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At least 1,369 records · Page 76

Boosting RDataFrame performance with transparent bulk event processing

RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. Thanks to its design inspired by declarative programming principles, RDataFrame enables the development of highperformance, highly parallel analyses without requiring expert knowledge of multi-threading and I/O: user logic is expressed in terms of self-contained, small computation kernels tied together by a high-level API. This design completely decouples analysis logic from its actual execution, and opens several interesting avenues for workflow optimization. In particular, in this work we explore the benefits of moving internal data processing from an event-by-event to a bulkby-bulk loop. This refactoring dramatically reduces the framework’s runtime overheads; in collaboration with the I/O layer it improves data access patterns; it exposes information that optimizing compilers might use to auto-vectorize the invocation of user-defined computations; finally, while existing user-facing interfaces remain unaffected, it becomes possible to additionally offer interfaces that explicitly expose bulks of events, useful e.g. for the injection of GPU kernels into the analysis workflow. In order to inform similar future R&D, design challenges will be presented, as well as an investigation of the relevant timememory trade-off backed by novel performance benchmarks.

Guiraud, Enrico↗

Templates of expected measurement uncertainties

The covariance committee of CSEWG (Cross Section Evaluation Working Group) established templates of expected measurement uncertainties for neutron-induced total, (n,γ), neutron-induced charged-particle, and (n,xn) reaction cross sections as well as prompt fission neutron spectra, average prompt and total fission neutron multiplicities, and fission yields. Templates provide a list of what uncertainty sources are expected for each measurement type and observable, and suggest typical ranges of these uncertainties and correlations based on a survey of experimental data, associated literature, and feedback from experimenters. Information needed to faithfully include the experimental data in the nuclear-data evaluation process is also provided. These templates could assist (a) experimenters and EXFOR compilers in delivering more complete uncertainties and measurement information relevant for evaluations of new experimental data, and (b) evaluators in achieving a more comprehensive uncertainty quantification for evaluation purposes. This effort might ultimately lead to more realistic evaluated covariances for nuclear-data applications. In this topical issue, we cover the templates coming out of this CSEWG effort–typically, one observable per paper. This paper here prefaces this topical issue by introducing the concept and mathematical framework of templates, discussing potential use cases, and giving an example of how they can be applied (estimating missing experimental uncertainties of 235 U(n,f) average prompt fission neutron multiplicities), and their impact on nuclear-data evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Impact of spatiotemporal smoothing on the two-plasmon–decay instability

Higher levels of hot electrons from the two-plasmon–decay instability are observed when smoothing by spectral dispersion (SSD) is turned off in directly driven inertial confinement fusion experiments at the Omega Laser Facility. This finding is explained using a hot-spot model based on speckle statistics and simulation results from the laser–plasma simulation environment. The model accurately reproduces the relative increase in hot-electron activity at two different drive intensities, although it slightly overestimates the absolute number of hot electrons in all cases. Extrapolating from the current ≈ 360-GHz system while adhering to the logic of the hot-spot model suggests that larger SSD bandwidth should significantly mitigate hot-electron generation, and legacy 1-THz OMEGA experiments appear to support this conclusion. These results demonstrate that it is essential to account for laser speckles and spatiotemporal smoothing to obtain quantitative agreement with experiments. A compilation of hot-electron data from the past two decades reveals several other important points: (1) many prior experiments are more easily understood using recent results from multibeam absolute instability theory; and (2) experiments with ignition-scale conditions produce less hot electrons compared to OMEGA spherical experiments for a given vacuum overlapped intensity, which is a promising result for validating performance predictions based on hydrodynamic scaling relations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data-driven materials research enabled by natural language processing and information extraction

Given the emergence of data science and machine learning throughout all aspects of society, but particularly in the scientific domain, there is increased importance placed on obtaining data. Data in materials science are particularly heterogeneous, based on the significant range in materials classes that are explored and the variety of materials properties that are of interest. This leads to data that range many orders of magnitude, and these data may manifest as numerical text or image-based information, which requires quantitative interpretation. The ability to automatically consume and codify the scientific literature across domains - enabled by techniques adapted from the field of natural language processing - therefore has immense potential to unlock and generate the rich datasets necessary for data science and machine learning. This review focuses on the progress and practices of natural language processing and text mining of materials science literature and highlights opportunities for extracting additional information beyond text contained in figures and tables in articles. Here, we discuss and provide examples for several reasons for the pursuit of natural language processing for materials, including data compilation, hypothesis development, and understanding the trends within and across fields. Current and emerging natural language processing methods along with their applications to materials science are detailed. We, then, discuss natural language processing and data challenges within the materials science domain where future directions may prove valuable.

