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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

General, Rigorous Approach for the Treatment of Interfragment Covalent Bonds

Here, a generalized, projection-based transformation of the method-agnostic Fock operator in various ab initio fragment-based quantum chemistry methods has been developed for the treatment of interfragment covalent bonds. This transformation freezes the relevant localized molecular orbital associated with each interfragment bond, thereby restricting the variational subspace of the fragment wave functions, in order to maintain the proper physical characteristics of the involved covalent bonds. In addition, sets of orbitals that would lead to multiple occupancy of certain orbitals are explicitly removed from the variational space. The transformation is developed for the specific case of mutually orthonormal frozen and unfrozen orbitals within each fragment. The newly developed approach is then used to study model systems with two popular ab initio fragment-based methods, and the results of these calculations are compared to those obtained by existing methodologies. Analysis is focused on both quantitative and qualitative accuracy as well as computational scalability and stability. Other methods for which the developed formalisms are appropriate are outlined, and future extensions of the methods are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Prediction of Highly Selective Electrocatalytic Nitrogen Reduction at Low Overpotential on a Mo-Doped g-GaN Monolayer

Identifying efficient electrocatalysts with low overpotential and high selectivity for producing ammonia from nitrogen gas is essential for any future electrocatalytic nitrogen reduction reaction (NRR)-based ammonia synthesis. Via density functional theory calculations and the computational hydrogen electrode model, we systematically examine the prospect of using a single-transition-metal (TM)-atom-doped graphene-like GaN (g-GaN) monolayer as an electrocatalyst for artificial nitrogen reduction. Among 15 TMs investigated, the Mo-doped g-GaN (Mo@g-GaN) monolayer is the only electrocatalyst predicted to be feasible for the NRR. The Mo@g-GaN monolayer satisfies all screening criteria considered for activating the inert N≡N triple bond effectively, including stabilization of the adsorbed (*) NRR intermediate *NNH and destabilization of the *NH 2 species. This monolayer also possesses sufficient overall stability. A complete analysis of the likely mechanisms involved in the NRR on this catalyst suggests that the Mo@g-GaN monolayer could exhibit promising NRR catalytic activity. It achieves this via one specific (distal) pathway, which has a very low onset potential of –0.33 V vs the reversible hydrogen electrode (RHE), corresponding to a low overpotential of 0.42 V vs the RHE, defined using the measured equilibrium potential for NRR of 0.09 V vs the RHE. The potential-determining step, conversion of *NH 2 to *NH 3 , also exhibits a surmountable barrier of 0.42 eV, suggesting kinetics will be facile. Finally, the Mo@g-GaN monolayer is predicted to exhibit substantial selectivity (~31%) toward ammonia synthesis over the competing hydrogen evolution reaction. The finding presented in this work may open a potential route for artificial ammonia synthesis using a single-atom catalyst under ambient conditions.

25 ENERGY STORAGE↗
DOE OSTI2016

Sequence-Dependent Structure/Function Relationships of Catalytic Peptide-Enabled Gold Nanoparticles Generated under Ambient Synthetic Conditions

Peptide-enabled nanoparticle (NP) synthesis routes can create and/or assemble functional nanomaterials under environmentally friendly conditions, with properties dictated by complex interactions at the biotic/abiotic interface. Manipulation of this interface through sequence modification can provide the capability for material properties to be tailored to create enhanced materials for energy, catalysis, and sensing applications. Fully realizing the potential of these materials requires a comprehensive understanding of sequence-dependent structure/function relationships that is presently lacking. In this work, the atomic-scale structures of a series of peptide-capped Au NPs are determined using a combination of atomic pair distribution function analysis of high-energy X-ray diffraction data and advanced molecular dynamics (MD) simulations. The Au NPs produced with different peptide sequences exhibit varying degrees of catalytic activity for the exemplar reaction 4-nitrophenol reduction. The experimentally derived atomic-scale NP configurations reveal sequence-dependent differences in structural order at the NP surface. Replica exchange with solute-tempering MD simulations are then used to predict the morphology of the peptide overlayer on these Au NPs and identify factors determining the structure/catalytic properties relationship. We show that the amount of exposed Au surface, the underlying surface structural disorder, and the interaction strength of the peptide with the Au surface all influence catalytic performance. A simplified computational prediction of catalytic performance is developed that can potentially serve as a screening tool for future studies. Our approach provides a platform for broadening the analysis of catalytic peptide-enabled metallic NP systems, potentially allowing for the development of rational design rules for property enhancement.

