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DOE OSTI2024

Challenges and Opportunities for Basic Efficiency Measures in Low-Income Homes: A Southeast Alaska Case Study

Juneau, Alaska, is the state's capital city and aims to reach 80% renewable energy for the space heating and transportation sectors by 2045. This goal highlights a need to electrify both sectors to take advantage of the inexpensive hydropower available from the local electric utility, Alaska Electric Light and Power. To that end, researchers examined the feasibility of deploying storm windows via a case study of installing storm windows in two local low-income homes. Newer models of storm windows provide an extra layer of insulation over existing windows while preserving operability and views. They can also improve comfort and reduce noise. In addition to conducting pre- and post-installation air leakage tests, energy monitoring, and occupant interviews, researchers worked with the regional housing authority and a local builder to install the storm windows and replace inoperable windows in the two houses in 2021. The team encountered several challenges, including a lack of egress windows, energy data from a wide variety of heating systems, extremely leaky homes, and installation issues, such as windows that were not square. These results point to several barriers to the widespread deployment of window upgrades in the area and open the door to opportunities to design deployment programs that improve safety and efficiency.

cold climate↗

DOE OSTI2020

Pre-Commercial Scale-Up of a Gas-Fired Absorption Heat Pump

The project sought to advance the maturity of SMTI’s 80 kBTU/hr residential space and water heating GAHP from the engineering prototype stage (TRL-7) to pre-production readiness by addressing manufacturing, balance of system design and installation, cost, reliability, and field application questions. As part of this project, the project team has: (1) Matured the design package for a commercially ready product (2) Demonstrated compliance with relevant ANSI standards (3) Completed manufacturing and assembly process specifications (4) Completed total production cost estimates and capital equipment requirements (5) Initiated component and system level reliability assessments (6) Completed a small field demonstration including measured performance, installation requirements and expected costs, and customer/key stakeholder feedback. (7) Completed a Techno-economic analysis for representative applications and climate zones, including justification for utility incentive programs. (8) Completed a market intelligence report. Scope of Work: A multi-faceted project was completed that included: (a) design for manufacturing tasks for both the sealed system and balance of system, (b) development and trial of key manufacturing processes and techniques, (c) evaluation of component and system level reliability, (d) exploration of make/buy decisions including impact on cost and required capital. Additionally, (e) installation and monitoring of a small number of field test units was completed to demonstrate energy savings and collect customer/installer feedback, and (f) a focused market research task was completed to explore potential barriers and improve market introduction plans. These tasks addressed many of the remaining technical risks regarding long-term reliability, verification of manufacturing cost estimates and identification of cost concerns, identify installation and balance of system design criteria necessary to achieve energy savings and installed cost goals, and identify market barriers and strategies prior to product market introduction.

03 NATURAL GAS↗

DOE OSTI2024

ORBITAL ANGULAR MOMENTUM BEAMS RESEARCH USING A FREE-ELECTRON LASER OSCILLATOR

Strong Hadron Cooling (SHC), utilizing the coherent electron cooling scheme, has been extensively investigated for the Electron Ion Collider (EIC). Throughout our cooling optimization studies, we realized that a Super-Gaussian electron bunch offers enhanced performance in comparison to a Gaussian bunch. Our approach involves initiating the electron beam distribution in a double peak form, transitioning them into a Super-Gaussian distribution due to the longitudinal space charge. Subsequently, a chicane within the linac section compresses the bunch to meet the required bunch length. We tuned a third harmonic cavity amplitude to reduce the nonlinear term of the chicane. Moreover, given the low initial current leading to a small but non-uniform slice energy spread, we evaluated utilizing laser heating techniques to achieve a uniformly distributed slice energy spread. In this report, we discuss the concepts and simulation results

Wang, E.↗

DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on Banshee Distribution Network

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on the Banshee Distribution Network: Preprint

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Morphological–Electrical Property Relation in Cu(In,Ga)(S,Se) 2 Solar Cells: Significance of Crystal Grain Growth and Band Grading by Potassium Treatment

