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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Techno-Economic Analysis of Green Hydrogen Energy Storage in a Cryogenic Flux Capacitor

Abstract The Cryogenic Flux Capacitor (CFC) is a cold, dense energy storage core that is being studied in the cryo-compressed, about 300 bar and 80K, region of gaseous hydrogen (GH2) storage and liquid hydrogen (LH2) region near the normal boiling point. Hydrogen storage is improved by physically bonding the molecules within the nanoscale pores of the aerogel composite blanket material. The process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (∼1,000 m2/g) allows its storage performance to easily exceed capacities of high-pressure GH2 storage for an equivalent volume. With the integrated aerogel, subscale tests have shown that storage is increased by about 36% over a simple tank filled with GH2 at the same operating temperature and pressure. For LH2 conditions, the CFC is shown to operate at improved densities, but testing is ongoing. For the techno-economic analysis (TEA), the source of hydrogen is compared between onsite steam methane reforming (SMR) and onsite solar photovoltaic (PV) panels providing power to electrolyzers to produce green GH2. The TEA compares pure hydrogen produced at a small scale for a 25 MW power system and at a large scale in a 500 MW power system. The system allowed for hydrogen imports and exports at a set price with a tank sized for 10 hours of power production. The two power producing technologies are a combined cycle gas turbine (CCGT) and hydrogen fuel cells. The SMR system uses natural gas as an input and includes a carbon capture and storage (CCS) system. The levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH), and levelized cost of storage (LCOS) are developed based on the capital cost and operating cost of the systems. The results are shown for current costs using a 2021 benchmark and DOE projections for cost improvements by 2030. The TEA showed that onsite hydrogen generation from SMR has an LCOH of about 1.4 to 2 USD per kg over the life of the plant and the PV hydrogen production LCOH is about 5.2 to 5.5 USD per kg. The LCOS of conventional GH2 systems is estimated to be $210/MWh and cost of storage for LH2 systems is $205/MWh for fuel cell systems and $249/MWh for CCGT systems. CFC improved the LCOS of all these systems to $198/MWh, $191/MWh and $233/MWh respectively. The LCOE also improved with conventional systems between $171/MWh and $228/MWh improved by CFC to between $167/MWh and $212/MWh. Using projections for improvement in costs following DOE’s goals by 2030, green hydrogen improved to as low as $78/MWh LCOS and LCOE for conventional cases. CFC improved over conventional storage with the lowest LCOS being $62/MWh and the lowest LCOE being $73/MWh. These results correspond to an LCOH of $2/kg. Finally, the TEA shows how LCOE is improved for hydrogen conditioning and storage over conventional systems and caverns in the 10 to 50 hour range.

08 HYDROGEN↗
DOE OSTI2026

Coupling of high-resolution mass spectrometer and photosynthesis system for comprehensive leaf volatile metabolite profiling

Background Leaf-level biogenic volatile organic compounds (BVOCs) emissions represent a major source of organic gases in the atmosphere, influencing both climate and air quality. These emissions are strongly driven by environmental perturbations, which affect individual plant- to ecosystem-level processes. Uncovering all the BVOCs and understanding how their emissions respond to altered environmental conditions provide critical insights into vegetation-driven changes in atmospheric chemistry. We developed a tandem instrumentation setup that integrates a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) with parts-per-trillion detection limits and a photosynthetic infrared gas exchange system for the untargeted survey of all the BVOCs. This novel system enables simultaneous, real-time monitoring of BVOC emissions and photosynthetic parameters at the leaf level, offering new opportunities to disentangle the physiological and environmental drivers of VOC release. Furthermore, we established the VOC Analysis and Processing Optimization Resource (VAPOR), an open-access software tool designed for rapid data post-processing and the analysis of the variability of hundreds of BVOCs. We assessed the performance of the tandem system under varying background conditions, using standard gas mixtures and a range of environmental factors. Results Blank emissions were substantially lower for major BVOCs (e.g., isoprene) compared to those observed in plant emissions. Despite this, the observation of background-level VOCs highlights the importance of routinely acquiring and accounting for blank measurements in analyses using the coupled instrumentation. Introduction of known VOC concentrations to the system demonstrated a linear response across different compounds with varying molecular compositions, indicating minimal gas loss regardless of chemical moieties within the coupled instrumentation. We applied the optimized system to investigate the physiological mechanisms driving BVOC emissions across different genotypes of poplar and pennycress. The high mass resolution capabilities of the PTR-ToF-MS, coupled with comprehensive VAPOR-driven data analysis, enabled the identification of several important BVOCs, including methanol and methanethiol; these BVOCs displayed substantial variation across pennycress genotypes and showed concentrations ~ 100–350% higher than the blank. Moreover, isoprene emissions varied significantly among poplar genotypes grown in different potting media. Conclusions Tandem instrumentation offers a powerful tool for profiling volatile molecular markers and elucidating their genetic and environmental underpinnings. This approach enhances our ability to predict BVOC emissions in response to genotype by environmental interactions and contributes to a deeper understanding of vegetation responses to environmental changes.

