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DOE OSTI2024

The impact of plant‐derived fire management prescriptions on fire‐responsive bird species

Abstract In fire‐prone regions, the occurrence of some faunal species is contingent on the presence of resources that arise through post‐fire plant succession. Through planned burning, managers can alter resource availability and aim to provide the conditions required to promote biodiversity. Understanding how species occurrence changes at different spatial and temporal scales after fire is essential to achieve this goal. However, many fire prescriptions are guided primarily by the responses of fire‐sensitive plants when setting tolerable fire intervals. This approach assumes that maintaining floristic diversity will satisfy the requirements of fauna. We surveyed bird species in two semi‐arid vegetation types across an environmental gradient in south‐eastern Australia. We conducted four surveys at each of 253 sites across a 75‐year chronosequence of time since fire and used generalized additive mixed models to examine changes in the occurrence of birds in response to time since fire. Model predictions were compared to plant‐derived fire prescriptions currently guiding fire management in the region. Time since fire was a significant predictor for 18 of 28 species modeled, in at least one vegetation type, over a gradient of 1.3° of latitude. We detected considerable variation in the responses of some species, both between vegetation types and geographically within a vegetation type. Our evaluation of plant‐derived fire prescriptions suggests that the intervals considered acceptable for maintaining floristic diversity may not be sustainable for populations of birds requiring longer unburnt vegetation, with 6 of the 12 species assessed attaining a mean occurrence probability of 20.3% by the minimum tolerable fire interval, and 57.3% by the maximum tolerable fire interval, in their respective vegetation types. Our findings highlight the potential vulnerability of fire‐responsive bird species if fire prescriptions are applied in a manner that fails to account for the slow development of habitat resources needed by some species, and the variation detected within the responses of species. This highlights the need for species‐specific data collected at an appropriate spatial scale to inform management plans.

Makdissi, Rhys↗

DOE OSTI2021

Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding

Antigen-specific immunotherapies (ASI) require successful loading and presentation of antigen peptides into the major histocompatibility complex (MHC) binding cleft. One route of ASI design is to mutate native antigens for either stronger or weaker binding interaction to MHC. Exploring all possible mutations is costly both experimentally and computationally. To reduce experimental and computational expense, here we investigate the minimal amount of prior data required to accurately predict the relative binding affinity of point mutations for peptide-MHC class II (pMHCII) binding. Using data from different residue subsets, we interpolate pMHCII mutant binding affinities by Gaussian process (GP) regression of residue volume and hydrophobicity. We apply GP regression to an experimental data set from the Immune Epitope Database, and theoretical data sets from NetMHCIIpan and Free Energy Perturbation calculations. We find that GP regression can predict binding affinities of nine neutral residues from a six-residue subset with an average R 2 coefficient of determination value of 0.62 ± 0.04 (±95% CI), average error of 0.09 ± 0.01 kcal/mol (±95% CI), and with an receiver operating characteristic (ROC) AUC value of 0.92 for binary classification of enhanced or diminished binding affinity. Similarly, metrics increase to an R2 value of 0.69 ± 0.04, average error of 0.07 ± 0.01 kcal/mol, and an ROC AUC value of 0.94 for predicting seven neutral residues from an eight-residue subset. Our work finds that prediction is most accurate for neutral residues at anchor residue sites without register shift. This work holds relevance to predicting pMHCII binding and accelerating ASI design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Surrogate Model Guided Optimization of Expensive Black-Box Multi-Objective Problems: A Posteriori Methods

Many engineering applications require the simultaneous optimization of multiple conflicting objective functions. Often, these objective functions are evaluated using highly accurate computer simulations that are computationally too expensive to be evaluated hundreds or thousands of times during optimization. Thus, the goal is to find good approximations of the Pareto front using as few of these expensive simulations as possible. Here, we describe an optimization approach based on surrogate models and diverse sampling strategies to accelerate the search for the Pareto solutions. We use a separate surrogate model for approximating each objective function and then we use the surrogate models to inform where additional expensive simulations should be run. The surrogate models are updated in an active learning framework whenever new information from the expensive simulations becomes available. The sampling strategies aim at balancing local improvements of the approximate Pareto front and global exploration to identify the extrema and fill in large gaps of the approximate Pareto front. We demonstrate on a large set of benchmark problems the effectiveness of the method for finding good approximations of the Pareto front.

MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Constraints on Future Analysis Metadata Systems in High Energy Physics

In high energy physics (HEP), analysis metadata comes in many forms—from theoretical cross-sections, to calibration corrections, to details about file processing. Correctly applying metadata is a crucial and often time-consuming step in an analysis, but designing analysis metadata systems has historically received little direct attention. Among other considerations, an ideal metadata tool should be easy to use by new analysers, should scale to large data volumes and diverse processing paradigms, and should enable future analysis reinterpretation. This document, which is the product of community discussions organised by the HEP Software Foundation, categorises types of metadata by scope and format and gives examples of current metadata solutions. Important design considerations for metadata systems, including sociological factors, analysis preservation efforts, and technical factors, are discussed. A list of best practices and technical requirements for future analysis metadata systems is presented. These best practices could guide the development of a future cross-experimental effort for analysis metadata tools.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Violating Kirchhoff’s Law of Thermal Radiation in Semitransparent Structures

Kirchhoff’s law of thermal radiation imposes a constraint on photon-based energy harvesting processes since part of the incident energy flux is inevitably emitted back to the source. By breaking the reciprocity of the system, it is possible to overcome this restriction and improve the efficiency of energy harvesting. Here, we design and analyze a semitransparent emitter that fully absorbs normally incident energy from a given direction with zero backward and unity forward emissivity. The nearly ideal performance with wavelength-scale thickness is achieved due to the magneto-optical effect and the guided-mode resonance engineered in the emitter structure. We derive the general requirements for the nonreciprocal emitter using the temporal coupled mode theory and the symmetry considerations. As a result, we provide a realistic emitter design based on a photonic crystal slab consisting of a magnetic Weyl semimetal and silicon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Equally high efficiencies of organic solar cells processed from different solvents reveal key factors for morphology control

The power conversion efficiency of organic solar cells (OSCs) is exceeding 20%, an advance in which morphology optimization has played a significant role. It is generally accepted that the processing solvent (or solvent mixture) can help optimize morphology, impacting the OSC efficiency. Here we develop OSCs that show strong tolerance to a range of processing solvents, with all devices delivering high power conversion efficiencies around 19%. By investigating the solution states, the film formation dynamics and the characteristics of the processed films both experimentally and computationally, we identify the key factors that control morphology, that is, the interactions between the side chains of the acceptor materials and the solvent as well as the interactions between the donor and acceptor materials. Our work provides new understanding on the long-standing question of morphology control and effective guides to design OSC materials towards practical applications, where green solvents are required for large-scale processing.

14 SOLAR ENERGY↗

DOE OSTI2026

Octave-spanning terahertz quarter-wave plates based on over-coupled Fabry–Pérot resonances in reflective metal–dielectric–metal metasurfaces

Compact devices for broadband polarization control in the terahertz (THz) regime remain challenging to realize due to the intrinsic phase dispersion associated with birefringent materials and resonant structures. Here, we demonstrate achromatic THz quarter-wave plates with near-unity efficiency and operating under a wide range of incidence angles, based on over-coupled metal–dielectric–metal reflective metasurfaces. The devices operate as single-port anisotropic Fabry–Pérot cavities, in which the phase dispersion of the over-coupled resonances is engineered to maintain an approximately constant relative phase delay between orthogonal field components over a broad frequency range. Four complementary metasurface designs operating at an incidence angle of 45° collectively cover the 0.25–3 THz frequency range accessible to a typical THz time-domain spectroscopy system. Each device exhibits an approximately octave-wide operational bandwidth, with axial ratios below 3 dB and polarization-conversion efficiencies exceeding 80% across most of the operating band. Systematic structural optimization suppresses coupling to diffraction and guided-wave modes, thereby further extending the usable bandwidth while preserving the required phase relationship between orthogonal polarizations. The demonstrated metasurfaces are compatible with wafer-scale fabrication processes, and experimental results show excellent agreement with simulations. These findings establish over-coupled reflective metasurfaces as a robust, scalable, and versatile platform for broadband THz polarization control.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Modeling efficient and equitable distribution of COVID-19 vaccines

