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DOE OSTI2021

Seismic waves in medium with poroelastic/elastic interfaces: a two-dimensional P-SV finite-difference modelling

SUMMARY We present a new methodology of the finite-difference (FD) modelling of seismic wave propagation in a strongly heterogeneous medium composed of poroelastic (P) and (strictly) elastic (E) parts. The medium can include P/P, P/E and E/E material interfaces of arbitrary shapes. The poroelastic part can be with (i) zero resistive friction, (ii) non-zero constant resistive friction or (iii) JKD model of the frequency-dependent permeability and resistive friction. Our FD scheme is capable of subcell resolution: a material interface can have an arbitrary position in the spatial grid. The scheme keeps computational efficiency of the scheme for a smoothly and weakly heterogeneous medium (medium without material interfaces). Numerical tests against independent analytical, semi-analytical and spectral-element methods prove the efficiency and accuracy of our FD modelling. In numerical examples, we indicate effect of the P/E interfaces for the poroelastic medium with a constant resistive friction and medium with the JKD model of the frequency-dependent permeability and resistive friction. We address the 2-D P-SV problem. The approach can be readily extended to the 3-D problem.

58 GEOSCIENCES↗

DOE OSTI2019

Structural correlations tailor conductive properties in polymerized ionic liquids

Polymerized ionic liquids (PolyILs) are enticing materials for applications in electrochemical devices spanning from fuel cells to capacitors and batteries. In principle, PolyILs have a competitive advantage over traditional electrolytes in being single ion conductors and thus enabling a transference number close to unity. Despite this perceived advantage, surprisingly low room temperature ionic conductivities measured in the lab raise an important fundamental question: how does the molecular structure mediate conductivity? Here, wide-angle X-ray scattering (WAXS), vibrational sum frequency generation (vSFG), and density functional theory (DFT) calculations were used to study the bulk and interfacial structure of PolyILs, while broad band dielectric spectroscopy (BDS) was used to probe corresponding dynamics and conductive properties for a series of the PolyIL samples with tunable chemistries and structures. Our results reveal that the size of the mobile anions has a tremendous impact on chain packing in PolyILs that wasn’t addressed previously. Larger mobile ions tend to create a well-packed structure, while smaller ions frustrate chain packing. The magnitude of these changes and level of structural heterogeneity are shown to depend on the chemical functionality and flexibility of studied PolyILs. Moreover, these experimental and computational results provide new insight into the correlation between conductivity and structure in PolyILs, suggesting that structural heterogeneity helps to reduce the activation energy for ionic conductivity in the glassy state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Evolution of HEP Processing Frameworks

HEP data-processing software must support the disparate physics needs of many experiments. For both collider and neutrino environments, HEP experiments typically use data-processing frameworks to manage the computational complexities of their large-scale data processing needs. Data-processing frameworks are being faced with new challenges this decade. The computing landscape has changed from the past three decades of homogeneous single-core x86 batch jobs running on grid sites. Frameworks must now work on a heterogeneous mixture of different platforms: multi-core machines, different CPU architectures, and computational accelerators; and different computing sites: grid, cloud, and high-performance computing. We describe these challenges in more detail and how frameworks may confront them. Given their historic success, frameworks will continue to be critical software systems that enable HEP experiments to meet their computing needs. Frameworks have weathered computing revolutions in the past; they will do so again with support from the HEP community

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Integration of theory and experiment in the modelling of heterogeneous electrocatalysis.

Theoretical modelling is essential to deepen our understanding of heterogeneous electrocatalytic energy conversion processes, such as water splitting. Here, Sharon Hammes-Schiffer and Giulia Galli offer their perspectives on the best strategies for successfully studying such systems. Heterogeneous electrocatalysis is critical to many energy conversion processes. Theoretical and computational approaches are essential to interpret experimental data and provide the mechanistic understanding necessary to design more effective catalysts. However, automated general procedures to build predictive theoretical and computational frameworks are not readily available; specific choices must be made in terms of the atomistic structural model and the level of theory, as well as the experimental data used to inform and validate these choices. Here we outline some best practices for modelling heterogeneous systems and present examples in the context of catalysis at metal electrodes and oxides. The level of theory should be chosen for the specific system and properties of interest, and experimental validation is essential from the beginning to the end of the study. Continuous feedback and ultimate integration between experiment and theory enhances the power of calculations to elucidate mechanisms, identify effective descriptors and clarify design principles.

