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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Full 3D Kinetic Modeling and Quantification of Positive Streamer Evolution in an Azimuthally Swept Pin-to-Plane Wedge Geometry

Cathode-directed streamer evolution in near atmospheric air is modeled in 3D pin-to-plane geometries using a 3D kinetic Particle-In-Cell (PIC) code that simulates particle-particle collisions via the Direct Simulation Monte Carlo (DSMC) method. Due to the computational challenges associated with a complete 360° volumetric domain, a practical alternative was achieved using a wedge domain and a range of azimuthal angles was explored (5°, 15°, 30°, and 45°) to study possible effects on the streamer growth and propagation due to the finite wedge angle. A DC voltage of 6 kV is administered to a hemispherical anode of radius 100 μm, with a planar cathode held at ground potential, generating an over-volted state with an electric field of 4 MV/m across a 1500 μm gap. The domain is seeded with an initial ion and electron density of 10 18 m -3 at 1 eV temperature confined to a spherical region of radius 100 μm centered at the tip of the anode. The air chemistry model [1] includes standard Townsend breakdown mechanisms (electron-neutral elastic, excitation, ionization, attachment, and detachment collision chemistry and secondary electron emission) as well as streamer mechanisms (photoionization and ion-neutral collisions) via tracking excited state neutrals which can then either quench via collisions or spontaneously emit a photon based on specific Einstein-A coefficients [2, 3]. In this work, positive streamer dynamics are formally quantified for each wedge angle in terms of electron velocity and density as temporal functions of coordinates r, Φ, and z. Applying a random plasma seed for each simulation, particles of interest are tracked with near femtosecond temporal resolution out to 1.4 ns and spatially binned. This process is repeated six times and results are averaged. Prior 2D studies have shown that the reduced electric field, E/n, can significantly impact streamer evolution [4]. We extend the analysis to 3D wedge geometries, to limit computational costs, and examine the wedge angle’s effect on streamer branching, propagation, and velocity. Results indicate that the smallest wedge angle that produced an acceptably converged solution is 30°. The potential effects that a mesh, when under-resolved with respect to the Debye length, can impart on streamer dynamics and numerical heating were not investigated, and we explicitly state here that the smallest cell size was approximately 10 times the minimum λ D in the streamer channel at late times. This constraint on cell size was the result of computational limitations on total mesh count.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Systems Packages for Washington State Building Performance Standard Incentive Program: Phase 1 Analysis

Starting in 2026 Washington State building performance standards will come into effect that require commercial buildings larger than 50,000 sf to meet site energy use intensity targets. To support a state incentive program designed to encourage building owners to start complying early, we characterized the building stock energy use of 11 building types, analyzed 43 energy upgrade measures, and developed seven packages of energy upgrade measures using the ComStock energy analysis tool. Each energy upgrade package included from 4 to 17 energy measures consisting of lighting, HVAC, and envelope upgrades. Package savings were calculated for four priority building types using a sample of 35,000 buildings characterized by four building area bins, three climate zones, and two county types (urban and rural). Of the 28 package and building type combinations analyzed, 17 (61%) met or exceeded program energy savings targets and two packages met targets for all four building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Dynamic Species Reduction for Multi-Cycle CFD Simulations (Final Technical Report)

