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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗
DOE OSTI2025

Milky way bulge extra-tidal star survey: MWBest

The Milky Way Bulge Extra-Tidal Star Survey (MWBest) is a spectroscopic initiative aimed at identifying stars that have been tidally stripped from globular clusters in the inner regions of the Galaxy. As part of the Visiting Faculty Program at Fermilab, we have developed theoretical tools and simulations to compare against observed signatures of extra-tidal stars surrounding both bulge globular clusters (GCs) and low-luminosity clusters. By combining the spatial distributions of simulated stripped stars with new MWBest observations, we are gaining insight into the gravitational potential of the inner Galaxy and the role that bulge GCs may play in enriching the surrounding field star population. We further explore the hypothesis that some low-luminosity bulge GCs may in fact be dense clumps of debris, stripped from more massive GCs as they migrate inward due to dynamical friction.

Kunder, Andrea [Unlisted, US, WA]↗
DOE OSTI2025

Integrating Energy-Efficient Computing with Computational Research to Accelerate Energy Technology

NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Universal Injector at LERF – Baseline Design

A new electron injector complex has been proposed within the Low Energy Recirculating Facility (LERF) vault, which would serve both the 22 GeV CEBAF and the positron programs, while being compatible with the electron source required to produce positrons for Ce+BAF. The baseline design of a 3-pass recirculator features a main linac configured with three cryomodules, five isochronous arcs and three straight sections, allowing electron beam acceleration up to 650 MeV. The injector offers the flexibility to extract 1-pass and 2-pass energy electrons, as needed for positron production, with final reconfiguration to a 3-pass 650 MeV injector for 22 GeV CEBAF. This paper provides an overview of the baseline design of the Universal injector complex, including the 8 MeV injector and the recirculator. A comprehensive suite of beam dynamics studies to validate our design is being launched, starting with start-to-end tracking with Elegant followed by the orbit correction and error mitigation.

Bogacz, A. [Thomas Jefferson National Accelerator ↗
DOE OSTI2025

Preliminary modeling of triply periodic minimal surface (TPMS) structures using RELAP5-3D

With the United States Department of Energy (DOE)’s goal of quadrupling the nation’s nuclear energy supply by 2050, and with the Advanced Fuels Campaign pushing for new types of advanced reactor fuels and geometries, the need has arisen for new nuclear fuel designs. One such design is to swap out current nuclear fuel geometries in exchange for another type of geometry, called a Triply Periodic Minimal Surface (TPMS). TPMSs are self-supporting, infinitely repeating lattices—attributes that lend themselves well to additive manufacturing. These surfaces also possess enhanced heat transfer properties thanks to their internal area changes and large surface-area-to-volume ratios. Their drawback, however, is an increased pressure drop. Given the small amount of correlations and data (Reynolds numbers in the 2,000–8,000 range), and the minimal amount of experience so far obtained by modeling TPMS structures using 1D systems codes such as the Reactor Excursion and Leak Analysis Program (RELAP5-3D), further research into this topic was needed. Using data from the University of Wisconsin - Madison (UW), curve fits were created for both a Heat Transfer Coefficient (HTC) correlation and a Darcy friction factor empirical coefficient correlation. The curves’ coefficients and multipliers were then output and utilized in RELAP5-3D models of two upcoming experiments—Flow Loop for INFLUX Pressure drop (FLIP) and Microreactor Agile Non-nuclear Experimental Test (MAGNET)—aimed at increasing the available data for Reynolds numbers to the 16,000–36,000 range for TPMS structures. The models were run under the conditions utilized by a Computational Fluid Dynamics (CFD) analysis performed by another group at Idaho National Laboratory. Only CFD pressure drop values were obtained from the FLIP test, and those values showed that the RELAP5-3D models had a lower rate of pressure increase in comparison to the CFD values. In addition, there seemed to be a vertical shift upward in the pressure drop for both models whenever the TPMS porosity decreased, and the RELAP5-3D models showed a higher vertical shift in comparison to the CFD values. The MAGNET results did not correspond to any CFD or experimental results against which they could be compared, so they were instead compared against the proposed CFD input conditions. These values were then compared with each other to make sure the model seemed to be performing as expected, paving the way for future tests that can be run for the purpose of further analyses and comparisons. The pressure drop increased with temperature and mass flow rate independently. The temperature change would decrease with increasing mass flow rate and temperature, which was just as we expected based on the fact that the lower viscosity and decreased density would result in higher friction and churning losses. The last metric that was assessed was the enthalpy flow change, which increased with increasing mass flow rate and decreasing temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Journey over Destination: Dynamic Sensor Placement Enhances Generalization