Hammes-Schiffer, Sharon↗

DOE OSTI2012

Optimization of Large-Scale Heterogeneous System-of-Systems Models

Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2015

Mineral density volume gradients in normal and diseased human tissues

Clinical computed tomography provides a single mineral density (MD) value for heterogeneous calcified tissues containing early and late stage pathologic formations. The novel aspect of this study is that, it extends current quantitative methods of mapping mineral density gradients to three dimensions, discretizes early and late mineralized stages, identifies elemental distribution in discretized volumes, and correlates measured MD with respective calcium (Ca) to phosphorus (P) and Ca to zinc (Zn) elemental ratios. To accomplish this, MD variations identified using polychromatic radiation from a high resolution micro-computed tomography (micro-CT) benchtop unit were correlated with elemental mapping obtained from a microprobe X-ray fluorescence (XRF) using synchrotron monochromatic radiation. Digital segmentation of tomograms from normal and diseased tissues (N=5 per group; 40-60 year old males) contained significant mineral density variations (enamel: 2820-3095mg/cc, bone: 570-1415mg/cc, cementum: 1240-1340mg/cc, dentin: 1480-1590mg/cc, cementum affected by periodontitis: 1100-1220mg/cc, hypomineralized carious dentin: 345-1450mg/cc, hypermineralized carious dentin: 1815-2740mg/cc, and dental calculus: 1290-1770mg/cc). A plausible linear correlation between segmented MD volumes and elemental ratios within these volumes was established, and Ca/P ratios for dentin (1.49), hypomineralized dentin (0.32-0.46), cementum (1.51), and bone (1.68) were observed. Furthermore, varying Ca/Zn ratios were distinguished in adapted compared to normal tissues, such as in bone (855-2765) and in cementum (595-990), highlighting Zn as an influential element in prompting observed adaptive properties. Hence, results provide insights on mineral density gradients with elemental concentrations and elemental footprints that in turn could aid in elucidating mechanistic processes for pathologic formations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Coupled Physics Environment (CouPE) library - Design, Implementation, and Release

Over several years, high fidelity, validated mono-physics solvers with proven scalability on peta-scale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a unified mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. In this report, we present details on the design decisions and developments on CouPE, an acronym that stands for Coupled Physics Environment that orchestrates a coupled physics solver through the interfaces exposed by MOAB array-based unstructured mesh, both of which are part of SIGMA (Scalable Interfaces for Geometry and Mesh-Based Applications) toolkit. The SIGMA toolkit contains libraries that enable scalable geometry and unstructured mesh creation and handling in a memory and computationally efficient implementation. The CouPE version being prepared for a full open-source release along with updated documentation will contain several useful examples that will enable users to start developing their applications natively using the native MOAB mesh and couple their models to existing physics applications to analyze and solve real world problems of interest. An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is also being investigated as part of the NEAMS RPL, to tightly couple neutron transport, thermal-hydraulics and structural mechanics physics under the SHARP framework. This report summarizes the efforts that have been invested in CouPE to bring together several existing physics applications namely PROTEUS (neutron transport code), Nek5000 (computational fluid-dynamics code) and Diablo (structural mechanics code). The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The design of CouPE along with motivations that led to implementation choices are also discussed. The first release of the library will be different from the current version of the code that integrates the components in SHARP and explanation on the need for forking the source base will also be provided. Enhancements in the functionality and improved user guides will be available as part of the release. CouPE v0.1 is scheduled for an open-source release in December 2014 along with SIGMA v1.1 components that provide support for language-agnostic mesh loading, traversal and query interfaces along with scalable solution transfer of fields between different physics codes. The coupling methodology and software interfaces of the library are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the CouPE library.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Posterior Covariance Matrix Approximations

Here, the Davis equation of state (EOS) is commonly used to model thermodynamic relationships for high explosive (HE) reactants. Typically, the parameters in the EOS are calibrated, with uncertainty, using a Bayesian framework and Markov Chain Monte Carlo (MCMC) methods. However, MCMC methods are computationally expensive, especially for complex models with many parameters. This paper provides a comparison between MCMC and less computationally expensive Variational methods (Variational Bayesian and Hessian Variational Bayesian) for computing the posterior distribution and approximating the posterior covariance matrix based on heterogeneous experimental data. All three methods recover similar posterior distributions and posterior covariance matrices. This study demonstrates that for this EOS parameter calibration application, the assumptions made in the two Variational methods significantly reduce the computational cost but do not substantially change the results compared to MCMC.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Revealing the Distribution of Metal Carboxylates in Oil Paint from the Micro- to Nanoscale

Oil paints comprise pigments, drying oils, and additives that together confer desirable properties, but can react to form metal carboxylates (soaps) that may damage artworks over time. To obtain information on soap formation and aggregation, we introduce in this study a new tapping-mode measurement paradigm for the photothermal induced resonance (PTIR) technique that enables nanoscale IR spectroscopy and imaging on highly heterogenous and rough paint thin sections. PTIR is used in combination with μ-computed tomography and IR microscopy to determine the distribution of metal carboxylates in a 23-year old oil paint of known formulation. Results show that heterogeneous agglomerates of Al-stearate and a Zn-carboxylate complex with Zn-stearate nano-aggregates in proximity are distributed randomly in the paint. The gradients of zinc carboxylates are unrelated to the Al-stearate distribution. These measurements open a new chemically sensitive nanoscale observation window on the distribution of metal soaps that can bring insights for understanding soap formation in oil paint.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Surface-supported cluster catalysis: Ensembles of metastable states run the show