This project primarily sought to address some of the computational cost concerns of detailed simulations by developing improved methods of handling species transport, and chemical kinetics evaluation in a commercial 3D Computational Fluid Dynamics (CFD) environment. Secondary goals were to apply these techniques to fuels and conditions of interest to better understand the key species and reactions required to adequately capture cycle to cycle coupling. Improved modeling will lead to better understanding of these combustion modes and their dependence on fuel composition, which can then enable more clean and efficient engines, ultimately benefiting the consumer as well as the general public. Two approaches were used to address the computational cost. A “Dynamic Species Reduction” (DSR) procedure was developed to remove chemical species from the simulation during periods when chemical reactions were not expected to be important, particularly during gas exchange when temperatures are low and little fuel remains. This modelling procedure automatically detects relevant species to retain in the simulation domain based on their local concentration, removes species below a specified concentration threshold, and then adjusts the remaining species mass to conserve not only the number of H, C, and O atoms in each cell, but also the relative proportions between species and the heating value of the mixture in every cell. The second procedure was a “Product Directed Remapping” (PDR) updates the algorithm used to group individual computational cells for chemical kinetics evaluation to account for non-uniform temperature distributions and the CO to CO 2 ratio in the cells. The model techniques developed in this work successfully demonstrated computational performance improvements for a range of conditions relevant for Highly Dilute SI and HCCI engine operation. Runtime reductions of 10% were observed for small mechanisms, with further reductions of up to 36% observed for larger mechanisms. Improvements were primarily related to reducing the number of chemical species tracked during the gas exchange process using the Dynamic Species Reduction method. With smaller benefits observed from changes to the kinetics binning and evaluation strategy in the post combustion region using the PDR method. The results of this work show the potential for improved computational runtime for complicated simulations. They can and should be extended to additional conditions and new bio-derived and renewable fuels as they are developed and new kinetic mechanisms become available.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Sparse Data Machine Learning Integration with Theory, Experiment and Uncertainty Quantification: Process-Structure-Property-Performance of Friction Deformation Processing

Computer vision and deep learning tools that advance the ability to establish processing-structure-property-performance (PSPP) relations are presented. The Bayesian binning method for image segmentation enables quantitative analysis of microstructural features in an automated way, while the analysis of shapes and relative orientation of these features reveals local deformation maps indicative of both, material flow and residual stresses due to materials processing. The deep learning method leads to the previous knowledge agnostic mapping of empirically observed microstructural zones in friction stir welding (FSW) process and synthetic microstructure generation capability that is statistically equivalent to experimentally collected data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Bayesian Cloud Property Retrievals from ARM Active and Passive Measurements

The optimum use of the continuous measurements of thermodynamics, radiation, aerosols, clouds and precipitation from the DOE Atmospheric Radiation Measurement (ARM) program is key to achieve the DOE Atmospheric System Research (ASR)’s objectives. One of the key mission requirements is to retrieve cloud and precipitation properties, as well as vertical motion parameters, along the vertical cross- section defined by the profiling active sensors. Such retrievals are challenging to perform continuously in the entire spectrum of cloud and precipitation conditions due to the large natural microphysical and dynamical variability, the often-limited information content in the measurements, and the lack of proper characterization of measurement quality and uncertainty. Today, the acquisition of new remote and in-situ sensors by the ARM program creates opportunities to address the microphysical retrieval problem by exploiting new, more robust retrieval techniques and integrating various scattered advancements in both sensor techniques and retrieval algorithms. During this project, we constructed a robust Bayesian Markov chain Monte Carlo (MCMC) cloud property retrieval algorithm that includes a state of the art radar forward model. Our MCMC-based retrieval produces both the best estimate of height-resolved cloud and precipitation properties in the radar profile, as well as an estimate of the in-cloud vertical motion and turbulence. In addition, the MCMC algorithm automatically produces robust and flexible estimates of retrieval uncertainty. We tested the algorithm on several synthetic cloud profiles obtained from large eddy simulation (LES) models with bin-resolved microphysics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Radiological Dispersal Device (RDD) Recovery Guidance: After Action Report from Pilots - Responding to Feedback from Pilots Reviewing RDD Recovery Guidance