Biogenic volatile organic compounds↗
DOE OSTI2021

An initial exploration of Bayesian model calibration for estimating the composition of rocks and soils on Mars

The Mars Curiosity rover carries an instrument, ChemCam, designed to measure the composition of surface rocks and soil using laser-induced breakdown spectroscopy (LIBS). The measured spectra from this instrument must be analyzed to identify the component elements in the target sample, as well as their relative proportions. This process, which we call disaggregation, is complicated by so-called matrix effects, which describe nonlinear changes in the relative heights of emission lines as an unknown function of composition due to atomic interactions within the LIBS plasma. In this work, we explore the use of the plasma physics code ATOMIC, developed at Los Alamos National Laboratory, for the disaggregation task. ATOMIC has recently been used to model LIBS spectra and can robustly reproduce matrix effects from first principles. The ability of ATOMIC to predict LIBS spectra presents an exciting opportunity to perform disaggregation in a manner not yet tried in the LIBS community, namely via Bayesian model calibration. However, using it directly to solve our inverse problem is computationally intractable due to the large parameter space and the computation time required to produce a single output. Therefore, we also explore the use of emulators as a fast solution for this analysis. We discuss a proof of concept Gaussian process emulator for disaggregating two-element compounds of sodium and copper. The training and test datasets were simulated with ATOMIC using a Latin hypercube design. After testing the performance of the emulator, we successfully recover the composition of 25 test spectra with Bayesian model calibration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Tool Kit for Generating Simulated Radiation Measurements for Advanced Reactor Safeguards and Security

A tool kit was developed to simulate and analyze passive radiation measurements of molten salt reactor (MSR) operations to support development of nuclear safeguards approaches for this emerging reactor technology. A Transient Simulation Framework of Reconfigurable Modules (TRANSFORM) multiphysics simulation of an MSR produces time-dependent isotopic inventories at user-selected locations within the model. The tool kit implements the Gamma Detector Response and Analysis Software (GADRAS) application programming interface to inject the TRANSFORM isotopic inventories extracted/processed by a Python pipeline into GADRAS models of user-defined geometries. The TRANSFORM inventories are the source terms used to obtain synthetic measurements from GADRAS-defined detectors. The speed of TRANSFORM and GADRAS simulations enables surveying the large design space of MSRs (e.g., fuel type, fuel salt composition, number of loops) and the plethora of measurements (e.g., location, detector type, and collimation) within the reactor. This has enabled timely assessment of the various measurement locations and detectors to identify the most effective and efficient safeguards approach for a specific MSR design. Lastly, the tool kit also simulates extracted samples that can be aged to a desired dose, enabling stakeholders to optimize a measurement plan to use sample analysis as an element within a broader material accountancy plan.

Westphal, Greg↗
DOE OSTI2024

CMPLE: Correlation Modeling to Decode Photosynthesis Using the Minorize–Maximize Algorithm

In plant genomic experiments, correlations among various biological traits (phenotypes) give new insights into how genetic diversity may have tuned biological processes to enhance fitness under diverse conditions. Consequently, knowing how the correlations are affected by genetic (G) and environmental (E) factors helps develop climate-resilient plants. However, the current literature lacks any method for assessing the effect of predictors on pairwise correlations among multiple phenotypes together with easily interpretable model parameters. To address this need, we propose to model pairwise correlations directly in terms of G and E and develop a computationally efficient inference procedure. Two major novelties in our methodology are (1) the use of a composite pairwise likelihood method to avoid the positive definiteness restriction on the correlation matrix and (2) the use of a novel Minorize–Maximize (MM) algorithm for the efficient estimation of a large number of parameters. The proposed method shows excellent numerical performance on synthetic datasets. Here, the analysis of the motivating data on cowpea reveals that the rates of solar energy storage by photosynthesis (the aggregate trait) are differentially affected by different genetic loci through two distinct processes: “photoinhibition” which results from photodamage caused by excess light, and “photoprotection” which protects plants from photodamage but also results in energy loss.