It has recently been demonstrated that the dynamic behaviour of surface-supported nanocluster catalysts in realistic reaction conditions defies conventional models used in catalysis. This opens new doors in catalysis by giving more leverage in catalyst design, but also requires a major revision of the understanding of how dynamic heterogeneous catalytic interfaces operate, as well as of the computational approaches of catalyst modelling, and experimental methods of catalyst characterization. Key aspects of the new paradigm include the collective action of many catalyst states that form a statistical ensemble in reacting conditions, the catalytic activity and selectivity being driven by rare and metastable catalyst states, reaction thermodynamics and kinetics being controlled by different states of the catalyst, broken scaling relationships, non-Arrhenius behaviours, and catalyst dynamic restructuring being an essential part of the reaction mechanism. For computation, this complexity means the departure from the standard DFT calculations of reaction mechanisms on a single catalyst structure. For experiment, it calls for the development of operando characterization tools with the per-site resolution and the ability to find the minority sites that govern the catalytic activity. For catalyst design, the goal becomes the creation of the catalyst state (geometric and electronic) that might not be present in the as-prepared catalyst, but would develop in the reaction conditions and would have the desired activity then. While cluster catalysts are the most dramatic in their dynamic fluxionality, other amorphous interfaces also exhibit some of it, and thus are also subject to similar paradigm revision.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence.

Bernholdt, David↗

DOE OSTI2021

HTR-1.3 solver: Predicting electrified combustion using the hypersonic task-based research solver

Here this manuscript presents an updated open-source version of the Hypersonics Task-based Research (HTR) solver. The solver, whose main features are presented in Di Renzo et al. (2020) and Di Renzo & Pirozzoli (2021), is designed for direct numerical simulation of reacting flows at high Reynolds numbers. This new version extends the applications of the HTR solver to turbulent combustion in the presence of external electric fields. In particular, a new distributed Poisson solver compatible with heterogeneous architectures has been incorporated in the algorithm to compute the electric potential distribution in bi-periodic configurations. The drift fluxes of the electrically charged species are now included in the transport equations using a targeted essentially non-oscillatory scheme. A verification of these new features of the solver is provided using one-dimensional burner stabilized flames, whereas a three dimensional turbulent flame is utilized to discuss the scalability of the proposed numerical tool.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

Using Generalized Equivalent Uniform Dose Atlases to Combine and Analyze Prospective Dosimetric and Radiation Pneumonitis Data From 2 Non-Small Cell Lung Cancer Dose Escalation Protocols

Purpose: To demonstrate the use of generalized equivalent uniform dose (gEUD) atlas for data pooling in radiation pneumonitis (RP) modeling, to determine the dependence of RP on gEUD, to study the consistency between data sets, and to verify the increased statistical power of the combination. Methods and Materials: Patients enrolled in prospective phase I/II dose escalation studies of radiation therapy of non-small cell lung cancer at Memorial Sloan-Kettering Cancer Center (MSKCC) (78 pts) and the Netherlands Cancer Institute (NKI) (86 pts) were included; 10 (13%) and 14 (17%) experienced RP requiring steroids (RPS) within 6 months after treatment. gEUD was calculated from dose-volume histograms. Atlases for each data set were created using 1-Gy steps from exact gEUDs and RPS data. The Lyman-Kutcher-Burman model was fit to the atlas and exact gEUD data. Heterogeneity and inconsistency statistics for the fitted parameters were computed. gEUD maps of the probability of RPS rate {>=}20% were plotted. Results: The 2 data sets were homogeneous and consistent. The best fit values of the volume effect parameter a were small, with upper 95% confidence limit around 1.0 in the joint data. The likelihood profiles around the best fit a values were flat in all cases, making determination of the best fit a weak. All confidence intervals (CIs) were narrower in the joint than in the individual data sets. The minimum P value for correlations of gEUD with RPS in the joint data was .002, compared with P=.01 and .05 for MSKCC and NKI data sets, respectively. gEUD maps showed that at small a, RPS risk increases with gEUD. Conclusions: The atlas can be used to combine gEUD and RPS information from different institutions and model gEUD dependence of RPS. RPS has a large volume effect with the mean dose model barely included in the 95% CI. Data pooling increased statistical power.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2011

Uncertainty Studies of Real Anode Surface Area in Computational Analysis for Molten Salt Electrorefining