The goal of this After Action report is to utilize feedback from the pilot participants to improve the guidance for responding to radiological dispersal device (RDD) events, which can include deliberate acts to release radioactive materials into the environment using explosives or other means or accidental releases (e.g., release from a medical isotope source). This longer-term recovery guidance is an extension of the initial response guidance that was released in a 2017 interagency report called RDD Response Guidance: Planning for the First 100 Minutes. Recovery teams reviewed the longer-term recovery guidance during pilot sessions that were held in Harris County, Texas (March 8-10, 2022) and Seattle, Washington (May 2-3, 2022). The pilot teams reviewed the RDD Recovery Guidance Presentation, which contains a summary of the more detailed RDD Recovery Guidance draft document. The feedback from both pilots was grouped and binned into unique themes (e.g., “checkpoint challenges”) that align with the recovery missions and tactics that they reviewed. PNNL authors of the recovery guidance then prepared responses that describe how they recommend addressing the feedback for each theme. The responses typically included recommendation plans for improving the guidance document, but also described when no changes are needed because the guidance already contains the suggested improvement. These pilot recommendations will be brought to the interagency team to finalize plans for updating and improving recovery guidance materials.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

DES-Y3 galaxies & ACT DR4 CMB lensing tomography

We present a measurement of the cross-correlation between the \maglim galaxies selected from the Dark Energy Survey (DES) first three years of observations (Y3) and cosmic microwave background (CMB) lensing from the Atacama Cosmology Telescope (ACT) Data Release 4 (DR4), reconstructed over $\sim 436$ $\sqdeg$ of the sky. Our galaxy sample, which covers $\sim 4143$ $\sqdeg$, is divided into six redshift bins spanning the redshift range of $0.20<z<1.05$. We adopt a blinding procedure until passing all consistency and systematics tests. After imposing scale cuts for the cross-power spectrum measurement, we reject the null hypothesis of no correlation at 9.1$\sigma$. We constrain cosmological parameters from a joint analysis of galaxy and CMB lensing-galaxy power spectra considering a flat \LCDM model, marginalized over 23 astrophysical and systematic nuisance parameters. We find the clustering amplitude $S_8\equiv \sigma_8 (\Omega_m/0.3)^{0.5} = 0.75^{+0.04}_{-0.05}$. In addition, we co nstrain the linear growth of cosmic structure as a function of redshift. Our results are consistent with recent DES Y3 analyses and suggest a preference for a lower $S_8$ compared to results from measurements of CMB anisotropies by the \textit{Planck} satellite, although at a mild level ($< 2 \sigma$) of statistical significance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Sequential Inference of Hospitalization Electronic Health Records Using Probabilistic Models

In the dynamic hospital setting, decision support can be a valuable tool for improving patient outcomes. Data-driven inference of future outcomes is challenging in this dynamic setting, where long sequences such as laboratory tests and medications are updated frequently. This is due in part to heterogeneity of data types and mixed-sequence types contained in variable length sequences. In this work we design a probabilistic unsupervised model for multiple arbitrary-length sequences contained in hospitalization Electronic Health Record (EHR) data. The model uses a latent variable structure and captures complex relationships between medications, diagnoses, laboratory tests, neurological assessments, and medications. It can be trained on original data, without requiring any lossy transformations or time binning. Inference algorithms are derived that use partial data to infer properties of the complete sequences, including their length and presence of specific values. We train this model on data from subjects receiving medical care in the Kaiser Permanente Northern California integrated healthcare delivery system. The results are evaluated against held-out data for predicting the length of sequences and presence of Intensive Care Unit (ICU) in hospitalization bed sequences. Our method outperforms a baseline approach, showing that in these experiments the trained model captures information in the sequences that is informative of their future values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Methodology of the Extraction of Multi-Differential Cross Sections of Charged-Current $\nu_\mu$-Argon Interactions in MicroBooNE Using Wire-Cell $\nu_\mu$CC Selection

