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DOE OSTI2022

Impact of 2D-3D heterointerface on remote epitaxial interaction through graphene

Remote epitaxy has drawn attention as it offers epitaxy of functional materials that can be released from the substrates with atomic precision. The realization of remote epitaxy leads to profound impact on production and heterointegration of flexible, transferrable, and stackable freestanding single-crystalline membranes, which can be extremely useful in manufacturing next generation electronic and photonic devices. In addition, the remote interaction of atoms and adatoms through two-dimensional (2D) materials in remote epitaxy allows investigation and utilization of electrical/chemical/physical coupling of bulk (3D) materials via 2D materials (3D-2D-3D coupling). Here, we unveil the respective roles and impacts of the substrate material, graphene, substrate-graphene interface, and epitaxial material for electrostatic coupling of these materials. The coupling governs cohesive ordering and can lead to single-crystal epitaxy in the overlying film. We show that simply coating a graphene layer on wafers does not guarantee successful implementation of remote epitaxy, since atomically precise control of the graphene-coated interface is required. Also, it provides key considerations for maximizing the remote electrostatic interaction between the substrate and adatoms. This was enabled by exploring various material systems and processing conditions, and we demonstrate that the rules of remote epitaxy vary significantly depending on the ionicity of material systems as well as the graphene-substrate interface and the epitaxy environment. The general rule of thumb discovered here enables expanding 3D material libraries that can be stacked in freestanding form.

Lu, KUANGYE↗

DOE OSTI2025

ORBITaL-Net: A labeled training library for large-scale building feature extraction

Over the course of several years, nearly 1.5 million building outlines have been created from approximately 128,000 training tiles covering roughly 7,000 km 2 of very high-resolution multispectral overhead imagery, primarily dated between 2010 and 2020. This dataset, dubbed the Oak Ridge Building Image and TrAining Label Net (ORBITaL-Net), is designed for machine learning applications and is global in scope, with samples drawn from 72 countries across North America, South America, Africa, Europe, and Asia. ORBITaL-Net captures a great diversity in geographic setting, structural characteristics, land use (urban and rural), terrain, and imagery conditions. While the labeled building outlines are themselves valuable, the dataset’s true strength lies in the pairing of these labels with corresponding reference imagery, which is being released for open source use. Similar to SpaceNet and Replicable AI For Microplanning (ramp), this building outline dataset will allow the larger computer vision community from academia, government, and industry the opportunity to develop robust, scalable, and generalizable geospatial machine learning techniques. Unlike SpaceNet and ramp, which offer high resolution labels and imagery primarily for large urban cities, ORBITaL-Net is not focused on training samples from heavily populated areas but instead aims to capture the innate variability of conditions present in both the physical environment and imagery collections.

Geography↗

DOE OSTI2020

Activity profiling and crystal structures of inhibitor-bound SARS-CoV-2 papain-like protease: A framework for anti–COVID-19 drug design

Viral papain-like cysteine protease (PLpro, NSP3) is essential for SARS-CoV-2 replication and represents a promising target for the development of antiviral drugs. Here, we used a combinatorial substrate library and performed comprehensive activity profiling of SARS-CoV-2 PLpro. On the scaffold of the best hits from positional scanning, we designed optimal fluorogenic substrates and irreversible inhibitors with a high degree of selectivity for SARS PLpro. We determined crystal structures of two of these inhibitors in complex with SARS-CoV-2 PLpro that reveals their inhibitory mechanisms and provides a molecular basis for the observed substrate specificity profiles. Last, we demonstrate that SARS-CoV-2 PLpro harbors deISGylating activity similar to SARSCoV-1 PLpro but its ability to hydrolyze K48-linked Ub chains is diminished, which our sequence and structure analysis provides a basis for. Together, this work has revealed the molecular rules governing PLpro substrate specificity and provides a framework for development of inhibitors with potential therapeutic value or drug repurposing.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Visualizing Comparisons of Bill of Materials