Bedford, Nicholas M.↗
DOE OSTI2022

A Typology for Characterizing Human Action in MultiSector Dynamics Models

The role of individual and collective human agency is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short-term (hourly to daily) to long-term (annually to centennial) timescales, and from the local to the global, pushing systems towards either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human-natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system-of-systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services towards some human end. We trace the salient features of modeled representations of human systems by organizing the typology around three key questions: 1) Who are the modeled actors in MSD systems? 2) What are their modeled actions? 3) How and for what purpose are these actors and actions operationalized in a computational model? The typology is used to critically examine existing models and chart the frontier of future human systems modeling for MSD research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Elucidating the structure of the magnesium aluminum chloride complex electrolyte for magnesium-ion batteries

Non-aqueous Mg-ion batteries offer a promising way to overcome safety, costs, and energy density limitations of state-of-the-art Li-ion battery technology. Here, we present a rigorous analysis of the magnesium aluminum chloride complex (MACC) in tetrahydrofuran (THF), one of the few electrolytes that can reversibly plate and strip Mg. We use ab initio calculations and classical molecular dynamics simulations to interrogate the MACC electrolyte composition with the goal of addressing two urgent questions that have puzzled battery researchers: (i) the functional species of the electrolyte, and (ii) the complex equilibria regulating the MACC speciation after prolonged electrochemical cycling, a process termed as conditioning, and after prolonged inactivity, a process called aging. A general computational strategy to untangle the complex structure of electrolytes, ionic liquids and other liquid media is presented. The analysis of formation energies and grand-potential phase diagrams of Mg–Al–Cl–THF suggests that the MACC electrolyte bears a simple chemical structure with few simple constituents, namely the electro-active species MgCl + and AlCl 4 - in equilibrium with MgCl 2 and AlCl 3 . Knowledge of the stable species of the MACC electrolyte allows us to determine the most important equilibria occurring during electrochemical cycling. We observe that Al deposition is always preferred to Mg deposition, explaining why freshly synthesized MACC cannot operate and needs to undergo preparatory conditioning. Similarly, we suggest that aluminum displacement and depletion from the solution upon electrolyte resting (along with continuous MgCl 2 regeneration) represents one of the causes of electrolyte aging. Finally, we compute the NMR shifts from shielding tensors of selected molecules and ions providing fingerprints to guide future experimental investigations.

25 ENERGY STORAGE↗
DOE OSTI2023

Synergy of semiempirical models and machine learning in computational chemistry

Catalyzed by enormous success in the industrial sector, many research programs have been exploring data-driven, machine learning approaches. Performance can be poor when the model is extrapolated to new regions of chemical space, e.g., new bonding types, new many-body interactions. Another important limitation is the spatial locality assumption in model architecture, and this limitation cannot be overcome with larger or more diverse datasets. The outlined challenges are primarily associated with the lack of electronic structure information in surrogate models such as interatomic potentials. Given the fast development of machine learning and computational chemistry methods, we expect some limitations of surrogate models to be addressed in the near future; nevertheless spatial locality assumption will likely remain a limiting factor for their transferability. Here, we suggest focusing on an equally important effort—design of physics-informed models that leverage the domain knowledge and employ machine learning only as a corrective tool. In the context of material science, we will focus on semi-empirical quantum mechanics, using machine learning to predict corrections to the reduced-order Hamiltonian model parameters. The resulting models are broadly applicable, retain the speed of semiempirical chemistry, and frequently achieve accuracy on par with much more expensive ab initio calculations. These early results indicate that future work, in which machine learning and quantum chemistry methods are developed jointly, may provide the best of all worlds for chemistry applications that demand both high accuracy and high numerical efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The electronic structure, crystal fields, and magnetic anisotropy in RECo 5 magnets

