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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 271 records · Page 15

Evolution of PTCDA-derived seeds prior to graphene nanoribbon growth on Ge(001)

The synthesis of graphene nanoribbons (GNRs) can be realized via CH4 chemical vapor deposition (CVD) on substrates such as Ge(001) that promote highly anisotropic growth kinetics. Small polycyclic aromatic hydrocarbons (PAHs) are first sublimed onto Ge near room temperature to form graphene-like seeds that subsequently initiate GNR growth with CH4 exposure at 1173 K. The behaviors of PAHs in the time in between their sublimation onto Ge and GNR growth are unclear. Here, we study an archetypical PAH, perylene-3,4,9,10-tetracarboxyl acid dianhydride (PTCDA), on Ge(001) using both scanning tunneling microscopy (STM) and density functional theory (DFT) to characterize PAH conformation, surface diffusivity, and clustering, versus temperature. PTCDA becomes mobile above 673 K (consistent with a DFT calculated diffusion barrier of 2.01 eV). The mobile PTCDA molecules meet, cluster, and fuse at Ge step edges. These clusters have an apparent height of 0.4 nm, similar to small graphene islands, and grow laterally with increasing temperature – reaching 1.2 – 2.1 nm in width at 1173 K, consistent with the seed size extrapolated from CVD experiments. These results provide a plausible picture for how PTCDA forms seeds for anisotropic GNR CVD and show that PAHs with reduced surface diffusivity and inter-molecular reactivity are needed to enable more monodisperse PAH-seeded GNR synthesis.

36 MATERIALS SCIENCE↗

Programmable bionanocomposite coated fertilizers for prolonged controlled release of nitrogen

Controlled-release fertilizers (CRFs) present a promising solution for alleviating food and nutrient scarcity. However, their development has been mainly hindered by both rapid and unsynchronized nutrient release and unsustainable coating materials. In this study, we address this issue by developing a new coating layer for CRFs using a programmable biopolyurethane nanocomposite. This nanocomposite is prepared from diphenylmethane diisocyanate (MDI)-functionalized bentonite nanoclay (BNT-MDI) and a biopolyol from biomass waste. The results show that the BNT-MDI-doped CRFs (BCRFs) exhibit an impressive nitrogen (N)-release longevity of approximately 120 days at a 4 wt% coating ratio, surpassing previous CRF formulations. In a 30-day snap bean cultivation study, BCRF significantly improved root length (1000%), leaf length (257%), leaf width (400%), and plant height (1400%) compared to the control. The superior performance of BCRF is attributed to the PU-nanoclay biocomposite film, with full nano-exfoliation, controllable porosity, and high crosslinking density. Furthermore, we introduce a new dynamic release mechanism and establish a quantitative relationship between the nanostructure, property, and release performance of BCRF by combining the multiplicative and diffusion models for porous materials. Finally, this study provides a theoretical framework and a straightforward methodology for designing programmable nanocomposite structures for future biobased CRFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Universal scaling of electron transmission for nearly ballistic and quantum dragon nanodevices

Here, we predict two different universal scaling regimes for the quantum transmission of metallic nanodevices following the addition of a small amount of uncorrelated disorder. A nanodevice is connected to two thin semi-infinite uniform leads, and the Non-Equilibrium Green’s Function (NEGF) methodology yields the electron transmission $\mathscr{T}(E)$ as a function of the injected electron energy $E$. Ballistic nanodevices have no disorder and have $\mathscr{T}(E)=1$for all $E$ that allow electron propagation in the leads. Quantum dragon nanodevices can have extremely strong properly correlated disorder, and still have $\mathscr{T}(E)=1$for all $E$. Additional uncorrelated site disorder leads to Fano resonances in $\mathscr{T}(E)$. Averaging over the uncorrelated disorder we predict using perturbation theory two universal scaling regimes for $\mathscr{T}_{ave}(E)$. The functional form of both universal scaling regimes depend on the device length and width, energy, and variance of the uncorrelated disorder. The second scaling regime, valid for small but somewhat larger uncorrelated disorder than the first scaling regime, also has the form dependent on the density of states of the system. These two scaling regimes are demonstrated to be valid via large scale computer calculations.

