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At least 415 records · Page 23

Modeling Nanosecond-Pulsed Spark Discharge and Flame Kernel Evolution

Dilute combustion, either using exhaust gas recirculation or with excess air, is considered a promising strategy to improve the thermal efficiency of internal combustion engines. However, the dilute air-fuel mixture, especially under intensified turbulence and high-pressure conditions, poses significant challenges for ignitability and combustion stability, which may limit the attainable efficiency benefits. In-depth knowledge of the flame kernel evolution to stabilize ignition and combustion in a challenging environment is crucial for effective engine development and optimization. To date, a comprehensive understanding of ignition processes that result in the development of fully predictive ignition models usable by the automotive industry does not yet exist. Spark-ignition consists of a wide range of physics that includes electrical discharge, plasma evolution, joule-heating of gas, and flame kernel initiation and growth into a self-sustainable flame. In this study, an advanced approach is proposed to model spark-ignition energy deposition and flame kernel growth. To decouple the flame kernel growth from the electrical discharge, a nanosecond-pulsed high-voltage discharge is used to trigger spark-ignition in an optically accessible small ignition test vessel with a quiescent mixture of air and methane. Initial conditions for the flame kernel, including its thermodynamic state and species composition, are derived from a plasma-chemical equilibrium calculation. The geometric shape and dimension of the kernel are characterized using a multi-dimensional thermal plasma solver. Here, the proposed modeling approach is evaluated using a high-fidelity computational fluid dynamics procedure to compare the simulated flame kernel evolution against flame boundaries from companion Schlieren images.

42 ENGINEERING↗

Prediction and Control of Atomic Ordering in Electrodeposited Binary Alloy Films: Direct Synthesis of L10 Magnetic Phases

Permanent magnet materials are essential components in renewable energy technology, underlying, electric vehicles, hybrids, wind turbines and more. Today commercial permanent magnets based on Nd-Fe-B exhibit an energy product of ~ 400 kJ/m 3 , capable to run wind turbines efficiently. Unfortunately, the supplies of rare-earth elements are centralized, and their availability may see volatility over time. This state of affairs stimulates the search for the search for rare-earth-free permanent magnetic materials. The L1 0 crystal structure underlines an important class of chemical ordered alloys that exhibit uniaxial magnetocrystalline anisotropy. This material has been considered an excellent candidate for rare-earth-free permanent magnets. In this program, a series of systematic experiments were performed and analysed in order to understand the effect of each. In order to synthesize L 10-Fe-Ni, one has to circumvent the sluggish kinetic and the limited driving force resulted from the low order-disorder temperature (~320°C) of the system. A strategy was found to trigger a martensitic transformation from the FCC phase to one of the non-cubic phases by high-strain methods. The body-centered tetragonal Fe-Ni obtained by this strategy was considered as a precursor of L10 Fe-Ni. The formation of BCT Fe-Ni via a displacive process was also implemented at the nanoscale by using tailored AuNi@FeNi core@shell.

36 MATERIALS SCIENCE↗

Evaluating Radiation Impact on Superconducting Transmon Qubits in Above and Underground Facilities

Superconducting qubits can be sensitive to sudden energy deposits into the substrate from cosmic rays and ambient radioactivity. While previous studies have primarily focused on exploring correlated effects over time and distance due to cosmic rays, this study uniquely offers a direct comparison of a transmon qubit's response at Fermilab SQMS above-ground facilities and the deep-underground Gran Sasso Laboratory (INFN-LNGS, Italy). Despite the vastly different radiation environments, we observe a similar average qubit lifetime (T1) of approximately 80 microseconds at both sites. We then employ a fast decay detection protocol and investigate the time structure, sensitivity, and relative rates of triggered events due to radiation versus intrinsic noise. We compare the above and underground performance of several high-coherence qubits with similar designs. Our findings reveal no significant difference in events with radiation-like signatures between above-ground and underground conditions for these sapphire and niobium-based transmon qubits. This suggests that most such events are likely due to other noise sources, which predominantly contribute to single-qubit errors in contemporary transmon qubits. By exposing the qubits to gamma sources with varying activity levels, we further evaluate their response to radiation in a low-background environment. The results show that qubits can indeed detect particle impacts; however, this capability is only realized by substantially reducing other noise sources, which in turn affects detection efficiency [1].