The current progress in describing rare-earth-based magnets' electronic structure and magnetic properties is discussed. We use several currently popular electronic structure methods to show the typical values of critical parameters that define the physics of RECo 5 (RE = rare earth atom) materials. The magnetic moments and magnetic anisotropy of 4f atoms are obtained using several approaches, including anisotropic 4f-charge density-constrained DFT and DFT+HI methods. We also suggest the introduction of "penalty" functional for obtaining correct variational total energy in the traditional Hund's rule-constrained DFT-based techniques. The applicability and future extensions are discussed. The proposed combination of methods is potentially suitable for high-throughput computational searches of new rare-earth-containing magnetic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Deciphering the evolution of flavin-dependent monooxygenase stereoselectivity using ancestral sequence reconstruction

Controlling the selectivity of a reaction is critical for target-oriented synthesis. Accessing complementary selectivity profiles enables divergent synthetic strategies, but is challenging to achieve in biocatalytic reactions given enzymes’ innate preferences of a single selectivity. Thus, it is critical to understand the structural features that control selectivity in biocatalytic reactions to achieve tunable selectivity. Here, we investigate the structural features that control the stereoselectivity in an oxidative dearomatization reaction that is key to making azaphilone natural products. Crystal structures of enantiocomplementary biocatalysts guided the development of multiple hypotheses centered on the structural features that control the stereochemical outcome of the reaction; however, in many cases, direct substitutions of active site residues in natural proteins led to inactive enzymes. Ancestral sequence reconstruction (ASR) and resurrection were employed as an alternative strategy to probe the impact of each residue on the stereochemical outcome of the dearomatization reaction. These studies suggest that two mechanisms are active in controlling the stereochemical outcome of the oxidative dearomatization reaction: one involving multiple active site residues in AzaH and the other dominated by a single Phe to Tyr switch in TropB and AfoD. Moreover, this study suggests that the flavin-dependent monooxygenases (FDMOs) adopt simple and flexible strategies to control stereoselectivity, which has led to stereocomplementary azaphilone natural products produced by fungi. This paradigm of combining ASR and resurrection with mutational and computational studies showcases sets of tools for understanding enzyme mechanisms and provides a solid foundation for future protein engineering efforts.

Science & Technology - Other Topics↗
DOE OSTI2017

Squeezed bispectrum in the δ N formalism: local observer effect in field space

The prospects of future galaxy surveys for non-Gaussianity measurements call for the development of robust techniques for computing the bispectrum of primordial cosmological perturbations. In this paper, we propose a novel approach to the calculation of the squeezed bispectrum in multiple-field inflation. With use of the δ N formalism, our framework sheds new light on the recently pointed out difference between the squeezed bispectrum for global observers and that for local observers, while allowing one to calculate both. For local observers in particular, the squeezed bispectrum is found to vanish in single-field inflation. Furthermore, our framework allows one to go beyond the near-equilateral ('small hierarchy') limit, and to automatically include intrinsic non-Gaussianities that do not need to be calculated separately. The explicit computational programme of our method is given and illustrated with a few examples.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Power Profile Monitoring and Tracking Evolution of System-Wide HPC Workloads

The power & energy demands of HPC machines have grown significantly. Modern exascale HPC systems require tens of megawatts of combined power for computing resources and cooling facilities at full capacity. The current energy trend is not sustainable for future HPC systems, and there is a need to work toward the energy efficiency aspect of HPC performance. Energy awareness of the HPC applications at the job level is essential for running an efficient HPC system. This work aims to develop a pipeline to provide a production-level system-wide overview of the HPC workloads' power profile while handling evolving workloads exhibiting new power trends. We developed an open-set classification model for HPC jobs based on the properties of power profiles to continuously provide a system-wide holistic view of recently completed jobs. The pipeline helps continuously monitor the job-level power usage pattern of HPC and enables us to capture the new trends in applications' power behavior. We employed a comprehensive set of techniques to generate job-level data, custom-designed feature extraction methods to extract critical features from jobs' power profiles, clustering techniques powered by generative modeling, and open-set classification for identifying job profiles into known classes or an unknown set. With extensive evaluations, we demonstrate the effectiveness of each component in our pipeline. We provide an analysis of the resulting clusters that characterize the power profile landscape of the Summit supercomputer from more than 60K jobs executed in a year. The open-set classification classifies the known data sets into known classes with high accuracy and identifies unknown data noints with over 85% accuracy.