Neutrino physics experiments rely on accurate nuclear-interaction models that are in part guided by experimental observations. Multi-differential cross section measurements are particularly valuable for exploring the underlying physics described in these models, making them a significant step forward in the field. This note presents methodology in preparation to unfold neutrino flux-averaged double and triple-differential cross sections of the inclusive muon neutrino charged-current interaction on Argon. This work builds upon the existing framework and methodology presented in recent energy dependent cross section measurements at MicroBooNE using the Wire-Cell tomographic event reconstruction. The signal definition, choice of binning, and handling of estimated detector uncertainties are discussed, and the MicroBooNE simulation model is validated over the multi-dimensional phase space of muon momentum, muon polar angle, and visible hadronic energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Double-differential Measurements of Mesonless Charged-current Muon Neutrino Interactions on Argon with Final-State Protons using the MicroBooNE Detector

This note reports the first double-differential measurements of charged-current $ν_µ$ scattering on argon leading to final states containing zero mesons and one or more protons. This event topology (hereafter abbreviated as CC0$πNp$) is the most common at the neutrino energies typically produced by the Fermilab Booster Neutrino Beam. A detailed understanding of neutrino-argon scattering in the CC0$πNp$ channel is therefore crucial for the success of the precision neutrino oscillation analyses planned for the Short-Baseline Neutrino (SBN) program. This remains true for the upcoming Deep Underground Neutrino Experiment (DUNE), but the higher mean neutrino energy used there will ensure that more inelastic reaction modes, such as single pion production, will also play a major role. The analysis described in this note builds on a previous MicroBooNE study of the CC0$πNp$ channel which obtained the first single-differential cross-section measurements on an argon target. Since that foundational work, significant improvements have been made to MicroBooNE’s simulation software, event reconstruction algorithms, and procedure for calculating systematic uncertainties. When combined with a larger dataset (corresponding to a beam exposure of 6.79 × 10 20 protons-on-target versus 1.60 × 10 20 in Ref. [3]), these enhancements allow the important CC0$πNp$ channel to be studied in more detail. This note begins with a description of the data and simulation samples used as input to the analysis. Section 3 then defines the CC0$πNp$ signal event topology, and Section 4 describes a set of selection criteria designed to identify these events in MicroBooNE data. Binning schemes are then defined in Section 5 for two double-differential measurements of event rates. The first of these considers the momentum and scattering cosine of the outgoing muon, while the second reports the same observables for the leading proton, i.e., the final-state proton with the largest momentum. After a discussion of systematic uncertainties in Section 6, the note concludes by comparing the predictions of MicroBooNE Monte Carlo (MC) simulations to the measured double-differential distributions. These results will form the basis for a future extraction of flux-averaged double-differential CC0$πNp$ cross sections that will be immediately comparable to the theoretical predictions of multiple neutrino event generators. The selection described herein may also be used to study various other observables in CC0$πNp$ events, including those which are sensitive to correlations between leptonic and hadronic kinematics in the final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Measurement of Triple-Differential Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

We report the first measurement of the differential cross section $d^2σ(E_ν)/dcos(θ_µ)dP_µ$for inclusive muon neutrino charged-current scattering on argon. This measurement utilizes data from6.5×10 20 protons on target of exposure collected using the MicroBooNE liquid argon time projection chamber located on-axis in the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8 GeV. In this note, the mapping from reconstructed kinematics to truth quantities, particularly from reconstructed to true neutrino energy, is validated by comparing the distribution of reconstructed hadronic energy in data to that of the model prediction in different muon scattering angle bins after conditional constraint from the muon momentum distribution in data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well-modeled within its uncertainties in simulation, enabling the unfolding to an energy-dependent triple-differential measurement over muon momentum, muon scattering angle, and neutrino energy. The unfolded measurement covers an extensive phase space, providing a wealth of information useful for future LArTPC experiments measuring neutrino oscillations. Comparisons with model predictions show the best agreement with Neut 5.4.0.1 at low energy, and with NuWro 19.02.01 at higher energies, particularly at forward muon scattering angles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Solid State Solar Thermochemical Fuel (SoFuel) for Long Duration Storage