Roy, Tanay↗

A high-capacity cathode for rechargeable K-metal battery based on reversible superoxide-peroxide conversion

Abstract As a promising low-cost energy storage device, the development of a rechargeable potassium-ion battery (KIB) is severely hindered by the limited capacity of cathode candidates. Regarded as an attractive capacity-boosting strategy, triggering the O-related anionic redox activity has not been achieved within a sealed KIB system. Herein, in contrast to the typical gaseous open K-O2 battery (O2/KO2 redox), we originally realize the reversible superoxide/peroxide (KO2/K2O2) interconversion on a KO2-based cathode. Controlled within a sealed cell environment, the irreversible O2 evolution and electrolyte decomposition (induced by superoxide anion (O2−) formation) are effectively restrained. Rationally controlling the reversible depth-of-charge at 300 mAh/g (based on the mass of KO2), no obvious cell degradation can be observed during 900 cycles. Moreover, benefitting from electrolyte modification, the KO2-based cathode is coupled with a limited amount of K-metal anode (merely 2.5 times excess), harvesting a K-metal full-cell with high energy efficiency (∼90%) and long-term cycling stability (over 300 cycles).

25 ENERGY STORAGE↗

In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device

Abstract Resistive switching (RS) devices with ultra‐low‐voltage threshold and reliable switching repeatability exhibits great potential applications in energy‐efficient data storage and neuromorphic computing. Understanding switching mechanisms at nanoscale is critical to design RS devices with improved performance. In this work, a lamella memristive device using focused ion beam (FIB) method based on the metal/TiO x /TiN/Si structure device is fabricated. In situ transmission electron microscopy (TEM) and current–voltage ( I–V ) characteristic demonstrate that the lamella device shows a volatile RS behavior with a threshold switching at ≈ ± 0.4 V. In situ scanning transmission electron microscopy (STEM) experiments with electron energy loss spectroscopy (EELS) reveal that the charge carriers such as oxygen vacancies migrate under positive/negative DC bias and modulate Schottky barriers at the top and bottom metal/semiconductor interfaces. The RS mechanism of the lamella device is based on the Schottky barriers modulation and Joule heating assisted electric field triggered thermal runaway (FTTR) occurred at the metal/semiconductor interfaces. The fundamental insights gained from this study presents a perspective on interface‐type RS devices processing and opens up new technological opportunities of fabricating ultra‐low‐energy memristive devices.

36 MATERIALS SCIENCE↗

Distributed Inference with Sparse and Quantized Communication

Here, we consider the problem of distributed inference where agents in a network observe a stream of private signals generated by an unknown state, and aim to uniquely identify this state from a finite set of hypotheses. We focus on scenarios where communication between agents is costly, and takes place over channels with finite bandwidth. To reduce the frequency of communication, we develop a novel event-triggered distributed learning rule that is based on the principle of diffusing low beliefs on each false hypothesis. Building on this principle, we design a trigger condition under which an agent broadcasts only those components of its belief vector that have adequate innovation, to only those neighbors that require such information. We prove that our rule guarantees convergence to the true state exponentially fast almost surely despite sparse communication, and that it has the potential to significantly reduce information flow from uninformative agents to informative agents. Next, to deal with finite-precision communication channels, we propose a distributed learning rule that leverages the idea of adaptive quantization. We show that by sequentially refining the range of the quantizers, every agent can learn the truth exponentially fast almost surely, while using just 1 bit to encode its belief on each hypothesis. For both our proposed algorithms, we rigorously characterize the trade-offs between communication-efficiency and the learning rate.

42 ENGINEERING↗

High resolution time interval counter

In recent years, we have developed two types of high resolution, multi-channel time interval counters. In the NIST two-way time transfer MODEM application, the counter is designed for operating primarily in the interrupt-driven mode, with 3 start channels and 3 stop channels. The intended start and stop signals are 1 PPS, although other frequencies can also be applied to start and stop the count. The time interval counters used in the NIST Frequency Measurement and Analysis System are implemented with 7 start channels and 7 stop channels. Four of the 7 start channels are devoted to the frequencies of 1 MHz, 5 MHz or 10 MHz, while triggering signals to all other start and stop channels can range from 1 PPS to 100 kHz. Time interval interpolation plays a key role in achieving the high resolution time interval measurements for both counters. With a 10 MHz time base, both counters demonstrate a single-shot resolution of better than 40 ps, and a stability of better than 5 x 10(exp -12) (sigma(sub chi)(tau)) after self test of 1000 seconds). The maximum rate of time interval measurements (with no dead time) is 1.0 kHz for the counter used in the MODEM application and is 2.0 kHz for the counter used in the Frequency Measurement and Analysis System. The counters are implemented as plug-in units for an AT-compatible personal computer. This configuration provides an efficient way of using a computer not only to control and operate the counters, but also to store and process measured data.