Karimi, Ahmad Maroof↗
DOE OSTI2014

SU-E-T-347: Validation of the Condensed History Algorithm of Geant4 Using the Fano Test

Purpose: To validate the condensed history algorithm and physics of the Geant4 Monte Carlo toolkit for simulations of ionization chambers (ICs). This study is the first step to validate Geant4 for calculations of photon beam quality correction factors under the presence of a strong magnetic field for magnetic resonance guided linac system applications. Methods: The electron transport and boundary crossing algorithms of Geant4 version 9.6.p02 were tested under Fano conditions using the Geant4 example/application FanoCavity. User-defined parameters of the condensed history and multiple scattering algorithms were investigated under Fano test conditions for three scattering models (physics lists): G4UrbanMscModel95 (PhysListEmStandard-option3), G4GoudsmitSaundersonMsc (PhysListEmStandard-GS), and G4WentzelVIModel/G4CoulombScattering (PhysListEmStandard-WVI). Simulations were conducted using monoenergetic photon beams, ranging from 0.5 to 7 MeV and emphasizing energies from 0.8 to 3 MeV. Results: The GS and WVI physics lists provided consistent Fano test results (within ±0.5%) for maximum step sizes under 0.01 mm at 1.25 MeV, with improved performance at 3 MeV (within ±0.25%). The option3 physics list provided consistent Fano test results (within ±0.5%) for maximum step sizes above 1 mm. Optimal parameters for the option3 physics list were 10 km maximum step size with default values for other user-defined parameters: 0.2 dRoverRange, 0.01 mm final range, 0.04 range factor, 2.5 geometrical factor, and 1 skin. Simulations using the option3 physics list were ∼70 – 100 times faster compared to GS and WVI under optimal parameters. Conclusion: This work indicated that the option3 physics list passes the Fano test within ±0.5% when using a maximum step size of 10 km for energies suitable for IC calculations in a 6 MV spectrum without extensive computational times. Optimal user-defined parameters using the option3 physics list will be used in future IC simulations to calculate beam quality correction factors under the presence of a magnetic field. Elekta-MD Anderson Research Agreement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets—from soil and seawater microbiomes—to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon’s abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Impurity lattice Monte Carlo for hypernuclei

Abstract We consider the problem of including $$\varLambda $$ Λ hyperons into the ab initio framework of nuclear lattice effective field theory. In order to avoid large sign oscillations in Monte Carlo simulations, we make use of the fact that the number of hyperons is typically small compared to the number of nucleons in the hypernuclei of interest. This allows us to use the impurity lattice Monte Carlo method, where the minority species of fermions in the full nuclear Hamiltonian is integrated out and treated as a worldline in Euclidean projection time. The majority fermions (nucleons) are treated as explicit degrees of freedom, with their mutual interactions described by auxiliary fields. This is the first application of the impurity lattice Monte Carlo method to systems where the majority particles are interacting. Here, we show how the impurity Monte Carlo method can be applied to compute the binding energies of the light hypernuclei. In this exploratory work we use spin-independent nucleon–nucleon and hyperon–nucleon interactions to test the computational power of the method. We find that the computational effort scales approximately linearly in the number of nucleons. The results are very promising for future studies of larger hypernuclear systems using chiral effective field theory and realistic hyperon–nucleon interactions, as well as applications to other quantum many-body systems.