Producing and distributing COVID-19 vaccine during the pandemic is a major logistical challenge requiring careful planning and efficient execution. This report presents information on logistical, policy and technical issues relevant to rapidly fielding a COVID-19 vaccination program. For this study we (a) conducted literature review and subject matter expert elicitation to understand current vaccine manufacturing and distribution capabilities and vaccine allocation strategies, (b) designed a baseline vaccine distribution strategy and modeling strategy to provide insight into the potential for targeted distribution of limited initial vaccine supplies, and (c) developed parametric interfaces to enable vaccine distribution scenarios to be analyzed in depth with Sandias Adaptive Recovery Model that will allow us evaluate the additional sub- populations and alternative distribution scenarios from a public health benefit and associated economic disruption Principal issues, challenges, and complexities that complicate COVID-19 vaccine delivery identified in our literature and subject matter expert investigation include these items: The United States has not mounted an urgent nationwide vaccination campaign in recent history. The existing global manufacturing and distribution infrastructure are not able to produce enough vaccine for the population immediately. Vaccines, once available will be scarce resources. Prioritization for vaccine allocation will be built on existing distribution networks. Vaccine distribution may not have a universal impact on disease transmission and morbidity because of scarcity, priority population demographics, and underlying disease transmission rates. Considerations for designing a vaccine distribution strategy are discussed. A baseline distribution strategy is designed and tested using the Adaptive Recovery Model, which couples a deterministic compartmental epidemiological model and a stochastic network model. We show the impact of this vaccine distribution strategy on hospitalizations, mortality, and contact tracing requirements. This model can be used to quantitatively evaluate alternative distribution scenarios, guiding policy decisions as vaccine candidates are narrowed down.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Laws in Order: An Inventory of State Renewable Energy Siting Policies

This report identifies which government entity or entities in each state or territory have the jurisdictional authority to make siting and permitting decisions about large scale wind and solar projects. The report also covers established timelines for siting and permitting processes, requirements for public involvement in those processes, and the availability of permitting guides and model ordinances designed to assist local jurisdictions. It details state renewable energy siting policies and permitting authorities across the United States, profiling all 50 states plus Puerto Rico. The report release also includes an interactive map that allows users to easily explore each state’s authorities and policy features. The map, hosted by DOE, includes high-level information on each state’s siting and permitting processes and link directly to the profiles in the report.

14 SOLAR ENERGY↗

DOE OSTI2024

Puck Loop Seal (Final Project Technical Report)

Sandia National Laboratories (SNL) is advancing technical capabilities used in passive loop seals. The “Puck” seal used a set of International Atomic Energy Agency (IAEA) requirements for new passive loop seals published in 2020 as a design guide. The seal is based on an oxygen-sensitive inner mixture encased in an oxygen-impermeable shell, is monolithic rather than two-part, incorporates self-capturing wire features, contains colored water beads and bubbles formed during processing as unique identifiers (UIDs), and visually indicates tamper (whether from seal body penetration or from seal wire removal) by irreversibly changing the seal body from multi-colored to black. This paper will provide details on the design, development, and testing of Puck seal prototypes.

