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DOE OSTI2026

PERFORMANCE ANALYSIS OF AN ENGINEERING SCALE HYDROTHERMAL LIQUEFACTION SYSTEM

This work evaluates the Modular Hydrothermal Liquefaction System (MHTLS), an engineering-scale, integrated continuous HTL plant operated at the Pacific Northwest National Laboratory (PNNL), for converting realistic wet wastes into energy-dense biocrudes. The production campaigns discussed here processed algae, sewage sludges, lignocellulosic blends, Industrial food waste, and engineered food-waste slurries at 350?°C and around 200?bar, with nominal feed rates of ~12?L?h?¹. We report biocrude yields and composition, establish mass and elemental (C, N) balances, and quantify energy performance via heater duties, heat-exchanger behavior, and system-level efficiencies. Biocrudes contained 76–80?wt?% C (dry, ash-free) with HHVs of 38-41?MJ?kg?¹, substantially higher than feed materials HHVs of 16.6–26.1?MJ?kg?¹ and approaching petroleum fuels. Dry, ash-free biocrude yields of 32–53?wt?% corresponded to 43–71?wt?% carbon yields, with 18–40?wt?% of feed carbon routed to the aqueous phase. Thermal efficiencies were 50-65%, and total energy efficiencies, including reactor heat input, were 35-55%. A counter-current tube-in-tube heat exchanger delivered U values of 200–450?W?m?²?K?¹, with fouling-induced declines impacting heat recovery and heater duty. The analysis highlights three priorities for the process intensification of HTL: robust, fouling-resistant heat recovery, hydrodynamically suitable reactor and heat-exchanger designs, simplified and predictable solids management, and biocrude-water separation.

Biocrude production↗

DOE OSTI2026

The effectiveness of D 2 pellet and gas injection in reducing intra-ELM tungsten erosion and heat flux in the DIII-D small angle slot divertor

Edge localized modes (ELMs) in H-mode plasmas can melt and erode plasma-facing components (PFCs) and lead to impurities in the core, reducing confinement. This study analyzes the use of D 2 pellet and gas injection for ELM mitigation on the DIII-D tokamak during the 2022 Small Angle Slot V-shaped Tungsten (W) (SAS-VW) divertor campaign, reducing W erosion and heat flux during ELMs. D α (656 nm) and WI (400.9 nm) filterscopes and Langmuir probes provide photon emission and electron density/temperature to estimate W atom erosion using the S/XB method, while surface eroding thermocouples measured ELM peak heat flux at the outer strike point (OSP). Thomson Scattering measurements of pedestal T e and n e provided input to predict W divertor erosion and heat flux during ELMs via the Free-Streaming plus Recycling Model (FSRM). While a greater D 2 mass injection rate decreased the ELM peak heat flux, the impact on W erosion was not monotonic. The average ‘large’ intra-ELM W erosion was lower for plasma shots with D 2 mass injection compared to the plasma shots without any D 2 mass injection in the SAS-VW divertor. However, plasma shots did not see significant changes in ‘large’ intra-ELM W divertor erosion as the D 2 mass injection rate increased. On average, the FSRM overestimated SAS-VW experimental intra-ELM W erosion by a factor of 6.9, but the overestimation is reduced to a factor of 3.6 with the implication of C deposition effects. Generally, experimentally measured and predicted quantities were worse for plasma shots with a lower D 2 mass injection rate and corresponding higher plasma carbon (C) impurity percentage (f C ). The discrepancies are postulated to be due to C/W material mixing, for which a simple analytic mixed-material model is presented. These results highlight the importance of incorporating and improving the robustness of a mixed-material layer model in the analysis of PFC erosion on present and future tokamak devices.

Carbon (C)↗

DOE OSTI2023

Origins of Conformational Heterogeneity in Peptoid Helices Formed by Chiral N -1-Phenylethyl Sidechains