Protecting critical infrastructure from cyber attacks, natural disasters, and other disruptions is a priority of the U.S. Government. Critical infrastructure includes providing electricity to homes and businesses, supplying natural gas for heating, and producing renewable energy sources. A loss of these services, as seen in the Solarwinds supply chain attack in 2020 , Texas snowstorm of 2021, the Colonial Pipeline cyber incident of 2021, and the Washington power substation attacks in 2022 result in high costs to consumers, disruption of everyday life, and even death. To protect the infrastructure, we first have to know what equipment we are protecting. The complexity of distributed manufacturing and development coupled with the increasing prevalence of cyber and supply chain attacks necessitates a greater understanding of the hardware and software components that comprise equipment in critical infrastructure. When a vulnerability in a single software library can have disastrous consequences, it is vital to understand critical equipment and systems at a granular level. This need has led to increased energy around the development and incorporation of bill-of-materials (BOM) into existing asset management practices to aid in mitigating, and responding to future attacks \cite{noauthor_software_nodate}. While much of the current research is devoted to creating BOMs, it is equally important to develop methodologies for leveraging BOMs to answer questions, such as: How has my software changed? Are two pieces of equipment equivalent? Does this piece of equipment that just arrived match my historical information? In this work, we demonstrate how BOMs can be represented by graph structures. We then describe how these structures can be fed into a graph comparison algorithm to produce a novel interactive visualization that allows us to not only identify differences in BOMs, but show exactly where they are in the product.

Jones, Rebecca D.↗

DOE OSTI2023

The first two chromosome‐scale genome assemblies of American hazelnut enable comparative genomic analysis of the genus Corylus

Summary The native, perennial shrub American hazelnut ( Corylus americana ) is cultivated in the Midwestern United States for its significant ecological benefits, as well as its high‐value nut crop. Implementation of modern breeding methods and quantitative genetic analyses of C. americana requires high‐quality reference genomes, a resource that is currently lacking. We therefore developed the first chromosome‐scale assemblies for this species using the accessions ‘Rush’ and ‘Winkler’. Genomes were assembled using HiFi PacBio reads and Arima Hi‐C data, and Oxford Nanopore reads and a high‐density genetic map were used to perform error correction. N50 scores are 31.9 Mb and 35.3 Mb, with 90.2% and 97.1% of the total genome assembled into the 11 pseudomolecules, for ‘Rush’ and ‘Winkler’, respectively. Gene prediction was performed using custom RNAseq libraries and protein homology data. ‘Rush’ has a BUSCO score of 99.0 for its assembly and 99.0 for its annotation, while ‘Winkler’ had corresponding scores of 96.9 and 96.5, indicating high‐quality assemblies. These two independent assemblies enable unbiased assessment of structural variation within C. americana , as well as patterns of syntenic relationships across the Corylus genus. Furthermore, we identified high‐density SNP marker sets from genotyping‐by‐sequencing data using 1343 C. americana , C. avellana and C. americana × C. avellana hybrids, in order to assess population structure in natural and breeding populations. Finally, the transcriptomes of these assemblies, as well as several other recently published Corylus genomes, were utilized to perform phylogenetic analysis of sporophytic self‐incompatibility (SSI) in hazelnut, providing evidence of unique molecular pathways governing self‐incompatibility in Corylus .

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗

DOE OSTI2021

Core Analysis E-Reports Produced for the Southwest Regional Partnership on Carbon Sequestration for Wells 13-10A, 13-14, and 32-8 of the Farnsworth Unit, Texas

