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DOE OSTI2022

Support Vector Machines for Classification of Direct Energy Deposition Standoff Distance for Improved Process Control

A critical factor in the implementation of direct energy deposition is the ability to maintain the standoff distance between the nozzle and the build surface, as this influences powder capture efficiency and overall part quality. Due to process-related variations, layer height may vary, causing unintended variation in standoff distance and poor build quality. While prior work has utilized contact probing to qualify standoff distance during processing, in situ methods for qualification of standoff distance are of major interest. The present work seeks to understand efficacy of image-based methods for classifying standoff distance variation in real-time using support vector machines (SVMs). It was hypothesized that the size of the melt pool and the amount of spatter will have significant correlations with deviations in the standoff distance; thus, SVMs were used on a dataset that is comprised of morphological features of melt pool size and image entropy. The SVM model was used to classify melt pool images into categories according to standoff distance variation from nominal. K-folds cross validation was used to find the optimal hyperparameters for the SVM model. To understand the impact of the selected features on the classification performance and inference speed, multiple models were trained with differing numbers of included features. Results for classification score, inference time, and image preprocessing/feature extraction from these data are reported. The present results show that the SVM model was able to predict the standoff distance classification with an accuracy of 97 percent and a speed of 0.122 s per image, making it a viable solution for real-time control of standoff distance.

Klesmith, Zoe↗

DOE OSTI2023

Multiphysics Analysis of the MSRE Experiment Using Griffin-SAM Coupled Code System

Molten salt reactors (MSRs) with flowing fuel have the unique feature of utilizing the fuel salt for heat generation and extraction at the same time since the fuel salt is circulating through the whole primary loop of the reactor. This movement of the fuel salt results in a partial decay of the delayed neutron precursors (DNPs) outside the core and corresponding redistribution in the active core region. To capture this phenomenon accurately, neutronics and thermal hydraulics computational tools need to be modified to handle the movement of the DNPs and their decay. Idaho and Argonne National Laboratories are actively working on developing neutronics and thermal hydraulics tools to model MSRs with flowing fuel. The neutronics code Griffin and the thermal hydraulics code SAM were extended to handle flowing fuel with the drift of the DNPs under the MOOSE framework. In this work, a simplified Multiphysics model of the Molten Salt Reactor Experiment (MSRE) is developed and utilized to perform steady-state and transient analyses. The MSRE experiments were designed to show the impact of the DNPs losses on core reactivity. The following section provides a description of the MSRE experiment with the core main parameters used to develop the model. Then, the developed Multiphysics model of the MSRE is presented. Finally, steady-state verification tests and unprotected loss of flow transient tests are discussed followed by a summary and conclusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

CNRS Molten Salt Reactor Benchmark Analysis Using Griffin-Pronghorn Coupled Multi-physics Code System

Molten salt reactors (MSRs) with flowing fuel have the unique feature of utilizing the fuel salt for heat generation and extraction at the same time, since the fuel salt is circulating through the whole primary loop. This movement of fuel salt results in a partial decay of the delayed neutron precursors (DNPs) outside the core and the corresponding redistribution of the DNPs in the active region of the core. To capture this effect, neutronics and thermal-hydraulics (T/H) codes need to be able to handle the movement of DNPs and their decay [1, 2]. Idaho National Laboratory (INL) is actively working on developing the neutronics and T/H codes to model the MSRs with flowing fuel. As one of the efforts, the neutronics code Griffin [3] and the T/H code Pronghorn [4] that are built upon the MOOSE framework [5] have been extended to handle the flowing fuel involving the drift of DNPs, and this capability is being tested and verified with MSR benchmark problems including the CNRS benchmark problem [6]. Additionally, a multi-physics analysis of the molten salt reactor experiment (MSRE) is being conducted to verify and validate the codes against available experimental data [7]. This work presents the analysis of the CNRS benchmark problem using the Griffin-Pronghorn coupled multi-physics code system of INL. Both steady-state and transient problems are analyzed, and the results are compared with those of other participants presented in [6]. The following section provides a description of the benchmark, along with input parameters and observables for each step. Then, the results for each step are presented in comparison with other participants’ results, followed by summary and conclusion.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Hydropower Fish Passage Webmap

