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DOE OSTI2020

Energy Storage Analysis

This study presents a comprehensive techno-economic characterization of energy storage and exible low carbon power generation technologies that can shift energy across days, weeks, or months to balance daily, weekly, and seasonal disparities in supply and demand. Energy storage technologies evaluated here include pumped hydropower storage (PHS), adiabatic and diabatic compressed air energy storage (CAES), vanadium redox flow batteries (VRBs), pumped thermal energy storage (P-TES), and renewably produced hydrogen stored in either geologic formations or underground pipes with re-electrification via combustion turbines in combined cycles, stationary proton exchange membrane (PEM) fuel cells, or the novel use of PEM fuel cells designed for heavy-duty vehicles (HDVs) which are expected to have shorter lives but also lower capital costs. We also evaluate flexible low-carbon power generation systems, including ethanol combustion in gas turbines and natural gas combustion with carbon capture and sequestration (CCS). We estimate current costs with literature data, use learning rates to characterize future costs, and develop capacity factors calibrated to an 85% renewables grid to calculate the levelized cost of energy (LCOE) of each technology. Results illustrate that at the 12-hour storage duration, PHS and CAES have the lowest LCOE with current costs, and VRBs become competitive if future costs are achieved. At the 120-hour storage duration, hydrogen systems with geologic storage and natural gas with CCS achieve the lowest LCOE in both current and future capital cost scenarios. In particular, the new configuration of HDV-PEM fuel cells with hydrogen storage in geologic formations evaluated here could lower the LCOE by 22-27% compared to stationary fuel cell systems typically evaluated and might help enable very high (>80%) renewable energy electric power systems. P-TES and hydrogen stored in underground pipes are the least-cost options at the 120-hour storage duration rating that do not require some form of geologic storage. Sensitivity analysis and Monte Carlo analysis illustrate that the general trends seen in this study are valid for a wide range of capacity factors and future cost scenarios. The study also illustrates that coproducing and selling hydrogen to other markets could reduce the LCOE of hydrogen systems by up to 39%.

carbon capture and sequestration↗

DOE OSTI2020

Measurement of temperature of a dusty plasma from its configuration

A new concept called “configurational temperature” is introduced in the context of dusty plasma, where the temperature of the dust particles submerged in the plasma can be measured directly from the positional information of the individual dust particles and the interaction potential between the dust grains. This method does not require the velocity information of individual particles, which is a key parameter to measure the dust temperature in the conventional method. The technique is initially tested using two-dimensional (2D) OpenMP parallel molecular dynamics and Monte Carlo simulation and then compared with the temperature evaluated from experimental data. The experiment have been carried out in the Dusty Plasma Experimental (DPEx) device, where a 2D stationary plasma crystal of melamine formaldehyde particles is formed in the cathode sheath of a DC glow discharge argon plasma. The kinetic temperature of the dust is calculated using the standard particle image velocimetry technique at different pressures. An extended simulation result for the three-dimensional case is also presented, which can be employed for the temperature measurement of a three-dimensional dust crystal in laboratory devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Sensitivity of Fine‐Resolution Urban Heat Island Simulations to Soil Moisture Parameterization

ABSTRACT Urban areas experience the impact of natural disasters, such as heatwaves and flash floods, disparately in different neighbourhoods across a city. The demand for precise urban hydrometeorological and hydroclimatological modelling to examine this disparity, and the interacting challenges posed by climate change and urbanisation, has thus surged. The Weather Research and Forecasting (WRF) model has served such operational and research purposes for decades. Recent advancements in WRF, including enhanced numerical schemes and sophisticated urban atmospheric‐hydrological parameterizations, have empowered the simulation of urban geophysical processes at high resolution (~1 km), but even this resolution misses significant urban microclimate variability. This study applies the large‐eddy simulations (LES) mode within WRF, coupled with single‐layer urban canopy models (SLUCM), to enable even finer‐scale modelling (150 m) of the Urban Heat Island (UHI) effect in the Baltimore metropolitan area. We run nine scenarios to evaluate various methods of initializing soil moisture and various spinup lead times, and to assess the impact of WRF's Mosaic approach in depicting subgrid‐scale processes. We evaluate the scenarios by comparing the WRF simulated land surface temperature (LST) against Landsat LST and the WRF simulated hourly 2‐m air temperatures (AT) with observations from eight weather stations across the domain. Results underscore the paramount influence of the lead spinup time on the spatiotemporal distribution of simulated soil moisture, consequently shaping WRF's efficacy in predicting the UHI. Furthermore, interpolating soil moisture‐related parameters from the parent for child domain initialization yields a notable reduction in mean and root‐mean‐squared errors. This improvement was particularly evident in simulations with the longest spinup time, affirming the importance of carefully designing the initialization of soil moisture for improved urban temperature predictions.