The submission is three electronic reports (e-reports) produced by Terra Tek, a former Schlumberger company, for and under the oversight of the Southwest Regional Partnership on Carbon Sequestration (SWP). The SWP designed and implemented a coring and core analysis program in conjunction with the previous field operator Chaparral Energy, L.L.C. The main SWP contacts who oversaw the coring and core analysis program, including geologic core descriptions and sample selection for testing by the Terra Tek, are listed below in the Authors section. The three reports are for Wells 13-10A, 13-14, and 32-8 of the Farnsworth Unit, TX, a site of the SWP's CO2 storage and enhanced oil recovery project. The e-reports include many data types that are not listed in full detail here, but may include: geomechanical, geochemical, and petrophysical measurements; white light and UV core photos; spectral gamma logs on the core; and Heterogeneous Rock Analysis logs. Fracture core review reports are included for Wells 13-14 and 32-8. The three e-reports each have many subfolders with the various types of data in spreadsheets, pdfs, image files, or other formats. The main e-reports for each well are listed by the well name. The sub-folder “E-Report” for each well has a Report.html file, which, when opened, will have hyperlinks to the various data sets and information. The files in the zipped folder will need to be extracted for the Report.html files to work properly. These authors thank Joseph Hall, a geologist formerly of Chaparral Energy, L.L.C., for assistance in designing the coring program, his geologic expertise of the Farnsworth Unit, and his assistance with characterizing the core. Christopher Gillespie, of Terra Tek at the time, managed the myriad geomechanical, geochemical, and petrophysical measurements provided by Terra Tek for this project. The core from which the samples were collected for this project are housed at the Subsurface Data and Core Libraries of the New Mexico Bureau of Geology and Mineral Resources, Socorro, New Mexico, USA. Funding for this project is provided by the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) through the Southwest Regional Partnership on Carbon Sequestration (SWP) under Award No. DE-FC26-05NT42591. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. These e-reports describe objective technical results and analysis. Any subjective views or opinions that might be expressed in the reports do not necessarily represent the views of the US Department of Energy or the United States Government.

Caprock↗

DOE OSTI2022

Taylor wave solution for a general equation of state

This document describes a solution procedure for calculating the Taylor wave behind an unsupported Chapman–Jouguet (CJ) detonation in planar, cylindrical, and spherical geometries given a general equation of state. The resulting semi-analytic solution can be utilized to examine new equation of state models for detonation products and during the verification of hydrodynamic codes. The governing partial differential equations are reduced to ordinary differential equations in both characteristic and self-similar forms. The first-order systems corresponding to each geometry are amenable to solution numerically using commonly available methods. A difficulty arises at the CJ point in radial coordinates where the similarity equations become singular. Two separate strategies are proposed to integrate the first-order system. The first one uses an asymptotic approximation near the CJ point that can be used to perturb the boundary conditions. The second one applies a change of variables which removes the singularity at the expense of an additional equation to be integrated. A test problem is provided for the Davis products equation of state to illustrate the qualitative features of the Taylor wave in each geometric configuration and compared with a Lagrangian hydrodynamics research code. A Python code listing gives an implementation using the SciPy library to assists users in generating the results.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty

Bayesian inference provides a systematic framework for integration of data with mathematical models to quantify the uncertainty in the solution of the inverse problem. However, the solution of Bayesian inverse problems governed by complex forward models described by partial differential equations (PDEs) remains prohibitive with black-box Markov chain Monte Carlo (MCMC) methods. We present hIPPYlib-MUQ, an extensible and scalable software framework that contains implementations of state-of-the art algorithms aimed to overcome the challenges of high-dimensional, PDE-constrained Bayesian inverse problems. These algorithms accelerate MCMC sampling by exploiting the geometry and intrinsic low-dimensionality of parameter space via derivative information and low rank approximation. The software integrates two complementary open-source software packages, hIPPYlib and MUQ. hIPPYlib solves PDE-constrained inverse problems using automatically-generated adjoint-based derivatives, but it lacks full Bayesian capabilities. MUQ provides a spectrum of powerful Bayesian inversion models and algorithms, but expects forward models to come equipped with gradients and Hessians to permit large-scale solution. By combining these two complementary libraries, we created a robust, scalable, and efficient software framework that realizes the benefits of each and allows us to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering disciplines. To illustrate the capabilities of hIPPYlib-MUQ, we present a comparison of a number of MCMC methods available in the integrated software on several high-dimensional Bayesian inverse problems. These include problems characterized by both linear and nonlinear PDEs, various noise models, and different parameter dimensions. The results demonstrate that large (~ 50×) speedups over conventional black box and gradient-based MCMC algorithms can be obtained by exploiting Hessian information (from the log-posterior), underscoring the power of the integrated hIPPYlib-MUQ framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