Ballistic transport↗

A fast and accurate domain decomposition nonlinear manifold reduced order model

Here, this paper integrates nonlinear-manifold reduced order models (NM-ROMs) with domain decomposition (DD). NM ROMs approximate the full order model (FOM) state in a nonlinear-manifold by training a shallow, sparse autoencoder using FOM snapshot data. These NM-ROMs can be advantageous over linear-subspace ROMs (LS-ROMs) for problems with slowly decaying Kolmogorov n-width. However, the number of NM-ROM parameters that need to be trained scales with the size of the FOM. Moreover, for “extreme-scale” problems, the storage of high-dimensional FOM snapshots alone can make ROM training expensive. To alleviate the training cost, this paper applies DD to the FOM, computes NM-ROMs on each subdomain, and couples them to obtain a global NM-ROM. This approach has several advantages: Subdomain NM-ROMs can be trained in parallel, involve fewer parameters to be trained than global NM-ROMs, require smaller subdomain FOM dimensional training data, and can be tailored to subdomain specific features of the FOM. The shallow, sparse architecture of the autoencoder used in each subdomain NM-ROM allows application of hyper-reduction (HR), reducing the complexity caused by nonlinearity and yielding computational speedup of the NM-ROM. This paper provides the first application of NM-ROM (with HR) to a DD problem. In particular, this paper details an algebraic DD reformulation of the FOM, training a NM-ROM with HR for each sub domain, and a sequential quadratic programming (SQP) solver to evaluate the coupled global NM-ROM. Theoretical convergence results for the SQP method and a priori and a posteriori error estimates for the DD NM-ROM with HR are provided. The proposed DD NM-ROM with HR approach is numerically compared to a DD LS-ROM with HR on the 2D steady-state Burgers’ equation, showing an order of magnitude improvement in accuracy of the proposed DD NM-ROM over the DD LS-ROM.

97 MATHEMATICS AND COMPUTING↗

Comparison of excess free energy at an interface according to the applied interpolation scheme for elasticity: A phase-field method

Phase-field modeling is an effective simulation technique for modeling microstructure evolution of elastically anisotropic systems. To introduce the elastic energy contribution in a phase field model, an interpolation scheme is used to define the mechanical properties within the phases and across the continuous interface. Several existing interpolation schemes introduce a potential excess elastic energy at the interface, which undesirable effect on microstructure evolution needs to be evaluated. In this study, we focused on three interpolation schemes including Khachaturyan’ scheme (KHS), Voigt–Taylor’s scheme (VTS), and Steinbach–Apel’s scheme (SAS). Comparisons of these schemes’ performances were performed in three configuration types using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework: bi-crystal, isotropic particle-matrix and anisotropic particle-matrix. The contribution of excess elastic energy on the interface energy as a function of interface width and the computational time to steady-state were evaluated in these three configurations. SAS introduces the lowest excess elastic energy contribution and the VTS has the biggest contribution amongst the considered schemes. Moreover, when modeling precipitation in an anisotropic elastic material, the SAS approach seems to predict more physical convex shapes during growth, making it preferable to KHS and VTS. Finally, as currently implemented, SAS requires the largest computational time and KHS requires the smallest time to reach steady-state amongst the considered schemes.

36 MATERIALS SCIENCE↗

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↗

Microstructure prediction for Ti-22Al-25Nb in laser powder bed fusion

This work presents a physics-informed framework for predicting solidification morphology and defect susceptibility in additively manufactured Ti–22Al–25Nb across a broad processing space. The framework integrates solidification microstructure selection (SMS) analysis with a single-track defect-based printability map to establish a unified methodology linking processing parameters to both interfacial morphology and manufacturability. Thermal gradients G and solidification rates R are first computed using the Thermo-Calc Additive Manufacturing (TC-AM) module, a finite-interface-dissipation (FID) phase-field (PF) model coupled with CALPHAD method is then employed to systematically distinguish planar and dendritic regimes as functions of $G$ and $R$. By superimposing the printability map onto the morphology projections, a comprehensive process–structure framework is obtained. Across most processing conditions, the predicted microstructure is predominantly dendritic, while planar growth emerges only under selected laser power $P$ and scan speed $v$ combinations. In addition to morphology classification, the framework quantifies the dendritic area fraction and introduces a width-based morphology descriptor to characterize the spatial extent of planar/dendritic regions within the melt pool. It provides mechanistic insight into the interplay between solidification physics and defect formation, offering practical guidance for parameter selection and microstructural control in Ti–22Al–25Nb additive manufacturing (AM).