Reconstructing complex, high-dimensional global fields from limited data points is a challenge across various scientific and industrial domains. This is particularly important for recovering spatio-temporal fields using sensor data from, for example, laboratory-based scientific experiments, weather forecasting, or drone surveys. Given the prohibitive costs of specialized sensors and the inaccessibility of
certain regions of the domain, achieving full field coverage is typically not feasible. Therefore, the development of machine learning algorithms trained to reconstruct fields given a limited dataset is of critical importance. In this study, we introduce a general
approach that employs moving sensors to enhance data exploitation during the training of an attention based neural network, thereby improving field reconstruction. The training of sensor locations is accomplished using an end-to-end workflow, ensuring
differentiability in the interpolation of field values associated to the sensors, and is simple to implement using differentiable programming. Additionally, we have incorporated a correction mechanism to prevent sensors from entering invalid regions within the domain. We evaluated our method using two distinct datasets; the results show that our approach enhances learning, as evidenced by improved test scores.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Measurement of fifth- and sixth-order fluctuations of (net-)proton number in Au + Au collisions from phase II of the beam energy scan program at RHIC

We report high-statistics measurements of fifth- and sixth-order factorial cumulants and cumulant ratios of (net-)proton multiplicity distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7–27GeV, using data from the STAR experiment collected during the Beam Energy Scan Phase II at RHIC. Protons and antiprotons are identified at midrapidity (|𝑦| < 0.5) with transverse momentum 0.4 < 𝑝 𝑇 < 2.0GeV/𝑐. The proton factorial cumulants 𝜅 4 , 𝜅 5 , and 𝜅 6 increase with order but exhibit no sign alternation within current uncertainties, offering no evidence for a two-component structure in the proton multiplicity distribution, as might be expected near a first-order phase transition. The cumulant ratios 𝐶 5 /𝐶 1 and 𝐶 6 /𝐶 2 fluctuate around zero in collisions at 0–40% centrality. The results are consistent with both the negative predictions from lattice QCD and the positive trends obtained from the ultrarelativistic quantum molecular dynamics (UrQMD) model. At $\sqrt{s_{NN}}$ ≳ 27GeV, the 𝐶 4 /𝐶 2 and 𝐶 5 /𝐶 1 results are compatible with predictions from lattice QCD, functional renormalization group (FRG), and hadron resonance gas (HRG) models, while UrQMD describes the data better at lower energies. Here, these measurements place constraints on baryon number fluctuations and offer valuable insights into the QCD phase structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Cost of emulating a small quantum annealing problem in the circuit model

Demonstrations of quantum advantage for certain sampling problems have generated considerable excitement for quantum computing and have further spurred the development of circuit-model quantum computers, which represent quantum programs as a sequence of quantum gates acting on a finite number of qubits. Amongst this excitement, analog quantum computation has become less prominent, with the expectation that circuit-model quantum computers will eventually be sufficient for emulating analog quantum computation and thus rendering analog quantum computation obsolete. In this work we explore the basic requirements for emulating a specific analog quantum computation in the circuit model: the preparation of a biased superposition of degenerate ground states of an Ising Hamiltonian using an adiabatic evolution. We show that the overhead of emulation is substantial even for this simple problem. This supports using analog quantum computation for solving time-dependent Hamiltonian dynamics in the short term and midterm, assuming analog errors can be made low enough and coherence times long enough to solve problems of practical interest.