N-substituted glycines (polypeptoids) containing chiral hydrophobic sidechains are known to fold into biomimetic alpha helices. These helix formers often produce conformationally heterogeneous structures and are difficult to characterize at a sub-nanometer resolution. Previously, peptoid N-1-phenylethyl (S)-enantiomer sidechains (Nspe) were inferred from various experiments to form right-handed helices and (R)-enantiomers (Nrpe), left-handed helices. Prior computational work for N(s/r)pe oligomers has struggled to reproduce this trend. Herein, quantum mechanics calculations and molecular dynamics simulations are used to understand the origins of this discrepancy. Results from DFT and molecular mechanics calculations on a variety of Nspe and Nrpe oligomers as a function of chain length are in agreement, showing that Nspe and Nrpe prefer left- and right-handed helices, respectively. Additional metadynamics simulations are used to study Nrpe and Nspe oligomers folding in water. These results show that the free-energy driving forces for assembly into a helical backbone configuration are very small (within ~k B T). Lastly, we compare DFT calculations for other experimentally characterized peptoid sidechains, N(r/s)sb, N(r/s)tbe, and N(r/s)npe. In this analysis, we show that peptoid sidechains determined to be more robust experimentally (tbe and npe) have helical preferences opposite the trend seen in less robust assemblies formed by N(r/s)pe and N(r/s)sb chemistries. Furthermore, the more robust tbe and nnpe favor the (S)-enantiomer to right-handed and the (R)-enantiomers to left-handed helices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Insights into pulmonary phosphate homeostasis and osteoclastogenesis emerge from the study of pulmonary alveolar microlithiasis

Pulmonary alveolar microlithiasis is an autosomal recessive lung disease caused by a deficiency in the pulmonary epithelial Npt2b sodium-phosphate co-transporter that results in accumulation of phosphate and formation of hydroxyapatite microliths in the alveolar space. The single cell transcriptomic analysis of a pulmonary alveolar microlithiasis lung explant showing a robust osteoclast gene signature in alveolar monocytes and the finding that calcium phosphate microliths contain a rich protein and lipid matrix that includes bone resorbing osteoclast enzymes and other proteins suggested a role for osteoclast-like cells in the host response to microliths. While investigating the mechanisms of microlith clearance, we found that Npt2b modulates pulmonary phosphate homeostasis through effects on alternative phosphate transporter activity and alveolar osteoprotegerin, and that microliths induce osteoclast formation and activation in a receptor activator of nuclear factor-κB ligand and dietary phosphate dependent manner. This work reveals that Npt2b and pulmonary osteoclast-like cells play key roles in pulmonary homeostasis and suggest potential new therapeutic targets for the treatment of lung disease.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Sterile-neutrino search based on 259 days of KATRIN data

Neutrinos are the most abundant fundamental matter particles in the Universe and play a crucial part in particle physics and cosmology. Neutrino oscillation, discovered about 25 years ago, shows that the three known species mix with each other. Anomalous results from reactor and radioactive-source experiments suggest a possible fourth neutrino state, the sterile neutrino, which does not interact through the weak force. The Karlsruhe Tritium Neutrino (KATRIN) experiment, primarily designed to measure the neutrino mass using tritium β-decay, also searches for sterile neutrinos suggested by these anomalies. A sterile-neutrino signal would appear as a distortion in the β-decay energy spectrum, characterized by a discontinuity in curvature (kink) related to the sterile-neutrino mass. This signature, which depends only on the shape of the spectrum rather than its absolute normalization, offers a robust, complementary approach to reactor experiments. Here we report the analysis of the energy spectrum of 36 million tritium β-decay electrons recorded in 259 measurement days within the last 40 eV below the endpoint. The results exclude a substantial part of the parameter space suggested by the gallium anomaly and challenge the Neutrino-4 claim. Together with other neutrino-disappearance experiments, KATRIN probes sterile-to-active mass splittings from a fraction of an eV 2 to several hundred eV 2 , excluding light sterile neutrinos with mixing angles above a few per cent.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

Planck 2015 results: III. LFI systematic uncertainties

In this paper, we present the current accounting of systematic effect uncertainties for the Low Frequency Instrument (LFI) that are relevant to the 2015 release of the Planck cosmological results, showing the robustness and consistency of our data set, especially for polarization analysis. We use two complementary approaches: (i) simulations based on measured data and physical models of the known systematic effects; and (ii) analysis of difference maps containing the same sky signal (“null-maps”). The LFI temperature data are limited by instrumental noise. At large angular scales the systematic effects are below the cosmic microwave background (CMB) temperature power spectrum by several orders of magnitude. In polarization the systematic uncertainties are dominated by calibration uncertainties and compete with the CMB E-modes in the multipole range 10–20. Based on our model of all known systematic effects, we show that these effects introduce a slight bias of around 0.2σ on the reionization optical depth derived from the 70GHz EE spectrum using the 30 and 353GHz channels as foreground templates. At 30GHz the systematic effects are smaller than the Galactic foreground at all scales in temperature and polarization, which allows us to consider this channel as a reliable template of synchrotron emission. We assess the residual uncertainties due to LFI effects on CMB maps and power spectra after component separation and show that these effects are smaller than the CMB amplitude at all scales. We also assess the impact on non-Gaussianity studies and find it to be negligible. Finally, some residuals still appear in null maps from particular sky survey pairs, particularly at 30 GHz, suggesting possible straylight contamination due to an imperfect knowledge of the beam far sidelobes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

