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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Utilizing a Dynamic Segmentation Convolutional Neural Network for Microstructure Analysis of Additively Manufactured Superalloy 718

Additive manufacturing (AM) is revolutionizing almost all industries through the production of intricate geometries previously prohibited by cost or machinability. Ni-based superalloys form a primary alloy class for high temperature applications in the petrochemical, aerospace, and nuclear industries because of their intrinsic resistance to creep and the ability to heat treat the superalloy for high strength. Despite these attractive properties, the extreme work hardening of Ni-based superalloys makes traditional manufacturing of complex shapes difficult and thus, these alloys are an attractive target for AM. Superalloy 718 was chosen as an example superalloy because of the wide variety of precipitates that can form within its composition space from the repetitive heating and cooling cycles of the AM process. The precipitates and other microstructure features, such as grain boundaries and dislocations, will dictate the mechanical properties and thus, there is an extensive challenge to characterize the size, number density, composition, and volume fraction of each microstructural feature from AM fabrication using analytical electron microscopy. This work focused on the application of a pixel-wise classification machine learning (ML) model called a dynamic segmentation convolutional neural network (DSCNN) to identify the microstructural features of an as-fabricated additively manufactured superalloy 718.

Taller, Stephen↗
DOE OSTI2026

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗
DOE OSTI2025

Unveiling Atomistic Mechanisms Governing Additive Manufacturing Processability and Mechanical Behavior of a Refractory Complex Concentrated Alloy

Extending the concept of complex concentrated alloys (CCAs) to the refractory alloys (solidus temperature over 2000 °C) space potentially facilitates the design of lightweight structural alloys with service temperatures that exceed those of Ni and Co‐based alloys. However, the room and elevated temperature tensile properties of the current refractory‐CCAs (R‐CCAs) are inferior to those of the Ni/Co‐based alloys. Furthermore, the manufacturing scalability of R‐CCAs remains challenging, in that cracks are prevalent in all R‐CCAs when processed using near‐net shape manufacturing processes, such as fusion‐based additive manufacturing (F‐BAM). Still, mechanisms governing the poor F‐BAM processability of R‐CCAs remain unexplored. Here, to this end, this work unveils the atomistic mechanisms underlying F‐BAM process‐induced cracking in a NbTiTaMoHfZrC R‐CCA. The implications of light elements’ presence for intrinsic ductility and grain boundary cohesion, and subsequently for F‐BAM processability and mechanical behavior, are revealed. Leveraging the insights, we accomplish what is, to the best of the knowledge, the first instance of crack‐free F‐BAM processing of any R‐CCA. Additionally, the R‐CCA exhibits over 20% tensile ductility and ≈160 MPa tensile yield strength at 1200 °C. In addition to facilitating the design of lightweight R‐CCAs, findings enable scalable manufacturing of these ultra‐high temperature alloys for structural applications.

Refractory alloys↗
DOE OSTI2024

Solidification and crystallographic texture modeling of laser powder bed fusion Ti-6Al-4V using finite difference-monte carlo method

Laser powder bed fusion (LPBF) additive manufacturing makes near-net-shaped parts with reduced material cost and time, rising as a promising technology to fabricate Ti-6Al-4V, a widely used titanium alloy in aerospace and medical industries. However, LPBF Ti-6Al-4V parts produced with 67° rotation between layers, a scan strategy commonly used to reduce microstructure and property inhomogeneity, have varying grain morphologies and weak crystallographic textures that change depending on processing parameters. Here, this study predicts LPBF Ti-6Al-4V solidification at three energy levels using a finite difference-Monte Carlo method and validates the simulations with large-area electron backscatter diffraction (EBSD) scans. The developed model accurately shows that a <001> texture forms at low energy and a <111> texture occurs at higher energies parallel to the build direction but with a lower strength than the textures observed from EBSD. A validated and well-established method of combining spatial correlation and general spherical harmonics representation of texture is developed to calculate a difference score between simulations and experiments. The quantitative comparison enables effective fine-tuning of nucleation density (N 0 ) input, which shows a nonlinear relationship with increasing energy level. Future improvements in texture prediction code and a more comprehensive study of N 0 with different energy levels will further advance the optimization of LPBF Ti-6Al-4V components. These developments contribute a novel understanding of crystallographic texture formation in LPBF Ti-6Al-4V, the development of robust model validation and calibration pipeline methodologies, and provide a platform for mechanical property prediction and process parameter optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Pivotal Roles of Triple Screening-Topological, Electrostatic, and Hydrodynamic-On Dynamics in Semidilute Polyelectrolyte Solutions