Quantum algorithms & computation↗
DOE OSTI2025

Myco-CORPSE simulations assessing mycorrhizal carbon allocation across U.S. forests and global change scenarios

Plants allocate a substantial portion of their fixed carbon belowground to mycorrhizal fungi in exchange for nutrients and other benefits. However, most current ecosystem models omit mycorrhizal processes, limiting our ability to predict plant–soil carbon dynamics under environmental change. To address this gap, we used a mycorrhiza-explicit soil biogeochemical model, Myco-CORPSE (Mycorrhizal Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment), to simulate tree carbon allocation to arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi in temperate forests.The dataset includes outputs from two sets of model simulations:1. Perturbation experiments: Simulations across gradients of ECM dominance (0–100%), nitrogen deposition, soil temperature, and net primary productivity (NPP) to test how these factors affect mycorrhizal C allocation and nutrient cycling.2. FIA-based simulations: Model applications to over 1,800 U.S. forest sites using site-specific data from the U.S. Forest Inventory and Analysis (FIA) program, including vegetation composition, mycorrhizal type, climate, litter traits, soil properties, and N deposition.Model outputs include simulated mycorrhizal carbon allocation and related biogeochemical variables, such as soil and microbial carbon and nitrogen stocks. Data are provided in CSV format and organized by experiment type (in separate ZIP files). Python scripts for running simulations, plotting, and spatial mapping are also included and organized similarly. No proprietary software is required. These outputs support a peer-reviewed study and were used to generate figures and tables in the associated publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Chloroplast Stress Signals: Control of Retrograde Signaling, Chloroplast Turn-Over, and Cell Fate Decisions

Chloroplasts (photosynthetic plastids) are semiautonomous organelles that contain their own small genomes. The proteomes of chloroplasts, however, are a mixture of plastid and nuclear-encoded proteins. Chloroplasts perform photosynthesis, which is prone to damaging the organelles, leading to the production of reactive oxygen species (ROS) that damage the cell under environmental stresses. Thus, for the cell to maintain proper chloroplast function, efficient photosynthesis, and avoid ROS damage, it relies on complex crosstalk between the chloroplast, the nucleus, other organelles within the cell, and the cytoplasm in between. This communication involves retrograde signals from chloroplasts to control nuclear gene expression, programmed cell death (PCD), and chloroplast degradation. Here we review these signals with an emphasis on the roles of the ROS singlet oxygen ( 1 O 2 ) and plastid gene expression. We cover (1) recent work on understanding how multiple 1 O 2 signaling pathways can be initiated within stressed chloroplasts, (2) how individualized post-translational regulatory systems allow chloroplasts to control their proteomes and degradation, and (3) how chloroplast signals ultimately control cell fate decisions, such as PCD, senescence, and vacuole-mediated degradation of chloroplasts (chloroplast quality control). Overall, this chapter discusses how chloroplasts can act as environmental sensors for the cell and allow plants to acclimate to stress and thrive in dynamic environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Impact of lead on an axisymmetric, single bead blown powder DED overhung geometry

Metal additive manufacturing can be utilized for the near net-shape manufacture of components in a layer wise technique. Traditionally, the buildup process is conducted in the direction of gravity or bottom to top in the vertical orientation; however, with the availability of commercial systems with additive heads or fixturing that can index from vertical, and the need to manufacture larger parts without modifying available systems, the limitation of manufacturing from bottom to top is removed enabling the buildup of larger components printed at an angle from vertical. The effect of gravity on the melt pool and as-deposited component quality when printing off vertical is unknown in literature, especially for axisymmetric components. This understanding is critical for the advancement of manufacturing components of increased size in 4 and 5-axis additive systems. This investigation utilizes blown powder directed energy deposition to evaluate the change in as-printed geometry when the start point is altered in relation to gravity while the part rotates to manufacture an axisymmetric component. The objectives of this work are to determine the impact of the deposition location on the geometric variability on axisymmetric components. This investigation tests the hypothesis that differences in layer height exist due to a change in catchment efficiency when the deposition location is moved to a tangent of the round geometry due to a change in the melt pool dynamics. It was found the ideal deposition location when printing at 26.6-degrees from vertical was at −90-degrees from the top center point of the component, along the tangent, where gravity was pushing the melt pool down, but the rotation of the part was pulling the deposited material towards the top center of the component. This work provides an understanding of layer height stability and catchment efficiency to guide print orientation strategy for high-aspect ratio components. It was found the −90-degree lead deposition had the best layer height stability at 0.6 % as compared to the top-center at 6.3 % and +90-degree deposition location at 9.2 % for the nominal programmed layer height. The change in layer height also effected the final diameter the greatest for the top center deposition location where the diameter diverged by 2.5 % during the overbuild condition and converged by 0.6 %. In conclusion, this finding will increase the manufacturing efficiency of axisymmetric components by increasing the passive stability of the printing process for the successful manufacture of parts without the need for perfectly calibrated manufacturing parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A research program to measure the lifetime of spin polarized fuel