A stochastic simulation method for the assessment of resistive random access memory retention reliability

This study presents an evaluation method for resistive random access memory retention reliability based on the Metropolis Monte Carlo algorithm and Gibbs free energy. The method, which does not rely on a time evolution, provides an extremely efficient way to compare the relative retention properties of metal-insulator-metal structures. It requires a small number of iterations and may be used for statistical analysis. The presented approach is used to compare the relative robustness of a single layer ZrO{sub 2} device with a double layer ZnO/ZrO{sub 2} one, and obtain results which are in good agreement with experimental data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Revisiting heat treatment and surface activation of GaAs photocathodes: In situ studies using scanning tunneling microscopy and photoelectron spectroscopy

The lifetime of GaAs photocathodes in polarized electron guns is limited due to the delicate activation layer. An atomically clean and smooth GaAs surface is needed to deposit a robust activation layer, such as Cs 2 Te, with longer lifetime compared to traditional (Cs,O) activation. A previous experiment with Cs 2 Te activation on GaAs used heat cleaning temperatures around 400°C to avoid an increase in surface roughness [Bae et al., Appl. Phys. Lett. 112, 154101 (2018)]. Furthermore, high-temperature heat cleaning around 580°C, which results in a relatively contamination-free surface, could be one possible way to improve quantum efficiency. However, one should be cautious about surface roughness degradation during high-temperature heat cleaning. In this paper, we report results of surface roughness measurements on native, heat cleaned, and (Cs,O) activated GaAs photocathodes under vacuum. The results, measured by ultrahigh vacuum scanning tunneling microscopy, show that the surface roughness improves as the heat cleaning temperature is increased, by at least a factor of three for 580°C heat cleaning, compared to the native sample. Activation with (Cs,O) is shown to increase surface roughness by a factor of four compared to a 580°C heat cleaned sample. This confirms that high-temperature heat cleaning can be useful for depositing good quality robust activation layers on GaAs. Additionally, we also report chemical analysis for each step of preparation for p-doped GaAs photocathodes using X-ray photoelectron spectroscopy (XPS), angle-resolved XPS, and ultraviolet photoelectron spectroscopy. Our results indicate that the (Cs,O) activation layer forms a sandwich structure consists of Cs and oxygen. We found no formation of any specific compound such as Cs 2 O or Cs 11 O 3 .

43 PARTICLE ACCELERATORS↗

DOE OSTI2014

Search for gamma-ray-emitting active galactic nuclei in the Fermi-LAT unassociated sample using machine learning

The second Fermi-LAT source catalog (2FGL) is the deepest all-sky survey available in the gamma-ray band. It contains 1873 sources, of which 576 remain unassociated. Machine-learning algorithms can be trained on the gamma-ray properties of known active galactic nuclei (AGNs) to find objects with AGN-like properties in the unassociated sample. This analysis finds 231 high-confidence AGN candidates, with increased robustness provided by intersecting two complementary algorithms. A method to estimate the performance of the classification algorithm is also presented, that takes into account the differences between associated and unassociated gamma-ray sources. Follow-up observations targeting AGN candidates, or studies of multiwavelength archival data, will reduce the number of unassociated gamma-ray sources and contribute to a more complete characterization of the population of gamma-ray emitting AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

3D correlations in the Lyman-α forest from early DESI data

We present the first measurements of Lyman-α (Lyα) forest correlations using early data from the Dark Energy Spectroscopic Instrument (DESI). We measure the auto-correlation of Lyα absorption using 88 509 quasars at z > 2, and its cross-correlation with quasars using a further 147 899 tracer quasars at z ≳ 1.77. Then, we fit these correlations using a 13-parameter model based on linear perturbation theory and find that it provides a good description of the data across a broad range of scales. We detect the BAO peak with a signal-to-noise ratio of 3.8σ, and show that our measurements of the auto- and cross-correlations are fully-consistent with previous measurements by the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). Even though we only use here a small fraction of the final DESI dataset, our uncertainties are only a factor of 1.7 larger than those from the final eBOSS measurement. As a result, we validate the existing analysis methods of Lyα correlations in preparation for making a robust measurement of the BAO scale with the first year of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