Zhang, Victor S.↗

Xenon doping of liquid argon in ProtoDUNE single phase

The Deep Underground Neutrino Experiment (DUNE) will be the next generation long-baseline neutrino experiment. The far detector is designed as a complex of four LAr-TPC (Liquid Argon Time Projection Chamber) modules with 17 kt of liquid argon each. The development and validation of the first far detector technology is pursued through ProtoDUNE Single Phase (ProtoDUNE-SP), a 770 t LAr-TPC at CERN Neutrino Platform. Crucial in DUNE is the photon detection system that will ensure the trigger of non-beam events — proton decay, supernova neutrino burst and BSM searches — and will improve the timing and calorimetry for neutrino beam events. Doping liquid argon with xenon is a known technique to shift the light emitted by argon (128 nm) to a longer wavelength (178 nm) to ease its detection. The largest xenon doping test ever performed in a LAr-TPC was carried out in ProtoDUNE-SP. From February to May 2020, a gradually increasing amount of xenon was injected to also compensate for the light loss due to air contamination. The response of such a large TPC has been studied using the ProtoDUNE-SP Photon Detection System (PDS) and a dedicated setup installed before the run. With the first it was possible to study the light collection efficiency with respect to the track position, while with the second it was possible to distinguish the xenon light (178 nm) from the LAr light (128 nm). The light shifting mechanism proved to be highly efficient even at small xenon concentrations (<20 ppm in mass) furthermore it allowed recovering the light quenched by pollutants. The light collection improved far from the detection plane, enhancing the photon detector response uniformity along the drift direction and confirming a longer Rayleigh scattering length for 178 nm photons, with respect to 128 nm ones. The charge collection by the TPC was monitored proving that xenon up to 20 ppm does not impact its performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Mismatching integration-enabled strains and defects engineering in LDH microstructure for high-rate and long-life charge storage

Layered double hydroxides (LDH) have been extensively investigated for charge storage, however, their development is hampered by the sluggish reaction dynamics. Herein, triggered by mismatching integration of Mn sites, we configured wrinkled Mn/NiCo-LDH with strains and defects, where promoted mass & charge transport behaviors were realized. The well-tailored Mn/NiCo-LDH displays a capacity up to 518 C g -1 (1 A g -1 ), a remarkable rate performance (78%@100 A g -1 ) and a long cycle life (without capacity decay after 10,000 cycles). We clarified that the moderate electron transfer between the released Mn species and Co 2+ serves as the pre-step, while the compressive strain induces structural deformation with promoted reaction dynamics. Theoretical and operando investigations further demonstrate that the Mn sites boost ion adsorption/transport and electron transfer, and the Mn-induced effect remains active after multiple charge/discharge processes. This contribution provides some insights for controllable structure design and modulation toward high-efficient energy storage.

25 ENERGY STORAGE↗

Integration of physiologically relevant photosynthetic energy flows into whole genome models of light‐driven metabolism

SUMMARY Characterizing photosynthetic productivity is necessary to understand the ecological contributions and biotechnology potential of plants, algae, and cyanobacteria. Light capture efficiency and photophysiology have long been characterized by measurements of chlorophyll fluorescence dynamics. However, these investigations typically do not consider the metabolic network downstream of light harvesting. By contrast, genome‐scale metabolic models capture species‐specific metabolic capabilities but have yet to incorporate the rapid regulation of the light harvesting apparatus. Here, we combine chlorophyll fluorescence parameters defining photosynthetic and non‐photosynthetic yield of absorbed light energy with a metabolic model of the pennate diatom Phaeodactylum tricornutum. This integration increases the model predictive accuracy regarding growth rate, intracellular oxygen production and consumption, and metabolic pathway usage. Through the quantification of excess electron transport, we uncover the sequential activation of non‐radiative energy dissipation processes, cross‐compartment electron shuttling, and non‐photochemical quenching as the rapid photoacclimation strategy in P. tricornutum. Interestingly, the photon absorption thresholds that trigger the transition between these mechanisms were consistent at low and high incident photon fluxes. We use this understanding to explore engineering strategies for rerouting cellular resources and excess light energy towards bioproducts in silico . Overall, we present a methodology for incorporating a common, informative data type into computational models of light‐driven metabolism and show its utilization within the design–build–test–learn cycle for engineering of photosynthetic organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Protoplanetary Disk Rings as Sites for Planetesimal Formation

