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DOE OSTI2024

rNets: a standalone package to visualize reaction networks

In the study of chemical processes, visualizing reaction networks is pivotal for identifying crucial compounds and transformations. Traditional methods, such as network schematics and reaction path linear plots, often struggle to effectively represent complex reaction networks due to their size and intricate connectivity. Alternatives capable of leading with complexity include graph methods, but they are not user-friendly, lacking simplicity and modularity, which hinders their integration with widely-used research software. This work introduces rNets an innovative tool designed for the efficient visualization of reaction networks with a user-friendly interface, modularity, and seamless integration with existing software packages. The effectiveness of rNets is demonstrated through its application in analyzing three catalytic reactions, showcasing its potential to significantly enhance research both in homogeneous and heterogeneous catalysis fields. This tool not only simplifies the visualization process but also opens new avenues for exploring complex reaction networks in diverse research contexts.

Pablo-García, Sergio↗

NASA NTRS2005

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

Paris, Deidre E.↗

DOE OSTI2021

Aging and Lifetimes Milestone 7777, G.C. #4: Assess the ability of MRI to identify chemical and mechanical heterogeneity in polymers at various length scales

Polysiloxane foams utilized for stockpile applications experience changes over time induced by exposure to thermal, radiative, and mechanical stresses. The interplay of these stresses can lead to chemical and/or physical changes in the polymer, such as compression set and material degradation over time. Understanding the mechanisms of material aging and identifying material degradation prior to failure are critical in maintaining the integrity of the nuclear stockpile. Our prior work using solid-state NMR spectroscopy has shown that we can observe signatures of thermal, radiative, and mechanical aging of silicone elastomers using differences in NMR parameters such as relaxation (T1 and T2). However, most of our measurements have been on bulk samples and have only provided an average aging behavior of each sample. Here, we have used magnetic resonance imaging (MRI) to provide relaxation-weighted images that are a metric of structural heterogeneity (cross-link density) in polymers across multiple length scales. In addition, the larger sample size that can be accommodated in animal MRI scanners has the potential to make the technique adaptable to detecting heterogeneities whole parts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Crystallization Mechanisms of Poly(vinylidene Fluoride- co -chlorotrifluoroethylene): Nucleation Transitions, Growth Kinetics, and Microstructure Evolution

The crystallization kinetics of FK-800, a commercial semicrystalline copolymer of chlorotrifluoroethylene and vinylidene fluoride (poly(CTFE-co-VDF)), dictate its microstructure and functional performance. Crystallization occurs between the glass transition (T g ≈ 31 °C) and melting point (T m ≈ 110 °C), with grain boundaries playing a key role in applications such as memristors, where they regulate filament growth. This study integrates in situ atomic force microscopy (AFM), grazing-incidence wide-angle X-ray scattering (GIWAXS), and differential scanning calorimetry (DSC) to characterize nucleation, growth, and morphology across the full crystallization window. Hot-stage AFM reveals a transition from homogeneous to heterogeneous nucleation near 45 °C and a shift from reaction-limited to diffusion-limited growth above 60 °C. Kinetics are analyzed using Lauritzen–Hoffman, Turnbull–Fisher, and Avrami models to extract surface free energies and activation barriers. A multiscale modeling framework is developed in which nucleation densities and growth rates measured by AFM are used to reconstruct Avrami kinetics, which are then validated against coverage data, and extrapolated to predict bulk crystallization behavior observed by DSC. GIWAXS confirms a primarily flat-on chain orientation at all temperatures, linking orientation to domain morphology. This integrative approach quantitatively connects nanoscale crystallization dynamics with macroscopic phase evolution, establishing a quantitative framework for modeling crystallization across time, temperature, and length scales.

Crystallization↗

DOE OSTI2020

SIMPLE-G: A multiscale framework for integration of economic and biophysical determinants of sustainability

We introduce SIMPLE-G, a Simplified International Model of agricultural Prices, Land use, and the Environment- Gridded version, which is a novel tool for evaluating sustainability policies in a global context while factoring in local heterogeneity in land and water resources and natural ecosystem services. This multi-scale model can provide boundary conditions for local decision makers, as well as capturing feedback from local policies to national and global scales. Additionally, to illustrate its value in environmental analysis, we provide two applications of the model. First, we quantify the local stresses on land and water resources due to global changes in population, income, and productivity. Second, we quantify the global impacts of local policy responses and adaptations to water scarcity.