The role of atmospheric stability/turbulence on wakes at the Egmond aan Zee offshore wind farm

Here, the aim of the paper is to present results from the NREL SOWFA project that compares simulations from models of different fidelity to meteorological and turbine data from the Egmond aan Zee wind farm. Initial results illustrate that wake behavior and impacts are strongly impacted by turbulence intensity. This includes both power losses from wakes and loading illustrated by the out of plane bending moment. Here we focus on understanding the relationship between turbulence and atmospheric stability and whether power losses due to wakes can effectively be characterized by measures of turbulence alone or whether atmospheric stability as a whole plays a fundamental role in wake behavior. The study defines atmospheric stability using the Monin-Obukhov length estimated based on the temperature difference between 116 and 70 m. The data subset selected using this method for the calculation of the Monin-Obukhov length indicate little diurnal or directional dependence of the stability classes but a dominance of stable classes in the spring/unstable classes in fall and of near-neutral classes at high wind speeds. The analysis is complicated by the need to define turbulence intensity. We can select the ratio of the standard deviation of wind speed to mean wind speed in each observation period using data from the meteorological mast, in which case a substantial amount of data must be excluded due to the presence of the wind farm. An alternative is to use data from the wind turbines which could provide a larger data set for analysis. These approaches are examined and compared to illustrate their robustness. Finally, power losses from wakes are categorized according to stability and/or turbulence in order to understand their relative importance in determining the behavior of wind turbine wakes.

17 WIND ENERGY↗

DOE OSTI2023

Deep neural network uncertainty quantification for LArTPC reconstruction

We evaluate uncertainty quantification (UQ) methods for deep learning applied to liquid argon time projection chamber (LArTPC) physics analysis tasks. As deep learning applications enter widespread usage among physics data analysis, neural networks with reliable estimates of prediction uncertainty and robust performance against overconfidence and out-of-distribution (OOD) samples are critical for their full deployment in analyzing experimental data. While numerous UQ methods have been tested on simple datasets, performance evaluations for more complex tasks and datasets are scarce. Here we assess the application of selected deep learning UQ methods on the task of particle classification using the PiLArNet monte carlo 3D LArTPC point cloud dataset. We observe that UQ methods not only allow for better rejection of prediction mistakes and OOD detection, but also generally achieve higher overall accuracy across different task settings. We assess the precision of uncertainty quantification using different evaluation metrics, such as distributional separation of prediction entropy across correctly and incorrectly identified samples, receiver operating characteristic curves (ROCs), and expected calibration error from observed empirical accuracy. We conclude that ensembling methods can obtain well calibrated classification probabilities and generally perform better than other existing methods in deep learning UQ literature.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Deep-inelastic and quasielastic electron scattering from A = 3 nuclei

We perform a combined analysis of inclusive electron scattering data from $A=3$ nuclei in the deep-inelastic and quasielastic scattering regions, using Monte Carlo analysis methods and the nuclear weak binding approximation to establish the range over which the data can be described within the same theoretical framework. Comparison with quasielastic $^3$He cross sections from SLAC and Jefferson Lab suggests that most features of the $x \gtrsim 1$ data can be reasonably well described in the impulse approximation with finite-$Q^2$ nuclear smearing functions for momentum transfers $Q^2 \gtrsim 1$~GeV$^2$. For the DIS region, we analyze the recent $^3$He to deuterium cross section ratio from the Jefferson Lab E03-103 experiment to explore the possible isospin dependence of the nuclear effects. We discuss the implications of this for the MARATHON experiment, and outline how a Bayesian analysis of $^3$He, $^3$H and deuterium data can robustly determine the free neutron structure function.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Hyper-Differential Sensitivity Analysis of Uncertain Parameters in PDE-Constrained Optimization

Many problems in engineering and sciences require the solution of large scale optimization constrained by partial differential equations (PDEs). Though PDE-constrained optimization is itself challenging, most applications pose additional complexity, namely, uncertain parameters in the PDEs. Uncertainty quantification (UQ) is necessary to characterize, prioritize, and study the influence of these uncertain parameters. Sensitivity analysis, a classical tool in UQ, is frequently used to study the sensitivity of a model to uncertain parameters. In this article, we introduce "hyper-differential sensitivity analysis" which considers the sensitivity of the solution of a PDE-constrained optimization problem to uncertain parameters. Our approach is a goal-oriented analysis which may be viewed as a tool to complement other UQ methods in the service of decision making and robust design. We formally define hyper-differential sensitivity indices and highlight their relationship to the existing optimization and sensitivity analysis literatures. Assuming the presence of low rank structure in the parameter space, computational efficiency is achieved by leveraging a generalized singular value decomposition in conjunction with a randomized solver which converts the computational bottleneck of the algorithm into an embarrassingly parallel loop. Two multi-physics examples, consisting of nonlinear steady state control and transient linear inversion, demonstrate efficient identification of the uncertain parameters which have the greatest influence on the optimal solution.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Need for portable accelerators in cultural heritage