Efficient thermal storage systems, when coupled with renewable energy, enable the decarbonization of numerous industrial processes requiring high temperature steam or air, and provide a path for seasonal building heating, especially for colder climates. Existing thermal storage systems face a significant challenge due to losses inherent to all high temperature systems. A viable route to long-term storage is to use thermochemical reactions to convert concentrated solar energy to a fuel that is shelf-stable and can be stored at room temperature, thus eliminating losses associated with high temperature storage. The Solid-State Solar Thermochemical Fuel (SoFuel) technology developed by Michigan State University, Oregon State University, and Mississippi State University provides reactors and processes with minimal sensible heat losses and allows storing solar energy as a solid-state fuel at room temperature for long duration. The production of SoFuel occurs within a cylindrical cavity reduction chemical reactor that captures concentrated solar radiation from a solar field. Reactive magnesium manganese oxide (Mg-Mn-O) resides within the cylindrical cavity chemical reactor and undergoes thermal reduction as the temperature exceeds 1350°C. The thermally reduced Mg-Mn-O pellets (the SoFuel) are cooled down through a recuperative process and stored within a bin until used. The SoFuel can directly supply up to 1100°C heat to an adjacent power plant for electricity generation or industrial heating. Oxidation of SoFuel pellets occurs in a counter flow reactor and supplies heat to the user for electricity generation or industrial processing, after which the fuel is returned to the concentrating solar field where it is regenerated for re-use. Both reactors can be controlled well using a variety of strategies. With the low cost of the material, its cyclability, and the possibility of using the pelletized with on-sun reactors, or with electricity that would be curtailed, this project offers a viable option of medium- and long-term thermal energy storage.

14 SOLAR ENERGY↗
DOE OSTI2022

Low-Cost, Easy-To-Integrate and Reliable Grid Energy Storage System with 2 nd Life Lithium Batteries

Batteries retired from electric vehicles have the potential to extend their service as low-cost stationary energy storage systems. However, disperse battery state of health (SOH) and nonuniform battery characters often lead to compromised battery performance and reliability, which greatly hinder their adoption. A Heterogenous Unifying Battery (HUB) system is proposed to stage 2 nd life battery bricks for a period, and enable them to attain improved SOH uniformity, performance, and reliability before being sold for 2 nd life applications, while simultaneously providing grid services. It may offer a technically and economically advantageous solution for the broad utilization of 2 nd use batteries. The goal of this project was to develop the hardware and software that enables the key functions of the HUB system. The first achievement of the project was the development of a 1kW scale proof-of-concept (POC) system, which comprises (i) a modular plug-n-play DC-DC power converter matrix with isolated series output connections to achieve fully independent control of energy flow to each of the connected battery units at low voltage; (ii) enhanced model based control that drives each batteries’ SOH towards uniformity while collectively providing grid energy storage services; and (iii) comprehensive procedures to perform battery diagnostics and prognostics. The second achievement was the development of a 100kW scale HUB system and demonstrated its performance of re-establishing battery SOH uniformity through a period of battery cycling operation. The final HUB system incorporates six DC-DC power converter matrices paired with six battery bricks. Hot swapping of a single battery brick while maintaining consistent system power was demonstrated and system operation was validated to be capable of implementing the approved grid duty cycle and of balancing and conditioning the battery bricks. Through the course of the project, the team optimized the building-block design, form-factors, and adjusted life balancing control. An up-sized 250kW Scale was developed and deployed in October 2022 with pack-level battery form factors, see photo in Figure 1 The third achievement of the project was to perform a techno-economic analysis in order to better understand the cost and revenue potentials in this new “recondition-then-resell" value proposition. The final TEA quantified the economics of new Li-ion batteries as well as second-life batteries processed via reconditioning and traditional binning. Results showed the reconditioned second-life batteries in this project to be economically favorable and viable in grid energy storage markets. The TEA results were published in the Applied Energy journal. The fourth achievement of the project was to deliver a tech-to-market plan for the HUB system that includes funding, IP, and manufacturing strategies. The final T2M plan outlines a business strategy in which the HUB provides a B2B service to EV companies as an alternative to battery recycling that can prepare batteries for 2nd life applications. A company named Smartville Inc. was founded to carry on the commercialization, funding, and technical IP licensing activities of the OPEN project.