The National Fish Passage Webmap application provides an environment that allows users to visualize information information on fish passage facility existence, type, and direction at hydropower developments across the conterminous United States. It was developed through collaborative partnerships with fish passage engineers and biologists at both the US Fish and Wildlife Service (USFWS) and the National Marine Fisheries Service (NMFS), and hydropower experts at the Low Impact Hydropower Institute (LIHI). Data on fish passage facilities at hydropower features were compiled from numerous sources including published and non-published datasets, published reports, email communications with federal and state resource managers and hydropower operators, and by extracting information from regulatory documents within the FERC eLibrary. The number of sources for a given feature varied, which occasionally resulted in conflicting information regarding the existence of fish passage facilities or in the type or sub-type of passage technologies. Such discrepancies were reviewed and resolved individually, based on the weight of evidence or, when available, on direct observations from information providers or aerial imagery.

13 HYDRO ENERGY↗

DOE OSTI2016

High Brightness Room Temperature III-Nitride Based Single Photon Source

Single photon sources (SPS) are quantum light sources where photons are emitted one at a time instead of randomly (e.g. lasers) or in a bunch (e.g. thermal) that can significantly impact quantum information science (computing and secure communications) and quantum metrology. Some highly desirable features of SPS are low second order correlation (g 2 ),controllable emission, electrically injected room temperature operation with high photon rate, high extraction efficiency and controllable directionality. Approaches taken thus far using different material systems have only addressed a subset of these features. III-nitride based approach offers a clear pathway to deterministic, room temperature (R.T.), electrically injected practical SPS as one can potentially also leverage the knowledge and technology from the light emitting diode (LED) world. Here we will describe a hybrid approach wherein a TiO2 based photonic crystal (PC) cavity is fabricated around an InGaN quantum dot (QD) embedded nanoscale post deterministically placed inside a photonic crystal cavity. This project takes the initial steps necessary to achieve a practical, compact SPS. We have used finite difference time domain simulations to optimize the cavity design to achieve high quality factor, mode overlap with QD and high extraction. We have fabricated InGaN quantum dots using a top-down approach involving dry etch and photoelectrochemical etch followed by electron beam lithography based nanofabrication of photonic crystal cavities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Modeling occupancy distribution in large spaces with multi-feature classification algorithm

We present that occupancy information enables robust and flexible control of heating, ventilation, and air-conditioning (HVAC) systems in buildings. In large spaces, multiple HVAC terminals are typically installed to provide cooperative services for different thermal zones, and the occupancy information determines the cooperation among terminals. However, a person count at room-level does not adequately optimize HVAC system operation due to the movement of occupants within the room that creates uneven load distribution. Without accurate knowledge of the occupants’ spatial distribution, the uneven distribution of occupants often results in under-cooling/heating or over-cooling/heating in some thermal zones. Therefore, the lack of high-resolution occupancy distribution is often perceived as a bottleneck for future improvements to HVAC operation efficiency. To fill this gap, this study proposes a multi-feature k-Nearest-Neighbors (k-NN) classification algorithm to extract occupancy distribution through reliable, low-cost Bluetooth Low Energy (BLE) networks. An on-site experiment was conducted in a typical office of an institutional building to demonstrate the proposed methods, and the experiment outcomes of three case studies were examined to validate detection accuracy. One method based on City Block Distance (CBD) was used to measure the distance between detected occupancy distribution and ground truth and assess the results of occupancy distribution. Finally, the results show the accuracy when CBD = 1 is over 71.4% and the accuracy when CBD = 2 can reach up to 92.9%.

42 ENGINEERING↗

DOE OSTI2023

gRNA-SeqRET: a universal tool for targeted and genome-scale gRNA design and sequence extraction for prokaryotes and eukaryotes

