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At least 1,315 records · Page 73

Design and engineering challenges of a multi-energy hard x-ray camera for long-pulse profile measurements at WEST tokamak

The WEST tokamak has recently been prepared for long pulse operation with a water-cooled full first wall. Heating is provided by radiofrequency systems, including Lower Hybrid Current Drive (LHCD). The Princeton Plasma Physics Laboratory has developed a multi-energy hard x-ray camera for profile measurements at WEST. The camera is based on a new generation of 2D pixel array detectors that allow the energy threshold to be independently set for each pixel. The diagnostic will provide spatial, temporal and energy resolved measurements of the hard x-ray emission from the full plasma cross-section, investigating several physical quantities such as the electron temperature from continuum emission, the fast electron tail density produced by radiofrequency current drive and runaway electrons, as well as characteristic tungsten x-rays due to beam-target emission at the edge. Overall, this work describes the engineering challenges that the WEST long pulse scenario poses for this diagnostic and how the design addresses and solves them. Vacuum, thermal stress and heat transfer calculations are presented and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Control-oriented core-SOL-divertor model to address integrated burn and divertor control challenges in ITER

The real-time regulation of a burning plasma’s temperature and density, or burn control, will be necessary to produce high fusion power in future tokamaks like ITER. This is made more challenging due to the plasma’s nonlinear characteristics and the interdependence between the core-plasma and edge-plasma regions. For example, a raising plasma temperature leads to increasing reactivity and therefore to more alpha-particle heating, which further increases temperature. Furthermore, a raise of the fusion power increases the heat flow through the scrape-off-layer (SOL), which can compromise the integrity of the divertor without proper safeguards. For control design, a model-based approach is attractive because it can directly incorporate the nonlinear, coupled, burning-plasma dynamics into the design. To facilitate this design approach, a control-oriented core-SOL-divertor (CSD) model is presented in this work. In this CSD model, a core-plasma model captures the nonlinear dynamics of the core’s density and temperature, and a SOL-divertor model defines the plasma conditions at the separatrix and divertor including the heat load on the target plates. The core-plasma and SOL-divertor models are coupled through the exchange of various variables. In particular, the SOL-divertor model yields the separatrix temperature and the influx of recycled particles into the core-plasma. Further, these variables influence the power and particle balances captured by the core-plasma model. In return, the core-plasma model determines the intensity of the heat and particles fluxes across the separatrix, and this outflow strongly impacts the SOL-divertor model. Therefore, the power and density of the core-plasma, which can be readily modulated through external heating systems and pellet injection, can be viewed as control knobs for the SOL-divertor region in addition to the gas puffing. In simulations of the CSD model, it is demonstrated how external actuation can be utilized to meet burn control and divertor control objectives simultaneously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum-centric supercomputing for materials science: A perspective on challenges and future directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. Here in this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

36 MATERIALS SCIENCE↗

Virioplankton assemblages from challenger deep, the deepest place in the oceans

Hadal ocean biosphere, that is, the deepest part of the world’s oceans, harbors a unique microbial community, suggesting a potential uncovered co-occurring virioplankton assemblage. Herein, we reveal the unique virioplankton assemblages of the Challenger Deep, comprising 95,813 non-redundant viral contigs from the surface to the hadal zone. Almost all of the dominant viral contigs in the hadal zone were unclassified, potentially related to Alteromonadales and Oceanospirillales. 2,586 viral auxiliary metabolic genes from 132 different KEGG orthologous groups were mainly related to the carbon, nitrogen, sulfur, and arsenic metabolism. Lysogenic viral production and integrase genes were augmented in the hadal zone, suggesting the prevalence of viral lysogenic life strategy. Abundant rve genes in the hadal zone, which function as transposase in the caudoviruses, further suggest the prevalence of viral-mediated horizontal gene transfer. This study provides fundamental insights into the virioplankton assemblages of the hadal zone, reinforcing the necessity of incorporating virioplankton into the hadal biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗

Atmospheric clusters to nanoparticles: Recent progress and challenges in closing the gap in chemical composition