42 ENGINEERING↗

DOE OSTI2025

LAMP Technical Readiness Evaluation Report

An internal preliminary evaluation of Critical Technology Elements (CTEs) for the LANSCE Modernization Project (LAMP) was completed in 2023. This included determining corresponding Technical Readiness Levels (TRLs) for all subsystems using the criteria of DOE G 413.3-4A, Technical Readiness Assessment Guide. This revised report includes a summary of the recent design modifications required to meet the project Key Performance Requirements (KPPs), some of which may reduce technical risk to the project. These recent design modifications include: • Further optimization of the low-energy and medium-energy beam transport regions (LEBT and MEBT, respectively), including relocation of various functional elements (ie choppers, kickers, and bunchers). • An additional H - ion source to separate ion-source function based on beam delivery requirements. • A high-repetition-rate pulsed kicker magnet to select/merge the two H ion beams into a common low-energy beam transport. • Modification and further optimization to a more conventional RFQ design. Performance of the RFQ has been optimized to deliver the required three types of beams while meeting the project KPPs. • The addition of a second chopper in the medium-energy beam transport (MEBT) line to reduce the required pulser voltages. The scope of the evaluation was limited to the project Work Breakdown Structure (WBS) elements as defined for the RFQ Injector and Drift Tube Linac (DTL) systems only. Integration of Instrumentation and Controls (I&C) and Safety Systems was not considered, although specific technologies as related to the RFQ and DTL systems were included. Other elements of the project such as Shielding, System Design, Technical Management, and additional facility integration needed to enable off-line testing and pre-installation commissioning were also not evaluated. Each technical subsystem element was evaluated for technical readiness, however, not all were found to meet the criteria for a CTE. Three subsystem elements were determined to meet the CTE criteria. Their associated TRLs are summarized in the table below. These subsystem elements of the project have the lowest technical readiness due to either being new, novel or modified, requiring additional R&D before being capable of meeting the project Key Performance Parameters (KPPs) and subsystem requirements, or present technology exists but has not yet been demonstrated in a relevant environment. All other subsystems were determined to have a TRL of 8, indicating that actual operating systems exist having similar performance requirements as needed for LAMP. Details of the technical readiness evaluation for each subsystem is given in the following sections of this report.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

LAMP Technical Readiness Evaluation Report: LAMP-ENG-RPT-003 (Revision 2)

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Optimization with Neural Network Feasibility Surrogates: Formulations and Application to Security-Constrained Optimal Power Flow

In many areas of constrained optimization, representing all possible constraints that give rise to an accurate feasible region can be difficult and computationally prohibitive for online use. Satisfying feasibility constraints becomes more challenging in high-dimensional, non-convex regimes which are common in engineering applications. A prominent example that is explored in the manuscript is the security-constrained optimal power flow (SCOPF) problem, which minimizes power generation costs, while enforcing system feasibility under contingency failures in the transmission network. In its full form, this problem has been modeled as a nonlinear two-stage stochastic programming problem. In this work, we propose a hybrid structure that incorporates and takes advantage of both a high-fidelity physical model and fast machine learning surrogates. Neural network (NN) models have been shown to classify highly non-linear functions and can be trained offline but require large training sets. In this work, we present how model-guided sampling can efficiently create datasets that are highly informative to a NN classifier for non-convex functions. We show how the resultant NN surrogates can be integrated into a non-linear program as smooth, continuous functions to simultaneously optimize the objective function and enforce feasibility using existing non-linear solvers. Overall, this allows us to optimize instances of the SCOPF problem with an order of magnitude CPU improvement over existing methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Guide to the Distributed Energy Resource Risk Management Framework

The emergence of distributed energy resources (DERs) has transformed the electric power sector and will likely have even more profound impacts on the future evolution of the United States energy sector as it modernizes and becomes more reliant upon complex informatics programming and systems to ensure that our power grid remains safe from malicious interference. To mitigate risks associated with the increased and diversified use of DERs, the Distributed Energy Resource Cybersecurity Framework (DER-CF) was developed in 2019. The National Renewable Energy Laboratory extended the scope of the DER-CF to include the RMF. To address the challenges faced by federal energy managers and energy system stakeholders in applying the RMF to DER systems, the Distributed Energy Resource Risk Manager (DER-RM) is a six-step process to proactively manage cybersecurity risk in a methodical manner. The DER-RM is independent of the DER-CF's existing assessment, allowing users to focus specifically on the RMF steps. The tools are targeted to different processes - DER-CF enables organizations to perform self-assessments to improve their cybersecurity posture, while DER-RM assists organizations in achieving compliance with specific requirements. This document provides an overview of the DER-RM. The RMF process outlined in this report serves as a guide to diagnose information and operational system threats, gather required materials to comply with industry standards, and document plans for achieving Authority to Operate. Using the DER-RM, federal agencies and other organizations can easily and intuitively follow the RMF process, manage the risks to their grid-edge infrastructure through the integration of their on-site DERs, and comply with appropriate requirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model