Talebpour, Mahdad↗

DOE OSTI2022

A Fish Out of Basin: Increased Stress Physiology and Reduced Performance of Salmon River Hatchery Chinook Salmon

Abstract Variation in rearing conditions across hatcheries and basins can affect the performance of hatchery salmonids in the wild. In 2008, the Shoshone-Bannock Tribes began planning an out-of-basin hatchery facility on the eastern Snake River Plain for rearing threatened Chinook Salmon Oncorhynchus tshawytscha for release in tributaries of the upper Salmon River, Idaho, USA. To help determine the viability of the planned out-of-basin hatchery, we reared 100,000 juvenile Chinook Salmon from the same genetic stock at one in-basin (Sawtooth Fish Hatchery on the Salmon River) and one out-of-basin (Springfield Fish Hatchery on the Snake River Plain) site in Idaho that are characterized by significant differences in water hardness and temperature regime. In October 2018 and April 2019, we tested whether fish condition, stress physiology, acute mortality, and downstream survival differed between the two groups at the parr and smolt life stages upon release in the Yankee Fork Salmon River, which is characterized by low water hardness. For both release groups, parr experienced low acute mortality during the 48 h after release; however, the out-of-basin group had a downstream survival rate through an unimpounded portion of the migration corridor that was an order of magnitude lower than that for the in-basin group. During the smolt release, the out-of-basin group showed signs of extreme physiological stress, acute mortality rates of 40–80%, and low survival in the unimpounded portion of the migratory corridor. The in-basin group recovered from the stress of transport and release, had no acute mortality, and survived through the unimpounded migratory corridor at a rate comparable to that of previous years’ releases. Based on the results of this comparative study, comanagers are evaluating alternatives to the proposed out-of-basin hatchery program. This case study highlights the effects of differences between rearing and release conditions on salmon physiology and survival as well as the value of conducting preliminary evaluations prior to implementing large-scale hatchery supplementation programs.

Ebel, Jonathan D.↗

DOE OSTI2025

The Dynamic Networks Experiments: Virtual Experiments to Quantify Gains in Nuclear Explosion Monitoring

We describe an ongoing series of virtual experiments conducted collaboratively by four United States National Laboratories: Sandia National Laboratories, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory. These Dynamic Network Experiments (DNEs) provide an experimental framework to evaluate the potential impact of new research tools on nuclear explosion monitoring. The second DNE (DNE2), completed in 2024, exploited waveform data (seismic, infrasound, and electromagnetic) that was recorded by multi-modal sensors within and near the Nevada National Security Site and synthetic radionuclide signatures over multiple time periods. During the execution of DNE2, we processed and analyzed data through a multi-stage event processing pipeline that ingested raw data, performed quality control, detected signals, built events from these signals, located these events, and characterized the events’ source types and sizes. For each stage and over the entire event processing pipeline, we evaluated performance changes by comparing the performance of new data processing methods, models, and algorithms against a baseline. We also performed an additional execution phase to assess event processing pipeline function, speed, and efficiency against that of an expert analyst, including computational and manual efforts. Finally, we assessed the impact and effort of modern computing infrastructure on the monitoring pipeline. This paper describes key elements of the DNEs, from formulation through execution, as demonstrated in DNE2. The DNEs introduce several novel concepts to quantitatively measure the potential impact of new methods on explosion monitoring, including the collaborative design of multi-modal datasets, performance and logistical metrics, and integrated analyses.