Frame, Dillon↗
DOE OSTI2013

Application of Plasma Waveguides to High Energy Accelerators

The eventual success of laser-plasma based acceleration schemes for high-energy particle physics will require the focusing and stable guiding of short intense laser pulses in reproducible plasma channels. For this goal to be realized, many scientific issues need to be addressed. These issues include an understanding of the basic physics of, and an exploration of various schemes for, plasma channel formation. In addition, the coupling of intense laser pulses to these channels and the stable propagation of pulses in the channels require study. Finally, new theoretical and computational tools need to be developed to aid in the design and analysis of experiments and future accelerators. Here we propose a 3-year renewal of our combined theoretical and experimental program on the applications of plasma waveguides to high-energy accelerators. During the past grant period we have made a number of significant advances in the science of laser-plasma based acceleration. We pioneered the development of clustered gases as a new highly efficient medium for plasma channel formation. Our contributions here include theoretical and experimental studies of the physics of cluster ionization, heating, explosion, and channel formation. We have demonstrated for the first time the generation of and guiding in a corrugated plasma waveguide. The fine structure demonstrated in these guides is only possible with cluster jet heating by lasers. The corrugated guide is a slow wave structure operable at arbitrarily high laser intensities, allowing direct laser acceleration, a process we have explored in detail with simulations. The development of these guides opens the possibility of direct laser acceleration, a true miniature analogue of the SLAC RF-based accelerator. Our theoretical studies during this period have also contributed to the further development of the simulation codes, Wake and QuickPIC, which can be used for both laser driven and beam driven plasma based acceleration schemes. We will continue our development of advanced simulation tools by modifying the QuickPIC algorithm to allow for the simulation of plasma particle pick-up by the wake fields. We have also performed extensive simulations of plasma slow wave structures for efficient THz generation by guided laser beams or accelerated electron beams. We will pursue experimental studies of direct laser acceleration, and THz generation by two methods, ponderomotive-induced THz polarization, and THz radiation by laser accelerated electron beams. We also plan to study both conventional and corrugated plasma channels using our new 30 TW in our new lab facilities. We will investigate production of very long hydrogen plasma waveguides (5 cm). We will study guiding at increasing power levels through the onset of laser-induced cavitation (bubble regime) to assess the role played by the preformed channel. Experiments in direct acceleration will be performed, using laser plasma wakefields as the electron injector. Finally, we will use 2-colour ionization of gases as a high frequency THz source (<60 THz) in order for femtosecond measurements of low plasma densities in waveguides and beams.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Embedded Sensor Development in Metallic Structures for the Transformational Challenge Reactor

The ability to make minimally intrusive measurements of process conditions has tremendous potential for improving system performance and control in applications such as nuclear power generation. Towards this end, emerging and evolving advanced manufacturing methods, such as additive manufacturing, present new opportunities for more seamlessly integrating sensing with structure. This technical report summarizes the progress of work performed to assess the feasibility of embedding commercial off-the-shelf (COTS) sensors in a metallic reactor core using advanced manufacturing methods. The progress of four research and development tasks are documented: 1) A survey of COTS sensors for nuclear applications that are candidates for embedded fabrication, 2) Development of a conceptual framework for investigating the feasibility of sensor embedment, 3) Definition of structural geometries and other characteristics that will represent compelling proof-of-concept, and 4) Preliminary prototyping of embedded sensors. For the purposes of this initial study, nuclear grade K-type thermocouples were selected for investigation of embedment methodologies. This sensor was selected as an initial candidate because it represents one of the simplest sensor configurations that can provide useful process information. A selective laser melting (SLM) additive manufacturing process was used to fabricate structures with complexity representative of the core design of the transformational challenge reactor (TCR) and methods were developed to embed a thermocouple with a complex two-dimensional routing path. There are many challenges associated with embedding sensors during the additive manufacturing process including securing the sensor in the structure, relocating the part in the additive machine if using a “pick and place” sensor placement method, mitigating the potential for powder contamination, optimizing energy deposition parameters to build as closely as possible around the sensor path and improve structural integrity of the part, and tuning energy deposition to mitigate thermally induced warpage of the sensor and part as well as potential for damaging the sensing device. Preliminary results indicate that it is feasible to integrate the sensor while minimally compromising the structural integrity of the part and preserving sensor performance. This first phase of this work focused on developing a workflow for embedding sensors and controlling energy deposition during the additive manufacturing process to better understand the build characteristics around the sensor. Future work will perform more in-depth characterization of prototype parts using X-ray computed tomography and scanning electron microscopy to better understand fabricated structures, performance testing of embedded sensors in high temperature environments, adding new embedded measurement modalities, embedding devices with dissimilar materials in contact with additive powders, and the development of methods for embedding sensors with three-dimensional routing paths.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