Aerosol nanoclusters (AN), defined here as molecular aggregates suspended in a gas with dimensions between 2 and 10 nm, are the link between substances that we think of as molecules, or the “gas phase,” and those that we consider as particles, or the “condensed phase.” The ability to measure and model the physical and chemical properties of size-resolved AN, which at present is rudimentary at best, is crucial for understanding how particles form and evolve in a number of environments that are natural or influenced by human activities. This review describes the current state-of-the-art for measuring and modeling the size-resolved composition of atmospheric AN. We focus specifically on instruments, many relying on mass spectrometry, that show promise for closing the measurement gap under atmospherically relevant conditions by increasing the size of measurable gas-phase clusters (bottom-up approaches) and by decreasing the size of measurable nanoparticles (top-down approaches). Theoretical methods for predicting AN composition have similarly relied on bottom-up approaches that extend the accuracy of quantum chemistry calculations to larger molecular systems, as well as top-down approaches that correct bulk composition aerosol models for size-dependent properties such as viscosity and volatility. Finally, current measurement and modeling challenges that must be overcome in order to close the gap are discussed.

42 ENGINEERING↗

Process mining for healthcare: Characteristics and challenges

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

59 BASIC BIOLOGICAL SCIENCES↗

Oxygen evolution electrocatalysis using mixed metal oxides under acidic conditions: Challenges and opportunities

Shaping the energy landscape through development of more efficient electrochemical energy conversion and storage devices requires significant advancements in the catalysis of key electrochemical processes involving oxygen. This is especially the case for the oxygen evolution reaction (OER), which is largely challenged by the cost-ineffectiveness of the best performing electrocatalysts (i.e., Ru, Ir), along with their limited stability under acidic conditions. This presents a roadblock in the development of robust acid-based polymer exchange membrane electrochemical systems, currently the most advanced technologies for electrochemical energy conversion. Approaches such as dilution of Ru/Ir into flexible mixed metal oxide frameworks have been used as alternative strategies in designing robust OER electrocatalysts. Herein, we discuss the state of research in this area and detail the effect of the composition and structure of mixed metal oxides on their acidic OER activity and stability. Future directions for developing mixed metal oxide electrocatalysts suitable for acidic electrochemical environments are devised.

36 MATERIALS SCIENCE↗

Electronic coarse graining enhances the predictive power of molecular simulation allowing challenges in water physics to be addressed

One key factor that limits the predictive power of molecular dynamics simulations is the accuracy and transferability of the input force field. Force fields are challenged by heterogeneous environments, where electronic responses give rise to biologically important forces such as many-body polarisation and dispersion. The importance of polarisation in the condensed phase was recognised early on, as described by Cochran in 1959 [Philosophical Magazine 4 (1959) 1082–1086] [32]. Currently in molecular simulation, dispersion forces are treated at the two-body level and in the dipole limit, although the importance of three-body terms in the condensed phase was demonstrated by Barker in the 1980s [Phys. Rev. Lett. 57 (1986) 230–233] [72]. One approach for treating both polarisation and dispersion on an equal basis is to coarse grain the electrons surrounding a molecular moiety to a single quantum harmonic oscillator (cf. Hirschfelder, Curtiss and Bird 1954 [The Molecular Theory of Gases and Liquids (1954)] [37]). The approach, when solved in strong coupling beyond the dipole limit, gives a description of long-range forces that includes two- and many-body terms to all orders. In the last decade, the tools necessary to implement the strong coupling limit have been developed, culminating in a transferable model of water with excellent predictive power across the phase diagram. Transferability arises since the environment automatically identifies the important long range interactions, rather than the modeler through a limited set of expressions. Here, we discuss the role of electronic coarse-graining in predictive multiscale materials modelling and describe the first implementation of the method in a general purpose molecular dynamics software: QDO-MD. - Highlights: • Electronic coarse graining unites many-body dispersion and polarisation beyond the dipole limit. • It consists of replacing the electrons of a molecule using a quantum harmonic oscillator, called a Quantum Drude Oscillator. • We present the first general implementation of Quantum Drude Oscillators in the molecular dynamics package QDO-MD. • We highlight the successful construction of a new, transferable molecular model of water: QDO-water. - Graphical abstract:.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Challenges and opportunities in plasma-activated reactions of CO 2 with light alkanes

We present upgrading CO 2 with surplus light alkanes to value-added chemicals using one-step plasma-activated processes under mild conditions, where opportunities and challenges for improving product selectivity focus on understanding reaction pathways, decoupling and benchmarking plasma and catalyst roles in reactions, tuning catalyst structural and electronic properties under plasma activation, and developing in situ characterization techniques.