High-throughput genetic screening is frequently employed to rapidly associate gene with phenotype and establish sequence-function relationships. With the advent of CRISPR technology, and the ability to functionally interrogate previously genetically recalcitrant organisms, non-model organisms can be investigated using pooled guide RNA (gRNA) libraries and sequencing-based assays to quantitatively assess fitness of every targeted locus in parallel. To aid the construction of pooled gRNA assemblies, we have developed an in silico design workflow for gRNA selection using the gRNA Sequence Region Extraction Tool (gRNA-SeqRET). Built upon the previously developed CCTop, gRNA-SeqRET enables automated, scalable design of gRNA libraries that target user-specified regions or whole genomes of any prokaryote or eukaryote. Additionally, gRNA-SeqRET automates the bulk extraction of any regions of sequence relative to genes or other features, aiding in the design of homology arms for insertion or deletion constructs. We also assess in silico the application of a designed gRNA library to other closely related genomes and demonstrate that for very closely related organisms Average Nucleotide Identity (ANI) > 95% a large fraction of the library may be of relevance. The gRNA-SeqRET web application pipeline can be accessed at https://grna.jgi.doe.gov. The source code is comprised of freely available software tools and customized Python scripts, and is available at https://bitbucket.org/berkeleylab/grnadesigner/src/master/ under a modified BSD open-source license (https://bitbucket.org/berkeleylab/grnadesigner).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Identifying local structural states in atomic imaging by computer vision

Abstract The availability of atomically resolved imaging modalities enables an unprecedented view into the local structural states of materials, which manifest themselves by deviations from the fundamental assumptions of periodicity and symmetry. Consequently, approaches that aim to extract these local structural states from atomic imaging data with minimal assumptions regarding the average crystallographic configuration of a material are indispensable to advances in structural and chemical investigations of materials. Here, we present an approach to identify and classify local structural states that is rooted in computer vision. This approach introduces a definition of a structural state that is composed of both local and nonlocal information extracted from atomically resolved images, and is wholly untethered from the familiar concepts of symmetry and periodicity. Instead, this approach relies on computer vision techniques such as feature detection, and concepts such as scale invariance. We present the fundamental aspects of local structural state extraction and classification by application to simulated scanning transmission electron microscopy images, and analyze the robustness of this approach in the presence of common instrumental factors such as noise, limited spatial resolution, and weak contrast. Finally, we apply this computer vision-based approach for the unsupervised detection and classification of local structural states in an experimental electron micrograph of a complex oxides interface, and a scanning tunneling micrograph of a defect-engineered multilayer graphene surface.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2019

Distinction between Intrinsic and X-ray-Induced Oxidized Oxygen States in Li-Rich 3d Layered Oxides and LiAlO 2

Resonant inelastic X-ray scattering (RIXS) at the O K-edge is considered a prime technique to identify bulk oxidized oxygen formation, but its fundamental interpretation is not straightforward. In this study, we intentionally induce RIXS signatures of oxidized oxygen upon beam exposure in LiAlO 2 polymorphs that are easily distinguished because of their wide band gaps. After careful consideration of beam exposure effects on Li[Li 0.144 Ni 0.136 Mn 0.544 Co 0.136 ]O 2 (LR-NMC), we conclude that oxidized oxygen features are inherent at high states of charge and are lost upon aggressive beam exposure. The extracted oxidized oxygen line shapes from our X-ray irradiation studies for both LiAlO 2 (induced) and LR-NMC (inherent) are found to have an additional oxidized oxygen RIXS feature not observed in O 2 gas studies. This study highlights the unique insight of O K-edge RIXS into determining the nature and stability of oxidized oxygen states.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Lignin extraction and upgrading using deep eutectic solvents

Deep eutectic solvents (DESs) are a class of green solvents exhibiting low vapor pressure, high thermal stability,low toxicity, and biodegradability. These features make them attractive solvents for lignocellulosic biomassprocessing, especially for lignin valorization. DESs not only solubilize lignin from lignocellulose biomass, butalso confer extracted lignin with properties favorable to its further upgrading. This review summarizes recentadvances in biomass fractionation using DESs for lignin extraction. It also covers lignin upgrading in DESs interms of depolymerization and functionalization. The challenges of tailoring lignin properties by DESs for differentvalorization routes are also discussed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Green synthesis of gold nanoparticles using aqueous ethanol extract of Curcuma mangga rhizomes as reducing agent