For semidilute polyelectrolyte solutions, it is generally assumed that topological, electrostatic, and hydrodynamic interactions are screened (called triple screening). Despite a large body of research focused on polyelectrolyte solutions, the concept of triple screening has never been rigorously verified. In this work, we test the concept by probing concentration fluctuations in aqueous solutions containing a well-studied polyelectrolyte, sodium poly(styrenesulfonate) (NaPSS) with neutron scattering, theory, and molecular dynamics simulations. Neutron spin–echo (NSE) and small-angle neutron scattering (SANS) data from semidilute solutions of NaPSS are presented at different polymer and salt (NaCl) concentrations. A combined theory for structure (J. Chem. Phys. 105, 5183 (1996)) and dynamics (J. Chem. Phys. 107, 2619 (1997)), which captures effects of hydrodynamic, topological, and electrostatic screening, is used to interpret the experimental results. Here, the theory quantitatively predicts the decay rate obtained from the NSE measurements while capturing the shape and concentration dependencies of the polyelectrolyte peak observed in the SANS spectra. Detailed comparisons of the theory and the experiments reveal that the wavevector-dependent decay rate of concentration fluctuations in semidilute solutions of polyelectrolytes is dictated by the screening of hydrodynamic, topological, and electrostatic interactions. This conclusion is corroborated by coarse-grained molecular dynamics simulations, executed without any hydrodynamic interactions, which fail to capture the correct wavevector dependence of the decay rate. These results highlight that the theories based on the concept of triple screening provide a quantitative framework for predicting a relation between the structure and dynamics of polyelectrolyte solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Crystal plasticity modeling for the strengthening effect of multilayered copper–graphene nanocomposites

The paper explores plastic deformation mechanisms in metal–graphene nanocomposites, illustrating their material strengthening effects through a crystal plasticity finite element (CPFE) model. This model is compared with published experimental results, which have previously shown that the two-dimensional shape of graphene effectively controls dislocation motion and significantly enhances the strength of metals. Simulated nanopillar compression tests, using a physics-based CP model that incorporates surface nucleation and single-arm source dislocation mechanisms, help us understand dislocation motions at submicron length scales. The crystal plasticity models are applied to nanolayered composites with copper grain layers and monolayer graphene, featuring repeat layer spacings of 200 nm, 125 nm, and 70 nm, respectively. This study quantifies the accumulation of dislocations at the graphene interfaces, contributing to the ultra-high strength of copper–graphene composites. Furthermore, a Hall–Petch-like correlation is established between yield strength and the number of embedded graphene layers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Double Sided LGAD-Based Detector Providing Timing, Position, and Track Angle Information

We describe a detector concept which combines small pixels enabled by 3D sensor-electronics integration with gain produced by a Low Gain Avalanche Diode (LGAD) layer. The detector is double-sided, with electrons collected by the cathode, which provides timing information, and an anode with small pixels to provide position and angle information. The cathode can be coarse grained, providing timing with fewer fast amplifiers to limit power consumption. The anode layer benefits from the gain of the LGAD, with larger signals that also limit the power needed. Position can be reconstructed by measuring the pattern of total charge deposited on the anode. Angle and depth of charge deposit can be measured by the shapes of the anode pulses. We describe a possible assembly technology based on 3D integration.