Correlation modeling↗
DOE OSTI2021

Corrosion of rebar in concrete. Part III: Artificial Neural Network analysis of chloride threshold data

Active corrosion of carbon steel in reinforced concrete occurs when the chloride ion concentration exceeds the chloride threshold (CT). CT is affected by many physical and chemical parameters including primary variables (pH, corrosion potential, breakdown potential, and temperature) and secondary variables (cemenet composition, concreete porosity, and water/cement ratio). A Kohonen-self organized map (KSOM) and regression artificial neural network (ANN) coupled methodology was developed to find the missing values of independent variables in the sparse database and for quantitatively evaluating the effects of these variables on CT values that are expressed in %TotalCl/cem (or %FreeCl/cem), and [Cl - ]/[OH - ].

36 MATERIALS SCIENCE↗
DOE OSTI2020

Design and Analysis of a 250 MW Plate-fuel Reactor for Nuclear Thermal Propulsion

Nuclear thermal propulsion (NTP) system is a viable option for deep space missions considering its high thrust and lightweight. Promising fuel options being considered for the high operating temperature of NTP include the graphite composite fuel and the tungsten cermet fuel. As there remains uncertainties in the fabrication and performance of these two fuel elements, alternative designs using fuel plates and more standard fuels that are based on proven and tested nuclear technologies are being considered. This paper provides a summary of thermal hydraulic and neutronic analyses of the straight fuel plate concept used for a 250 MW NTP core. The summary of technical findings from a series of scoping studies might be useful for the future NTP engine designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Anomalously high elastic modulus of a poly(ethylene oxide)-based composite electrolyte

The practical use of lithium metal anodes in solid-state batteries requires a polymer membrane with high lithium-ion conductivity, thermal/electrochemical stability, and mechanical strength. The primary challenge is to effectively decouple the ionic conductivity and mechanical strength of the polymer electrolytes. We report a remarkably facile single step synthetic strategy based on in-situ crosslinking of poly(ethylene oxide) (xPEO) in the presence of a woven glass fiber (GF). Such a simple method yields composite polymer electrolytes (CPE) of anomalously high elastic modulus up to 2.5 GPa over a broad temperature range (20 °C – 245 °C) that has never been previously documented. An unsupervised machine learning algorithm, K-mean clustering analysis, was implemented on the hyperspectral Raman mapping at the xPEO/GF interface. Using such a unique means, we show for the first time that the promoted mechanical strength originates from xPEO and GF interactions through dynamic hydrogen and ionic bonding. High ionic conductivity is achieved by the addition plasticizer (e.g. tetraglyme), where trifluoromethanesulfonate anions are tethered to the xPEO matrix and Li + cations are favorably transported through coordination with the plasticizer. Further, stringent galvanostatic cycling tests indicates the CPE can be stably cycled for >3000 h in a Li-metal symmetric cell at a moderate temperature (nearly 1500 Coulombs/cm 2 Li equivalents), outperforming most of the PEO-based electrolytes. The GF reinforced CPE reported here has multifunctional uses, such as solid electrolytes for all solid-state batteries and membranes for redox-flow batteries. Although the focus of this study is on lithium-based batteries, the results are equally promising for other alkali metal based batteries such as sodium and potassium.

25 ENERGY STORAGE↗
DOE OSTI2023

Fission neutron activations of stainless steel and its corresponding elemental components

Characterizing neutron activation of stainless steel is a critical task for many applications, and yet little activation data is available for this alloy. To address the need, a series of neutron activation experiments have been performed using the Flattop critical assembly at the National Criticality Experiments Research Center. Several experimental conditions were probed for complete understanding of the neutron environment, including foil composition and position within the assembly. The experimental results reported here will aid in the production of stainless steel benchmarks for a range of nuclear data applications including those used in nuclear forensics analysis.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2019

The Dissolution of Fe in HCl from the Ilmenite Concentrate; Evaluating the Effect of Operating Parameters and Mutual Interactions

