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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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At least 433 records · Page 24

Microbially mediated nitrification improves modeled temperate forest responses to declining nitrogen deposition

As nitrogen deposition declines across the US, uncertainty remains in whether temperate forests will continue to sequester carbon. This uncertainty is amplified by ecosystem models that inaccurately capture the microbial mechanisms that drive soil carbon sequestration and nitrogen loss. Further, even soil process models that represent decomposer microbes and better capture soil carbon retention under nitrogen deposition broadly underrepresent microbial nitrogen transformations. To address this limitation, we leveraged three decades of biogeochemical cycling data from a whole-watershed nitrogen fertilization experiment to incorporate microbially-driven nitrification in the FUN-CORPSE (Fixation and Uptake of Nitrogen-Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment) model. Our objectives include: 1) Reproducing key ecosystem responses to fertilization, 2) Integrating microbially-explicit nitrification in FUN-CORPSE, and 3) Assessing modeled soil C and N under projected N deposition shifts. FUN-CORPSE accurately represented soil C and streamwater N losses under ambient N deposition and captured how fertilization induced a 25 % decline in plant C cost of N acquisition, reducing decomposition and increasing soil C. Furthermore, with microbially-explicit nitrification, FUN-CORPSE captured the 100 % increase in nitrification rates and the 50 % increase in streamwater nitrate loss under N fertilization. Specifically, incorporating microbial nitrification improved modeled streamwater N leaching from R 2 = 0.01 to R 2 = 0.57. Under declining N deposition, FUN-CORPSE simulates that N losses recover more quickly than soil C pools. However, the predicted return of soil C to pre-fertilized levels suggests that additional C sequestered due to N deposition may be vulnerable to loss over the next century.

Microbial nitrification model↗

Interpretation of wide-angle x-ray diffraction patterns from mesophase pitch-based carbon fibers – a simulation and experimental study

Carbon fiber is a critical material in a wide range of industries, where it is highly valued for its high specific strength/stiffness, excellent wear resistance, efficient electrical and thermal transport properties, chemical resistance, and low coefficient of thermal expansion. The properties of a specific carbon fiber are closely tied to its structural characteristics at all length scales. Here, in this work, we applied wide-angle x-ray diffraction to a set of heat-treated mesophase pitch-based carbon fibers, with the goal of elucidating the crystalline structures as a function of fiber orientation. To assist with analysis and interpretation of the experimental data, we employed diffraction pattern simulations using the scalar and vector forms of the Debye scattering equation to determine the influence of basal plane orientation, crystalline ordering (turbostratic-graphitic), and basal plane asymmetry on the diffraction patterns. The results presented here suggest that growth of the transverse crystallites in mesophase pitch-based carbon fiber is fixed until graphitization temperatures are reached. The work completed here provides a framework for the analysis of carbon fiber and other oriented carbon-based materials via diffraction.

36 MATERIALS SCIENCE↗

Novel insight into the kinetics of amide bond glycolysis for nylon-6 depolymerization

Chemical recycling of nylon-6 to short-chain oligomers and monomer ε-caprolactam via catalytic glycolysis is a potential solution for plastic waste remediation. Here, in this work, the kinetics of amide bond glycolysis (with ethylene glycol) in nylon-6 and the model compound N-phenethyl-3-phenylpropanamide (M1) were evaluated at 473 K in the presence of the cyclic amidine catalyst 1,5,7-triazabicyclo[4.4.0]dec-5-ene. Rates of polymer glycolysis were determined by the time-dependent shift in molecular weight distribution, whereas rates of M1 glycolysis were determined using liquid chromatography. The similarity of the first-order rate constants for glycolysis of nylon-6 and M1 at 473 K with 0.03 M amidine catalyst (5 mol% relative to amide bonds), 1.22 × 10 −5 s −1 and 2.18 × 10 −5 s −1 , respectively, confirmed the suitability of M1 as a model compound for nylon-6 glycolysis. Similar rates of glycolysis in the presence of other cyclic amidine catalysts as well as sodium methoxide revealed little influence of base strength. Glycolysis rates were unexpectedly non-linear in catalyst loading and deactivation occurred with long reaction times, presumably by non-selective decomposition of products as detected by liquid chromatography.