3D Integration↗
DOE OSTI2025

Sediment transport and morphodynamic changes due to upstream variation and sea level rise on the Western Mekong Delta, Vietnam

The hydrological and morphological dynamics across the Vietnam Mekong Delta (VMD) coastline are increasingly shaped by human interventions and climate change, affecting the sustainability of socio-economic environments. This study employs the TELEMAC-MASCARET modeling system (TELEMAC-2D, TOMAWAC, and SISYPHE modules) to simulate hydrodynamics, sediment transport, and morphological changes for a 10-year period under baseline (SC1) and future climate (SC2) scenarios, considering wave climatology of Northeast (NEM) and Southwest monsoons (SWM). The results of sedimentation and erosion were analyzed across five key coastal zones from Ca Mau Cape (KV1) to Ha Tien (KV5). Model results highlight distinct seasonal patterns of sediment redistribution shaped by monsoonal flows, wave action, and seabed morphology. During the NEM, sediment deposition is concentrated near estuarine zones, while the SWM favors offshore sediment accumulation due to perpendicular wave actions, and shallow, gently sloping bathymetry that dissipates wave energy. Coastal erosion predominantly occurs at convex shoreline features subjected to stronger coastal currents, particularly in fine-grained sediment areas. Under future sea level rise and land subsidence scenarios, reduced flow velocities lead to lower bottom shear stress, promoting deposition and mitigating erosion problems despite increased wave energy. Besides that, sediment transport analyses across 14 cross-sections (C-S) reveal a southward trend during the NEM and a northward reversal during the SWM, with upstream sediment reductions primarily influencing near-estuarine zones and exerting minimal impact beyond the mid-coastal regions. Furthermore, these findings advance the understanding of sediment redistribution processes under climate change and seasonal change, and provide a scientific basis for adaptive coastal management and sustainable development.

Climate change↗
DOE OSTI2023

Mycorrhizal status and host genotype interact to shape plant nutrition in field grown maize ( Zea mays ssp. mays )

Arbuscular mycorrhizal fungi (AMF) establish symbioses with the major cereal crops, providing plants with increased access to nutrients while enhancing their tolerance to toxic heavy metals. However, not all plant varieties benefit equally from this association. In this study, we used quantitative trait loci (QTL) mapping to evaluate the combined effect of host genotypic variation (G) and AMF across 141 genotypes on the concentration of 20 mineral elements in the leaves and grain of field grown maize (Zea mays spp. mays). Our mapping design included selective incorporation of a castor AMF-incompatibility mutation, allowing estimation of AMF, QTL and QTLxAMF effects by comparison of mycorrhizal and non-mycorrhizal plants. Overall, AMF compatibility was associated with higher concentrations of boron (B), copper (Cu), molybdenum (Mo), phosphorus (P), selenium (Se) and zinc (Zn) and lower concentrations of arsenic (As), iron (Fe), magnesium (Mg), manganese (Mn), potassium (K) and strontium (Sr). In addition to effects on individual elements, pairwise correlation matrices for element concentration differed between mycorrhizal and non-mycorrhizal plants. We mapped 22 element QTLs, including 18 associated with QTLxAMF effects that indicate plant genotype-specific differences in the impact of AMF on the host ionome. Although there is considerable interest in AMF as biofertilizers, it remains challenging to estimate the impact of AMF in the field. Our design illustrates an effective approach for field evaluation of AMF effects. Furthermore, we demonstrate the capacity of the ionome to reveal host genotype-specific variation in the impact of AMF on plant nutrition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

(Towards) DNS of a Laboratory Lean CH4/H2 Low-Swirl Flame Impinging on an Inclined Wall