Green synthesis of gold nanoparticles (AuNPs) had been developed as an alternative to chemical and physical methods due to its simplicity, cost effectiveness and eco-friendliness. The high biocompatibility and biostability features of AuNPs have found importance in biomedical applications in recent years. In this study, aqueous ethanol extract of Curcuma mangga rhizomes which acts as reducing and stabilizing agent was used to synthesize stable AuNPs by bioreduction of chloroauric acid. The formation of AuNPs was highlighted by the color change of the suspension from light yellow to reddish purple. Time-evolution was monitored by UV-visible spectroscopy, while surface plasmon (SP) absorption band of the AuNPs suspension was observed at a maximum absorption of 540 nm. Hydrodynamic radii and size distribution of the AuNPs in the suspension were evaluated using dynamic light scattering (DLS) and zeta potential measurement demonstrated negative surface charge. The particle size was calculated in the range of 2-30 nm using High Resolution Transmission Electron Microscopy (HRTEM). The morphology and elemental composition were further determined by Field Effect Scanning Electron Microscopy (FESEM) and Energy Dispersive X-ray (EDX) spectroscopy. Fourier transform infrared (FTIR) spectroscopy meanwhile was used to confirm the presence of AuNPs and functional groups involved in the gold bio-reduction process. Influence of the volume of extract and concentration of gold (III) chloride trihydrate (HAuCl{sub 4}.3H{sub 2}O) on the synthesis of AuNPs were also investigated. The results obtained indicate potential optimization and functionalization of AuNPs for future applications in bionanotechnology especially in the field of medicine.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

The Hubble Space Telescope's Near-UV and Optical Transmission Spectrum of Earth as an Exoplanet

We observed the 2019 January total lunar eclipse with the Hubble Space Telescope’s STIS spectrograph to obtain the first near-UV (1700–3200 Å) observation of Earth as a transiting exoplanet. The observatories and instruments that will be able to perform transmission spectroscopy of exo-Earths are beginning to be planned, and characterizing the transmission spectrum of Earth is vital to ensuring that key spectral features (e.g., ozone, or O{sub 3}) are appropriately captured in mission concept studies. O{sub 3} is photochemically produced from O{sub 2}, a product of the dominant metabolism on Earth today, and it will be sought in future observations as critical evidence for life on exoplanets. Ground-based observations of lunar eclipses have provided the Earth’s transmission spectrum at optical and near-IR wavelengths, but the strongest O{sub 3} signatures are in the near-UV. We describe the observations and methods used to extract a transmission spectrum from Hubble lunar eclipse spectra, and identify spectral features of O{sub 3} and Rayleigh scattering in the 3000–5500 Å region in Earth’s transmission spectrum by comparing to Earth models that include refraction effects in the terrestrial atmosphere during a lunar eclipse. Our near-UV spectra are featureless, a consequence of missing the narrow time span during the eclipse when near-UV sunlight is not completely attenuated through Earth’s atmosphere due to extremely strong O{sub 3} absorption and when sunlight is transmitted to the lunar surface at altitudes where it passes through the O{sub 3} layer rather than above it.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Development of a bench-scale dissolution concept for the direct extraction of nuclear fuel

Current used nuclear fuel reprocessing efforts utilize a hydrometallurgical approach in which the UNF is dissolved in hot nitric acid followed by solvent extraction into an organic solvent to harvest target nuclides. Previous studies have shown that the dissolution and loading process could be combined into a single organic dissolution/extraction step, producing loaded organic in a single step process. This single step process also includes the advantage of selectively targeting key nuclides in the dissolution while leaving undesirable constituents as part of the undissolved solids. This process is referred to hereafter as direct extraction. Ongoing research from multiple national labs has proven the effectiveness of this technique at research scale. Therefore, potential methods to implement direct extraction at both bench and industrial scale have been developed. The key features of potential dissolver system designs were identified via the team at Pacific Northwest National Laboratory and several designs based on industrial counterparts were assessed for feasibility. This report summarizes the advantages and disadvantages of multiple methods, concluding with a path forward to create multiple unique dissolver designs. The first design will be a single stage recirculating eductor mixer. The second design recommendation is a stator rotor static mixing flow loop design. Each dissolver could be utilized separately, simultaneously, or in series to answer questions surrounding reaction kinetics including residence time, provide a proof of concept for targeted extractions of specific nuclides, and inform needs for industrial scale implementation

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

PNNL-Predictive-Phenomics/ProCaliper

ProCaliper is a Python library that curates, organizes, and computes protein structure features in a way that easily interfaces with user-provided experimental data. It extracts or computes protein binding site, active site, charge, pLDDT (order/disorder), acid dissociation, protonation, solvent accessible surface area, disulfide bond distance, and protein secondary structure data using precomputed protein structures and publicly available databases. It provides a unified API for integrating additional residue-level data and for visualizing residue features in 3D.