The use of spin polarized fuel could increase the deuterium-tritium (D-T) fusion cross section by a factor of 1.5 and, owing to alpha heating, increase the fusion power by an even larger factor. Issues associated with the use of polarized fuel in a reactor are identified. Theoretically, nuclei remain polarized in a hot fusion plasma. The similarity between the Lorentz force law and the Bloch equations suggests polarization can be preserved despite the rich electromagnetic spectrum present in a magnetic fusion device. The most important depolarization mechanisms can be tested in existing devices. The use of polarized deuterium and 3 He in an experiment avoids the complexities of handling tritium, while encompassing the same nuclear reaction spin-physics, making it a useful proxy to study issues associated with full D-T implementation. 3 He fuel with 65% polarization can be prepared by permeating optically-pumped 3 He into a shell pellet. Dynamically polarized 7 Li-D pellets can achieve 70% vector polarization for the deuterium. Cryogenically-frozen pellets can be injected into fusion facilities by special injectors that minimize depolarizing field gradients. Alternatively, polarized nuclei could be injected as a neutral beam. Once injected, the lifetime of the polarized fuel is monitored through measurements of escaping charged fusion products. Multiple experimental scenarios to measure the polarization lifetime in the DIII-D tokamak and other magnetic-confinement facilities are discussed, followed by outstanding issues that warrant further study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

NbZr_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys niobium-zirconium (Nb-Zr). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Nb and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name "case-N" where N ranges between 11 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system FILES contained in each subdirectory with name "case-N" where N ranges between 1 and 10, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. {ID}.POSCAR: input file that defines the atomic structure of a system at the beginning of ID execution of geometry optimization with PREC=LOW 4. {ID}.CONTCAR: output file that provides the atomic positions and cell parameters at the end of ID execution of geometry optimization with PREC=LOW in the INCAR file 5. {ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of geometry optimization that has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.{ID}.out: file with diagnostic information about the execution of the ID execution of the geometry optimization with precision variable set to PREC=Low in the INCAR file 7. N{ID}.POSCAR: input file that defines the atomic structure of a system after the geometry optimization run at low precision. This represents the input for the ID execution of the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. N{ID}.CONTCAR: output file that provides the atomic positions and cell parameters after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 9. N{ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.{ID}.out: file with diagnostic information about the ID execution of geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15–50 (1996) (4) Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2024

TaZr_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys tantalum-zirconium (Ta-Zr). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Ta and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name "case-N" where N ranges between 11 and 80, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system FILES contained in each subdirectory with name "case-N" where N ranges between 1 and 10 and between 81 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. {ID}.POSCAR: input file that defines the atomic structure of a system at the beginning of ID execution of geometry optimization with PREC=LOW 4. {ID}.CONTCAR: output file that provides the atomic positions and cell parameters at the end of ID execution of geometry optimization with PREC=LOW in the INCAR file 5. {ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of geometry optimization that has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.{ID}.out: file with diagnostic information about the execution of the ID execution of the geometry optimization with precision variable set to PREC=Low in the INCAR file 7. N{ID}.POSCAR: input file that defines the atomic structure of a system after the geometry optimization run at low precision. This represents the input for the ID execution of the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. N{ID}.CONTCAR: output file that provides the atomic positions and cell parameters after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 9. N{ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.{ID}.out: file with diagnostic information about the ID execution of geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15–50 (1996) (4) Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2025