42 ENGINEERING↗

DOE OSTI2026

A transport-based framework for solidification cracking in Ni-based superalloys processed by laser powder bed fusion

Solidification cracking remains a persistent barrier to laser powder bed fusion (LPBF) processing of solid-solution-strengthened (SSS) Ni-based superalloys and is commonly attributed to carbide formation, liquation-type failure, or elemental segregation. In this work, the cracking behavior of three SSS Ni-based superalloys—Inconel 625 (625), Inconel 617 (617), and Haynes 230 (230)—is examined under comparable LPBF conditions to evaluate the origins of their cracking susceptibility. Carbides were present in both 625 and 230, yet cracking behavior differed significantly. MC-type carbides in 625 remain discrete and preserve liquid connectivity, whereas Cr-rich M23C6 carbides in 230 form at cellular triple junctions that bottleneck the interdendritic liquid network, influencing cracking through liquid connectivity rather than as an independent cause. Alloy 617 exhibited anomalous segregation without resolvable secondary phases yet cracked mildly, indicating that extensive carbide formation is not a prerequisite for cracking. To rationalize these observations, a transport-limited framework is proposed in which cracking occurs when terminal-liquid feeding cannot accommodate solidification-induced strain; among the mechanisms evaluated, this framework is most consistent with the physical constraints imposed by LPBF solidification. Transport-based crack-susceptibility indexes incorporating permeability, viscosity, and solidification kinetics distinguish the alloy hierarchy; permeability ratios Krat increased from approximately 7 (625) to 11.5 (617) and 14.5 (230), with corresponding increases in the μ-weighted mushy zone risk index (CSIMZRM). These results are consistent with transport-limited liquid feeding as a rate-limiting contributor to solidification cracking in LPBF-processed SSS Ni-based superalloys, providing a physically grounded basis for alloy and process design.

Hyer, Holden [ORNL] (ORCID:0000000343915561)↗

DOE OSTI2024

Ensemble Monte Carlo calculations with five novel moves

We introduce five novel types of Monte Carlo (MC) moves that brings the number of moves of ensemble MC calculations from three to eight. So far such calculations have relied on affine invariant stretch moves that were originally introduced by Christen (2007), walk moves by Goodman and Weare (2010) and quadratic moves by Militzer (2023). Ensemble MC methods have been very popular because they harness information about the fitness landscape from a population of walkers rather than relying on expert knowledge. Here we modified the affine method and employed a simplex of points to set the stretch direction. We adopt the simplex concept to quadratic moves. We also generalize quadratic moves to arbitrary order. Finally, we introduce directed moves that employ the values of the probability density while all other types of moves rely solely on the location of the walkers. We apply all algorithms to the Rosenbrock density in 2 and 20 dimensions and to the ring potential in 12 and 24 dimensions. We evaluate their efficiency by comparing error bars, autocorrelation time, travel time, and the level of cohesion that measures whether any walkers were left behind. Our code is open source.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m 2 ), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. Furthermore, the algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

14 SOLAR ENERGY↗

DOE OSTI2020

Phase-field simulations of intergranular fission gas bubble behavior in U 3 Si 2 nuclear fuel

U 3 Si 2 is a potential accident-tolerant fuel that shows promise due to its high thermal conductivity and higher uranium density relative to UO 2 . However, its swelling and fission gas release behavior in light water reactor (LWR) conditions is relatively unknown. To provide mechanistic insight and determine parameters for engineering-scale fuel performance modeling of pellet-form U 3 Si 2 , phase-field simulations of the growth, interconnection, and venting of intergranular fission gas bubbles were performed. The fractional coverage of the grain boundary and the fraction of bubble area that is vented were calculated as a function of time. From the simulation data, the fractional grain boundary coverage at saturation, an important parameter needed in engineering-scale modeling of swelling and fission gas release, was determined. Multiple simulations were run to determine the uncertainty in the calculated value. Finally, the effect of model assumptions and input parameters that are not well known was evaluated. Simulation results are compared to related theoretical and computational work. Based on the simulation results, a value of 0.60 for the fractional grain boundary coverage at saturation is recommended for U 3 Si 2 fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Correlative STEM-APT characterization of radiation-induced segregation and precipitation of in-service BWR 304 stainless steel

In this study, radiation induced segregation and precipitation phenomena in an in-service boiling water reactor 304 stainless steel component were investigated using directly correlated 3D-atom probe tomography and scanning transmission electron microscopy. Significant quantitative differences in measured segregation at grain boundaries were found between the atom probe and energy dispersive spectroscopy measurements of the exact same locations. In particular, a much stronger Si segregation (~10 atomic% via atom probe versus ~4 atomic% via electron microscopy) and different Cr profile shapes were detected that are critical to models of radiation induced segregation and stress corrosion cracking behavior. These quantitative differences highlight the need for comparative microscopy and critical evaluation of limitations in each analytical method. Elemental segregation to dislocations and conjoined-clusters were also highlighted by atom probe; confirming and expanding upon what has been observed in test reactor neutron and accelerator-based ion irradiations.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Delivery drone route planning over a battery swapping network