Ion Beam Accelerators (IBA) centres have provided researchers with powerful techniques to analyse objects of cultural significance in a non-destructive and non-invasive manner. However, in some cases it is not feasible to remove an object from the field or museum and transport it to the laboratory. In this contributed talk, we present as a manner of a short review, examples of the benefits provided from these techniques in the study of material culture and discuss the initial steps to consider when investigating the feasibility of a compact accelerator that can be taken to sites of cultural significance for PIXE analysis. In particular, we consider the application of a compact, robust 2 MeV proton accelerator that can be taken into the field to perform PIXE measurements on rock art. We detail the main challenges and considerations for such a device.

Charles, T. K.↗

DOE OSTI2018

Process for Conducting a Cost Benefit Analysis for New Radiation Portal Monitors

The Domestic Nuclear Detection Office (DNDO) has deployed over 1,400 radiation portal monitors (RPMs) around the United States to enhance border security. DNDO is now considering deployment of a newer generation of RPMs, intended to have equal or better sensitivity but a considerably lower nuisance alarm rate due to Naturally Occurring Radioactive Material (NORM) that is common in the stream of commerce. If the nuisance alarm rate is sufficiently reduced at a site, US Customs and Border Protection (CBP) may be able to reduce the staffing necessary to respond to nuisance alarms generated by the RPMs. This document provides an overview of some possible processes for conducting a cost benefit analysis to place a reliable dollar amount on the value of these new systems. While there is no hard and fast guide for conducting a cost benefit analysis, an austere method is provided for quick estimating. Two robust methods are also provided, one taking guidance from an Office of Management and Budget circular and the other from the Government Accountability Office.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Sensitivity and Uncertainty Workflow of Full System SIERRA Models Supporting High Consequence Applications (Executive Summary)

The overall goal of this work was to advance the integrated workflow capabilities to provide the weapon system analysts the tools to construct, communicate and robustly execute end-to-end computational simulation models and analysis. Specifically, this includes developing and running automated, CompSim workflows that map model inputs to responses from large-scale studies executed on a distributed, heterogenous computing environment (e.g., CAD applications on Windows laptop to Sierra FEM codes on Trinity within a single workflow). The workflows developed enable ensemble calculations in support of ND program decisions, including sensitivity analysis, optimization and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

The Algae Testbed Public Private Partnership -ATP 3 (Final Closeout Report)

The Algae Testbed Public Private Partnership (ATP3) was proposed in response to the ADVANCEMENTS IN SUSTAINABLE ALGAL PRODUCTION (ASAP) FUNDING OPPORTUNITY NUMBER: DE-FOA-0000615 TOPIC AREA 2-DEVELOPMENT OF REGIONAL ALGAL FEEDSTOCK TESTBED (RAFT) PARTNERSHIPS in 2012. For six years, from 2013 through 2019, ATP 3 was operated as a multi-institutional effort funded by the Department of Energy to establish a network of operating testbeds that brought together world-class scientists, engineers and business executives whose goal it was to increase stakeholder access to high quality facilities by making available an unparalleled array of outdoor cultivation, downstream equipment, and laboratory facilities to the algal R&D community. ATP 3 utilized the same powerful combination of facilities and technical expertise to support TEA, LCA and resource modeling and analysis activities, helping to close critical knowledge gaps and inform robust analyses of the state of technology for algal based biofuels and bioproducts. ATP 3 included testbed facilities at Arizona State University’s (ASU) Arizona Center for Algae Technology and Innovation (AzCATI), and augmented by university and commercial facilities in Hawaii (Cellana), California (Cal Poly San Luis Obispo), Georgia (Georgia Institute of Technology), and Florida (Florida Algae), in addition to partners at the National Renewable Energy Laboratory, Sandia National Laboratories, Valicor Renewables (Michigan), University of Texas at Austin (Texas), Commercial Algae Management (Georgia), Harmon Consulting (Hawaii), Evodos (Netherlands), and Litree (China).

09 BIOMASS FUELS↗