DOE OSTI2026

Two-Level Sketching Alternating Anderson Acceleration for Complex Physics Applications

We present a novel two-level sketching extension of the Alternating Anderson–Picard (AAP) method for accelerating fixed-point iterations in challenging single- and multiphysics simulations governed by discretized PDEs. Our approach combines a static, physics-based projection that reduces the least-squares (LS) problem to the most informative field (e.g., via Schur-complement insight) with a dynamic, algebraic sketching stage driven by a backward stability analysis under Lipschitz continuity. We introduce inexpensive estimators for stability thresholds and cache-aware randomized selection strategies to balance computational cost against memory access overhead. The resulting algorithm solves reduced LS systems in place, minimizes memory footprints, and seamlessly alternates between low-cost Picard updates and Anderson mixing. Implemented in Julia, our two-level sketching AAP achieves up to 50% time-to-solution reductions compared to standard Anderson acceleration—without degrading convergence rates—on benchmark problems including Stokes, 𝑝-Laplacian, bidomain, and Navier–Stokes formulations at varying problem sizes. These results demonstrate the method’s robustness, scalability, and potential for integration into high-performance scientific computing frameworks. Our implementation is available open source in the AAP.jl library.

Barnafi, Nicolas [University of Chile, Santiago]↗

DOE OSTI2026

Single-Molecule Electron Transport in Peptoids

Peptoids are structural analogs of peptides in which side chains are appended to the backbone nitrogen rather than the α-carbon. The sequence-defined modularity of peptoids enables precise control over structure−function relationships, enabling applications in energy storage and biomedical materials. Despite recent progress, the role of sequence and conformation on electron transport in peptoid molecules is not fully understood. Here, we synthesize a library of peptoid oligomers and characterize their molecular electronic properties using the scanning tunneling microscope-break junction (STM-BJ) technique. Our results show well-defined electron transport behavior for peptoid sequences containing aromatic side groups lacking hydrogen bonds (H-bonds) and without chemical substitutions at the N−C α position. This behavior fundamentally differs from electron transport in peptides, where H-bond interactions give rise to higher conductance states. All-atom molecular dynamics (MD) simulations are used to understand the conformational heterogeneity of peptoids, and molecular conformations obtained from MD simulations are used in quantum mechanical calculations based on the nonequilibrium Green’s function−density functional theory (NEGF-DFT) formalism. In all cases, computational results are in reasonable qualitative agreement with experiments. Our work demonstrates that the conductance behavior of peptoids depends on monomer identity, including side-chain aromaticity and substitution at the N−C α position. Overall, this work provides new insights into the structure−function relationships governing electron transport in peptoid-based materials and establishes design rules for peptoid-based molecular junctions.

Charge transport↗

DOE OSTI2021

Zinc binding alters the conformational dynamics and drives the transport cycle of the cation diffusion facilitator YiiP

YiiP is a secondary transporter that couples Zn 2+ transport to the proton motive force. Structural studies of YiiP from prokaryotes and Znt8 from humans have revealed three different Zn 2+ sites and a conserved homodimeric architecture. These structures define the inward-facing and outward-facing states that characterize the archetypal alternating access mechanism of transport. To study the effects of Zn 2+ binding on the conformational transition, we use cryo-EM together with molecular dynamics simulation to compare structures of YiiP from Shewanella oneidensis in the presence and absence of Zn 2+ . To enable single-particle cryo-EM, we used a phage-display library to develop a Fab antibody fragment with high affinity for YiiP, thus producing a YiiP/Fab complex. To perform MD simulations, we developed a nonbonded dummy model for Zn 2+ and validated its performance with known Zn 2+ -binding proteins. Using these tools, we find that, in the presence of Zn 2+ , YiiP adopts an inward-facing conformation consistent with that previously seen in tubular crystals. After removal of Zn 2+ with high-affinity chelators, YiiP exhibits enhanced flexibility and adopts a novel conformation that appears to be intermediate between inward-facing and outward-facing states. This conformation involves closure of a hydrophobic gate that has been postulated to control access to the primary transport site. Comparison of several independent cryo-EM maps suggests that the transition from the inward-facing state is controlled by occupancy of a secondary Zn 2+ site at the cytoplasmic membrane interface. This work enhances our understanding of individual Zn 2+ binding sites and their role in the conformational dynamics that govern the transport cycle.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Metal-organic frameworks as effective sensors and scavengers for toxic environmental pollutants