Abstract Solution‐processed Cu(In,Ga)(S,Se) 2 (CIGS) has a great potential for the production of large‐area photovoltaic devices at low cost. However, CIGS solar cells processed from solution exhibit relatively lower performance compared to vacuum‐processed devices because of a lack of proper composition distribution, which is mainly instigated by the limited Se uptake during chalcogenization. In this work, a unique potassium treatment method is utilized to improve the selenium uptake judiciously, enhancing grain sizes and forming a wider bandgap minimum region. Careful engineering of the bandgap grading structure also results in an enlarged space charge region, which is favorable for electron–hole separation and efficient charge carrier collection. Besides, this device processing approach has led to a linearly increasing electron diffusion length and carrier lifetime with increasing the grain size of the CIGS film, which is a critical achievement for enhancing photocurrent yield. Overall, 15% of power conversion efficiency is achieved in solar cells processed from environmentally benign solutions. This approach offers critical insights for precise device design and processing rules for solution‐processed CIGS solar cells.

Kim, Joo‐Hyun↗

DOE OSTI2022

Sand Migration Simulation during Gas Production from Gas Hydrate Reservoir at Kuparuk 7–11–12 site in the Prodhoe Bay Unit, Alaska

Uncontrolled sand production impedes continuous gas production from a hydrate reservoir as observed in the past field-scale gas production tests. Sand mobilization is strongly linked with sediment deformation and high pressure gradient. Sand production occurs when the mobilized sands reach the well. Throughout gas production from a hydrate reservoir, because of hydrate dissociation, deformation and pressure gradient change both in time and space. Therefore, it is necessary to consider the entire process to identify where sand is likely mobilized and how much mobilized sand could reach the well. Here, this study utilizes a coupled thermal, hydrological, chemical, and mechanical (thermo-hydro-chemo-mechanical) sand migration model to simulate a year long gas production from the hydrate reservoir at the Kuparuk 7–11–12 site in the Prodhoe Bay Unit, Alaska. It is found that sand would mainly come from the lower portion of the production zone where faster hydrate dissociation occurs. The relatively faster hydrate dissociation coupled with the fact that hydrate-bearing sediments and hydrate-free sediments have similar stiffness but different strengths causes complex stress transfer, which results in excessive shear deformation when the upper portion of the production zone starts to dissociate. This is evident not only near the well but also away from the well, leading to a large amount of sand mobilization. Another focus of the modeling study is evaluation of the effect of sand migration on gas production. The comparison of two extreme cases–with sandscreen and without sandscreen–suggests that migrated and settled solids around a sand control device can prevent pressure drop across the near-wellbore zone and lead to reduction of the gas production rate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

NCAP: Noncanonical Amino Acid Parameterization Software for CHARMM Potentials

Noncanonical Amino Acids (NCAAs) provide numerous avenues for introduction of novel functionality to peptides and proteins. NCAAs can be incorporated through solid phase synthesis or genetic code expansion in conjugation with heterologous expression of the encoded protein modification. Due to the difficulty of synthesis, wide chemical space and lack of empirically resolved structures modeling the effects of NCAA mutation is critical for rational protein design. To evaluate the structural and functional perturbations NCAAs introduce we utilize molecular potentials that describe the forces in protein structure. Most potentials such as CHARMM are designed to model canonical residues but can be parameterized in include novel NCAAs. Here, in this work, we introduce NCAP a software package to generate CHARMM compatible parameters from quantum chemical calculation. Unlike currently available tools NCAP is designed to recognize NCAA structure and automatically bridge the gap between DFT calculations and potential parameters. For our software we discuss workflow, validation against canonical parameter sets and comparison to published NCAA-protein structures.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

The GFDL‐CM4X Climate Model Hierarchy, Part I: Model Description and Thermal Properties