Depolymerization rate and rate constant↗

Identification and characterization of substrate- and product-selective nylon hydrolases

Enzymes can rapidly and selectively hydrolyze diverse natural and anthropogenic polymers, but few have been shown to hydrolyze synthetic polyamides. Here, in this work, we synthesized and characterized a panel of 95 enzymes from the N-terminal nucleophile hydrolase superfamily with 30%–50% pairwise amino acid identity. We found that nearly 40% of the enzymes had substantial nylon hydrolase activity, but there was no relationship between phylogeny and activity, nor any evidence of prior evolutionary selection for nylon hydrolysis. Several newly identified hydrolases showed substrate selectivity, generating up to 20-fold higher product titers with nylon-6,6 versus nylon-6. However, the yield was still less than 1%, necessitating further optimization before potential applications. Finally, we determined the crystal structure and oligomerization state of a nylon-6,6-selective hydrolase to elucidate structural factors that could affect activity and selectivity. These new enzymes provide insights into nylon hydrolase evolution and opportunities for analysis and engineering of improved hydrolases.

nylon↗

Geochemical evolution in Cacapon member: Fluid-rock interaction experiments and model insights for Appalachian Basin geothermal development

Here, this study combines recirculated flow-through experimental results conducted for 17 days at 90C and 200 PSI with reactive transport modeling to estimate fluid-rock interactions occurring in a sandy mudstone using an interbedded sandstone-shale sample from the Cacapon Member of the upper Tuscarora Sandstone/lower Rose Hill Formation for the purpose of geothermal exploration. Results suggest that the fluid and rock are likely to be in or near partial-equilibrium after approximately one year. In addition, after >400 h of continuous injection at 0.05 mL/min (5*10 −8 m 3 /min) the reactive front is restricted to the first ∼13% of the 4 cm*1.6 cm experimental rock length, whereas after >9100 h (∼1 year), the reactive front extends to 30% total length. The rate of changes in dissolution or precipitation are however, very minimal, with all major rock-forming minerals having rates <10 −11 mol/L porous media/s. Reservoir rock in the presence of dilute brine as may be the case during operation of an enhanced geothermal system would experience little alteration during the shut-in phase, and possibly up to one year. These results have utility in geothermal exploration for reservoirs at similar temperatures as well as general fluid-sandy mudstone rock interaction geochemistry.

Appalachian Basin↗

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗

Enhanced MPM framework with multipatch isogeometric analysis for geotechnical applications

Achieving stable stress solutions at large strains using the Material Point Method (MPM) is challenging due to the accumulation of errors associated with geometry discretization, cell-crossing noise, and volumetric locking. Several simplified attempts exist in the literature to mitigate these errors, including higher-order frameworks. However, the stability of the MPM solution in such frameworks has been limited to simple geometries and the single-phase formulation (i.e., neglecting pore fluid). Although never explored, multipatch isogeometric analysis offers desirable qualities to simulate complex geometries while mitigating errors in the MPM. The degree of required high-order spatial integration has also never been investigated to infer a minimum limit for the stability of the stress solution in MPM. This paper presents a general-purpose numerical framework for simulating stable stresses in porous media, capturing both near incompressibility and multiphase interactions. First, the numerical framework is presented considering Non-Uniform Rational B-splines (NURBS) to perform isogeometric analysis (IGA) in MPM. Additionally, a volumetric strain smoothing algorithm is used to alleviate errors associated with volumetric locking. Second, the manifestation of cell-crossing errors is assessed via a series of problems with orders ranging from linear to cubic interpolation functions. Third, the use of NURBS is investigated and verified for problems with circular geometries. Finally, multipatch analysis is deployed to simulate plane strain and 3D penetration in soils, considering nearly incompressible elastoplastic (total stress) analysis and fully-coupled hydro-mechanical (effective stress) analysis. The stability of the solution is also analyzed for different constitutive models. From the results, it can be concluded that the framework using cubic interpolation functions with strain smoothing is the most convenient, presenting stable stress solutions for a broad range of multiphase geotechnical applications.