42 ENGINEERING↗

DOE OSTI2020

Improving the performance of medical imaging applications using SYCL

As opposed to the Open Computing Language (OpenCL) programming model, in which host and device codes are generally written in different programming languages, SYCL can combine host and device codes for an application in a type-safe way to improve development productivity and performance portability. Hence, this report shows the experimental results of applying the SYCL programming model to medical imaging applications for a study on performance portability and programming productivity between OpenCL and SYCL. Rodinia is a widely used open-source benchmark suite for heterogeneous computing. We choose two medical imaging applications (Heart Wall and Particle Filter) in the benchmark suite, migrate the OpenCL implementations of the applications to the SYCL implementations, and evaluate their performance and productivity on Intel® microprocessors that contain a central processing unit (CPU) and an integrated graphics processing unit (GPU). The maturing SYCL compilers, which are based on a conformant implementation of the SYCL 1.2.1 Khronos specification, have been actively optimized for Intel® computing platforms. The experimental results are promising in terms of the raw performance and productivity. Although the SYCL implementation of the Heart Wall application does not execute successfully on a CPU, the SYCL implementations of the application can achieve comparable or better performance than the OpenCL implementation on Intel® integrated GPUs. For the Particle Filter application, the performance difference between the SYCL and OpenCL implementations is comparable on the GPUs for most cases, but the SYCL implementations are on average 4X faster than the OpenCL implementations on Intel® Xeon® CPUs. For programming productivity, we arguably use lines of code as a way to measure programming productivity in software. The SYCL programs reduce the lines of code of the OpenCL programs by 52% and 38% for the Heart Wall and Particle Filter, respectively. The results indicate that SYCL is a promising programming model for heterogeneous computing with the maturing compilers. We organize the remainder of the report as follows. Section II introduces the SYCL programming model, compares the major differences between an OpenCL program and a SYCL program, and describes the characteristics of the two applications. Section III describes the SYCL programming model in more details, and shows the SYCL implementation of a kernel function in the Particle Filter application as an example. In Section IV, we evaluate the performance of the applications on the CPUs and GPUs. Section V concludes the report.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Novel and Emerging Capabilities that Can Provide a Holistic Understanding of the Plant Root Microbiome

In recent years, the root microbiome (i.e., microorganisms growing inside, on, or in close proximity to plant roots) has been shown to play an important role in plant health and productivity. Despite its importance, the root microbiome is challenging to study because of its complexity, heterogeneity, and subterranean location. Fortunately, root microbiome research has seen a tremendous influx of novel technologies (e.g., imaging tools, robotics, and molecular analyses), experimental platforms (e.g., micro- and mesocosms), and data integration, modeling, and prediction tools in the past decade that have greatly increased our ability to dissect the complex network of interactions between above- and belowground environmental parameters, plants, bacteria, and fungi that dictate soil and broader ecosystem health. Herein, we discuss methods that are currently used in root microbiome research and that can be expanded to phytobiome research in general ranging from laboratory studies to mesocosm-scale studies and, finally, to field studies; evaluate their relevance to ecosystem studies; and discuss future root microbiome research directions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Dynamic Catalysis Fundamentals: I. Fast calculation of limit cycles in dynamic catalysis

Dynamic catalysis—the forced oscillation of catalytic reaction coordinate potential energy surfaces (PES)—has recently emerged as a promising method for the acceleration of heterogeneously-catalyzed reactions. Theoretical study of enhancement of rates and supra-equilibrium product yield via dynamic catalysis has, to-date, been severely limited by onerous computational demands of forward integration of stiff, coupled ordinary differential equations (ODEs) that are necessary to quantitatively describe periodic cycling between PESs. Here, we establish a new approach that reduces, by ≳108×, the computational cost of finding the time-averaged rate at dynamic steady state (i.e. the limit cycle for linear and nonlinear systems of kinetic equations). Our developments are motivated by and conceived from physical and mathematical insight drawn from examination of a simple, didactic case study for which closed-form solutions of rate enhancement are derived in explicit terms of periods of oscillation and elementary step rate constants. Generalization of such closed-form solutions to more complex catalytic systems is achieved by introducing a periodic boundary condition requiring the dynamic steady state solution to have the same periodicity as the kinetic oscillations and solving the corresponding differential equations by linear algebra or Newton-Raphson-based approaches. The methodology is well-suited to extension to non-linear systems for which we detail the potential for multiple solutions or solutions with different periodicities. For linear and non-linear systems alike, the acute decrement in computational expense enables rapid optimization of oscillation waveforms and, consequently, accelerates understanding of the key catalyst properties that enable maximization of reaction rates, conversions, and selectivities during dynamic catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Development of the Marble experimental platform at the National Ignition Facility