Abstract Metal-organic frameworks (MOFs) constructed from a rich library of organic struts and metal ions/clusters represent promising candidates for a wide range of applications. The unique structure, porous nature, easy tunability and processability of these materials make them an outstanding class of materials for tackling serious global problems relating to energy and environment. Among them, environmental pollution is one aspect that has increased at an alarming rate in the past decade or so. With rapid urbanization and industrialization, toxic environmental pollutants are constantly released and accumulated leading to serious contamination in water bodies and thereby having adverse effects on human health. Recent studies have shown that many toxic pollutants, as listed by the World Health Organization and the US Environmental Protection Agency, can be selectively detected, captured, sequestered and removed by MOFs from air and aquatic systems. Most of these sensing/capture processes in MOFs are quantifiable and effective for even a trace amount of the targeted chemical species. The functional sites (ligands and metals) play a critical role in such recognition processes and offer an extensive scope of structural tunability for guest (pollutants, toxic entities) recognition. Whereas on the one hand, the underlying mechanisms governing such sensing and capture are important, it is also crucial to identify MOFs that are best suited for commercial applications for the future. In this review article, we provide an overview of the most recent progress in the sensing, capture and removal of various common toxic pollutants, including neutral and ionic, inorganic and organic species, with brief discussions on the mechanism and efficacy of selected MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Thermally Activated Delayed Photoluminescence: Deterministic Control of Excited-State Decay

Thermally activated photophysical processes are ubiquitous in numerous organic and metal-organic molecules, leading to chromophores with excited state properties that can be considered an equilibrium mixture of the available low-lying states. Relative populations of the equilibrated states are governed by temperature. Such molecules have been devised as high quantum yield emitters in modern organic light-emitting diode technology and for deterministic excited state lifetime control to enhance chemical reactivity in solar energy conversion and photocatalytic schemes. This recent discovery of thermally activated photophysics at CdSe nanocrystal-molecule interfaces enables a new paradigm wherein molecule-quantum dot constructs are used to systematically generate material with predetermined photophysical response and excited state properties. Semiconductor nanomaterials feature size-tunable energy level engineering, which considerably expands the purview of thermally activated photophysics beyond what is possible using only molecules. This Perspective is intended to provide a non-exhaustive overview of the advances that led to the integration of semiconductor quantum dots in thermally activated delayed photoluminescence (TADPL) schemes and to identify important challenges moving into the future. The initial establishment of excited state lifetime extension utilizing triplet-triplet excited-state equilibria is detailed. Next, advances involving the rational design of molecules composed of both metal-containing and organic-based chromophores that produce the desired TADPL are described. Lastly, the recent introduction of semiconductor nanomaterials into hybrid TADPL constructs is discussed, paving the way towards the realization of fine-tuned deterministic control of excited state decay. It is envisioned that libraries of synthetically facile composites will be broadly deployed as photosensitizers and light emitters for numerous synthetic and optoelectronic applications in the near future.

14 SOLAR ENERGY↗

DOE OSTI2022

Total thermal neutron cross section measurements of hydrogen dense polymers from 0.0005–20 eV

Hydrogen dense polymers, specifically polyethylene, polystyrene, and Plexiglas, have served as neutron moderator and reflector materials in hundreds of separate critical benchmark experiments because of their low cost and abundance of hydrogen. In order to accurately model and simulate these critical benchmarks, the thermal scattering law (TSL) evaluation that governs how neutrons will thermalize must be well understood and rigorously validated. To support this validation, researchers at Rensselaer Polytechnic Institute performed total neutron cross section measurements for high-density polyethylene & polystyrene over the energy range 0.0005–20 eV and for Plexiglas G & Plexiglas G-UVT over the energy range 0.0005–3 eV. Comparisons were made between the measured cross section and that predicted by the ENDF/B-VIII.0 and Oak Ridge National Laboratory/European Spallation Source/Rensselaer Polytechnic Institute TSL evaluations for polyethylene, Plexiglas, and polystyrene, as available. These experiments represent the first total neutron cross section measurements for polystyrene.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Deuteron-induced reactions on natural Zr from threshold to 50 MeV: production of 86g Y

