark ground-state energies in potential nonrelativistic QCD using a wide range of color and spatial wave functions. We find no evidence for bound tetraquarks composed of equal-mass quarks and antiquarks. Conversely, we find clear evidence for the existence of bound tetraquarks for sufficiently unequal quark/antiquark mass ratios at all overall mass scales where our effective theory results are applicable. We predict the critical mass ratios for bound state formation and study tetraquark bound states’ spatial and color structure at leading order and next-to-leading order in potential nonrelativistic QCD. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Data refactoring↗

Electromagnetic cascades in pulsars

The development of pair-photon cascades initiated by high energy electrons above a pulsar polar cap is simulated numerically. The calculation uses the energy of the primary electron, the magnetic field strength, and the period of rotation as parameters, and follows the curvature radiation emitted by the primary, the conversion of this radiation to e(+)e(-) pairs in the intense fields, and the quantized synchrotron radiation by the secondary pairs. A recursive technique allows the tracing of an indefinite number of generations using a Monte Carlo method. Gamma-ray and pair spectra are calculated for cascades in different parts of the polar cap and with different acceleration models. It is found that synchrotron radiation from secondary pairs makes an important contribution to the gamma-ray spectrum above 25 MeV, and that the final gamma-ray and pair spectra are insensitive to the height of the accelerating region, as long as the acceleration of the primary electrons is not limited by radiation reaction.

Daugherty, J. K.↗

Oxygen measurements in thin ribbon silicon

The oxygen content of thin silicon ribbons grown by the dendritic web technique was measured using a modification of the ASTM method based on Fourier transform infrared spectroscopy. Web silicon was found to have a high oxygen content, ranging from 13 to 19 ppma, calculated from the absorption peak associated with interstitial oxygen and using the new ASTM conversion coefficient. The oxygen concentration changed by about 10 percent along the growth direction of the ribbon. In some samples, a shoulder was detected on the absorption peak. A similar shoulder in Czochralski grown material has been variously interpreted in the literature as due to a complex of silicon, oxygen, and vacancies, or to a phase of SiO2 developed along dislocations in the material. In the case of web silicon, it is not clear which is the correct interpretation.

Hyland, S. L.↗

Efficient Formation of Stratospheric Aerosol for Climate Engineering by Emission of Condensible Vapor from Aircraft

Recent analysis suggests that the effectiveness of stratospheric aerosol climate engineering through emission of non-condensable vapors such as SO2 is limited because the slow conversion to H2SO4 tends to produce aerosol particles that are too large; SO2 injection may be so inefficient that it is difficult to counteract the radiative forcing due to a CO2 doubling. Here we describe an alternate method in which aerosol is formed rapidly in the plume following injection of H2SO4, a condensable vapor, from an aircraft. This method gives better control of particle size and can produce larger radiative forcing with lower sulfur loadings than SO2 injection. Relative to SO2 injection, it may reduce some of the adverse effects of geoengineering such as radiative heating of the lower stratosphere. This method does not, however, alter the fact that such a geoengineered radiative forcing can, at best, only partially compensate for the climate changes produced by CO2.

Pierce, Jeffrey R.↗

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Chen, Jieyang↗

Recent Advances in Probing Electron Delocalization in Conjugated Molecules by Attached Infrared Reporter Groups for Energy Conversion and Storage

This review article reports an overview of the recent developments in the field of electron delocalization study in organic conjugated molecules by utilizing the vibration frequencies exhibited by the attached functional groups such as nitrile (–C≡N), alkyne (–C≡C–), or carbonyl (–C=O). A brief introduction to electron delocalization, methods for study, and their importance is given first, followed by the application of infrared spectroscopy in organic molecules. Details of molecules with various infrared reporter groups have been explained in respective subsections based on the functional groups. All the reported organic molecules have been structured and presented with the electron delocalization properties studied using an infrared reporter group. Finally, an outlook on this recently promising, exciting, and interesting field of probing electron delocalization using infrared reporter groups is provided.

25 ENERGY STORAGE↗

A new method for focusing and imaging X-rays and gamma-rays with diffraction crystals

Bent diffraction crystals in which the intercrystalline-plane spacing is varied as a function of position in the crystal are used to focus monochromatic radiation from a point source or parallel beam down to a point image. Conversely, radiation from a point source can be focused into an outgoing parallel beam. The Bragg angle for diffraction of monochromatic radiation will now vary as a function of position in the crystal and this new degree of freedom is used to obtain focusing and imaging of the diffracted beam. This approach to focusing and imaging is applied to the design of a large-area, high resolution X-ray telescope that is also a high resolution monochromator with the unique feature that the width of the energy increment that is diffracted can be controlled and varied during the operation of the instrument. The field can be scanned with a wide energy increment and then switched to a narrow energy increment for the high resolution work. Both transmission and reflection type diffraction crystals can be used.