The Marble experimental platform at the National Ignition Facility (NIF) was developed to quantify the influence of heterogeneous mix on fusion burn. The platform utilizes a plastic capsule filled with a deuterated plastic foam of controlled coarseness, with tritium gas filling the voids in the foam. The capsule implosion is driven with x rays generated in an NIF Hohlraum in which the time-dependent symmetry of the implosion can be controlled via dynamic beam phasing. Importantly, the Hohlraum drive conditions can be understood via integrated 2D radiation-hydrodynamic simulations, and capsule implosions can be reliably calculated. After several years of development and experimentation, the NIF Marble platform has become successful and has produced important experimental results. Here, the experimental results, which will be presented in a future publication by the LANL Marble team, provide the first definitive examination of the influence of heterogeneous mix on thermonuclear burn.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Effect of Nucleation Heterogeneity on Mineral Precipitation in Confined Environments

Abstract The formation of new mineral phases in confined environments, especially in porous media, is crucial for various geological processes like mineralization and diagenesis. The nucleation and precipitation of minerals are initiated at the microscale through fluid‐rock interaction, where dissolution of primary phases leads to supersaturated conditions and nucleation and growth of secondary ones. Previous research has focused primarily on either precipitation or nucleation, without fully exploring their combined impact. Our study introduces a computational framework that integrates classical nucleation theory with the micro‐continuum method. We validated our model by comparing with experiments, and discovered that different surface nucleation rate changes the mode of precipitation from a preferential to uniform precipitate textures. Furthermore, our study uncovered that the conventional deterministic precipitation method tends to underestimate the permeability of the porous matrix. In contrast, the new framework significantly improves model accuracy by incorporating preferential precipitation and heterogeneous nucleation.

58 GEOSCIENCES↗

DOE OSTI2023

Review of quantitative methods to assess impacts of changing climate and socioeconomic conditions on Arctic transportation systems

Rapid climate and socioeconomic changes are transforming Arctic human- Earth systems. An integral part of these systems is mobility, which encompasses the transport of humans and goods into, out of, and between Arctic regions. Impacts of climate and socioeconomic drivers on Arctic mobility are heterogenous. Methodologies are needed to quantify these impacts in measures that can be linked with broader socioeconomic systems. This article reviews existing such methods and organizes them into a conceptual framework to understand trends and gaps in the literature. We found methods quantifying impacts of a range of climate drivers on most transportation modes present in the Arctic, but few methods focused on socioeconomic drivers. Also underrepresented were methods explicitly considering adaptive capacity of transportation systems. In conclusion, we provide insight into the data and relationships relevant to understanding impacts of Arctic change on transportation systems and how these impacts fit into broader human- Earth systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Modulating Operational Conditions to Mitigate Deactivation in Formate Dehydrogenation on Pd Phases

In heterogeneous catalysis, poisoning by surface-bound intermediates poses a major barrier to sustained catalyst performance in (de)hydrogenation reactions. Formate/bicarbonate systems, as liquid organic hydrogen carriers (LOHCs), offer a CO 2 -integrated, low-temperature pathway for hydrogen storage and release, making them attractive for circular energy applications. However, their lower hydrogen density and susceptibility to catalyst deactivation limit their competitiveness compared to conventional LOHCs like methylcyclohexane. Here, this study investigates the mechanistic origins of formate (HCOO – ) dehydrogenation and associated deactivation on Pd interfaces. Using density functional theory (DFT) simulations, we show that under thermocatalytic conditions, strongly bound formate accumulates on the catalyst surface (Pd(111)), blocking active sites, raising activation barriers, and leading to progressive performance loss. Because formate adsorption involves charge transfer, we exploit its sensitivity to electronic structure by modulating the electrochemical potential of the catalyst. Our results reveal that hydrogen transfer from water and formate exhibits opposing potential dependencies, providing insights into the opposing driving forces behind both catalytic activity and poisoning. To further probe this phenomenon, we examine electrochemically induced phase transitions in Pd, focusing on PdO(100) and PdH(110), which are stable under oxidizing and reducing potentials, respectively, and demonstrate enhanced dehydrogenation activity between −0.4 and 0.2 V vs standard hydrogen electrode (SHE). Complementary thermal treatments help decouple kinetic and thermodynamic contributions to intermediate binding. These findings underscore the critical role of the catalyst phase and external stimuli in dictating poison-active site interactions and highlight phase engineering as a promising strategy to mitigate deactivation. This work offers mechanistic insights and design principles for developing more resilient and efficient catalysts for LOHC applications under realistic operating conditions.