Selective HCl dissolution of ilmenite components for obtaining Ti or titanium dioxide (TiO{sub 2}) has been highly recognized due to its advantages, greater environmental friendliness, and simplicity, compared to H{sub 2}SO{sub 4} and Cl{sub 2} methods. The effect of numerous parameters has been studied with the one-factor-at-a-time method. The present study aimed to evaluate the effect of key operation parameters, such as acid-to-solid ratio (A/S: 5 to 20 mL/g), reaction temperature (T: 70 °C to 100 °C), and acid concentration (A pct: 15 to 30 wt pct), on the dissolution of Fe in HCl solution with the minimum Ti losses to the leachate from its abundant, domestic, and low-cost mineral source (Kahnooj ilmenite concentrate) using central composite design–response surface methodology. After 90 minutes of leaching, the Ti/Fe (pct) in terms of dissolved amounts was selected as the process assessment response function. Based on the conducted experimental and statistical analysis, increasing the levels of parameters in the studied domain leads to an increase in Ti/Fe (pct), in the order of A pct > T > A/S. Two statistically significant mutual interactions between A/S-T and T-A pct, with 95 pct confidence level, were revealed for the first time in this study. The optimization strategy was set to the minimization of Ti/Fe (pct) by considering the objective of study and the selected response function. The A/S, T, and A pct were determined to be 5 mL/g, 70 °C, and 15 pct, respectively, for maximum impurity dissolution and minimum Ti loss to the leachate.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Hybrid fiber metal composite laminate interlaminar reinforcement through metal interlocks

Aircraft and automobile industries are continually seeking high-performance and lightweight solutions. Fiber-reinforced composites in conjunction with metals are being considered in the form of hybrid materials. There is a continuous need for improvement of interfacial bonding between composite layers and metal constituents. In this study, an innovative hybrid fiber interlocking metal hooks laminate (FIMHL) system was developed in which fiber-reinforced thermoset composite, and metal sheets are mechanically bonded together using out of plane hooks stamped in the metal. Process optimization was performed to gain the full benefit of the through-thickness reinforcement. Microstructural analysis showed improved interaction between the metal hooks and the fiber layers which reduced porosity and resin richness. This was reflected in mechanical properties, as tensile and flexural strength of FIMHL was enhanced by 38.5 and 18.8%, respectively, after process optimization. Furthermore, normalized weight fraction (76.4%) properties of FIMHL also confirmed that the increase in mechanical properties of optimized panel were not only due to increased reinforcement (glass fiber + aluminum) volume fraction but also because of improved metal hooks and fibers interaction. There was no significant effect on lap shear and fracture toughness, as they depend on bend back behavior of the hooks. A bilinear traction-separation model was used to characterize mode-I interlaminar fracture toughness properties, and 4.5% variation was recorded when modeling and experimental values were compared.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Design of a 2 MW ZrC/W-based molten-salt-to-sCO 2 PCHE for concentrated solar power

To increase the power cycle efficiency and lower the levelized cost of electricity (LCOE) of concentrated solar power (CSP) plants, printed circuit heat exchangers (PCHEs) capable of operating above 700 °C with molten chloride salt and a sCO 2 -based fluid are needed. In this paper, the design of a high-pressure, high-temperature, 2 MW PCHE comprised of a thermomechanically-robust, zirconium carbide/tungsten (ZrC/W) composite is conducted for CSP plants. The ZrC/W composite is a material with high thermal conductivity, high stiffness, and high failure strength at high temperatures, along with excellent resistance to thermal cycling and thermal shock. In this work, a thermomechanical design analysis was conducted to select appropriate material thicknesses of the ZrC/W plates, and to determine the geometrical dimensions and the thermal performance of the PCHE. The influences of the plate number and heat exchanger length on power density and pressure drop have also been systematically investigated. Economic analyses were conducted to compare the cost of ZrC/W-based PCHEs to those comprised of IN740H (a state-of-the-art, nickel-based superalloy) and 316 stainless steel (316SS). Finally, at a sufficiently high plate production rate, the manufacturing cost of ZrC/W-based PCHEs can be significantly lower, while achieving a much higher power density, compared with state-of-the-art, nickel alloy-based and stainless steel-based PCHEs.

14 SOLAR ENERGY↗
DOE OSTI2025

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗
DOE OSTI2020

Efficient and robust phase-split computations in the internal energy, volume, and moles ( UVN ) space

Phase-split computations in an isolated system, which in general may be defined as one where the total internal energy (U), volume (V), and the number of moles (N = N 1 , N 2 ,..., N n ) of the components are fixed at some specified set of values, involves the determination of the temperature (T), pressure (P), plus the amount and composition of the various phases that constitute the system. A simpler, but analogous problem is one where T, P, and N are specified instead. In TPN space, one may first perform a stability analysis to determine whether the system is stable, meaning whether at equilibrium it will split up into multiple phases or remain in single phase. If the single-phase state is unstable, the stability analysis reliably provides a good set of initial guesses in the subsequent phase-split computations. In UVN space, however, we demonstrate that the stability analysis (which is the main subject of our earlier study [1]) may not in general provide good enough initial guesses; we offer alternative strategies for setting up good initial guesses. Furthermore, we show that a combination of successive substitution iteration (SSI) and Newton's method---two iterative methods that are prevalent in the literature in TPN space---facilitates a robust and efficient algorithm for phase-split computations in isolated systems. Finally, this combination has so far not been applied in UVN space.