Smither, R. K.↗

The conversion of lignocellulosics to fermentable sugars - A survey of current research and applications to CELSS

This report provides an overview options for converting lignocellulosics into fermentable sugars in CELSS. A requirement for pretreatment is shown. Physical-chemical and enzymatic hydrolysis processes for producing fermentable sugars are discussed. At present physical-chemical methods are the simplest and best characterized options, but enzymatic processes will be the likely method of choice in the future. The use of pentose sugars by microorganisms to produce edibles is possible. The use of mycelial food production on pretreated but not hydrolyzed lignocellulosics is also possible. Simple trade-off analyses to regenerate waste lignocellulosics for two pathways are made, one of which is compared to complete oxidation.

Petersen, Gene R.↗

Data for Process Strategies for Recovery of Sugars, Lipids, and Lignin from Oilcane Bagasse Using Natural Deep Eutectic Solvents (NADES)

Sugarcane is being enhanced as a bioenergy crop by engineering it to accumulate and store lipids along with polymeric sugars in vegetative tissues. However, there is no existing process that allows for processing this new crop to recover both lipid and cellulosic sugars from the oilcane bagasse. Therefore, a comprehensive investigation of two pretreatment methods—natural deep eutectic solvents (NADES) and chemical-free hydrothermal pretreatment (HT) was conducted to judge their suitability for recovering fermentable sugars, lipids, and lignin from bagasse. Two NADES, i.e., choline chloride: lactic acid (ChCl:LA) and betaine: lactic acid (BT:LA) were prepared using a 1:2 M ratio and were evaluated for pretreatment of oilcane bagasse at 10, 20, and 50 % (w/w) solids, followed by enzymatic hydrolysis at 10 % (w/w) solids. Notably, ChCl:LA NADES treatment at 10 % (w/w) solids at 140 °C for 2 h, solubilized 78.8 % of lignin and 80.4 % of hemicellulose and allowed 82.7 % enzymatic conversion of glucans to glucose. In contrast, HT pretreatment removed approximately 87.6 % of the hemicellulose and provided an enzymatic glucose yield of 69.7 %. Furthermore, ChCl:LA operated at 50 % solids loading the enriched lipids 2.6-fold (9.2 wt%) in recovered solids compared to HT (6.4 %) and BT:LA (5.1 %) pretreatment processes. NMR-HSQC and GPC analysis showed that ChCl:LA also cleaved the most lignin β–O–4 linkages and demonstrated lower molecular weight compared to HT. This study demonstrates that NADES pretreatment is an effective green processing method for recovering lipids, sugars, and lignin from bioenergy crops at high solid loading (50 % w/w) within the context of an integrated biorefinery.

Conversion↗

Electrocatalysis in Alkaline Media and Alkaline Membrane-Based Energy Technologies

Hydrogen energy-based electrochemical energy conversion technologies offer the promise of enabling a transition of the global energy landscape from fossil fuels to renewable energy. Here, we present a comprehensive review of the fundamentals of electrocatalysis in alkaline media and applications in alkaline-based energy technologies, particularly alkaline fuel cells and water electrolyzers. Anion exchange (alkaline) membrane fuel cells (AEMFCs) enable the use of nonprecious electrocatalysts for the sluggish oxygen reduction reaction (ORR), relative to proton exchange membrane fuel cells (PEMFCs), which require Pt-based electrocatalysts. However, the hydrogen oxidation reaction (HOR) kinetics is significantly slower in alkaline media than in acidic media. Understanding these phenomena requires applying theoretical and experimental methods to unravel molecular-level thermodynamics and kinetics of hydrogen and oxygen electrocatalysis and, particularly, the proton-coupled electron transfer (PCET) process that takes place in a proton-deficient alkaline media. Extensive electrochemical and spectroscopic studies, on single-crystal Pt and metal oxides, have contributed to the development of activity descriptors, as well as the identification of the nature of active sites, and the rate-determining steps of the HOR and ORR. Among these, the structure and reactivity of interfacial water serve as key potential and pH-dependent kinetic factors that are helping elucidate the origins of the HOR and ORR activity differences in acids and bases. Additionally, deliberately modulating and controlling catalyst-support interactions have provided valuable insights for enhancing catalyst accessibility and durability during operation. The design and synthesis of highly conductive and durable alkaline membranes/ionomers have enabled AEMFCs to reach initial performance metrics equal to or higher than those of PEMFCs. We emphasize the importance of using membrane electrode assemblies (MEAs) to integrate the often separately pursued/optimized electrocatalyst/support and membranes/ionomer components. Operando/in situ methods, at multiscales, and ab initio simulations provide a mechanistic understanding of electron, ion, and mass transport at catalyst/ionomer/membrane interfaces and the necessary guidance to achieve fuel cell operation in air over thousands of hours. We hope that this Review will serve as a roadmap for advancing the scientific understanding of the fundamental factors governing electrochemical energy conversion in alkaline media with the ultimate goal of achieving ultralow Pt or precious-metal-free high-performance and durable alkaline fuel cells and related technologies.

