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DOE OSTI2024

Using MARCUS, MICRE, and COMBLE data to improve understanding and modeling of cloud, aerosol, and boundary layer processes at high-latitudes

Because it is believed general circulation (GCM) and numerical weather prediction (NWP) models underestimate shortwave radiation over the Southern Ocean (SO) due to inadequate representations of boundary layer (BL) and cloud processes, it is critical to improve our understanding of key aerosol, cloud, precipitation, and BL processes. Over the north Atlantic Ocean (NA), cold-air outbreaks are common, yet few studies of the aerosol and environmental controls of the associated convective BL clouds exist as needed to develop and evaluate GCM representations. Although processes cannot be observed, cloud and aerosol properties can be measured in-situ or remotely retrieved, which when combined with numerical simulations enable process level understanding required to improve model representations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Using Machine Learning to Improve Thermostability of MHETase

Protein engineering is a field which utilizes proteins as tools, which has many useful applications in medicine, industry, biofuels and more.1 One such protein is MHETase, which is a protein that plays an important function in the degradation of polyethylene terephthalate (PET) plastics, which are commonly used in water and soda bottles.2 However, these proteins are adapted to work in specific conditions, and may not satisfy the desired properties that a new application would desire, or could be improved. For instance, a more thermostable MHETase would be more effective in the plastic degradation conditions.3 To make these desired changes, the primary structure of the protein is mutated, but there are many possible mutations and positions to mutate to make with the 20 canonical amino acids. Therefore, to narrow down the possibilities and to make the process of finding a thermostable MHETase variant, we used sequence design tools that are grounded in machine learning to find mutations that would improve thermostability of MHETase.4 In particular, we used the tools Protein MPNN and Fireprot to design a more thermostable MHETase enzyme. We then compiled these mutations into a library and grew these proteins using bacteria colonies, and measured their effectiveness using a fluorescent protein marker. Thermostable proteins and their marker would fold correctly and fluorescence would be seen, but if neither folded correctly then there would be no marker detected. We grew these proteins in bacteria and then intend to use these methods to evaluate their thermostability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Using Machine Learning to Improve Thermostability of MHETase

Protein engineering is a field which utilizes proteins as tools, which has many useful applications in medicine, industry, biofuels and more. One such protein is MHETase, which is a protein that plays an important function in the degradation of polyethylene terephthalate (PET) plastics, which are commonly used in water and soda bottles.2 However, these proteins are adapted to work in specific conditions, and may not satisfy the desired properties that a new application would desire, or could be improved. For instance, a more thermostable MHETase would be more effective in the plastic degradation conditions.3 To make these desired changes, the primary structure of the protein is mutated, but there are many possible mutations and positions to mutate to make with the 20 canonical amino acids. Therefore, to narrow down the possibilities and to make the process of finding a thermostable MHETase variant, we used sequence design tools that are grounded in machine learning to find mutations that would improve thermostability of MHETase.4 In particular, we used the tools Protein MPNN and FireProt to design a more thermostable MHETase enzyme. We then compiled these mutations into a library and grew these proteins using bacteria colonies, and measured their effectiveness using a fluorescent protein marker. Thermostable proteins and their marker would fold correctly and fluorescence would be seen, but if neither folded correctly then there would be no marker detected. We grew these proteins in bacteria and then intend to use these methods to evaluate their thermostability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

TIGER, A thermodynamics Equilibrium Tool for Explosives Update: Improved Solver

The thermodynamic equilibrium code known as TIGER has been in use since the 1970s and is designed to calculate the performance of energetic materials during detonation at high temperatures and pressures. The original TIGER code utilized a limited database consisting of 12 gaseous and 3 condensed constituents, which were composed of the elements carbon (C), hydrogen (H), nitrogen (N), oxygen (O), and aluminum (Al). In contrast, the more modern JCZS3 database features a significantly larger dataset, including 756 gaseous species, 189 positive and negative ions, and 496 condensed constituents derived from 62 different elements. While this expanded product species database allows for the exploration of a broader range of problems relevant to our laboratory, it also introduces challenges related to convergence, particularly when both liquid and solid species coexist under a vapor dome. In this work, we present an improved TIGER solution technique aimed at accurately determining the equilibrium state for systems that can produce a diverse array of products, including both solid and liquid condensed species. This report presents the status of the TIGER solver as of the end of FY25. Ongoing efforts are focused on enhancing the solver, and the report outlines several planned improvements. We anticipate that further developments will require additional documentation in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Next-generation perovskite photovoltaics: improving, stabilizing, and lead-sealing of record-setting laboratory solar cells towards commercialization