25 ENERGY STORAGE↗
DOE OSTI2023

FY23 Update: Aerosol Sampling for the Canister Deposition Field Demonstration

This report describes the results of preliminary testing of aerosol monitoring equipment that will be used to continuously monitor the aerosol source term for the multi-year Canister Deposition Field Demonstration (CDFD). These data are required inputs for the development and validation of models for the deposition of dust and potentially corrosive salts on the surface of spent nuclear fuel (SNF) dry storage canisters. Surface salt loads correlate with the extent of corrosion damage on a metal surface, and potentially to the likelihood and timing of initiation of stress corrosion cracks. Aerosols will be monitored at the CDFD site using three instruments. A Dekati ® ELPI+ cascade impactor will be used for real-time monitoring of aerosol particle sizes. It will also collect dust in 14 size bins on impactor targets that can be chemically analyzed to determine the soluble salts present as a function of particle size. However, this instrument can only measure dried aerosols, with a diameter of <10 µm. The second instrument is a Topas laser particle size spectrometer, which provides real-time monitoring of aerosol particle sizes up to ~40 µm in size. It monitors both the ambient (potentially deliquesced) aerosol particle size distributions required for the dust deposition models and the distributions of the equivalent dried particles, allowing correlation with the Dekati ® data. However, it does not discriminate between inert dust particles and salt aerosols, and it does not retain samples of the different particle sizes for later analysis. The third instrument that will monitor aerosols at the CDFD site is a Clean Air Status and Trends Network (CASTNET) tower, which uses a multiple canister system to collect weekly samples for analysis to total suspended aerosol particle compositions and atmospheric gas concentrations. This status report describes work in FY23 to develop the capabilities for using these tools. In two training exercises, the cascade impactor and laser particle sizer were deployed in two different testing environments, one indoor and one outdoor. For the cascade impactor, the tests provided opportunities for the operators to familiarize themselves with impactor substrate preparation, and post-test sample removal and analysis. For the laser particle sizer, the tests were used to evaluate different instrument parameters, to determine the most appropriate settings for capturing transient events. Data and samples were collected for weeks to months for each test, and the results are presented here. In addition to the preliminary testing, contracts were developed with WSP Analytical Labs for sample preparation and analysis of the cascade impactor samples. The impactor tower from outdoor test was delivered to WSP and used to train the staff there in disassembly, sample extraction, sample analysis, and tower reassembly with new target substrates. These are tasks that WSP will be performing routinely for the CDFD project. The CASTNET system cannot be purchased or tested until an actual site has been selected for the CDFD test. Work for this FY has been restricted to preparation of contracts for purchasing the CASTNET tower, and for sample analysis, once the tower is in operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Quantum Random Walk Simulator Using Ultrafast Optical Switches

Quantum random walk processes have many intriguing applications in high energy physics including the simulation of parton shower evolution. We will present the design and initial results of a fiber loop time-bin quantum walk architecture using the hardware platform already in operation at the Fermilab Quantum Network in which the state of the photon is defined by its time-of-arrival. The fiber loop consists of an unbalanced Mach-Zehnder interferometer implemented using an ultrafast electro-optical switch. The input switch controls the photon path within the interferometer, while the output switch will direct the photon back into the interferometer or to single photon detectors to measure the probability distribution of arrival times. Depending on which path the photon takes each pass through the loop, its wave function will interfere on these optical switches similar to quantum interference on a beam splitter. This work is an important step towards utilizing real-world advantages of quantum information protocols to solve problems in high energy physics.