Two stacks of thin Zr foils were irradiated with 30 and 50 MeV deuterons, respectively, using the Lawrence Berkeley National Laboratory 88-Inch Cyclotron, and 19 excitation functions for nat Zr(d,x) reactions were measured over a beam energy range of 6.3–47.64 MeV, where the independent cross sections for nat Zr(d,x) 88 Nb and nat Zr(d,x) 86m,g Y were measured for the first time. The well-characterized nat Fe(d,x) 56 Co, nat Ni(d,x) 56 Co, nat Ni(d,x) 58 Co, nat Ni(d,x) 61 Cu, nat Ti(d,x) 46 Sc and nat Ti(d,x) 48 V monitor reactions were used to determine the deuteron beam current throughout the stacks. All cross sections were determined using High Purity Germanium (HPGe) detector γ-ray spectroscopy. A variance minimization technique was employed to simultaneously constrain the deuteron beam currents with multiple monitor reactions, thus reducing systematic uncertainties. An additional 16 channels are reported for reactions on the nickel, titanium, and iron monitor foils, leading to a total of 35 excitation functions, with seven reaction channels reported for the first time in this work. The measured excitation functions are compared to calculations provided by the reaction modeling codes TALYS – 2.0, ALICE – 2020, CoH – 3.5.3 and EMPIRE – 3.2.3, as well as the TENDL – 2023 data library. The degree of agreement between theory and experiments is discussed. The possible production of the important PET radionuclide 86g Y via the nat Zr(d,x) route was critically examined. The physical yields for nat Zr(d,x) 86 Y and other yttrium isotopes produced were calculated and compared to other production pathways. Due to high-level of associated radionuclide impurities, this route cannot deliver 86g Y suitable for medical applications.

86gY↗

DOE OSTI2023

Virtual Engineering Software Framework for Integrated Biomass Conversion Modeling

This presentation covers the design and implementation of a software tool to systematically connect computational models of unit operations to simulate an integrated process of low-temperature conversion of biomass to fuel. This virtual engineering (VE) software was designed with the overarching goal of connecting unit models written in various programming languages and requiring different computational resources within a single, flexible framework. The models and features currently considered for the VE library include mechanistic models for pretreatment, enzymatic hydrolysis, and aerobic bioreaction; high-fidelity computational fluid dynamics (CFD) simulations for enzymatic hydrolysis and aerobic bioreaction; and the capability to perform techno-economic analyses (TEA) using Aspen Plus, a commercial software package. The CFD models require access to high-performance computing (HPC) resources, so in addition to handling multiple programming languages and interfaces, the VE software must also be capable of interacting with an HPC scheduler to submit, run, and post-process jobs. Using the Python programming language, a new VE software package has been developed that contains functionality to manage the input-output communication between various unit models, schedule simulations to run on NREL's HPC and analyze those results, and interface with existing TEA software workflows. A Jupyter-notebook GUI was also created to solicit user input and provide documentation. In cases where multiple models for a particular unit-operation exist, selection between models is accomplished through a simple checkbox, with the appropriate inputs and outputs being parsed and converted seamlessly in the background. Each operation makes use of a different programming language, but the flow of information from pretreatment to enzymatic hydrolysis to bioreaction is managed with an intuitive, centralized file-communication strategy. In this talk, the programming approach and implementation details of the notebook are presented for multiple possibilities of the conversion process, including a demonstration of the ability to manage HPC resources. Additionally, an example of a sensitivity study of treatment parameters governing the overall conversion outcome is shown which highlights the ease of defining new problems using the VE Notebook workflow and leads into a discussion of ongoing work to enable outer-loop optimization studies.

biofuel↗