Summary: In the proposed program we plan to improve perovskite photovoltaic performance by developing (1) orientational control of 3D/2D perovskite heterostructures to simplify device architectures, thus improving device efficiencies and stability; (2) high-throughput optical measurements and real-time device simulations for device optimization; (3) robust, dual-pronged lead-sealing and oxygen/moisture/UV barrier films for long-term stability. Specifically, we seek to develop an in-depth understanding of the perovskite film formation, interface passivation, device stability, and environmentally friendly encapsulation, which together will lead to perovskite devices with PCE of over 28%, stability of T80 at 85/85 (85% humidity at 85 degrees C) for 10,000, expected to be equivalent to T90 of 100 hours), and architectures that would satisfy the U.S. EPA and RoHS limits of lead-leaching. The knowledge generated with this project will be applicable to tandem devices with wider-bandgap perovskites.

14 SOLAR ENERGY↗

DOE OSTI2025

Collaborative Proposal: Improving understanding of the internal structure and dynamics of deep convection using ARM observations and large eddy simulations

Recent observational and large eddy simulation (LES) modeling studies have nearly unanimously supported the view of deep cumulus convection being composed of a series of quasi-spherical bubbles of buoyant air, known as moist thermals. Despite the prevalence of moist thermals in deep convection, a comprehensive theory for the dynamics of these structures is lacking. Most current conceptual models for cumulus convection are based on canonical scaling theories for dry thermals or plumes; however, there is considerable evidence that the behavior of moist thermals differs markedly from these theories. Furthermore, the theoretical basis for most cumulus parameterizations originates from the plume conceptual model, and therefore these parameterizations are inconsistent with the real structure of moist convection. Motivated by the aforementioned knowledge gaps, this “end-to-end” research effort use theory, observations, numerical simulations, and direct improvements to the Zhang-McFarlane (ZM) convection scheme in the global climate Community Atmosphere Model (CAM) to address the following research questions: What key environmental parameters determine whether or not shallow convection will transition into deep convection, in the context of thermal-like updrafts? What factors regulate the size of thermals within cumulus updrafts? How does vertical wind shear influence thermal behavior, and as a consequence, vertical velocity and mass flux profiles and the shallow-to-deep convective transition? What are the critical processes that determine updraft vertical velocities and their connection to the vertical mass flux profile for thermal-like updrafts? Idealized LES modeling will be used in conjunction with theoretical models for the core properties of thermal-like updrafts to better understand key processes that regulate thermal ascent rates and entrainment properties. Thermal-tracking procedures will be used to characterize the behavior of thermals within the LES, and recently developed direct measures of entrainment and detrainment will be used to quantify entrainment/detrainment rates. Building from these results, we will analyze the structure of moist thermals from hemispheric range-height indicator scans taken during the Atmospheric Radiation Measurement Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign, and from “real case” LES of CACTI events. This combined modeling and observational analysis will provide essential validation for the existing body of research on moist thermal dynamics, which is based primarily on modeling studies. With the insight gained from the aforementioned activities, we will modify the Zhang-McFarlane convection scheme to improve its representation of updraft vertical velocity and entrainment rate profiles. These process-level changes will be tested in the Community Atmosphere Model to assess the impact on global climate simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