58 GEOSCIENCES↗

Testing and modeling of CLT-to-CLT joints made using hardwood dowels and screws with varying spacing

With the increasing popularity of mass timber, utilizing large-diameter wood screws and hardwood dowels can offer an easy and cost-efficient way to join structural elements. However, the existing research on hardwood dowels is limited to single fastener joints under monotonic loading. No research is available on the group effects of joints with multiple hardwood dowels. Here, this paper presents the results of 96 monotonic and cyclic single-shear plane CLT-to-CLT joint tests with hardwood dowels (Red Oak and Yellow Birch, 25.4 mm diameter) and self-tapping wood screws (8 mm diameter) in Grand-Fir CLT, where screws were inserted both perpendicular and at a 45-degree angle to the grain for comparison to hardwood dowels. The study evaluated the mechanical properties of the joints by changing fastener spacing. Mechanical properties such as yielding and peak strength, displacement, elastic and yielding stiffness, and ductility were evaluated. The results showed equal strength and stiffness properties for hardwood dowels comparable with large-diameter screws. Additionally, the hardwood dowel joints demonstrated moderate ductility properties. The strength and stiffness of the tested joints were compared with analytical equations found in the literature by considering the group action factor of the fasteners. Lastly, a nonlinear force-displacement model was presented and compared to the experimental results and analytical calculations, which gives the possibility to predict and optimize the mechanical behavior of hardwood dowel and screw joints with varying numbers and spacing between fasteners.

36 MATERIALS SCIENCE↗

Assessment of the hydromechanical higher-order MPM for the simulation of geotechnical problems

The Material Point Method (MPM) has been increasingly used to simulate large strain deformations. Linear interpolation functions are commonly used to perform the spatial integration. It is well-known that the discontinuities in the interpolation function derivatives induce shock-like artifacts known as ‘cell-crossing’ error. These errors compound with volumetric locking errors when used with hydromechanical formulations for porous media, where different velocity fields are used for each phase. The capabilities of higher-order MPM frameworks have not been explored for real-scale geotechnical problems. As such, this paper aims to assess, validate, and further discuss a higher-order B-spline MPM (BS-MPM) framework. First, the BS-MPM framework is verified against the large-strain oedometer consolidation problem. Second, the framework is validated against a real-scale slope failure experiment triggered by pore water pressure recharge. Landslide features that are captured using the higher-order framework are specifically highlighted, and results (e.g., pore water pressure and deformation) are validated with field measurements. A generally convergent numerical solution is observed when using cubic interpolation functions. Third, a footing penetration problem is simulated using the multi-patch BS-MPM. Trends are examined with respect to penetration velocity and variation in hydraulic conductivity. The BS-MPM framework ultimately presents a stabilized numerical solution that captures plausible hydromechanical interaction trends important in geotechnical engineering applications.

36 MATERIALS SCIENCE↗

Conversion of CO 2 from power plant into CaCO 3 nanoparticles

Carbon dioxide (CO 2 ), a main composition of flue gas, represents a significant and largely untapped carbon resource. Herein, mediated by glycine (Gly), we captured and converted CO 2 into CaCO 3 nanoparticles using real flue gas from a power plant, demonstrating for the first time the feasibility of using amino acid to convert CO 2 from power plant flue gasses. The method did not require extraneous energy and CaCO 3 nanoparticles with a size of ∼25 nm were obtained. Moreover, the potential toxicity of CO 2 -converted nanoparticles was investigated. It appeared that both the initial CO 2 loading and the carbamate percentage significantly influence the shape and size of the CaCO 3 particles. Our method was also proven effective for flue gas with varying CO 2 concentrations (4 %, 12 %, and 20 %). By tuning flue gas bubbling time and flow rate to achieve consistent CO 2 loading and carbamate levels, we produced CaCO 3 nanoparticles with similar shapes and sizes across all CO 2 concentrations studied. In addition, our data indicated that although real flue gas contains small amounts of gases like oxygen and CO, they insignificantly influence the shape and size of our nanoparticles but did impact the phase component of CaCO 3 . In conclusion, the toxicity experiments found that CaCO 3 nanoparticles produced from both real flue gas and simulated flue gas exhibited concentration- and time-dependent effects on cell viability.