36 MATERIALS SCIENCE↗

STORM: Scrape-off layer turbulence in tokamak fusion reactors

The scrape-off layer of a tokamak fusion reactor carries the plasma exhaust from the hot core plasma to the material surfaces of the reactor vessel. The heat loads imposed by the exhaust are a critical limit on the performance of fusion power plants. Turbulent transport of the plasma regulates the width of the scrape-off layer plasma and must be modelled to understand the intensity of these heat loads. STORM is a plasma turbulence code capable of simulating three dimensional turbulence across the full scrape-off layer of a tokamak fusion reactor, using a drift reduced, collisional fluid model. STORM uses mostly finite difference schemes, with a staggered grid in the direction parallel to the magnetic field. We describe the model, geometry and initialisation options used by STORM, as well as the numerical methods, which are implemented using the BOUT++ plasma simulation framework. BOUT++ has been enhanced alongside the development of STORM, providing better support for staggered grid methods. We summarise these enhancements, including a detailed explanation of the parallel derivative methods, which underwent a major update for version 4 of BOUT++.

BOUT++↗

Superconducting properties of commercially available solders for low-field applications

Solders with superconducting transitions around 4K are useful in low magnetic field environments for AC current leads or in electrical and mechanical bonds. Accurate knowledge of these solders’ superconducting properties is essential for improving high precision experiments. We have measured the electrical resistance of five commercially-available eutectic or near-eutectic solders: 50%Sn-50%Pb, 60%Sn-40%Pb, 60%Sn-40%Pb-0.3%Sb, 52%In-48%Sn, and 96.5%Sn-3.5%Ag, down to 2.3K and in applied magnetic fields from 0 to 0.1 T . We report critical temperatures T c (B), 90%–10% transition widths ΔT c , and zero-temperature critical fields B c,0 . Our best candidate for low-loss AC current wiring in low fields is 50%Sn-50%Pb, which has a zero-field T c,0 = 7.1K (with ΔT c = 0.6 K), and remained high at T c (0.1 T) = 6.9K (ΔT c = 0.6K ). We also report, for the first time, T c and B c of 60%Sn-40%Pb-0.3%Sb and B c,0 of 96.5%Sn-3.5%Ag. Our T c,0 - 3.31K (ΔT c = 0.08K) for 96.5%Sn-3.5%Ag disagrees with a widely adopted value.

Hickman, C. [North Carolina State University, Rale↗

Novel thermal energy storage component: Development, performance, and phase transition diagnosis

Thermal energy storage (TES) using phase change materials (PCMs) is a promising technology for capturing and storing excess thermal energy for later use. However, challenges such as poor heat transfer efficiency and a lack of modular, scalable designs have limited widespread adoption of TES in real-world applications. This study developed and evaluated modular brick-type and blade-type TES prototypes featuring an aluminum housing, an embedded serpentine coil for active or passive thermal exchange, and a cost-effective metal mesh to enhance PCM thermal conductivity. The blade-type TES achieved notable geometric efficiency, with a thickness-to-length ratio of 0.03 and a thickness-to-width ratio of 0.08, enabling highly compact and modular thermal storage suitable for space-constrained applications. The paper presents a detailed evaluation of the TES prototypes’ performance. The comparative analysis indicated that the TES prototypes provide a highly cost-effective, thermally optimized alternative for compact energy storage and load shifting. A novel diagnostic technique was also introduced: using a portable endoscope to capture real-time visualizations of PCM phase transitions inside the TES. This method provides critical insights into internal heat transfer mechanisms, identifies potential issues, and offers valuable support for optimizing the TES design and developing the control algorithm. Overall, the modular brick-type and blade-type TES designs demonstrated in this work provide a scalable, efficient, and economically viable solution for advancing TES across residential, commercial, and industrial sectors. The designs’ compact structure, enhanced thermal performance, and integrated diagnostic capabilities make them strong candidates for future deployment in energy-efficient systems.