We present the GFDL‐CM4X (Geophysical Fluid Dynamics Laboratory Climate Model version 4X) coupled climate model hierarchy. The primary application for CM4X is to investigate ocean and sea ice physics as part of a realistic coupled Earth climate model. CM4X utilizes an updated MOM6 (Modular Ocean Model version 6) ocean physics package relative to CM4.0, and there are two members of the hierarchy: one that uses a horizontal grid spacing of 0.25° (referred to as CM4X‐p25) and the other that uses a grid 0.125° (CM4X‐p125). CM4X also refines its atmospheric grid from the nominally 100 km (cubed sphere C96) of CM4.0–50 km (C192). Finally, CM4X simplifies the land model to allow for a more focused study of the role of ocean changes to global mean climate. CM4X‐p125 reaches a global ocean area mean heat flux imbalance of -0.02 W m -2 within $\mathcal{O}$ (150) years in a pre‐industrial simulation, and retains that thermally equilibrated state over the subsequent centuries. This 1850 thermal equilibrium is characterized by roughly 400 ZJ less ocean heat than present‐day, which corresponds to estimates for anthropogenic ocean heat uptake between 1870 and present‐day. CM4X‐p25 approaches its thermal equilibrium only after more than 1000 years, at which time its ocean has roughly 1100 ZJ more heat than its early 21st century ocean initial state. Furthermore, the root‐mean‐square sea surface temperature bias for historical simulations is roughly 20% smaller in CM4X‐p125 relative to CM4X‐p25 (and CM4.0). We offer the mesoscale dominance hypothesis for why CM4X‐p125 shows such favorable thermal equilibration properties.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Imaging how thermal capillary waves and anisotropic interfacial stiffness shape nanoparticle supracrystals

Abstract Development of the surface morphology and shape of crystalline nanostructures governs the functionality of various materials, ranging from phonon transport to biocompatibility. However, the kinetic pathways, following which such development occurs, have been largely unexplored due to the lack of real-space imaging at single particle resolution. Here, we use colloidal nanoparticles assembling into supracrystals as a model system, and pinpoint the key role of surface fluctuation in shaping supracrystals. Utilizing liquid-phase transmission electron microscopy, we map the spatiotemporal surface profiles of supracrystals, which follow a capillary wave theory. Based on this theory, we measure otherwise elusive interfacial properties such as interfacial stiffness and mobility, the former of which demonstrates a remarkable dependence on the exposed facet of the supracrystal. The facet of lower surface energy is favored, consistent with the Wulff construction rule. Our imaging–analysis framework can be applicable to other phenomena, such as electrodeposition, nucleation, and membrane deformation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2020

Systematically localizable operators for quantum simulations of quantum field theories

Correlations and measures of entanglement in ground-state wave functions of relativistic quantum field theories are spatially localized over length scales set by the mass of the field. We utilize this localization to design digital quantum circuits for preparing the ground states of lattice scalar quantum field theories. Controlled rotations that are exponentially localized in their position-space extent are found to provide exponentially convergent wave function fidelity. These angles scale with the correlation between sites and the classical two-point correlation function, as opposed to the more localized mutual information or the hyperlocalized (1×1)-site negativity. We anticipate that further investigations will uncover quantum circuit designs with controlled rotations dictated by the measures of entanglement. This work is expected to impact quantum simulations of systems of importance to nuclear physics, high-energy physics, and basic energy sciences research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Dynamic compression effects of H 2 ⁡O in a dynamic diamond anvil cell: Origin of metastable ice VII and its crystal growth kinetics

We report on the structural verification of metastable ice VII solidifying in the phase space of ice VI at 1.80 GPa at room temperature. Using time-resolved (TR) x-ray diffraction and TR ruby luminescence paired with high-speed microphotography utilizing a dynamic diamond anvil cell, an initial compression rate range from 0.12 to 95.84 GPa/s was explored. The solidification pressure of metastable ice VII has a potential sigmoidal dependence upon compression rate with a turnover compression rate of ∼80 GPa/s. The preferred crystallization of ice VII in the stability field of ice VI is due to the increased nucleation rate of ice VII over ice VI at 1.77 GPa that is driven by the surface energy difference between the liquid and solid phases along with the change in Gibbs free energy of solidification. The dynamic pressure-volume–compression behaviors of ice phases (VI and VII) show a lattice stiffening in both phases, especially during the compression loading. It is also found that the compression rate greatly affects the solid-solid phase transition between ice VI and VII but does not affect the liquid-solid transition between water and ice VI as much. Lastly, a third phase transition was found to occur after metastable ice VII transforms into high-density amorphous (HDA) ice, which could be a disordered hydrogen-bonded network configuration of ice VII forming out of HDA ice facilitated by the decoupling of the oxygen movement and reorientation of the H 2⁡ O molecule. These results demonstrate the complexity of a seemingly simple molecule H 2⁡ O, how it can readily change its static properties with the modification of (de)compression rate, and highlight the need to use multiple TR structural and spectroscopic probes at higher time resolutions to realize the most comprehensive understanding.