Pd phase↗

DOE OSTI2026

Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-Ion Battery Chemistry by Mass Spectrometry and Electrochemical Reaction Networks

The formation and stability of the solid-electrolyte interphase (SEI) play central roles in determining the long-term performance and safety of modern electrochemical energy storage systems. Despite decades of research, the SEI’s heterogeneous, dynamic, and multiphase nature has defied comprehensive molecular-level characterization, creating a critical knowledge gap that limits rational battery design. In this work, we introduce a computational−experimental framework that integrates high-throughput quantum chemistry calculations, data-driven electrochemical reaction networks (eCRNs), stochastic algorithms, and laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI-FTICR-MS) to unravel SEI formation in carbonatebased electrolytes without imposing predefined mechanisms. We constructed the most comprehensive eCRN to date, spanning over 10,000 species and 209 million reactions. Through stochastic network analysis, we successfully recovered 27 species that were previously reported in the literature and predicted 28 novel SEI species nearly doubling our scientific knowledge in this area. Each new species was rigorously confirmed through advanced mass spectral analysis of its distinct molecular and isotopic signatures. We kinetically refined the formation pathways for a select set of both previously reported and novel SEI products, revealing kinetically feasible elementary reaction mechanisms with activation barriers below 1 eV. This computational−experimental approach deepens our molecular-level understanding of SEI chemistry by resolving which species form and through which decomposition mechanisms they emerge. Such knowledge provides the foundation necessary to connect electrolyte composition to the resulting SEI components, a critical step toward a more informed electrolyte development in next-generation lithium-based batteries.

25 ENERGY STORAGE↗

DOE OSTI2024

Utilizing Distributed Heterogeneous Computing with PanDA in ATLAS

In recent years, advanced and complex analysis workflows have gained increasing importance in the ATLAS experiment at CERN, one of the large scientific experiments at LHC. Support for such workflows has allowed users to exploit remote computing resources and service providers distributed worldwide, overcoming limitations on local resources and services. The spectrum of computing options keeps increasing across the Worldwide LHC Computing Grid (WLCG), volunteer computing, high-performance computing, commercial clouds, and emerging service levels like Platform-as-a-Service (PaaS), Container-as-a-Service (CaaS) and Function-as-a-Service (FaaS), each one providing new advantages and constraints. Users can significantly benefit from these providers, but at the same time, it is cumbersome to deal with multiple providers, even in a single analysis workflow with fine-grained requirements coming from their applications’ nature and characteristics. In this paper, we will first highlight issues in geographically-distributed heterogeneous computing, such as the insulation of users from the complexities of dealing with remote providers, smart workload routing, complex resource provisioning, seamless execution of advanced workflows, workflow description, pseudointeractive analysis, and integration of PaaS, CaaS, and FaaS providers. We will also outline solutions developed in ATLAS with the Production and Distributed Analysis (PanDA) system and future challenges for LHC Run4.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Evolution of DUNE’s Production System

The DUNE experiment will start running in 2029 and record 30 PB/year of raw waveforms from Liquid Argon TPCs and photon detectors. The size of individual readouts can range from 100 MB to a typical 8 GB full readout of the detector, and even 100 TB for extended readouts from supernova candidates. These data then need to be cataloged, stored and distributed for processing worldwide. This massive amount of data and a heterogeneous computing environment necessitates a powerful and robust distributed computing infrastructure. In the process of building up that infrastructure, DUNE’s production system has recently undergone an overhaul, in which it has integrated 1) a new workflow management system (justIN) 2) a new data catalog (MetaCat) and 3) a state-of-the-art data management system (Rucio). Simulations of DUNE’s Far Detector and its prototypes ProtoDUNE Horizontal Drift (ProtoDUNE-HD) and ProtoDUNE Vertical Drift (ProtoDUNE-VD), as well as data from ProtoDUNE-HD serve as the first tests of this infrastructure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Structural characterization of ligand binding and pH-specific enzymatic activity of mouse Acidic Mammalian Chitinase