NARUC Resilience Framework

The NARUC Resilience Framework provides state regulators and other key stakeholders with a structured approach to considering policies and programs that will enhance grid resilience amid evolving technological, environmental and economic challenges. This Framework consolidates insights from nationwide workshops and peer discussions into six actionable components: (1) setting goals and objectives, (2) leveraging use cases, (3) establishing shared definitions, (4) ensuring inclusive process leadership, (5) addressing critical design questions, and (6) guiding implementation. This Framework is intended as a strategic tool for regulators to navigate resilience investments, prioritize affordability, integrate stakeholder needs, and foster collaboration across agencies, all while balancing cost-effectiveness with societal and economic resilience outcomes. By presenting a structured approach to decision-making rather than prescriptive solutions, the Framework supports nuanced, jurisdiction-specific resilience planning and is adaptable to the dynamic demands of modern energy systems

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The Hydropower Game: An Interactive Learning Tool for the Future Hydropower Workforce

This report documents a Seedling project supported by the U.S. Department of Energy (DOE) Water Power Technologies Office (WPTO), conducted by Argonne National Laboratory (ANL) and the National Laboratory of the Rockies (NLR). The Seedling and Sapling Program provides small grants over short duration to enable early-stage research at national laboratories. This funding mechanism is intended to cultivate innovative ideas and expand research road maps in hydropower and marine energy technologies. Under this Seedling award, the project team developed an educational outreach tool, or “serious game”, built in Python and powered by the Pygame library, aimed at teaching fundamental hydropower concepts through an engaging, interactive learning experience. The game features multiple lessons covering several hydropower topics while allowing for expansion and customization in the instance of future funding availability: • Hydropower Plant Types: Players explore and compare the mechanics and applications of run-of-river, dam hydropower, and pumped-storage hydropower. • Flow Dynamics and Power Generation: Interactive tasks demonstrate how release rate and hydraulic head combine to determine power output. • Grid Operations and Load Following: Simulations illustrate how hydropower facilities respond to fluctuating electricity demand to balance the grid. • Market Integration: Levels scaffold understanding of how hydropower interfaces with the broader energy market, including operational and economic considerations. The tool was showcased at several science, technology, engineering, and mathematics (STEM) outreach events, where it was demoed to students, educators, and the general public. These events provided valuable opportunities to collect feedback on the gameplay, storyline, and educational objectives from a wide audience. The game was presented at STEMapalooza, Introduce a Girl to Engineering Day, STEMCON, and Clean Currents 2025. Insights gathered during these demonstrations informed refinements to the game’s user experience and strengthened its effectiveness as an educational tool for teaching hydropower concepts. This report outlines the game’s design philosophy, educational objectives, technical implementation, user experience insights, and potential for broader deployment within educational and workforce development contexts. It emphasizes how gamified learning can demystify complex hydropower science and inspire interest in water-power technologies. The project’s success demonstrates the value of Seedling funding in fostering creative, lowcost educational tools that support DOE’s mission to advance energy literacy and innovation. The report concludes with recommendations for expanding the tool by adding new levels, integrating assessment metrics, and exploring commercialization or deployment pathways through future Sapling funding. The official webpage of the Hydropower Game, which includes a link to the educational tool, can be accessed at www.anl.gov/hydropower/hydropower-game.

13 HYDRO ENERGY↗
DOE OSTI2026

‘Universal Injector’ at LERF - Layout and Optics Architecture

Here, we present a next level design of a compact injector within the LERF vault, which would serve both the 22 GeV CEBAF and the positron program, while being compatible with the electron source required to produce positrons for Ce+BAF. The baseline design of a 3-pass recirculator features a main linac configured with three C-75 cryo-modules, five isochronous return arcs and three straight sections, facilitating electron beam acceleration up to 650 MeV. The Universal Injector offers flexibility of extraction 1-pass and 2-pass energy electrons, as needed for positron production, with a final 3-pass extraction required by the 650 MeV injector for 22 GeV CEBAF. This note provides an overview of the baseline optics design of the Universal Injector complex, including the 8 MeV injector merger and the recirculator racetrack, including individual extraction lines for all three passes. A comprehensive suite of beam dynamics studies to validate the design is under way; starting with the orbit correction scheme, followed by start-to-end tracking with lattice misalignments and magnet errors.

Bogacz, Alex [Thomas Jefferson National Accelerato↗