Gao, Zhiming [ORNL] (ORCID:0000000271397995)↗

Advanced blade-shaped thermal energy storage device: Development and application

Thermal energy storage (TES) using phase change materials (PCMs) is a promising approach for capturing and reusing excess thermal energy, yet widespread adoption is limited by low thermal conductivity, bulky configurations, and inadequate scalability. Here, this study presents a modular, blade-shaped TES prototype designed to address these challenges. The device integrates a lightweight aluminum shell, an embedded serpentine coil for active or passive heat exchange, and a cost-effective corrugated metal mesh for enhanced PCM thermal conductivity. With thickness-to-length and thickness-to-width ratios of 0.03 and 0.08, respectively, the blade-shaped TES achieves a compact, modular form factor suitable for space-constrained applications. Experimental testing demonstrated the efficient charge and discharge behavior of blade-shaped TES, capturing PCM superheating, phase-change transitions, and subcooling dynamics, with charging and discharging efficiencies of 94.9% and 94.6%, respectively. Also, the system can potentially achieve higher energy density than that of conventional TES designs. When integrated into a household refrigerator during the study, three blade-shaped TES modules successfully shifted 100% of peak-time compressor operation to off-peak hours, reducing energy consumption while maintaining more stable compartment temperatures. The blade-shaped TES's thin geometry, modularity, and enhanced thermal performance support scalable deployment across residential, commercial, and industrial applications, providing a versatile, cost-effective solution for high-efficiency, demand-flexible thermal energy management.

Blade-shaped↗

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗

Influences of shock imprinting on mix in a 3D-printed porous media

Mixing of materials in porous media can cause a significant impact on fusion yield as previously demonstrated by the National Ignition Facility (NIF) MARBLE Campaign. Initially, the reactants are separated, with deuterium in the lattice struts and a tritium gas fill in the voids. Lattice parameters such as the strut thickness and relative pitch, provide a control for the mix parameters in the experiment. Los Alamos National Laboratory’s (LANL) BOSQUE project looks to better understand how the mix of the reactants and shell materials impact the fusion burn and resultant yield on various laser platforms. xRAGE’s Eulerian hydrodynamics and adaptive mesh refinement (AMR) provide the unique ability to study the impacts of multiscale features of complex lattice structures. This modeling provides the ability to measure shock front variations as the wave progress’ through a given media. Initial conditions of the lattice are essential to accurately model mix and burn measured by experiment. By varying the initial orientation and densities of these lattice regions the early time dynamics of how the shock is launched into the system is changed and advocates for the study of resulting effects. In this work, we will study the sensitivities of shock effects in varying 3D printed geometric systems and how these shocks alter the structure and mix in the lattice. We will discuss both preliminary experimental results and simulations to help plan and constrain future experiments where we will study the impact of different lattice geometries and lattice bulk densities. This work concludes with the relative impacts of lattice geometries on shock speeds at different bulk densities and the resultant mix widths due to those shock interactions. We see agreement with theory at the higher end of our bulk density study, however, as we approach lower bulk density systems the dynamics of these interactions begin to change.

2 Photon Polymerization↗

2D CFD of lean premixed hydrogen–air flame quenching under locomotive engine conditions

Hydrogen (H 2 ) is a promising fuel for reducing emissions in heavy-duty internal combustion engines (ICEs), but its low quenching distance increases the risk of flame propagation into narrow crevice regions, such as piston-liner gaps. This work uses detailed CFD simulations with finite-rate chemistry to investigate premixed H 2 –air flame quenching in a two-dimensional (2D) region consistent with the piston-liner gap of a diesel ICE. Model accuracy was assessed by comparison with experimentally measured quenching distances in an annular stepwise diverging tube (ASDT). A parametric study was conducted to assess the influence of crevice width (0.05–1.18 mm), pressure (50–150 bar), unburned gas temperature (431–573 K), and equivalence ratio ( Φ= 0.3–0.6). Results show that the critical Péclet number for flame survival is no greater than 3.25, consistent with prior literature, even under ultra-lean and high-pressure conditions (Φ ≤ 0.3, > 50 bar). Additionally, flames with Péclet numbers exceeding 6.15 exhibited front wrinkling, suggesting the onset of velocity-driven instabilities and enhanced flame robustness. These findings help define thresholds for flame quenching in confined geometries and support the safe design of H 2 fueled ICEs.

08 HYDROGEN↗

Droplet breakup by multimodal nonlinear Rayleigh Taylor instability

A droplet impacted by a shock wave will undergo a process of fragmentation due to the development of interfacial hydrodynamic instabilities. The interface experiences variable acceleration and shear that result in the development of both inertial (Rayleigh–Taylor) and shear (Kelvin–Helmholtz) instabilities. These perturbations grow in time and drive the fragmentation and breakup of the deformed droplet. Experiments are performed on nominally 0.86 mm water droplet subjected to a Mach 7.6 detonation wave, resulting in a high Weber number (~36,000) breakup event. Perturbation growth is measured from a series of high-speed (> MHz) shadowgraph images. It is proposed that, given the size of the large-scale perturbations observed in experiments, these instabilities are growing in the non-linear regime and can be described by bubble-merger models for nonlinear mixing. Calculations are performed for the growth rates and size of these instabilities using deformation and external flow models to establish the time-dependent boundary conditions. The concurrence of the measured perturbation widths and the predictions of the simple model lend credence to the theory. This novel approach serves to open a new avenue in the characterization of droplet breakup via hydrodynamic instabilities.