FY20 Improvements to CTF Code Verification and Unit Testing

In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which focuses on improving Light Water Reactors (LWRs) through Modeling and Simulation. This hub, named the Consortium for the Advanced Simulation of LWRs (CASL), attempts to characterize and understand LWR behavior under normal operating conditions and use any gained insights to improve their efficiency. In collaboration with North Carolina State University (NCSU), CASL has worked extensively on the thermal-hydraulic subchannel code Coolant Boiling in Rod Arrays–Three Field (COBRA-TF). The NCSU/CASL version of COBRA-TF has been rebranded as CTF. This document focuses on code verification test problems that ensure CTF converges to the correct answer for the intended application. The suite of code verification tests are mapped to the underlying conservation equations of CTF, and significant gaps are addressed. Convergence behavior and numerical errors are quantified for each of the tests. Tests that converge at the correct rate to the corresponding analytic solution are incorporated into the CTF automated regression suite. A new verification utility is created for this purpose, which enables code verification by generalizing the process. For problems that do not behave correctly, the results are reported but the problem is not included in the regression suite. In addition to verification studies, this document also quantifies the existing tests of constitutive models. A few existing gaps are addressed by adding new unit tests.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

AOI 5 Improved Efficiency of Medium- and Heavy-Duty Natural Gas and Propane (LPG) Engines

Spark-ignited heavy-duty (HD) natural gas engines typically experience efficiency losses at part-load operation due to throttling requirements needed to maintain stoichiometric combustion. A substantial portion of medium- and heavy-duty engine operation occurs in this low-load region, resulting in increased brake-specific carbon dioxide emissions and reduced overall efficiency. This project designed, developed and demonstrated cylinder deactivation (CDA) technology on an HD natural gas engine to mitigate these losses. CDA enables selective deactivation of cylinders, reducing pumping losses while maintaining required torque output and meeting vehicle noise, vibration, and harshness (NVH) targets. The project objectives were successfully achieved, demonstrating up to 12% improvement in fuel consumption over the next generation HD NG engine on key low loaded HD cycles and maintained compliance with 0.02 g/hp-hr NO x emissions with comparable or better vibrations to current product. These results confirm that CDA technology can substantially improve the fuel efficiency and environmental performance of heavy-duty natural gas engines, reinforcing their potential as a low-carbon bridge solution in the transition toward zero-emission transportation technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Improved PARE (Pressurized Airborne Release Equipment) for ARF (Airborne Release Fraction) and RF (Respirable Fraction) Testing

An improved version of the PARE (Pressurized Airborne Release Equipment) system (Sutter 1983a and Sutter 1983b and Ballinger et al 1987) has been developed for powder venting testing. This effort seeks to improve the accuracy of risk estimation for the venting of pressurized powders and the venting of gases through pressurized powders.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2026

Improving Production in the Emerging Paradox Oil Play (Final Technical Report)

This report documents the results of the DOE-funded project Improving Production in the Emerging Paradox Oil Play, focused on integrating geological characterization, petrophysical analysis, reservoir simulation, and field development planning to improve hydrocarbon recovery from the Paradox Basin. Project activities included core and log analysis, assessment of reservoir heterogeneity and compartmentalization, evaluation of completion and stimulation strategies, and development of an uncertainty-aware field development framework. Findings highlight the importance of selective completions, geology-driven well placement, and targeted stimulation in vertically heterogeneous carbonate reservoirs.

02 PETROLEUM↗

DOE OSTI2025

Improving the Performance of Mid-T Baked Niobium Cavities through Post-Bake Surface Treatment

he Medium temperature (mid-T) baking of niobium superconducting radio-frequency cavities at 300 350 C in a vacuum furnace is known to enhance the quality factor (Q₀). However, despite this improvement, cavities treated with this process often exhibit premature quench at relatively low accelerating fields. This limitation is suspected to arise from the formation of surface contaminants, such as niobium carbides, during the furnace bake at 350 C for 3 h. To investigate the influence of potential surface contamination, this study applied an ultralight chemical removal to 1.3 GHz and 650 MHz single-cell cavities that had undergone medium-temperature baking. The removal of the top RF surface layer led to a notable improvement in the quench field and Q₀, indicating a beneficial effect of eliminating possible surface residues introduced during the bake.