03 NATURAL GAS↗

Challenges in Kinetic modeling of ammonia pyrolysis

Ammonia pyrolysis reactions have implications for its ignition and oxidation in engines and gas turbines. In the present work, the chemistry of ammonia pyrolysis is investigated by kinetic modeling and theory. Rate constants for key reactions are carefully evaluated based on available experimental and theoretical results. The high pressure limit k1,∞ for NH 2 + H (+M) ⇄ NH 3 (+M) (R1) is calculated to be essentially the collision frequency, indicating that dissociation of ammonia in combustion processes will be at or close to the low pressure limit even at engine and gas turbine conditions. The chemical kinetic model is validated against reported shock tube measurements of NH 3 , NH 2 , and NH in ammonia pyrolysis. Predictions are in good agreement with observations for dilute conditions (≤ 0.5% NH 3 ), but the model appears to underpredict the NH 3 consumption rate at longer times in less dilute mixtures. At short reaction times, thermal dissociation of NH3, together with the NH 3 + H reaction, controls conversion. At longer times, secondary reactions involving NH 2 and NH become important due to their impact on the radical pool. Predictions become sensitive to formation and consumption of diazene (tHNNH and cHNNH). Several of the key steps in the ammonia pyrolysis mechanism are radical-radical reactions that are difficult to measure accurately and challenging to calculate theoretically, and a more comprehensive experimental characterization is desirable to support further model development.

10 SYNTHETIC FUELS↗

Cone Beam Computed Tomography: The Challenges and Strategies in Its Application for Dose Accumulation

Online image guidance using cone beam computed tomography (CBCT) has greatly improved the geometric precision of radiotherapy. Changes in anatomy are common during a course of fractionated treatment, resulting in dose deviation from the planned distribution. There is increased interest in performing dose accumulation to compute the actual delivered dose and to adapt the treatment when necessary. This can be achieved by delineating the volume of interest and by generating “dose of the day” through dose computation on the CBCT. However, the image quality and the accuracy of the CT number of CBCT are deemed to be inferior to fan beam CT, which increases the uncertainty associated in this process. A review of literature was conducted to assess the reliability of and to examine strategies for overcoming the challenges in using CBCT for volume delineation and dose computation. The review demonstrates that the uncertainty varies across body sites, and different strategies have been recommended to generate comparable results to images from CT simulators. This facilitates a better understanding of the potential and the limitation of using CBCT for dose accumulation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Accident tolerant fuel cladding development: Promise, status, and challenges

The motivation for transitioning away from zirconium-based fuel cladding in light water reactors to significantly more oxidation-resistant materials, thereby enhancing safety margins during severe accidents, is laid out. A review of the development status for three accident tolerant fuel cladding technologies, namely coated zirconium-based cladding, ferritic alumina-forming alloy cladding, and silicon carbide fiber–reinforced silicon carbide matrix composite cladding, is offered. Technical challenges and data gaps for each of these cladding technologies are highlighted. Full development towards commercial deployment of these technologies is identified as a high priority for the nuclear industry.