Chemical bonding↗

DOE OSTI2021

Modeling quasielastic interactions of monoenergetic kaon decay-at-rest neutrinos

Monoenergetic muon neutrinos at 236 MeV are readily produced in intense medium-energy proton facilities (≳2–3GeV) when a positive kaon decays at rest (KDAR; K + →μ + ν μ ). These neutrinos provide a unique opportunity to both study the neutrino interaction and probe the nucleus with a monoenergetic weak-interaction-only tool. We present cross-section calculations for quasielastic scattering of these 236-MeV neutrinos off 12 C and 40 Ar, paying special attention to low-energy aspects of the scattering process. Our model takes the description of the nucleus in a mean-field approach as the starting point, where we solve Hartree-Fock equations using a Skyrme type nucleon-nucleon interaction. Thereby, we introduce long-range nuclear correlations by means of a continuum random-phase approximation (CRPA) framework where we solve the CRPA equations using a Green's function method. The model successfully describes (e,e') data on 12 C and 40 Ca in the kinematic region that overlaps with the KDAR ν μ phase space. In addition to these results, we present future prospects for precision KDAR cross-section measurements and applications of our calculations in current and future experiments that will utilize these neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space

Background Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens is often confounded by extreme sequence homology. This homology leads to “data leakage” in standard random validation splits, yielding inflated performance metrics that fail to translate into real-world biosurveillance utility. Results We present Protein Representation Inference for Mutation Evaluation (PRIME), a framework that integrates domain-specific fine-tuning with a rigorous position-stratified validation protocol to evaluate viral threats. Using a dataset of 347,432 SARS-CoV-2 receptor binding domain (RBD) sequences, we demonstrate that while random training data split yields deceptive R 2 values (> 0.90), they fail to generalize to novel mutational sites. By benchmarking models up to 650 M parameters, we show that domain-specific fine-tuning of the ESM-C 600 M model with correctly stratified data provides an initial demonstration of predictive signal for binding affinity and expression at unseen mutational sites of binding affinity and expression on unseen sites (R 2 ~0.23), a significant advancement over base foundation models which exhibit no predictive power (R 2 <0). PRIME’s embedding-based clustering identified 3.03% of bat coronavirus sequences as candidates for further experimental prioritization based on their functional similarity to human-infective strains in embedding space, offering a perspective complementary to traditional phylogenetic methods. Conclusion PRIME establishes a new benchmark for the application of PLMs in pathogen surveillance. Our findings demonstrate that state-of-the-art models and fine-tuning, when paired with stratified validation, provide biologically meaningful insights into pathogen evolution and zoonotic risk.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Interferometric 4D-STEM for Lattice Distortion and Interlayer Spacing Measurements of Bilayer and Trilayer 2D Materials

Van der Waals materials composed of stacks of individual atomic layers have attracted considerable attention due to their exotic electronic properties that can be altered by, e.g., manipulating the twist angle of bilayer materials or the stacking sequence of trilayer materials. To fully understand and control the unique properties of these few-layer materials, a technique that can provide information about their local in-plane structural deformations, twist direction, and out-of-plane structure is needed. In principle, interference in overlap regions of Bragg disks originating from separate layers of a material encodes 3D information about the relative positions of atoms in the corresponding layers. Here, an interferometric 4D scanning transmission electron microscopy technique is described that utilizes this phenomenon to extract precise structural information from few-layer materials with nm-scale resolution. It is demonstrated how this technique enables measurement of local pm-scale in-plane lattice distortions as well as twist direction and average interlayer spacings in bilayer and trilayer graphene, and therefore provides a means to better understand the interplay between electronic properties and precise structural arrangements of few-layer 2D materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Double Perovskite Interlayer Stabilized Highly Efficient Perovskite Solar Cells

Metal halide perovskite solar cell (PSC) technology has an impressive power conversion efficiency (PCE) exceeding 26.1% and demonstrates cost-effective manufacturing. However, the stability of these PSCs poses a significant challenge, hindering their widespread manufacturing and commercialization. To tackle the degradation issue inherent in PSCs, surface passivation techniques, particularly employing a thin layer of two-dimensional (2D) perovskites, create a 2D/3D heterostructure. Beyond this, the exploration of metal halide double perovskites adds a new dimension to the chemical and band gap phase space of materials for optoelectronic applications. In this study, we leverage a wide band gap double perovskite interlayer to enhance the stability of 3D metal halide perovskite. Specifically, the double perovskite nanoparticle Cs 2 AgBiBr 6 , with its substantial band gap of 2.2 eV and exceptional air stability, is utilized. Through optimization, a Cs 2 AgBiBr 6 -treated PSC achieves an open-circuit voltage of 1.12 V and an impressive PCE of 19.52%. Additionally, the Cs 2 AgBiBr 6 passivation layer proves to be effective in bolstering the stability of PSCs. This work demonstrates an additional strategy and design motif to simultaneously increase the PCE of PSCs along with achieving improved stability.