Many enterprises invest on drone delivery research and development to drop off packages at consumers’ doorsteps in a matter of minutes. We study delivery drone route planning over a battery swapping network allowing farther reach by penetrating current battery capacity constraints. A mixed-integer nonlinear programming model is created to plan efficient drone routing over the swapping machines by minimizing the delivery lead time. We develop an exact solution method, evaluate its performance, and compare it with a straightforward nonlinear solver application. A case study highlights the applicability of the model. Data and source code to the solver are publicly shared.

drone battery swapping↗

DOE OSTI2023

Techno-economic Analysis and Life Cycle Assessment of Gluconic Acid and Xylonic Acid Production from Waste Materials

Organic acid-based bioleaching has attracted significant research interest for the recovery of rare earth elements(REEs) and other critical metals. Utilizing biologically produced leaching agents, known as biolixiviants, derived from waste materials holds great promise for enhancing the economic viability and environmental sustainability of bioleaching processes. Here this study focuses on the modeling and optimization of biolixiviant production using corn stover (CS), date palm clippings (DP), and nonrecyclable paper (NP). Techno-economic analysis revealed that gluconic acid production from NP is more cost-effective than that from CS and DP, with respective costs of $0.04/kg, $0.06−0.08/kg, and $0.06−0.09/kg of the biolixiviant, yielding gluconic acid concentrations of 135.39, 172.90, and 176.87 mM, respectively. Life cycle assessment demonstrated that biolixiviant production from NP exerts the lowest environmental impact compared with the other evaluated substrates. When applied to the bioleaching of a neodymium−iron−boron magnet swarf, the biolixiviant derived from NP exhibits the highest leaching efficiencies, confirming its cost and environmental competitiveness in comparison to CS and DP

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Application of a long short-term memory for deconvoluting conductance contributions at charged ferroelectric domain walls

Ferroelectric domain walls are promising quasi-2D structures that can be leveraged for miniaturization of electronics components and new mechanisms to control electronic signals at the nanoscale. Despite the significant progress in experiment and theory, however, most investigations on ferroelectric domain walls are still on a fundamental level, and reliable characterization of emergent transport phenomena remains a challenging task. Here, we apply a neural-network-based approach to regularize local I ( V )-spectroscopy measurements and improve the information extraction, using data recorded at charged domain walls in hexagonal (Er 0.99 ,Zr 0.01 )MnO 3 as an instructive example. Using a sparse long short-term memory autoencoder, we disentangle competing conductivity signals both spatially and as a function of voltage, facilitating a less biased, unconstrained and more accurate analysis compared to a standard evaluation of conductance maps. The neural-network-based analysis allows us to isolate extrinsic signals that relate to the tip-sample contact and separating them from the intrinsic transport behavior associated with the ferroelectric domain walls in (Er 0.99 ,Zr 0.01 )MnO 3 . Our work expands machine-learning-assisted scanning probe microscopy studies into the realm of local conductance measurements, improving the extraction of physical conduction mechanisms and separation of interfering current signals.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A bending test protocol for characterizing the mechanical performance of flexible photovoltaics

Flexible photovoltaics (PV) represents a promising research field with great potential for wearable, portable, and indoor applications. Significant progress has been made in recent years, with flexible emerging PV reporting power conversion efficiency (PCE) over 24%. Yet, there is a need for a unifying protocol to assess PV performance, compare research results, and evaluate the state- of-the-art achievements in flexible PV. In this paper, a consensus protocol is presented for measuring PCE over 1,000 bending cycles under 1% strain. Moreover, several good practice guidelines are proposed including bending procedures, flexibility testing with and without encapsulation, and ambient conditions during testing (e.g., temperature, humidity, illumination). Notably, the importance of uniform application of bending radius and the testing of parallel and perpendicular orientations of bending axis with respect to the direction of the electric current are emphasized. These recommendations aim to promote consistency in device comparison and allow for better reproducibility.