Chitin is an abundant biopolymer and pathogen-associated molecular pattern that stimulates a host innate immune response. Mammals express chitin-binding and chitin-degrading proteins to remove chitin from the body. One of these proteins, Acidic Mammalian Chitinase (AMCase), is an enzyme known for its ability to function under acidic conditions in the stomach but is also active in tissues with more neutral pHs, such as the lung. Here, we used a combination of biochemical, structural, and computational modeling approaches to examine how the mouse homolog (mAMCase) can act in both acidic and neutral environments. We measured kinetic properties of mAMCase activity across a broad pH range, quantifying its unusual dual activity optima at pH 2 and 7. We also solved high-resolution crystal structures of mAMCase in complex with oligomeric GlcNAcn, the building block of chitin, where we identified extensive conformational ligand heterogeneity. Leveraging these data, we conducted molecular dynamics simulations that suggest how a key catalytic residue could be protonated via distinct mechanisms in each of the two environmental pH ranges. These results integrate structural, biochemical, and computational approaches to deliver a more complete understanding of the catalytic mechanism governing mAMCase activity at different pH. Engineering proteins with tunable pH optima may provide new opportunities to develop improved enzyme variants, including AMCase, for therapeutic purposes in chitin degradation.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2015

Operator Informational Needs for Multiple Autonomous Small Vehicles

With the anticipated explosion of small unmanned aerial vehicles, it is highly likely that operators will be controlling fleets of autonomous vehicles. To fulfill the promise of autonomy, vehicle operators will not be concerned with manual control of the vehicle; instead, they will deal with the overall mission. Furthermore, the one operator to many vehicles is becoming a constant meme with various industries including package delivery, search and rescue, and utility companies. In order for an operator to concurrently control several vehicles, his station must look and behave very differently than the current ground control station instantiations. Furthermore, the vehicle will have to be much more autonomous, especially during non-normal operations, in order to accommodate the knowledge deficit or the information overload of the operator in charge of several vehicles. The expected usage increase of small drones requires presenting the operational information generated by a fleet of heterogeneous autonomous agents to an operator. NASA Langley Research Center's Autonomy Incubator has brought together researchers in various disciplines including controls, trajectory planning, systems engineering, and human factors to develop an integrated system to study autonomy issues. The initial human factors effort is focusing on mission displays that would give an operator the overall status of all autonomous agents involved in the current mission. This paper will discuss the specifics of the mission displays for operators controlling several vehicles.

Trujillo, Anna C.↗

DOE OSTI2020

ICME and In-Situ Process Monitoring for Rapid Qualification of Components Made by Laser-based Powder Bed Additive Manufacturing Processes for Nuclear Structural Applications

Additive manufacturing (AM) through selective powder bed melting of successive layers is being considered as disruptive technology for rapid production of low-cost nuclear reactor internal components with complex geometries. However, there is a potential for non-uniform distribution of physical features, such as porosity or microstructural differences, due to variations of temperature across a component build. These heterogeneities make the deployment of traditional material qualification and non-destructive evaluation of AM components difficult. This research project explored the feasibility of using in-situ process monitoring methods and integrated computational materials engineering (ICME) principles as an alternate qualification methodology and approach. This project included six individual tasks: (i) design of artifacts relevant to the nuclear power industry, (ii) evaluation of laser processing and in-situ measurements, (iii) computational modeling, (iv) ex-situ microstructural characterization, (v) evaluation of scaling the methodology for large-scale structures, and (vi) development of a data package to codes and standards organizations. As a part of this research, laser powder bed fusion of metals (316L, Alloy 718, and Ti6Al4V) was explored. This document provides an overview of the research performed over three years and serves as the final U.S. Department of Energy report for this project. In the third year, the project focused on the following activities: (a) in-situ infrared and optical imaging of each layer during processing of representative stainless steel geometries; (b) development of methodologies to analyze the data; and (c) application of ICME methodologies and other experiments to estimate the relevance of defects and microstructure to tensile properties.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