36 MATERIALS SCIENCE↗

Challenges and opportunities to alloyed and composite fuel architectures to mitigate high uranium density fuel oxidation: uranium silicide

We report the challenges and opportunities to alloyed and composite fuel architectures designed and intended to mitigate oxidation of the fuel during a cladding breech of a water-cooled reactor are discussed in three review manuscripts developed in parallel, with the presented article focused on the oxidation performance of uranium silicide. Several high uranium density fuels are under consideration for deployment as accident tolerant and/or advanced technology nuclear reactor fuels, including UN, U 3 Si 2 , UC and UB 2 . Presented here are the literature for the U3Si2 degradation modes, thermodynamics, and oxidation performance of the pure compound and its reported alloyed and composite architectures. Furthermore, this review covers the materials and techniques for the incorporation of additives, dopants, or composite fuel architectures to improve the oxidation/corrosion behavior for high uranium density fuels for use in LWRs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Challenges and opportunities to alloyed and composite fuel architectures to mitigate high uranium density fuel oxidation: Uranium mononitride

We see the challenges and opportunities to alloyed and composite fuel architectures designed and intended to mitigate oxidation of the fuel during a cladding breech of a water-cooled reactor are discussed in three review manuscripts developed in parallel, with the presented article focused on the oxidation performance of uranium mononitride. Several high uranium density fuels are under consideration for deployment as accident tolerant and/or advanced technology nuclear reactor fuels, including one on each: UN, U 3 Si 2 , UC and UB 2 . Presented here is the research motivation for the incorporation of additives, dopants, or composite fuel architectures to improve the oxidation/corrosion behavior of high uranium density nuclear fuels for use in LWRs. Furthermore, this review covers the literature on the degradation modes, thermodynamics, and oxidation performance of pure UN and UN-compounds as well as reported alloyed and composite architectures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Challenges and opportunities to alloyed and composite fuel architectures to mitigate high uranium density fuel oxidation: Uranium diboride and uranium carbide

Here, the challenges and opportunities to alloyed and composite fuel architectures designed and intended to mitigate oxidation of the fuel during a cladding breach of a water-cooled reactor are discussed in three review manuscripts developed in parallel, with the presented article focused on the oxidation performance of uranium diboride and uranium monocarbide. Several high uranium density fuels are under consideration for deployment as accident tolerant and/or advanced technology nuclear reactor fuels, including UN, U 3 Si 2 , UB 2 , and UC. Presented here is the literature for UB 2 and UC degradation modes, thermodynamics, and oxidation performance of the pure compounds and reported alloyed and composite architectures. Furthermore, this review covers the materials and techniques for the incorporation of additives, dopants, or composite fuel architectures to improve the oxidation behavior for high uranium density fuels for use in LWRs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. Here, this knowledge is used to develop atomistically-informed, high-fidelity continuum and meso-scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

36 MATERIALS SCIENCE↗

FFT, FMM, and multigrid on the road to exascale: Performance challenges and opportunities

FFT, FMM, and multigrid methods are widely used fast and highly scalable solvers for elliptic PDEs. However, emerging large-scale computing systems are introducing challenges in comparison to current petascale computers. Recent efforts (Dongarra et al. 2011) have identified several constraints in the design of exascale software that include massive concurrency, resilience management, exploiting the high performance of heterogeneous systems, energy efficiency, and utilizing the deeper and more complex memory hierarchy expected at exascale. In this paper, we perform a model-based comparison of the FFT, FMM, and multigrid methods in the context of these projected constraints. Finally, we use performance models to offer predictions about the expected performance on upcoming exascale system configurations based on current technology trends.

97 MATHEMATICS AND COMPUTING↗

Anion exchange membrane fuel cells: Current status and remaining challenges

The anion exchange membrane fuel cell (AEMFC) is an attractive alternative to acidic proton exchange membrane fuel cells, which to date have required platinum-based catalysts, as well as acid-tolerant stack hardware. The AEMFC could use non-platinum-group metal catalysts and less expensive metal hardware thanks to the high pH of the electrolyte. Over the last decade, substantial progress has been made in improving the performance and durability of the AEMFC through the development of new materials and the optimization of system design and operation conditions. Here in this perspective article, we describe the current status of AEMFCs as having reached beginning of life performance very close to that of PEMFCs when using ultra-low loadings of Pt, while advancing towards operation on non-platinum-group metal catalysts alone. In the latter sections, we identify the remaining technical challenges, which require further research and development, focusing on the materials and operational factors that critically impact AEMFC performance and/or durability. Finally, these perspectives may provide useful insights for the development of next-generation of AEMFCs.

30 DIRECT ENERGY CONVERSION↗