This study examines how much cell potential changes with five differently assumed real anode surface area cases. Determining real anode surface area is a significant issue to be resolved for precisely modeling molten salt electrorefining. Based on a three-dimensional electrorefining model, calculated cell potentials compare with an experimental cell potential variation over 80 hours of operation of the Mark-IV electrorefiner with driver fuel from the Experimental Breeder Reactor II. We succeeded to achieve a good agreement with an overall trend of the experimental data with appropriate selection of a mode for real anode surface area, but there are still local inconsistencies between theoretical calculation and experimental observation. In addition, the results were validated and compared with two-dimensional results to identify possible uncertainty factors that had to be further considered in a computational electrorefining analysis. These uncertainty factors include material properties, heterogeneous material distribution, surface roughness, and current efficiency. Zirconium's abundance and complex behavior have more impact on uncertainty towards the latter period of electrorefining at given batch of fuel. The benchmark results found that anode materials would be dissolved from both axial and radial directions at least for low burn-up metallic fuels after active liquid sodium bonding was dissolved.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Experiential findings for sustainable software ecosystems to support experimental and observational science

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. Here, the study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: (i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and (ii) data management requirements for data-driven science using artificial intelligence.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Well-Defined Nanoparticle Electrocatalysts for the Refinement of Theory

The relationship between experiment and theory in electrocatalysis is one of profound importance. Until fairly recently, the principal role of theory in this field was interpreting experimental results. Over the course of the past decade (roughly the period covered by this review), however, that has begun to change, with theory now frequently leading the design of electrocatalytic materials. Though rewarding, this has not been a particularly easy union. For one thing, experimentalists and theorists have to come to grips with the fact that they rely on different models. Theorists make predictions based on individual, perfect structural models, while experimentalists work with more complex and heterogeneous ensembles of electrocatalysts. As discussed in this review, computational capabilities have improved in recent years, so that theory is better represented by the structures that experimentalists are able to prepare. Likewise, synthetic chemists are able to make ever more complex electrocatalysts with high levels of control, which provide a more extensive palette of materials for testing theory. Finally, the goal of this review is to highlight research from the last ~10 years that focuses on carefully controlled electrocatalytic experiments which, in combination with theoretical predictions, bring us closer to bridging the gap between real catalysts and computational models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Effect of Pore Connectivity on Li Dendrite Propagation within LLZO Electrolytes Observed with Synchrotron X-ray Tomography

Li 7 La 3 Zr 2 O 12 (LLZO) is a garnet type material that demonstrates promising characteristics for all solid-state battery applications due to its high Li-ion conductivity and its compatibility with Li metal. The primary limitation of LLZO is the propensity for short-circuiting at low current densities. Microstructure features such as grain boundaries, pore character, and density all contribute to this shorting phenomenon. Toward the goal of understanding structure-processing relationships for practical design of solid electrolytes, the present study tracks structural transformations in solid electrolytes processed at three different temperatures (1000, 1050 and 1150 °C) using synchrotron x-ray tomography. A sub volume of 300 μm 3 captures the heterogeneity of the solid electrolyte microstructure while minimizing the computational intensity associated with 3D reconstructions. While the porosity decreases with increasing temperature, the underlying connectivity of the pore region increases. In conclusion, solid electrolytes with interconnected pores short circuit at lower critical current densities than samples with less connected pores.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Automated Transformation of Lignin Topologies into Atomic Structures with LigninBuilder

Lignin is an abundant aromatic heteropolymer found in secondary plant cell walls and is a potential feedstock for conversion into bioderived fuels and chemicals. Lignin chemical diversity complicates traditional structural studies, and so, relatively little experimental evidence exists for how lignin structure exists in aqueous solution or how lignin polymers respond to changes in their chemical environment. Molecular modeling can address these concerns; however, prior computational structural lignin models typically did not capture lignin heterogeneity, as only a few polymers were considered. LigninBuilder creates a framework for building structural libraries for lignin from existing topological libraries, permitting significantly greater diversity of lignin structures to be sampled at atomic detail. As a demonstration of its capabilities, LigninBuilder was applied to three libraries of lignin from hardwood, softwood, and grass, and the resulting polymer structures were simulated in an aqueous environment. The lignins adopted compact globular structures, as would be expected for polymers in poor solvents. The differences between the libraries were largest when quantifying the packing of nonadjacent aromatic residues, with greater branching within the polymer resulting in poorer aromatic packing. Individual lignin polymers were also found to undergo rapid conformational changes, with the dwell time within a state growing as the square of the molecular weight. This first application of LigninBuilder demonstrates the potential for atomic-level insight into lignin interactions. LigninBuilder is distributed as a plugin to the visualization software VMD, lowering the barrier for modeling lignin structure in diverse environments.

09 BIOMASS FUELS↗