Cameron, Andrew [Fermilab]↗
DOE OSTI2025

Improving the Parameterization of Cloud and Rain Microphysics in E3SM using Novel Observationally-Constrained Bayesian Approach (Final Technical Report)

In this project, we sought to develop new cloud and rain microphysics frameworks within the Energy Exascale Earth System Model (E3SM). This work encompassed two primary avenues of research: 1) Further development of a Bayesian-based scheme called BOSS (Bayesian Observationally-constrained Statistical-physical Scheme) to represent cloud and rain microphysics, testing it in realistic high-resolution cloud models, and implementing it in E3SM; 2) Development of a methodology utilizing machine learning to enable computationally tractable use of tractable use of Markov chain Monte Carlo sampling for Bayesian parameter estimation in Earth system and cloud models. In this project, we adapted the BOSS microphysics scheme, originally formulated for rain-only, to include all liquid-phase microphysical processes for cloud and rain, in particular the processes that mediate between these two categories, for example the conversion from cloud to rain through collision and coalescence of drops. We constrained the scheme via comparison and testing against a detailed model that explicitly represents the evolution of cloud and rain particles, called a bin microphysics scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Solid State Solar Thermochemical Fuel (SoFuel) for Long Duration Storage

Efficient thermal storage systems, when coupled with renewable energy, enable the decarbonization of numerous industrial processes requiring high temperature steam or air, and provide a path for seasonal building heating, especially for colder climates. Existing thermal storage systems face a significant challenge due to losses inherent to all high temperature systems. A viable route to long-term storage is to use thermochemical reactions to convert concentrated solar energy to a fuel that is shelf-stable and can be stored at room temperature, thus eliminating losses associated with high temperature storage. The Solid-State Solar Thermochemical Fuel (SoFuel) technology developed by Michigan State University, Oregon State University, and Mississippi State University provides reactors and processes with minimal sensible heat losses and allows storing solar energy as a solid-state fuel at room temperature for long duration. The production of SoFuel occurs within a cylindrical cavity reduction chemical reactor that captures concentrated solar radiation from a solar field. Reactive magnesium manganese oxide (Mg-Mn-O) resides within the cylindrical cavity chemical reactor and undergoes thermal reduction as the temperature exceeds 1350°C. The thermally reduced Mg-Mn-O pellets (the SoFuel) are cooled down through a recuperative process and stored within a bin until used. The SoFuel can directly supply up to 1100C heat to an adjacent power plant for electricity generation or industrial heating. Oxidation of SoFuel pellets occurs in a counter flow reactor and supplies heat to the user for electricity generation or industrial processing, after which the fuel is returned to the concentrating solar field where it is regenerated for re-use. Both reactors can be controlled well using a variety of strategies. With the low cost of the material, its cyclability, and the possibility of using the pelletized with on-sun reactors, or with electricity that would be curtailed, this project offers a viable option of medium- and long-term thermal energy storage.

25 ENERGY STORAGE↗
DOE OSTI2025

EW Studies and CP Sensitivity in ZH Production at FCC-ee

Charge-Parity (CP) violation is a necessary condition to explain the relative abundance of matter in the universe in comparison to anti-matter. Nevertheless, known sources of CP-violation are insufficient to explain this disparity. Planned to commence its operations in 2040, the Future Circular Collider (FCC-ee) will collide electrons and positrons at a center of mass energy of 240 GeV, which optimizes the rate of production of a Higgs Boson in association with an on-shell Z boson: a process known as Higgs-strahlung. The associated Z boson is selected from electronic, muonic, and hadronic final states, while the Higgs is not explicitly reconstructed, but rather inferred from the recoiling four-momentum in each event. A binned, maximum-likelihood fit characterizes the relative contributions of CP-odd interactions at the HZZ-vertex while incorporating reconstructed detector effects from a proposed design to be used at FCC-ee.

Pinto, Nicholas [Johns Hopkins U.]↗