36 MATERIALS SCIENCE↗

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

Here, we present a perspective on recent progress in machine-learning (ML) force-field approaches for large-scale Landau–Lifshitz–Gilbert (LLG) simulations of metallic spin systems. Building on a generalization of the Behler–Parrinello (BP) architecture originally developed for quantum molecular dynamics, we develop scalable and transferable ML models that faithfully capture the complex, environment-dependent electron-mediated exchange fields characteristic of itinerant magnets. A central ingredient of this framework is the implementation of symmetry-aware magnetic descriptors based on group-theoretical bispectrum formalisms. Leveraging these ML force fields, LLG simulations faithfully reproduce hallmark non-collinear magnetic orders—such as the 120° and tetrahedral states—on the triangular lattice, and successfully capture the complex spin textures emerging in the mixed-phase states of a square-lattice double-exchange model under thermal quench. We further discuss a generalized potential theory that extends the BP formalism to incorporate both conservative and nonconservative electronic torques, thereby enabling ML models to learn nonequilibrium exchange fields from computationally demanding microscopic approaches such as nonequilibrium Green’s-function techniques. This extension yields quantitatively accurate predictions of voltage-driven domain-wall motion and establishes a foundation for quantum-accurate, multiscale modeling of nonequilibrium spin dynamics and spintronic functionalities.

Descriptors↗

Stress evolution and creep deformation in solid-oxide electrolysis cell systems – Dynamic modeling and multi-objective optimization to maximize stack life and efficiency

Here, this study develops a thermal stress model of solid-oxide electrolysis cells (SOECs) including a model for creep strain and failure probability that is integrated with a dynamic plant-wide model of a hydrogen production process. Uncertainties in key material properties of the cell are quantified to assess their impact on stress profile variability. The oxygen electrode is found to have about 10 times higher failure probability compared to the fuel electrode. The study shows that if the stack operation is not optimized, cycling operation would lead to stress build-up eventually leading to catastrophic failure. A dynamic optimization problem is set up for obtaining the optimal operational profile considering a variable hydrogen production rate. Due to the tradeoff between the efficiency and stress build-up, the dynamic optimization problem is multi-objective. It is observed that the optimizer can considerably reduce the stress build-up (i.e., can increase the stack life) albeit at the cost of a lower efficiency thus exhibiting strong tradeoffs between capital and operating costs. For example, if the stack would be replaced in 0.5 yr, specific energy requirement would be 48.5 kWh/kg H 2 while for a stack replacement time of about 6 yr, the specific energy requirement rises by about 4.2 %.

SOEC↗

Adiabatic fast passage spin manipulation measurements in solid polarized targets

Adiabatic fast passage (AFP) is a rapid method for reversing nuclear polarization and manipulating spin populations in polarized solid targets, avoiding the long repolarization times associated with dynamic nuclear polarization (DNP). We report AFP measurements in a 5 T, 1 K polarized-target system for irradiated 15 NH 3 , irradiated 14 ND 3 , and butanol-based materials prepared either with TEMPO doping or by irradiation. We also present a joint manipulated-lineshape analysis for spin-1 targets and demonstrate that vector and tensor polarizations can be extracted from AFP-manipulated deuteron NMR spectra even when the populations are not described by a single Boltzmann spin temperature. In conclusion, we report a reproducible polarization- and direction-dependent AFP response in a large irradiated 15 NH 3 sample. These ammonia results are presented as empirical observations under the specific sample–coil conditions of the experiment, with possible circuit-mediated mechanisms such as radiation damping or superradiant behavior discussed but not assigned as a definitive cause.

Adiabatic fast passage↗

Preheat effects in laser-driven Rayleigh–Taylor instability experiments at intensities greater than $10^{15}$ $\textrm{W}$ $\textrm{cm}^{-2}$ at OMEGA EP and the NIF

The propagation of high-energy X-rays or hot electrons have the potential to alter the initial conditions in experimental target designs, especially at material interfaces, for laser-driven inertial confinement fusion (ICF) and high-energy density (HED) experimental platforms. Hot-electron preheat can drastically modify the initial conditions of experimental targets used to study the deceleration-stage Rayleigh–Taylor instability (RTI) both with and without applied magnetic fields. Therefore, it is necessary to understand and quantify the impact of hot-electron preheat. The hydrodynamic (HD) capabilities in the Ares code are used to study the effects varying levels of preheat can have on RTI evolution. The experimental and computational studies presented in this work demonstrate that at high laser intensities of around or greater than 10 15 W cm −2 , there is hot-electron generation from laser plasma instabilities which induces substantial preheat and impacts the morphology of RTI evolution and even inhibits the intended RTI growth such that it is not observable experimentally. The necessity of better quantifying hot-electron induced preheat and mitigating its impact on such high-intensity direct-drive laser experiments in the future is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A New Nitrogen-Rich Energetic Material with So Many Tautomers