14 SOLAR ENERGY↗

DOE OSTI2020

LiDAR-Aided Interior Orientation Parameters Refinement Strategy for Consumer-Grade Cameras Onboard UAV Remote Sensing Systems

Unmanned aerial vehicles (UAVs) are quickly emerging as a popular platform for 3D reconstruction/modeling in various applications such as precision agriculture, coastal monitoring, and emergency management. For such applications, LiDAR and frame cameras are the two most commonly used sensors for 3D mapping of the object space. For example, point clouds for the area of interest can be directly derived from LiDAR sensors onboard UAVs equipped with integrated global navigation satellite systems and inertial navigation systems (GNSS/INS). Imagery-based mapping, on the other hand, is considered to be a cost-effective and practical option and is often conducted by generating point clouds and orthophotos using structure from motion (SfM) techniques. Mapping with photogrammetric approaches requires accurate camera interior orientation parameters (IOPs), especially when direct georeferencing is utilized. Most state-of-the-art approaches for determining/refining camera IOPs depend on ground control points (GCPs). However, establishing GCPs is expensive and labor-intensive, and more importantly, the distribution and number of GCPs are usually less than optimal to provide adequate control for determining and/or refining camera IOPs. Moreover, consumer-grade cameras with unstable IOPs have been widely used for mapping applications. Therefore, in such scenarios, where frequent camera calibration or IOP refinement is required, GCP-based approaches are impractical. To eliminate the need for GCPs, this study uses LiDAR data as a reference surface to perform in situ refinement of camera IOPs. The proposed refinement strategy is conducted in three main steps. An image-based sparse point cloud is first generated via a GNSS/INS-assisted SfM strategy. Then, LiDAR points corresponding to the resultant image-based sparse point cloud are identified through an iterative plane fitting approach and are referred to as LiDAR control points (LCPs). Finally, IOPs of the utilized camera are refined through a GNSS/INS-assisted bundle adjustment procedure using LCPs. Seven datasets over two study sites with a variety of geomorphic features are used to evaluate the performance of the developed strategy. The results illustrate the ability of the proposed approach to achieve an object space absolute accuracy of 3–5 cm (i.e., 5–10 times the ground sampling distance) at a 41 m flying height.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability

The ability of machine learning (ML) classification models to resist small, targeted input perturbations—known as adversarial attacks—is a key measure of their safety and reliability. We show that floating-point non associativity (FPNA) coupled with asynchronous parallel programming on GPUs is sufficient to result in misclassification, without any perturbation to the input. Additionally, we show that this misclassification is particularly significant for inputs close to the decision boundary and that standard adversarial robustness results may be overestimated up to 4.6 when not considering machine-level details. We first study a linear classifier, before focusing on standard Graph Neural Network (GNN) architectures and datasets used in robustness assessments. We develop a novel black-box attack using Bayesian optimization to discover external workloads that can change the instruction scheduling which bias the output of reductions on GPUs and reliably lead to misclassification. Motivated by these results, we present a new learnable permutation (LP) gradient-based approach to learning floating-point operation orderings that lead to misclassifications. The LP approach provides a worst-case estimate in a computationally efficient manner, avoiding the need to run identical experiments tens of thousands of times over a potentially large set of possible GPU states or architectures. Finally, using instrumentation-based testing, we investigate parallel reduction ordering across different GPU architectures under external background workloads, when utilizing multi-GPU virtualization, and when applying power capping. Our results demonstrate that parallel reduction ordering varies significantly across architectures under the first two conditions, substantially increasing the search space required to fully test the effects of this parallel scheduler-based vulnerability. These results and the methods developed here can help to include machine-level considerations into adversarial robustness assessments, which can make a difference in safety and mission critical applications.

Shanmugavelu, Sanjif [Maxeler Technologies, a Groq↗