Chouhan, Vijay [Fermilab]↗

DOE OSTI2026

Improving Performance via Energy Efficiency JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits

Energy efficiency is pivotal to achieving operational excellence, as it enhances value while reducing waste. This presentation explores the integration of non-energy benefits (NEBs) into energy efficiency projects, which can lead to risk reduction, value creation, and cost savings. By quantifying NEBs - such as improved safety, decreased pollution, and increased productivity - companies can strengthen their business cases for energy investments, ultimately improving payback periods and aligning with strategic goals. Designed for a diverse audience, from trained auditors to novices in energy assessments, we have developed open-source software called JUSTIFI, NEB finding methodology, and training materials which build on existing frameworks and leverages resources from the U.S. Department of Energy and Better Plants energy system analysis software suite such as MEASUR. This work aims to maximize ROI through NEB identification, utilizing tools like JUSTIFI and the NEBs Discovery Protocol.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Improvements to Stripping Foils in BTA

To achieve the desired charge state in the Alternating Gradient Synchrotron (AGS), there is a stripping foil in the Booster to AGS (BtA) transfer line. For light ions, such as p, d, and h, they are already fully stripped in the Booster, or ions such as O have few electrons to be stripped off, and a thin foil of aluminum is used. For medium weight ions, such as Zr and Ru, they use what foils are available which have been optimized for heavy and light ions at 100 MeV/u. This worked well in the Zr case which achieved a measured stripping efficiency of 87%, contrary to the Ru case which achieved a measured stripping efficiency of 63%. For the EIC early science, Ag is currently intended to be the first ion. Using our existing foils, this would, at best, yield a helium-like charge state with a theoretical stripping efficiency of 50%. To improve on this, two foils of Ti or Nb have been selected to provide optimal stripping efficiency of Ag, and other energetic medium ions, which can reach 90% efficiency to fully strip the Ag ions. For heavy ions, the Al+C or Al+Ni stripping foils (sandwich foils) are used to produce helium-like charge states. For high intensity operation of Au, the Al foil nears its melting point and, in some cases, has been severely damaged. To maximize foil lifetime, there is a maximum intensity per unit time in BTA dependent on the Booster and AGS timing configurations. To mitigate the risk of melting the Al, replacement foils that use Ti, Nb, or anodized Al have been evaluated for their improved thermal qualities. At the selected thicknesses, each foil has equivalent charge distributions before entering the C foil, and should provide the same stripping efficiency through the entire sandwich.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

2025 Advances in NekRS: Supporting improved performance for nuclear applications

This report presents several 2025 advancements in NekRS, a high-fidelity spectral element CFD code developed at Argonne National Laboratory to support the NEAMS thermal-hydraulics program. The forthcoming v25 release consolidates several of these advances, adding new features for portability across heterogeneous GPU architectures, real-time in situ visualization, improved turbulence modeling, and conjugate heat transfer coupling. Over the past year, NekRS has demonstrated strong scalability and performance on DOE’s leading exascale platforms, including Aurora and Frontier, confirming its readiness for some of the largest and most complex simulations attempted to date. These achievements provide a powerful new platform for high-fidelity data generation, which in turn supports the development and validation of advanced closure models critical for reactor safety and design. Significant algorithmic innovations have also been introduced. A new global runtime h-refinement capability simplifies workflows by reducing mesh preparation burdens and enabling coarse-to-fine restarts. Building on this, a novel multigrid strategy was implemented to accelerate pressure and transport solves at scale, addressing long-standing bottlenecks in exascale CFD. Together, these developments improve both the efficiency and accessibility of high-fidelity simulations for reactor-relevant problems. Collectively, these enhancements represent a major step forward in simulation technology, positioning NekRS as a cornerstone of NEAMS efforts to enable accurate, efficient, and scalable high-fidelity analysis of advanced nuclear systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Griffin Capability Improvements in Support of Ex-core Deep-Penetration Problems