Due to downsizing trends, flame-wall interaction (FWI) is increasingly prominent in gas turbines (GTs). FWI has direct consequences on flame stabilization and pollutant emissions, but it is not well understood in turbulent flows representative of GTs. We present results from a direct numerical simulation (DNS) of a turbulent CH4/H2 model GT low-swirl laboratory-scale flame interacting with an inclined wall. The results from the laboratory flame include simultaneous measurements of velocity using stereo particle imaging velocimetry and OHxCH2O planar laser induced fluorescence. The adaptive-mesh refinement solver PeleLMeX is used, with 24-species, 105-reaction reduced Aramco chemical kinetics mechanism. The premixed fuel-air mixture consists of hydrogen-enriched methane with 70% hydrogen volume fraction and 0.4 equivalence ratio. The inflow is prescribed to match experimental measurements at the burner exit. Karlovitz and turbulent Reynolds numbers are 300 and 400, respectively. The simulation and experimental results show excellent agreement. The flame features a bowl-shape stabilization, with a corrugated, continuous flame front at the leading edge, followed by fragmented reaction zones downstream. A large diffuse cloud of CH2O is formed downstream of the quenching point. The simulation results indicate that the cloud of CH2O is the result of incomplete methane combustion, with CH2O "leaking" from the locally quenched reaction zones.The DNS provides fine-grain resolution of turbulence-flame-wall interaction that cannot be captured with experimental measurements. With access to the entire solution vector at each cell of the computational domain, the local quenching.

flame-wall interactions↗
DOE OSTI2025

Production of Creep-Resistant FeCrAl-ODS

Four ODS FeCrAl alloys with base alloy composition Fe-16Cr-4Al-2Mo-0.2Y (wt.%) were mechanically alloyed with minor additions of CeO 2 and Y 2 O 3 additions and were successfully extruded into rectangular-shaped bars. Two oxide compositions were explored, which were designated NC with oxide addition of 0.5CeO 2 plus 0.2Yin solution of the base alloy powder and PC with additions of 0.5CeO 2 and 0.7Y 2 O 3 to elevate the O level. The microstructure of both alloys revealed by SEM and EBSD to consist of very small grains with sizes of ~450-520 nm and weak texture components. Sub-size tensile specimens fabricated from both alloys were tensile tested from room temperature to 800ºC. The results for both alloys from room temperature to 400ºC showed very high strengths, but low ductilities, especially uniform strain. From 500ºC to 800ºC, the strengths decreased rapidly, and the ductilities increased significantly. The reason for the rapid decreases in tensile strengths above 500ºC for both alloys is not clear, but will require advanced characterization techniques including atom probe tomography, to determine the size and number density of the nano-size oxide particles, and TEM/EFTEM, for investigating the dispersion of nano-size oxide particles on grain boundaries to assess the Zener grain boundary pinning effect, which will hinder grain coarsening at high temperatures that may enhance the Hall Petch strengthening mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Creation of Multi-Principal Element Alloy NiCoCr Nanostructures via Nanosecond Laser-Induced Dewetting

The multi-principal element alloy nanoparticles (MPEA NPs), a new class of nanomaterials, present a highly rewarding opportunity to explore new or vastly different functional properties than the traditional mono/bi/multimetallic nanostructures due to their unique characteristics of atomic-level homogeneous mixing of constituent elements in the nanoconfinements. Here, in this paper, the successful creation of NiCoCr nanoparticles, a well-known MPEA system is reported, using ultrafast nanosecond laser-induced dewetting of alloy thin films. Nanoparticle formation occurs by spontaneously breaking the energetically unstable thin films in a melt state under laser-induced hydrodynamic instability and subsequently accumulating in a droplet shape via surface energy minimization. While NiCoCr alloy shows a stark contrast in physical properties compared to individual metallic constituents, i.e., Ni, Co, and Cr, yet the transient nature of the laser-driven process facilitates a homogeneous distribution of the constituents (Ni, Co, and Cr) in the nanoparticles. Using high-resolution chemical analysis and scanning nanodiffraction, the environmental stability and grain arrangement in the nanoparticles are further investigated. Thermal transport simulations reveal that the ultrashort (≈100 ns) melt-state lifetime of NiCoCr during the dewetting event helps retain the constituent elements in a single-phase solid solution with homogenous distribution and opens the pathway to create the unique MPEA nanoparticles with laser-induced dewetting process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Martini 3 Coarse-Grained Force Field for Cholesterol

Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol. Here, we describe the development and validation of a Martini 3 cholesterol model, addressing issues related to its bonded setup, shape, volume, and hydrophobicity. In conclusion, the proposed model mitigates some limitations of its Martini 2 predecessor while maintaining or improving the overall behavior.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Visualizing the Internal Nanocrystallinity of Calcite Due to Nonclassical Crystallization by 3D Coherent X–Ray Diffraction Imaging

The internal crystallinity of calcite is investigated for samples synthesized using two approaches: precipitation from solution and the ammonium carbonate diffusion method. Scanning electron microscopy (SEM) analyses reveal that the calcite products precipitated using both approaches have a well–defined rhombohedron shape, consistent with the euhedral crystal habit of the mineral. The internal structure of these calcite crystals is characterized using Bragg coherent diffraction imaging (BCDI) to determine the 3D electron density and the atomic displacement field. BCDI reconstructions for crystals synthesized using the ammonium carbonate diffusion approach have the expected euhedral shape, with internal strain fields and few internal defects. In contrast, the crystals synthesized by precipitation from solution have very complex external shapes and defective internal structures, presenting null electron density regions and pronounced displacement field distributions. These heterogeneities are interpreted as multiple crystalline domains, created by a nonclassical crystallization mechanism, where smaller nanoparticles coalescence into the final euhedral particles. The combined use of SEM, X–ray diffraction (XRD), and BCDI allows for structurally differentiating calcite crystals grown with different approaches, opening new opportunities to understand how grain boundaries and internal defects alter calcite reactivity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sequence-defined Pareto frontier of a copolymer structure

The correlations between the sequence of monomers in a macromolecule and its three-dimensional (3D) structure is a grand challenge in polymer science. The properties and functions of macromolecules depend on their 3D shape that has appeared to be dictated by their monomer sequence. However, the progress towards understanding the sequence–structure-property correlations and their utilization in materials engineering are slow because it is almost impossible to characterize an astronomically large number of possible sequences of a copolymer using traditional experimental and simulation methods. To address this problem, here, we combine evolutionary computing and coarse-grained molecular dynamics (CGMD) simulation and study the sequence-structure correlations of a model AB-type copolymer in a solution and assess the impact of sequence on the packing density in its bulk phase. The CGMD-based evolutionary algorithm (EA) screens the sequence space of a single chain copolymer efficiently and identifies a wide range of single-molecule structures including extremal radii of gyration. The data are utilized to estimate the Pareto front of the structure-space of a binary copolymer as a function of its composition. The monomer packings in single-molecule solution phase and multimolecular bulk phase are found to be identical. Finally, this work highlights the opportunities of sequence-specific control of macromolecular structure for designing target materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Cooperative microbial interactions drive spatial segregation in porous environments

The role of microbial interactions and the underlying mechanisms that shape complex biofilm communities are poorly understood. Here we employ a microfluidic chip to represent porous subsurface environments and show that cooperative microbial interactions between free-living and biofilm-forming bacteria trigger active spatial segregation to promote their respective dominance in segregated microhabitats. During initial colonization, free-living and biofilm-forming microbes are segregated from the mixed planktonic inoculum to occupy the ambient fluid and grain surface. Contrary to spatial exclusion through competition, the active spatial segregation is induced by cooperative interactions which improves the fitness of both biofilm and planktonic populations. We further show that free-living Arthrobacter induces the surface colonization by scavenging the biofilm inhibitor, D-amino acids and receives benefits from the public goods secreted by the biofilm-forming strains. Collectively, our results reveal how cooperative microbial interactions may contribute to microbial coexistence in segregated microhabitats and drive subsurface biofilm community succession.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