36 MATERIALS SCIENCE↗

A compendium and meta-analysis of flatband potentials for TiO2, ZnO, and SnO2 semiconductors in aqueous media

Semiconductor/electrolyte interfaces are of great interest to numerous scientific fields including renewable energy, (photo)electrochemistry, and energy storage. The semiconductor flatband potential is a key parameter in locating the conduction band minimum or valence band maximum of the semiconductor material in electrolyte. Despite its importance for quantifying the energetic location of the semiconductor bands, literature reports for the same material demonstrate significant variability in the flatband potential. In this compendium and meta-analysis, reported flatband potentials of the common semiconductor materials TiO2, SnO2, and ZnO in aqueous electrolyte were compiled and assessed to quantify the spread in literature flatband potentials as well as determine the factors that lead to the significant spread. For TiO2, SnO2, and ZnO, literature flatband potentials referenced to the reversible hydrogen electrode span a range of nearly 2 V each. Flatband potential tabulations were separated by variables such as the solution pH, the crystalline polymorph, the crystal facet, the morphology, and the dimensions or combinations of these variables to assess the factors that contribute to the observed spread. Important and surprising findings from these categorizations are summarized: (1) Even for the narrowest categorizations, the spread in flatband potential is still large. (2) Flatband potentials of TiO2 and SnO2 follow the expected Nernstian dependence with solution pH. ZnO materials deviate from this Nernstian dependence. (3) In the aggregate, there is no statistically significant difference in the reported flatband potentials of anatase and rutile TiO2. Single crystal tabulations were the only distributions to have statistically significant differences in the flatband potential between anatase and rutile TiO2. (4) Anatase TiO2 materials with a nanotube morphology appear to have a +400 mV difference in mean flatband potential compared to all other morphologies, but we argue that this is likely due to widespread misuse of the Mott–Schottky analysis. Other interesting findings are revealed within the spread of literature flatband potentials, and possible explanations are provided to generate discussion. We also briefly review and discuss common techniques that were used to determine the flatband potential and the pitfalls/criticisms of these techniques. Last, we discuss some ways in which future research on the determination of the flatband potential can be performed to improve the reliability of reported values and the quality of the work. In total, the results from this meta-analysis suggest multiple factors can affect the measured flatband potential and that an abundance of caution should be applied when attempting to quantify the flatband potential of complex or nanostructured systems.

Patel, Milan Y. (ORCID:0000000291948141)↗

Progress toward fusion energy breakeven and gain as measured against the Lawson criterion

The Lawson criterion is a key concept in the pursuit of fusion energy, relating the fuel density n, pulse duration τ or energy confinement time τE, and fuel temperature T to the energy gain Q of a fusion plasma. The purpose of this paper is to explain and review the Lawson criterion and to provide a compilation of achieved parameters for a broad range of historical and contemporary fusion experiments. Although this paper focuses on the Lawson criterion, it is only one of many equally important factors in assessing the progress and ultimate likelihood of any fusion concept becoming a commercially viable fusion-energy system. Only experimentally measured or inferred values of n, τ or τE, and T that have been published in the peer-reviewed literature are included in this paper, unless noted otherwise. For extracting these parameters, we discuss methodologies that are necessarily specific to different fusion approaches (including magnetic, inertial, and magneto-inertial fusion). This paper is intended to serve as a reference for fusion researchers and a tutorial for all others interested in fusion energy.

Wurzel, Samuel E. (ORCID:0000000260548161)↗

Structure and lithium insertion in oxides of molybdenum

Oxides of molybdenum, MoO x , have a rich structural chemistry arising from the accommodation of oxygen deficiency as MoO 3 is reduced and varied redox behavior arising from the ability of Mo to take on several different oxidation states. We review MoO 3 , MoO 2 , and all the reduced Mo oxides with intermediate compositions for their performance as Li-ion battery electrode materials. These reduced oxides are perhaps the most structurally diverse in the field of energy storage materials, taking on structures ranging from ones with crystallographic shear to bronze-like structures and distorted rutile. The crystal structure can have a significant impact on the performance of battery materials, which makes the reduced Mo oxides a promising domain of study. Electrochemical studies of these oxides from as early as 1971 to as recently as 2022 are compiled, and characteristics of capacity, capacity retention, and rate performance are compared. We find that certain oxides indeed display promising and highly reversible capacities for Li + storage. Typical redox voltages for Mo oxides lie in a regime that hinders maximizing energy density when they are paired with higher-voltage cathodes or lower-voltage anodes. The possibility of decreasing the redox voltage in the future will expand the promise of these materials while offering an alternative to more critical elements such as Nb.