Abstract Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold‐adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Mechanism-guided engineering of a minimal biological particle for genome editing

The widespread application of genome editing to treat and cure disease requires the delivery of genome editors into the nucleus of target cells. Enveloped delivery vehicles (EDVs) are engineered virally derived particles capable of packaging and delivering CRISPR-Cas9 ribonucleoproteins (RNPs). However, the presence of lentiviral genome encapsulation and replication proteins in EDVs has obscured the underlying delivery mechanism and precluded particle optimization. Here, we show that Cas9 RNP nuclear delivery is independent of the native lentiviral capsid structure. Instead, EDV-mediated genome editing activity corresponds directly to the number of nuclear localization sequences on the Cas9 enzyme. EDV structural analysis using cryo-electron tomography and small molecule inhibitors guided the removal of ~80% of viral residues, creating a minimal EDV (miniEDV) that retains full RNP delivery capability. MiniEDVs are 25% smaller yet package equivalent amounts of Cas9 RNPs relative to the original EDVs and demonstrated increased editing in cell lines and therapeutically relevant primary human T cells. These results show that virally derived particles can be streamlined to create efficacious genome editing delivery vehicles with simpler production and manufacturing.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Optical design and synthetic analysis of the electron cyclotron emission imaging diagnostic of HL-2M tokamak

The electron cyclotron emission imaging (ECEI) diagnostic is a powerful tool to study the MHD and turbulent transport in magnetically confined fusion plasmas. In this work, the optical system including the local oscillator (LO) coupling and radio frequency (RF) receiving optics, has been designed and analyzed for the HL-2M ECEI diagnostic. The LO optics can illuminate the antenna array and drive the mixer diode to work efficiently, with more than 36% of the beam intensity for the channels which probe the plasma edge relative to those of channels which probe the plasma core. The RF optics aims at guiding the plasma emission signal to the antenna array. To meet different physical requirements, three types of field of view have been achieved for the plasma imaging, with zoom factors of around 1, 1.5 and 2, respectively. The focal surfaces are almost flat, with a maximum off-mapping (defined as the radial distance between the beam waists of the lower-/uppermost antennas and electron cyclotron emission layer) less than 2.5 cm, which can match the electron cyclotron emission layer quite well and suppress the image distortion in the plasma edge region. Furthermore, the impact of possible vibrations and installation error on the focal plane has been evaluated. In addition, the predefined MHD and turbulence perturbations are well reproduced by combining the optical simulation results and synthetic ECEI modeling, which further verifies the good performance of the RF optics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Mechanisms of Degradation of Toxic Nerve Agents: Quantum-chemical Insight into Interactions of Sarin and Soman with Molybdenum Dioxide

With the urgent need to provide an efficient and reliable protection for people from fatal chemical and biological weapons, our fundamental understanding of how toxins interact with filters is far from complete. The situation is further complicated by natural difficulties of performing experimental measurements with lethal toxins. Unlike experiments, computational modeling offers an attractive and safe yet reliable way of studying behavior of toxic agents on a variety of substrates at a great level of detail. Here, we report DFT-based quantum-chemical calculations of adsorption and decomposition of DMMP, sarin and soman on MoO 2 (011) surface. Our calculations show that MoO 2 strongly adsorbs toxic nerve agents and quickly decomposes them. Decomposition of DMMP on the MoO 2 (011) surface proceeds via the PO-CH 3 bond breaking and a formation of a surface methoxy group. The calculated activation barrier for this reaction is 131.5 kJ mol -1 . Unlike DMMP, decomposition of sarin and soman proceeds via the dealkylation reaction yielding propene and 3,3-dimethyl-1-butene, respectively. Decomposition of sarin requires a remarkably low energy (53.7 kJ mol- 1 ), whereas the similar reaction in soman requires 50 kJ mol -1 more energy. We also make specific predictions to guide Ambient-Pressure X-ray Photoelectron Spectroscopy (APXPS) experiments on sarin interaction with MoO 2 samples. We conclude that MoO 2 serves as an efficient substrate able of degrading toxins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