Droplet breakup↗

A careful examination of closure models in Euler–Lagrange Simulations of compressible multiphase flow in a planar shock particle curtain problem

In this work we present a comprehensive investigation of state-of-the-art closure models employed to represent interphase momentum, thermal, and work exchange between the gas and particulate phases for Euler–Lagrange (EL) simulations in shock-driven flows. A complete list of closures for the force, torque, heat transfer, and work exchange models is provided. In particular, the present work includes a stochastic closure for the particle-to-particle variation in the quasi-steady force and a deterministic closure for particle-to-particle variation in the added mass force in an EL framework. These variations arise due to the presence of neighboring particles and particle–particle interactions. To investigate the importance of each closure term, we carry out fully three-dimensional simulations for a planar shock propagating over a random bed of inert particles. The primary goal is to evaluate the role of each closure term on the gas dynamic features (such as transmitted and reflected shock locations) and particle curtain features (such as upstream and downstream curtain locations). To this end, thirteen cases are considered, with each case progressively including a closure model with the goal to identify and quantify its contribution to the simulated dynamics. We show that the volume fraction dependence of the mean force models plays an important role in generating wave-like instabilities that lead to concentration bands. In addition, fluctuations in quasi-steady and added mass forces primarily decrease the internal instabilities that tend to enhance local volume fraction variations. Particle rotation is primarily due to inter-particle collisions, is generally weak, and does not play an important role in the translational dynamics for the present configuration. Inter-phase heat transfer has a strong effect on gas phase temperature, slows down the transmitted and reflected shocks, and decreases the width of the curtain. Furthermore, the absence of a work-coupling model fails to conserve the total energy, greatly under-predicts the gas temperature which in turn affects the particle dynamics.

Compressible flow↗

The derivation of CRSS in pure Ti and Ti-Al alloys

The work focuses on the determination of the critical resolved shear stress (CRSS) in titanium (Ti) and titanium-aluminum (Ti-Al) alloys, influenced by an array of factors such as non-symmetric fault energies and minimum energy paths, dislocation core-widths, short-range order (SRO) effects which alter the local atomic environment, and tension-compression (T-C) asymmetry affected by intermittent slip motion. To address these multifaceted complexities, an advanced theory has been developed, offering an in-depth understanding of the mechanisms underlying slip behavior. The active slip systems in these materials are basal, prismatic, and pyramidal planes, with the latter involving both $\langle$a$\rangle$ and $\langle$c + a$\rangle$ dislocations. Each slip system is characterized by distinct Wigner-Seitz cell configurations for misfit energy calculations, varying partial dislocation separation distances, and unique dislocation trajectories—all critical to precise CRSS calculations. The theoretical CRSS results were validated against a comprehensive range of experimental data, demonstrating a strong agreement and underscoring the model's efficacy.

Critical stress↗

Comparison of machine learning and electrical resistivity arrays to inverse modeling for locating and characterizing subsurface targets

Here, this study evaluates the performance of multiple machine learning (ML) algorithms and electrical resistivity (ER) arrays for inversion with comparison to a conventional Gauss-Newton numerical inversion method. Four different ML models and four arrays were used for the estimation of only six variables for locating and characterizing hypothetical subsurface targets. The combination of dipole-dipole with Multilayer Perceptron Neural Network (MLP-NN) had the highest accuracy. Evaluation showed that both MLP-NN and Gauss-Newton methods performed well for estimating the matrix resistivity while target resistivity accuracy was lower, and MLP-NN produced sharper contrast at target boundaries for the field and hypothetical data. Both methods exhibited comparable target characterization performance, whereas MLP-NN had increased accuracy compared to Gauss-Newton in prediction of target width and height, which was attributed to numerical smoothing present in the Gauss-Newton approach. MLP-NN was also applied to a field dataset acquired at U.S. DOE Hanford site.

54 ENVIRONMENTAL SCIENCES↗