25 ENERGY STORAGE↗

Imaginary-time correlation function thermometry: A new, high-accuracy and model-free temperature analysis technique for x-ray Thomson scattering data

The accurate interpretation of experiments with matter at extreme densities and pressures is a notoriously difficult challenge. In a recent work [Dornheim et al., Nat. Commun. 13, 7911 (2022)], we have introduced a formally exact methodology that allows extracting the temperature of arbitrary complex materials without any model assumptions or simulations. Here, we provide a more detailed introduction to this approach and analyze the impact of experimental noise on the extracted temperatures. In particular, we extensively apply our method both to synthetic scattering data and to previous experimental measurements over a broad range of temperatures and wave numbers. We expect that our approach will be of high interest to a gamut of applications, including inertial confinement fusion, laboratory astrophysics, and the compilation of highly accurate equation-of-state databases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DeePMD-kit v2: A software package for deep potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.

97 MATHEMATICS AND COMPUTING↗

CMaize: Simplifying inter-package modularity from the build up

There is a growing desire for inter-package modularity within the chemistry software community to reuse encapsulated code units across a variety of software packages. Most comprehensive efforts at achieving inter-package modularity will quickly run afoul of a very practical problem, being able to cohesively build the modules. Writing and maintaining build systems has long been an issue for many scientific software packages that rely on compiled languages such as C/C++. The push for inter-package modularity compounds this issue by additionally requiring binary artifacts from disparate developers to interoperate at a binary level. Thankfully, the de facto build tool for C/C++, CMake, is more than capable of supporting the myriad of edge cases that complicate writing robust build systems. Unfortunately, writing and maintaining a robust CMake build system can be a laborious endeavor because CMake provides few abstractions to aid the developer. Further, the need to significantly simplify the process of writing robust CMake-based build systems, especially in inter-package builds, motivated us to write CMaize. In addition to describing the architecture and design of CMaize, the article also demonstrates how CMaize is used in production-level software.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental validation of a collision-radiation dataset for molecular hydrogen in plasmas

Quantitative spectroscopy of molecular hydrogen has generated substantial demand, leading to the accumulation of diverse elementary process data encompassing radiative transitions, electron-impact transitions, predissociations, and quenching. However, their rates currently available are still sparse, and there are inconsistencies among those proposed by different authors. In this study, we demonstrate an experimental validation of such a molecular dataset by composing a collisional-radiative model (CRM) for molecular hydrogen and comparing experimentally obtained vibronic populations across multiple levels. From the population kinetics of molecular hydrogen, the importance of each elementary process in various parameter space is studied. In low-density plasmas (electron density ne≲1017 m−3) the excitation rates from the ground states and radiative decay rates, both of which have been reported previously, determine the excited state population. The inconsistency in the excitation rates affects the population distribution the most significantly in this parameter space. However, in higher density plasmas (ne≳1018 m−3), the excitation rates from excited states become important, which have never been reported in the literature, and may need to be approximated in some way. In order to validate these molecular datasets and approximated rates, we carried out experimental observations for two different hydrogen plasmas; a low-density radio frequency heated plasma (ne≈1016 m−3) and the Large Helical Device (LHD) divertor plasma (ne≳1018 m−3). The visible emission lines from EF1Σg+, HH¯1Σg+, D1Πu±, GK1Σg+, I1Πg±, J1Δg±, h3Σg+, e3Σu+, d3Πu±,g3Σg+, i3Πg±, and j3Δg± states were observed simultaneously and their population distributions were obtained from their intensities. We compared the observed population distributions with the CRM prediction, in particular the CRM with the rates compiled by Janev et al., Miles et al., and those calculated with the molecular convergent close-coupling (MCCC) method. The MCCC prediction gives the best agreement with the experiment, particularly for the emission from the low-density plasma. However, the population distribution in the LHD divertor shows a worse agreement with the CRM than those from low-density plasma, indicating the necessity of the precise excitation rates from excited states. We also found that the rates for the electron attachment is inconsistent with experimental results. This requires further investigation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Similar photosynthetic but different yield responses of C 3 and C 4 crops to elevated O 3