Fukuda, Kenjiro↗

DOE OSTI2024

Towards optimal sensor placement for inverse problems in spaces of measures

The objective of this work is to quantify the reconstruction error in sparse inverse problems with measures and stochastic noise, motivated by optimal sensor placement. To be useful in this context, the error quantities must be explicit in the sensor configuration and robust with respect to the source, yet relatively easy to compute in practice, compared to a direct evaluation of the error by a large number of samples. In particular, we consider the identification of a measure consisting of an unknown linear combination of point sources from a finite number of measurements contaminated by Gaussian noise. The statistical framework for recovery relies on two main ingredients: first, a convex but non-smooth variational Tikhonov point estimator over the space of Radon measures and, second, a suitable mean-squared error based on its Hellinger–Kantorovich distance to the ground truth. To quantify the error, we employ a non-degenerate source condition as well as careful linearization arguments to derive a computable upper bound. This leads to asymptotically sharp error estimates in expectation that are explicit in the sensor configuration. Thus they can be used to estimate the expected reconstruction error for a given sensor configuration and guide the placement of sensors in sparse inverse problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Optimizing Charge-coupled Device Readout Enabled by the Floating-gate Amplifier

Multiple-Amplifier Sensing (MAS) charge-coupled devices (CCDs) have recently been shown to be promising silicon detectors that meet noise sensitivity requirements for next generation Stage-5 spectroscopic surveys and potentially, future space-based imaging of extremely faint objects on missions such as the Habitable Worlds Observatory. Building upon the capability of the Skipper CCD to achieve deeply sub-electron noise floors, MAS CCDs utilize multiple floating-gate amplifiers along the serial register to increase the readout speed by a factor of the number of output nodes compared to a Skipper CCD. We introduce and experimentally demonstrate on a 16-channel prototype device new readout techniques that exploit the MAS CCD’s floating-gate amplifiers to optimize the correlated double sampling by resetting once per line instead of once per pixel. With this new mode, we find an optimal filter to subtract the noise from the signal during read out. We also take advantage of the MAS CCD’s structure to tune the read time by independently changing integration times for the signal and reference level. Together with optimal weighted averaging of the 16 outputs, these approaches enable us to reach a sub-electron noise of 0.9 e − rms pix −1 at 19 μs pix −1 for a single charge measurement per pixel—simultaneously giving a 30% faster readout time and 10% lower read noise compared to performance previously evaluated without these techniques.

Lin, Kenneth W. (ORCID:0000000189672281)↗

DOE OSTI2024

Benchmarking characterization methods for noisy quantum circuits

Effective methods for characterizing the noise in quantum computing devices are essential for programming and debugging circuit performance. Existing approaches vary in the information obtained as well as the amount of quantum and classical resources required, with more information generally requiring more resources. Here we benchmark the characterization methods of gate set tomography, Pauli channel noise reconstruction, and empirical direct characterization for developing models that describe noisy quantum circuit performance on a 27-qubit superconducting transmon device. We evaluate these models by comparing the accuracy of noisy circuit simulations with the corresponding experimental observations. Here, we find that the agreement of noise model to experiment does not correlate with the information gained by characterization and that the underlying circuit strongly influences the best choice of characterization approach. Empirical direct characterization scales best of the methods we tested and produced the most accurate characterizations across our benchmarks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Measurement of C P asymmetries in Λ b 0 → p h − decays

A search for C P violation in Λ b 0 → p K − and Λ b 0 → p π − decays is presented using the full Run 1 and Run 2 data samples of p p collisions collected with the LHCb detector, corresponding to an integrated luminosity of 9 fb − 1 at center-of-mass energies of 7, 8, and 13 TeV. For the Run 2 data sample, the C P -violating asymmetries are measured to be A C P p K − = ( − 1.4 ± 0.7 ± 0.4 ) % and A C P p π − = ( 0.4 ± 0.9 ± 0.4 ) % , where the first uncertainty is statistical and the second is systematic. Following significant improvements in the evaluation of systematic uncertainties compared to the previous LHCb measurement, the Run 1 dataset is reanalyzed to update the corresponding results. When combining the Run 2 and updated Run 1 measurements, the final results are found to be A C P p K − = ( − 1.1 ± 0.7 ± 0.4 ) % and A C P p π − = ( 0.2 ± 0.8 ± 0.4 ) % , constituting the most precise measurements of these asymmetries to date. © 2025 CERN, for the LHCb Collaboration 2025 CERN

Aaij, R. (ORCID:0000000305331952)↗