Advanced reactor designs, especially portable reactors that are designed to be located closer to humans and operate autonomously, require the ability to accurately compute the ex-core neutron and gamma flux solutions in terms of shielding design optimization to reduce dose rates at the vessel boundary and detector signal prediction to drive the reactor control system. The Nuclear Energy Advanced Modeling and Simulation program has prioritized improvements to the Griffin discrete ordinates (SN) solver for deep-penetration problems in fiscal year 2025. Significant advancements have been made to the Griffin methodologies for solving ex-core deep-penetration problems for steady-state, fixed-source and transient calculations. This work presents the methodology improvements as well as a comprehensive demonstration with a Transient Test Reactor model and measurements.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Improving ProtoDUNE pion cross-section measurements with NuGraph Michel-electron tagging

Understanding hadron-argon interactions is essential for precise neutrino energy reconstruction and final-state interaction modeling in liquid-argon time projection chamber (LArTPC) experiments such as DUNE. In particular, pion absorption and charge-exchange processes constitute significant sources of systematic uncertainty in neutrino oscillation measurements. ProtoDUNE-SP, a large-scale LArTPC prototype operated at the CERN Neutrino Platform and exposed to charged-particle test beams in the few-GeV range, enables direct measurements of these processes. This work focuses on the measurement of differential cross sections for pion absorption and charge exchange using the 2 GeV/c pion beam data from the ProtoDUNE-SP run. A key component of this analysis is the identification of Michel electrons from $\pi \rightarrow \mu \rightarrow e$ decay chains, which helps separate different interaction topologies and improves background rejection. Michel electron identification will also assist in reliably calibrating the electromagnetic response in ProtoDUNE-SP data and for the future DUNE detectors. In this analysis, we apply NuGraph to identify Michel electrons. NuGraph is a graph neural network that models detector hits as nodes connected by spatial and temporal edges for particle and topology classification in LArTPC detectors. We first benchmark NuGraph’s Michel electron classification performance using ICEBERG data, a small-scale LArTPC prototype used for DUNE electronics and reconstruction development, and then transfer the approach to ProtoDUNE-SP. This poster presents the analysis strategy, NuGraph-based classification studies, and discusses how these developments are expected to improve the pion cross-section measurement.

Razafinime, Soamasina Herilala [Cincinnati U.] (OR↗

DOE OSTI2026

Developing New Beam Constraints to Improve Sterile Neutrino Searches at NOvA

NOvA is a long-baseline neutrino oscillation experiment utilizing two functionally identical liquid scintillator detectors located 14 mrad off-axis from the NuMI beam at Fermilab. The position of the Near Detector (ND), 1 km from the neutrino production target, means it sees a range of off-axis angles (12.6-17.2 mrad), resulting in a noticeable energy gradient across the detector face. In addition, the neutrino production points vary widely along the decay pipe, which leads to a distribution of true neutrino baselines (L), and limits the sensitivity of our current sterile neutrino searches. This work presents a new "baseline reconstruction" technique designed to exploit our off-axis position to triangulate the precise origin of neutrinos within the NuMI beamline. By projecting the total momentum vector of Charged Current (CC) and Neutral Current (NC) interactions back to the central beam axis, we estimate the individual baseline for each event. We describe the technique, evaluate its performance, and demonstrate how this can improve the sensitivity of future searches for sterile neutrinos through reduced flux systematic uncertainties and improved L/E resolution.

Burns, Jessica [Cincinnati U.]↗

DOE OSTI2023

$B$-meson semileptonic decays with highly improved staggered quarks

We present an update of the Fermilab Lattice and MILC Collaborations project to compute the form factors for semileptonic $B_{(s)}$-meson decays. Our calculation uses the highly improved staggered quark (HISQ) action for sea and valence quarks, and ensembles with up, down, strange, and charm quarks in the sea. Using a highly improved action with the MILC Collaboration's gauge ensembles with lattice spacings down to $a\approx0.03$ fm, allows the heavy valence quarks to be treated with the same discretization as the light and strange quarks. This unified treatment of the valence quarks allows for absolutely normalized vector currents, bypassing the need for perturbative matching, which has been a source of uncertainty in previous calculations of $B$-meson decay form factors by our collaboration. All preliminary form-factor results are blinded.

Lytle, Andrew↗