Axisymmetric dust rings are a ubiquitous feature of young protoplanetary disks. These rings are likely caused by pressure bumps in the gas profile; a small bump can induce a traffic-jam-like pattern in the dust density, while a large bump may halt radial dust drift entirely. The resulting increase in dust concentration may trigger planetesimal formation by the streaming instability (SI), as the SI itself requires some initial concentration of dust. Here we present the first 3D simulations of planetesimal formation in the presence of a pressure bump modeled specifically after those seen by Atacama Large Millimeter/submillimeter Array. We place a pressure bump at the center of a large 3D shearing box, along with an initial solid-to-gas ratio of Z = 0.01, and we include both particle back-reaction and particle self-gravity. We consider millimeter-sized and centimeter-sized particles separately. For simulations with centimeter-sized particles, we find that even a small pressure bump leads to the formation of planetesimals via the SI; a pressure bump does not need to fully halt radial particle drift for the SI to become efficient. Furthermore, pure gravitational collapse via concentration in pressure bumps (such as would occur at sufficiently high concentrations and without the SI) is not responsible for planetesimal formation. For millimeter-sized particles, we find tentative evidence that planetesimal formation does not occur. If this result is confirmed at higher resolution, it could put strong constraints on where planetesimals can form. Ultimately, our results show that for centimeter-sized particles planetesimal formation in pressure bumps is extremely robust.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications

Run to run variability in parallel programs caused by floating-point non-associativity has been known to significantly affect reproducibility in iterative algorithms, due to accumulating errors. Non-reproducibility can critically affect the efficiency and effectiveness of correctness testing for stochastic programs. Recently, the sensitivity of deep learning training and inference pipelines to floating-point non-associativity has been found to sometimes be extreme. It can prevent certification for commercial applications, accurate assessment of robustness and sensitivity, and bug detection. New approaches in scientific computing applications have coupled deep learning models with high-performance computing, leading to an aggravation of debugging and testing challenges. Here we perform an investigation of the statistical properties of floating-point non-associativity within modern parallel programming models, and analyze performance and productivity impacts of replacing atomic operations with deterministic alternatives on GPUs. We examine the recently-added deterministic options in PyTorch within the context of GPU deployment for deep learning, uncovering and quantifying the impacts of input parameters triggering run to run variability and reporting on the reliability and completeness of the documentation. Finally, we evaluate the strategy of exploiting automatic determinism that could be provided by deterministic hardware, using the Groq LPUTM accelerator for inference portions of the deep learning pipeline. We demonstrate the benefits that a hardware-based strategy can provide within reproducibility and correctness efforts.

Shanmugavelu, Sanjif↗

Dynamic modeling of orographically induced precipitation

Local orography governs the triggering of cloud formation and the enhancement of processes such as condensation and hydrometeor nucleation and growth in mountainous regions. Intense, lengthy precipitation events are typical upwind of the topographic divide, with sharply decreasing magnitude and duration on the lee side. Differences in mean annual precipitation of several hundred percent between windward slopes of orographic barriers and adjacent valleys or lee side slopes are not unusual. Because much of the streamflow in areas such as the western United States is derived from mountainous areas that are remote and often poorly instrumented, modeling of orographic precipitation has important implications for water resources management. Models of orographically induced precipitation differ by their treatment of atmospheric dynamics and by the extent to which they rely on bulk parameterization of cloud and precipitation physics. Adiabatic ascent and a direct proportionality between efficiency and orographically magnified updrafts are the most frequent assumptions in orographic precipitation modeling. Space-time discretization (i.e., resolution) is a major issue because of the high spatial variability of orographic precipitation. For a specific storm, relative errors as large as 50 to 100% are common in the forecast/hindcast of precipitation intensity and can be even larger in the case of catastrophic storms. When monthly or seasonal timescales are used to evaluate model performance, the magnitude of such errors decreases dramatically, reaching values as low as 10 to 15%. Current research is focusing on the development of data assimilation techniques to incorporate radar and satellite observations, and on the development of aggregation and disaggregation methodologies to address the implications of modeling a multiscale problem at restricted spatial and temporal resolutions.

Barros, Ana Paula↗

DNA Repair-Protein Relocalization After Heavy Ion Exposure

Ionizing radiation is good at making DNA double strand breaks, and high linear energy transfer (LET) radiations such as heavy ion particles are particularly efficient. For this reason, the proteins belonging to repair systems that deal with double strand breaks are of particular interest. One such protein is Ku, a component in the non-homologous recombination repair system. The Ku protein is an abundant, heterodimeric DNA end-binding complex, composed of one 70 and one 86 kDa subunit. Ku protein binds to DNA ends, nicks, gaps, and regions of transition between single and double-stranded structure. These binding properties suggest an important role in DNA repair. The Ku antigen is important in this study because it is present in relatively large copy numbers and it is part of a double-strand-break repair system. More importantly, we consistently measure an apparent upregulation in situ that is not verified by whole-cell-lysate immunoblot measurements. This apparent upregulation is triggered by very low doses of radiation, thus showing a potentially useful high sensitivity. However, elucidation of the mechanism underlying this phenomenon is still to be done.