02 PETROLEUM↗
DOE OSTI2025

System and Machine Learning-Guided Materials Design for High-Pressure Hydrogen Compression

Cost-effective and reliable hydrogen compression remains a challenging barrier in the widespread adoption of hydrogen as an energy carrier. The prevailing technology of mechanical compression suffers from several drawbacks, some of which can be addressed by nonmechanical compression strategies (e.g., electrochemical or metal hydride-based thermal compression). Thermally driven metal hydride compression strategies typically rely on multistage metal hydride-based compressors; however, discovering or optimizing low-stability metal hydrides that can pressurize hydrogen upward of 1000 bar is difficult, both with respect to computational predictions and experimental validation. Here, in this study, we (1) demonstrate that simple machine learning-derived design rules can inform the rational design of alloying strategies yielding low-stability hydrides, (2) validate their experimental pressure–composition–temperature (PCT) isotherms up to 875 bar, and (3) utilize a dynamic system-level model of a metal hydride compressor design to evaluate their performance under realistic operating conditions. Importantly, this analysis yields predicted operational efficiencies of both 2-stage (90–875 bar) and 3-stage (20–875 bar) metal hydride compressors to enable further evaluation of this technology and its techno-economic outlook.

alloy optimization↗
DOE OSTI2023

Designing Nuclear Fuels with a Multi-Principal Element Alloying Approach

Previous research has shown that multi-principal element alloys (MPEAs) using chromium, molybdenum, niobium, tantalum, titanium, vanadium, and zirconium can form stable body-centered-cubic (BCC) structures across a large temperature region (25°C to 1000°C). This is the same crystal structure as γ-uranium (U), which has shown desirable thermal and irradiation behavior in previous alloy fuel research. It is hypothesized then that the MPEA alloying approach can be used to produce a stable BCC uranium-bearing alloy and to retain its stability throughout anticipated operating regimes of power-producing reactors. Candidate elements were assessed using Monte Carlo N-Particle (MCNP) analysis to determine uranium densities necessary to make the alloy an economically viable fuel compared to conventional fuel forms. Following neutronic considerations, materials property databases and empirical predictors were used to determine the compositions with a high potential to form a BCC solid solution alloy. The final four alloys were MoNbTaU 2 , MoNbTiU 2 , NbTaTiU 2 , and NbTaVU 2 , which were cast using arc melting of raw elemental foils and chunks. Characterization of the fabricated alloys included scanning electron microscopy, X-ray diffraction, energy dispersive X-ray spectroscopy, and transmission electron microscopy. The results showed a two-phase system with a U-rich matrix phase surrounding the refractory precipitates. The U phase was found to contain varying concentrations of the alloying elements and was a BCC γ-U phase. These results warrant further research to identify ideal compositions for use as an advanced alloy fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Suppression of the valence transition in solution-grown single crystals of Eu 2 Pt 6 Al 15

Here, the study of Eu intermetallic compounds has allowed the exploration of valence fluctuations and transitions in 4⁢𝑓 electron systems. Recently, a Eu 2 ⁢Pt 6 ⁢Al 15 phase synthesized by arc-melting followed by a thermal treatment was reported M. Radzieowski et al. [J. Am. Chem. Soc. 140, 8950 (2018)], which undergoes a transition upon cooling below 45 K that was interpreted as a valence transition from Eu 2+ to Eu 3+ . In this paper, we present the discovery of another polymorph of Eu 2 ⁢Pt 6 ⁢Al 15 obtained by high temperature solution growth, which presents different physical properties than the arc-melted polycrystalline sample. Despite the similarities in crystal structure and chemical composition, the Eu valence transition is almost fully suppressed in the solution-grown crystals, allowing the moments associated with the Eu 2+ state to order antiferromagnetically at around 14 K. A detailed analysis of the crystal structure using single crystal x-ray diffraction reveals that, although the solution grown crystals are built from the same constituent layers as the arc-melted samples, these layers present a different stacking. The effect of different thermal treatments is also studied. Different anneal procedures did not result in significant changes in the intrinsic properties, and only by arc-melting and quenching the crystals we were able to convert them into the previously reported polymorph.

Schmidt, Juan [Ames Laboratory, and Iowa State Uni↗

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