LLNL Response to the DOE ASCR RFI, "Stewardship of Software for Scientific and High-Performance Computing"

For decades, Lawrence Livermore National Laboratory (LLNL) has been engaged in significant research, development, and support for software to enable scientific computing and, particularly, the use of high performance computing (HPC) in the NNSA mission space. In particular, the move in the mid-1990’s to simulation as a leading component of stockpile stewardship through the ASCI and the successor ASC programs, as well as the need for reliable data acquisition and control software for the National Ignition Facility, have been important drivers in building expertise in production-quality software development at LLNL. LLNL has also been a leader in the DOE SciDAC FASTMath Institute and the DOE Exascale Computing Project (ECP), both of which have striven to make scientific computing software – in particular, the enabling technologies underpinning simulation capabilities – more widely adopted and sustainable. As such, we believe that our experience can inform the broader goal of software stewardship for scientific and high-performance computing. LLNL strongly supports the formation of a new DOE ASCR program element in software stewardship and sustainment. Historically, DOE ASCR has funded applied mathematics and computer science research that has led to the development of important new capabilities and algorithms that are expressed as artifacts in research software. Such frameworks, libraries, and tools have seldom been directly funded to address the important issues of code maintenance, documentation, robustness, and community building. Software engineering and support have typically been done on the side in support of the ASCR-driven research products. DOE funding priorities have been slow to recognize that good software engineering, the kind that ensures research investments have more adoption and longevity, requires significant resources. Based upon our experiences, we have prepared this response to highlight the concerns and issues we believe to be important as DOE ASCR considers its role in scientific software stewardship. We believe that role is important and will require a significant investment of new funding to legitimately support the technologies past and future DOE ASCR investments have and will produce to facilitate their uptake and adoption in the broader scientific computing community. Following a summary of our involvement in scientific software development, the remainder our response is organized around the nine topics specifically identified in the RFI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

EQSIM: Exascale Predictions of Earthquake Effects on Critical Infrastructure

The great “San Francisco” earthquake of 1906 is one of the most recognized, and sobering, demonstrations of the havoc that can be caused by the sudden and violent movement of Earth’s tectonic plates. The estimated 7.9-magnitude quake and subsequent fires decimated the major metropolis and surrounding areas: buildings turned to ruins, hundreds of thousands of people left homeless, and a death toll exceeding 3,000. Today, as evidenced by the catastrophic 7.8-magnitude earthquake that struck Turkey in February 2023, these events still present a significant danger to life and economic security. To mitigate the potential devastation of future earthquakes and better prepare for these inevitable events, researchers are turning to high-performance computers to simulate the underlying geophysical processes and accurately quantify associated risks to critical infrastructure.

42 ENGINEERING↗
DOE OSTI2018

New Los Alamos Opacity Calculations

In 2015 Los Alamos National Laboratory (LANL) released a new set of OPLIB opacity tables for the elements hydrogen through zinc. The new LANL opacities are publicly available via our website and are already in use by the astrophysics community. In this contribution, we discuss the extension of our opacity calculations to elements beyond zinc. Such calculations are motivated by potential industrial applications (for elements such as Sn) as well as available experimental data with which to compare our calculations (for Ge and Br). After a short outline of our method for computing opacities for these elements, we make comparisons to available experimental data and find good agreement. Future plans are briefly discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