Rozum, Jordan [Pacific Northwest National Lab]↗

DOE OSTI2017

Early Assessment of Treatment Responses During Radiation Therapy for Lung Cancer Using Quantitative Analysis of Daily Computed Tomography

Purpose: To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans. Methods and Materials: Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from the daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed. Results: During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R{sup 2} > 0.99) and correlates weakly with the change in GTV (R{sup 2} = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction. Conclusion: Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2017

Identifying a new particle with jet substructures

Here, we investigate a potential of determining properties of a new heavy resonance of mass O(1)TeV which decays to collimated jets via heavy Standard Model intermediary states, exploiting jet substructure techniques. Employing the Z gauge boson as a concrete example for the intermediary state, we utilize a "merged jet" defined by a large jet size to capture the two quarks from its decay. The use of the merged jet bene ts the identification of a Z-induced jet as a single, reconstructed object without any combinatorial ambiguity. We also find that jet substructure procedures may enhance features in some kinematic observables formed with subjet four-momenta extracted from a merged jet. This observation motivates us to feed subjet momenta into the matrix elements associated with plausible hypotheses on the nature of the heavy resonance, which are further processed to construct a matrix element method (MEM)-based observable. For both moderately and highly boosted Z bosons, we demonstrate that the MEM in combination with jet substructure techniques can be a very powerful tool for identifying its physical properties. Finally, we discuss effects from choosing different jet sizes for merged jets and jet-grooming parameters upon the MEM analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Machine Learning Framework for Characterizing Processing–Structure Relationship in Block Copolymer Thin Films

The morphology of block copolymers (BCPs) critically influences material properties and applications. This work introduces a machine learning (ML)-enabled, high-throughput framework for analyzing grazing incidence small-angle X-ray scattering (GISAXS) data and atomic force microscopy (AFM) images to characterize BCP thin film morphology. A convolutional neural network was trained to classify AFM images by surface features, achieving 97% testing accuracy. Classified images were then analyzed to extract 2D grain size measurements from the samples in a high-throughput manner. ML models were trained to predict domain orientation based on processing parameters such as solvent ratio, additive type, and additive ratio. GISAXS-based properties were predicted with strong performances (R 2 > 0.75), while AFM-based property predictions were less accurate (R 2 < 0.60), likely due to the localized nature of AFM measurements compared to the bulk information captured by GISAXS. Beyond model performance, interpretability was addressed using SHapley Additive exPlanations (SHAP). SHAP analysis revealed that the additive ratio had the largest impact on morphological predictions, where additive provides the BCP chains with increased volume to rearrange into thermodynamically favorable morphologies. This interpretability helps validate model predictions and offers insight into parameter importance. Altogether, the presented framework combining high-throughput characterization and interpretable ML offers an approach to exploring and optimizing BCP thin film morphology across a broad processing landscape.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Robust Biaxial Anisotropy and Switchable Néel Vectors in LaFeO 3 Epitaxial Films

Antiferromagnets with highly stable but switchable Néel vectors are desired for antiferromagnetic spintronics with ultrafast speed and terahertz frequencies. Electrical switching of antiferromagnetic insulators has been demonstrated using binary antiferromagnets, while large families of complex antiferromagnets such as perovskites are largely unexplored. Here, we show that epitaxial LaFeO 3 thin films on SrTiO 3 (001) exhibit clear, robust biaxial anisotropy with a spin-flop field of a few tesla. Angular-dependent spin-Hall magnetoresistance (SMR) characterizations of Pt/LaFeO 3 bilayers with the current channel along SrTiO 3 [100] and [110] reveal distinct, intriguing shapes and field dependence. Simulations using a macrospin model accurately describe the main behavior and fine features of the SMR data from which key antiferromagnetic parameters are extracted. Furthermore, remanent SMR measurement confirms the high fidelity of the Néel vector along either easy axis of the biaxial anisotropy, indicating that epitaxial films of LaFeO 3 and potentially other perovskite antiferromagnets offer an attractive platform for antiferromagnetic spintronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