Metting, N. F.↗

Boosting the Activity of Pd Single Atoms by Tuning Their Local Environment on Ceria for Methane Combustion

Abstract Supported Pd single atom catalysts (SACs) have triggered great research interest in methane combustion yet with contradicting views on their activity and stability. Here, we show that the Pd SAs can take different electronic structure and atomic geometry on ceria support, resulting in different catalytic properties. By a simple thermal pretreatment to ceria prior to Pd deposition, a unique anchoring site is created. The Pd SA, taking this site, can be activated to Pd δ + (0< δ <2) that has greatly enhanced activity for methane oxidation: T 50 lowered by up to 130 °C and almost 10 times higher turnover frequency compared to the untreated catalyst. The enhanced activity of Pd δ + site is related to its oxygen‐deficient local structure and elongated interacting distance with ceria, leading to enhanced capability in delivering reactive oxygen species and decomposing reaction intermediates. This work provides insights into designing highly efficient Pd SACs for oxidation reactions.

Yang, Weiwei↗

Workflow Submit Nodes as a Service on Leadership Class Systems

DOE scientists, today, have access to high performance computing (HPC) facilities with very powerful systems that enable them to execute their computations faster, more efficiently, and at greater scales than ever before. To further their knowledge and produce new discoveries, scientists rely on workflows - sometimes very complex - that provide them with an easy way to automate, reproduce and verify their computations. However, historically, creating workflow submission environments in large HPC facilities has been cumbersome, requires expertise and many man-hours of effort due to the peculiarities, policies, and the restrictions that these systems present. In this paper we discuss the approach a large DOE facility (OLCF) is taking in order to provide containers as a service to its users. This capability is used to create Pegasus workflow management system submit nodes as a service (WSaaS) at the Oak Ridge Leadership Computing Facilities (OLCF), targeting the Summit supercomputer. This deployment builds upon the Kubernetes/Openshift cluster (Slate) that exists within OLCF’s DMZ and its automation triggers. Additionally, we evaluate our approach’s overhead and effort to deploy the solution as compared to previous solutions, such as setting up a Pegasus submission environment on OLCF’s login nodes or submitting jobs remotely via the rvGAHP.

Papadimitriou, George↗

Parameterized anomalous transport model for current-carrying collisionless plasmas in pulsed power inertial confinement fusion

Current delivery in pulsed power inertial confinement fusion is influenced by collisionless current-carrying microturbulent plasmas, which are sourced from electrode surfaces. In this setting, the lower hybrid drift instability—triggered by plasma acceleration—is a leading candidate driver of difficult-to-predict momentum and energy transport. To characterize the nonlinear state of the microturbulent plasma, a parameterized anomalous transport model is developed for the instability, with analytic formulas for anomalous collision frequency, resistivity, and species heating rates. The formulas are expressed in terms of linear-theory variables and four dimensionless parameters that characterize the macroscopic plasma state. The model is built on linear theory analysis, power law analysis, and quasilinear theory analysis, and is validated using a series of nonlinear continuum kinetic Vlasov–Poisson simulations. The theoretical and computational investigation demonstrates that the anomalous collision frequency associated with the instability can be reliably approximated, within about a factor of five or better, by the unscaled linear theory growth rate of the fastest-growing wavenumber mode. This finding enables efficient calculation of anomalous resistivity and species heating rates over a wide range of plasma conditions, resulting in improved predictive capabilities.

Complex functions↗

Boosting the Activity of Pd Single Atoms by Tuning Their Local Environment on Ceria for Methane Combustion

Supported Pd single atom catalysts (SACs) have triggered great research interest in methane combustion yet with contradicting views on their activity and stability. Here, in this paper, we show that the Pd SAs can take different electronic structure and atomic geometry on ceria support, resulting in different catalytic properties. By a simple thermal pretreatment to ceria prior to Pd deposition, a unique anchoring site is created. The Pd SA, taking this site, can be activated to Pd δ+ (0<δ<2) that has greatly enhanced activity for methane oxidation: T 50 lowered by up to 130 °C and almost 10 times higher turnover frequency compared to the untreated catalyst. The enhanced activity of Pd δ+ site is related to its oxygen-deficient local structure and elongated interacting distance with ceria, leading to enhanced capability in delivering reactive oxygen species and decomposing reaction intermediates. This work provides insights into designing highly efficient Pd SACs for oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