The deleterious effects of ozone (O 3 ) pollution on crop physiology, yield, and productivity are widely acknowledged. It has also been assumed that C 4 crops with a carbon concentrating mechanism and greater water use efficiency are less sensitive to O 3 pollution than C 3 crops. This assumption has not been widely tested. Therefore, we compiled 46 journal articles and unpublished datasets that reported leaf photosynthetic and biochemical traits, plant biomass, and yield in five C 3 crops (chickpea, rice, snap bean, soybean, and wheat) and four C 4 crops (sorghum, maize, Miscanthus × giganteus , and switchgrass) grown under ambient and elevated O 3 concentration ([O 3 ]) in the field at free-air O 3 concentration enrichment (O 3 -FACE) facilities over the past 20 y. When normalized by O 3 exposure, C 3 and C 4 crops showed a similar response of leaf photosynthesis, but the reduction in chlorophyll content, fluorescence, and yield was greater in C 3 crops compared with C 4 crops. Additionally, inbred and hybrid lines of rice and maize showed different sensitivities to O 3 exposure. This study quantitatively demonstrates that C 4 crops respond less to elevated [O 3 ] than C 3 crops. This understanding could help maintain cropland productivity in an increasingly polluted atmosphere.

60 APPLIED LIFE SCIENCES↗

New K-feldspar Pb isotope results for Mesozoic arc crust in the Pacific Northwest, U.S.A. and Canada: comparison with the Mojave-Salinia province of southern California and Implications for Baja-BC

Measurements of lead isotopic compositions in detrital K-feldspar have been increasingly used as a tool to assess sediment provenance. We compiled a database of previously published Pb isotope data from 700 bedrock K-feldspar samples and 1,423 age-corrected bedrock whole rock samples from western North American igneous and metamorphic bodies. Additionally, we report 66 new K-feldspar Pb isotope data for plutons throughout the Pacific Northwest region of the United States and British Columbia. Results show that the Pb isotope values of plutonic K-feldspar depend on the isotopically juvenile or evolved nature of underlying crust. Samples obtained from the mid Cretaceous – mid Eocene Coast Plutonic Complex, North Cascades, and Intermontane superterrane that occur west of the initial 87 Sr/ 86 Sr (Sri) = 0.706 isopleth exhibit a highly restricted 207 Pb/ 206 Pb and 208 Pb/ 206 Pb values centred upon 0.83 and 2.03, respectively. Conversely, rocks overlying older continental crust further east such as the Middle Jurassic – Late Cretaceous Omineca crystalline belt, Idaho batholith, and Boulder Batholith exhibit far greater variation of Pb isotope values that parallel the 100 Ma isochron calculated from a two-stage Pb evolution model. We demonstrate that Pb isotopic results from the Idaho and Boulder Batholith region can be used to define distinctive subregions for Pb isotopic provenance analysis, and compare these signatures to the Mojave-Salinian batholith of southern California and western Arizona, as these two areas have previously been proposed as source regions for extraregional sediment that was deposited within the Nanaimo Basin during the Campanian – Maastrichtian. Future Pb isotopic analysis of detrital K-feldspar from the Nanaimo Basin of southwestern British Columbia may effectively distinguish between potential extraregional sources separated by thousands of kilometres.

Coast Plutonic Complex↗

Electron Target Cooling Analyses of the KIPT ADS Using MCNP and Ansys Fluent

This study presents multiphysics analyses of the electron target cooling system of the accelerator-driven system (ADS) of the Kharkiv Institute of Physics and Technology (KIPT) using MCNP and Fluent computer programs. MCNP has been used to transport electrons, gammas, and neutrons, and to calculate the energy deposition in the target materials. The MCNP mesh-tally data have been imported into Fluent by a C subroutine that has been compiled and linked to Fluent as a user-defined function.The KIPT ADS is located in Ukraine and was in operation until February 2022. The Fluent model is based on the computer-aided design files from the manufacturing process of the target assembly. Here, the Fluent results for the reference case match very well the literature results obtained by STAR-CCM+ during the design phase. Other cases that differ from the reference one have been analyzed; in these cases, it is assumed a malfunction of the electron accelerator or of the water cooling system. The target cooling system operates normally for all the analyzed cases except when the inlet water mass flow rate is decreased. The transient analysis showed that the target cooling system can operate for 180 s with full power when the inlet water mass flow rate is decreased down by 75%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Emission factors of industrial boilers burning biomass-derived fuels