30 DIRECT ENERGY CONVERSION↗

The nth-plant scenario for blended feedstock conversion and preprocessing nationwide: biorefineries and depots

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Defining the future location and supply logistics of conversion plants is imperative to ultimately transform the nation’s renewable biomass resources into cost-competitive, high-performance feedstock for production of biofuels and bioproducts. Since the US has put restrictions on production levels of conventional biofuels from edible resources, the nation needs to plan for the widespread accessibility and development of the cellulosic biofuel scenario. Conventional feedstock supply systems will be unable to handle cellulosic biomass nationwide, making it essential to expand the industry with an advanced feedstock supply system incorporating a distributed network of preprocessing depots and conversion plants, or biorefineries. Current studies are mostly limited to designing supply systems for specific regions of the country. We developed a national database with potential locations for depots and biorefineries to meet the nation’s target demand of cellulosic biofuel. Blended feedstock with switchgrass and corn stover (harvested by either a two- or three-pass method) are considered in a Mixed Integer Linear Programming model to deliver on-spec biomass that considers both, a desired quantity and quality at the biorefinery. A total delivered feedstock cost that is less than $79.07/dt (2016$) is evaluated for years 2022, 2030, and 2040. In 2022, 124 depots and 59 biorefineries could be supplied with 42.8 million dt of corn stover and switchgrass. In 2030 and 2040, the total accessible biomass could increase to 215% and 393% respectively when compared to 2022. However, an $8/dry tons reduction in targeted delivery cost could reduce total accessible biomass by 67%. Kansas, Nebraska, South Dakota and Texas were identified as potential states with a strong biofuel economy given that they had six or more biorefineries located in all scenarios. In some scenarios, Colorado, Alabama, Georgia, Minnesota, Mississippi and South Carolina would greatly benefit from a depot network as these could only deliver to a biorefinery in a nearby state. To elaborate the impact of a nationwide consideration, the findings were compared with existing literature for different US regions. We also present results for biorefinery capacities that are double, triple, and quadruple in size.

09 BIOMASS FUELS↗

Dual-Fuel Ammonia Equivalence Ratio Sweep Data

Ammonia (NH3) has garnered significant interest as an alternative fuel for meeting international emissions reduction mandates in sectors with high weight and distance requirements, such as shipping. Technical barriers and unanswered questions remain on the combustion strategies that can maximize ammonia utilization and minimize emissions. Prior research studies at the US Department of Energy’s Oak Ridge National Laboratory have shown strong performance with NH3 under dual-fuel mode using conventional diesel combustion (CDC) manifold air pressure settings. Diesel airflow was initially used to simplify retrofitting (no turbocharger modification), which resulted in air-fuel equivalence ratios (λ) greater than 1.5. To characterize potential improvements in dual-fuel NH3 combustion performance at richer in-cylinder conditions, a global λ sweep compared the use of early (E-pilot) and late (L-pilot) single diesel injections. The experiments were conducted at 1200 RPM and 12.8 ± 0.2 bar (75 % load), and λ was varied by decreasing the commanded air flow to the engine at greater than 90 % ammonia energy substitution level. A diesel injection timing sweep was conducted for both the injection strategies at fixed λ, and the timing with the lowest engine-out N2O emissions was identified. The results indicated an optimal balance between CO2,eq and thermal efficiency benefits both E-pilot and L-pilot injection strategy cases compared with CDC at a λ of 1.4. The indicated nitrogen-based emissions exhibited a strong correlation to the ratio of CA5–50 and ignition delay for L-pilot, but no apparent trend emerged for the E-pilot injection strategy at the tested boundary conditions. This dataset includes the raw experimental data and documentation of the experiment conditions and methods.

30 DIRECT ENERGY CONVERSION↗