A new nitrogen-rich triazolo-triazole compound, (3-(6-methyl-1H-[1,2,4]triazolo[4,3-b][1,2,4]triazol-3-yl)-1H-1,2,4-triazol-5-amine), TTT1, has been prepared, and its acid–base and tautomeric behavior has been investigated. In the pH range of 0.3–12, TTT1 can accept up to two protons, forming a monocation and a dication, and can deliver one proton, forming a monoanion. The tautomeric behavior is particularly rich for the monocation, for which computational analysis predicts four different tautomers in a narrow energy range of 2 kcal/mol. Two of these tautomers (2H-7H-8H and 3H-7H-8H) have been isolated in salts of the monocation with suitable counterions (chloride, bromide, perchlorate). Surprisingly, the most stable predicted tautomer, 1H-3H-7H, has not been found in the four crystallized salts of the monocation. The energetic perchlorate salt of the monocation (3H-7H-8H tautomer) shows good thermal stability and good stability to impact, friction, and electric discharge. The packing of this compound shows the formation of H-bonded dimers with interactions between N8–H···N1. The crystal structure of this energetic salt was studied experimentally up to 2.8 GPa; no phase change or decomposition was observed.

Chemical structure↗

Strain-Based Assessment of Shale Caprock during Cyclic Underground Hydrogen Storage

Successful large-scale underground hydrogen storage (UHS) in depleted gas reservoirs depends on the integrity of the overlying caprock to prevent hydrogen loss during cyclic injection and depletion. Prior studies on crushed Marcellus shale, a potential caprock, indicate that cyclic hydrogen injection and depletion induces microstructural changes, increasing porosity and permeability. However, the extent of these changes in intact shale remains unclear. This study presents a strain-based experimental approach to quantify volumetric strain evolution in intact Marcellus shale matrix under unconstrained stress conditions. A quadrant-shaped shale sample without visible fractures underwent eight hydrostatic pore-pressure cycles (injection to 1500 psi and depletion to 500 psi in 250 psi steps). Linear strain gauges measured strain in three orthogonal directions. Results indicate progressive plastic strain accumulation, leading to an ∼12% increase in matrix porosity after eight cycles, with an estimated 19% increase after 30 cycles. This porosity increase follows a logarithmic trend, suggesting a diminishing effect in later cycles. Additionally, permeability and diffusive mass flux are projected to rise by ∼70% over 30 cycles, enhancing hydrogen migration risk. The shale matrix also exhibited mechanical stiffening over successive cycles, limiting large-scale deformation but not preventing porosity enhancement. A new parameter, α, was introduced to characterize shale sensitivity to cyclic loading, aiding UHS caprock assessments. These findings underscore the necessity of incorporating cyclic loading effects in UHS site selection and operational strategies to ensure long-term storage integrity.

08 HYDROGEN↗

Technoeconomic Analysis of a Microwave-Assisted Novel Process That Converts Polypropylene Plastic Waste to Propylene

Propylene is an important petrochemical that is used in various industries, including the automobile and polymer sectors. Conventionally, propylene has been produced through fluid catalytic cracking, steam cracking, and propane dehydrogenation. In this project, a novel process to produce propylene from polypropylene plastic waste using a microwave reactor is introduced. Propylene production is simulated in Aspen Plus for both the conventional propane dehydrogenation process and the novel design, with heat integration applied to minimize utility demands and the conventional process serving as the base case for comparison. Finally, a tailored technoeconomic analysis is carried out for both simulated cases to estimate important economic indicators. Analysis of the results shows that the novel microwave-assisted process outperforms the conventional route for propylene production, achieving a single-pass conversion of almost 100%, compared with only 33.8% in the conventional plant. The Net Present Value of the novel plant is $\$1720.3$ MM, which is 3.5 times higher than the conventional process, while the Levelized Cost of Propylene is reduced by 40%. Capital and operating expenditure are also improved in the proposed scheme, with reductions of approximately $\$29$ MM and $\$222$ MM/yr, respectively. In addition to cost savings, this novel process also provides a convenient means to recycle waste polypropylene.

42 ENGINEERING↗

Classical Preoptimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. Furthermore, by preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

ADAPT-VQE↗