Boilers are combustion devices that provide process heat and are integral to many industrial facilities. Historically, outside of the pulp and paper industry, most boilers burned fossil fuels, although interest in decarbonization has been leading to an increased use of renewable fuels in boilers. These boilers, including those in the biorefineries, are often large sources of air pollutant emissions, and the characterization of these emissions is critical to obtaining air permits and ensuring protection of the surrounding air quality. Several industrial boilers and new biorefineries allow utilization of biomass-derived fuels (e.g. wastewater sludge, lignin, etc.) produced during their operation as a fuel for the boiler to meet process energy needs. However, there is limited empirical data on emission factors for the burning of unconventional fuels, such as solid-gas mixtures containing biomass residues. To fill this gap, we carry out a comprehensive data survey, collecting information on emission factors for boilers burning either a single or a mixture of solid and gaseous biomass-derived fuels. We review multiple hard-to-obtain and unconventional data sources, such as air permit applications, stack test data, and industry-sponsored data collection efforts, to compile emission factors for biomass-derived fuels. We then compare this data with wood residue emission factors from the U.S. Environmental Protection Agency’s AP-42 emission factor database. Our results indicate that the emission factors for boilers burning unconventional fuels vary widely depending on the fuel composition, boiler type, and fuel characteristics. Overall, we find that median emission factors of selected biomass-derived fuels are typically lower than those of wood residue boilers in AP-42. The information collected herein could be useful to permitting agencies and industries utilizing boilers who may want to reduce the carbon impact of their facilities by combusting biomass-derived wastes for process energy needs, for more accurate emission estimation for permitting.

09 BIOMASS FUELS↗

Edge fluctuation measurements in EDA H-mode and QCE plasmas in ASDEX Upgrade using the correlation electron cyclotron emission diagnostic

The requirement of a plasma solution without large edge-localized modes (ELMs) for future fusion devices motivates the study of plasmas without Type I ELMs. The enhanced D–α (EDA) and quasi-continuous exhaust (QCE) scenarios are two such Type I ELM free plasmas, but their underlying physics principles are not fully understood. A database of EDA and QCE plasmas from ASDEX Upgrade was compiled and analyzed using the correlation electron cyclotron emission diagnostic in order to study differences between properties of the quasi-coherent mode (QCM) between these two regimes. Investigations into measured spectral properties of the QCM, radiated temperature fluctuations δT rad /T rad , and radial correlation lengths L c showed no differences between the two regimes. Spectral properties using the cross-power spectral density, G xy were similar between regimes, with the values measured to be a central frequency, $f$ $QCM$ ≈ 20 - 50 kHz; spectral width, Δ $f$ ≈ 5 - 40 kHz; δT rad /T rad ≈ 4-6%; and L c ≈ 1-2 cm. Investigations into a quantity representing the relative bandwidth Δ$f$/$f$ $QCM$ revealed differences between EDA and QCE plasmas when plotted radially, suggesting some type of interaction between the QCM in QCE plasmas with the surrounding broadband turbulence that is not present in EDA phases. Additionally, investigations into various drive terms for hypothesized instability drivers for the QCM are performed showing no difference in the parameter spaces of collisionality and the ion temperature, electron temperature, or electron pressure scale lengths between each regime indicating that there is no observable difference between the drive behind the QCM in each regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Standard model physics and the digital quantum revolution: thoughts about the interface

Advances in isolating, controlling and entangling quantum systems are transforming what was once a curious feature of quantum mechanics into a vehicle for disruptive scientific and technological progress. Pursuing the vision articulated by Feynman, a concerted effort across many areas of research and development is introducing prototypical digital quantum devices into the computing ecosystem available to domain scientists. Through interactions with these early quantum devices, the abstract vision of exploring classically-intractable quantum systems is evolving toward becoming a tangible reality. Beyond catalyzing these technological advances, entanglement is enabling parallel progress as a diagnostic for quantum correlations and as an organizational tool, both guiding improved understanding of quantum many-body systems and quantum field theories defining and emerging from the standard model. Here, from the perspective of three domain science theorists, this article compiles thoughts about the interface on entanglement, complexity, and quantum simulation in an effort to contextualize recent NISQ-era progress with the scientific objectives of nuclear and high-energy physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DESI 2024: reconstructing dark energy using crossing statistics with DESI DR1 BAO data

Here, we implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova compilations (PantheonPlus, Union3, and DES-SN5YR) and Planck CMB observations. Our results hint towards an evolving and emergent dark energy behaviour, with negligible presence of dark energy at z ≳ 1, at varying significance depending on data sets combined. In all these reconstructions, the cosmological constant lies outside the 95% confidence intervals for some redshift ranges. This dark energy behaviour, reconstructed using Crossing Statistics, is in agreement with results from the conventional w 0 –w a dark energy equation of state parametrization reported in the DESI Key cosmology paper. Our results add an extensive class of model-agnostic reconstructions with acceptable fits to the data, including models where cosmic acceleration slows down at low redshifts. We also report constraints on H 0 r d from our model-agnostic analysis, independent of the pre-recombination physics.

79 ASTRONOMY AND ASTROPHYSICS↗