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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sensitivity of cellular automata grain structure predictions for high solidification rates

Understanding as-solidified grain structure development during constrained (G 0) alloy solidification conditions is a necessary component of understanding the larger process-microstructure relationships during additive manufacturing (AM) processing. This study applies a cellular automata (CA) model, for static solidification velocities and thermal gradients on the order of those expected in AM melt pools, to investigate grain shape development across ranges of input parameters governing temperature field evolution, nucleation, and growth. Variation in nucleated grain shape from columnar to equiaxed as a function of thermal gradient and nucleation density is modeled with CA and verified against the established transition model of Hunt and Gaumann. Furthermore, while thermal conditions and nucleation density are shown to have the largest roles on microstructure development, the sensitivity of grain structure was very unevenly distributed across parameter space. In particular, it was found that microstructure is very sensitive to mean nucleation undercooling and the interfacial response function in process space regimes near grain structure transitions, but entirely controlled by a combination of thermal gradient, solidification velocity, and nucleation density away from such transitions. The understanding of grain shape sensitivity obtained through CA modeling, particularly at large thermal gradient and nucleation density, will be necessary for accurate microstructure prediction during the extreme processing conditions and large input parameter uncertainty common to AM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cellular mRNA triggers structural transformation of Ebola virus matrix protein VP40 to its essential regulatory form

The Ebola virus matrix protein VP40 forms distinct structures linked to distinct functions in the virus life cycle. Dimeric VP40 is a structural protein associated with virus assembly, while octameric, ring-shaped VP40 is associated with transcriptional control. In this study, we show that suitable nucleic acid is sufficient to trigger a dynamic transformation of VP40 dimer into the octameric ring. Deep sequencing reveals a binding preference of the VP40 ring for the 3' untranslated region of cellular mRNA and a guanine- and adenine-rich binding motif. Complementary analyses of the nucleic-acid-induced VP40 ring by native mass spectrometry, electron microscopy, and X-ray crystal structures at 1.8 and 1.4 Å resolution reveal the stoichiometry of RNA binding, as well as an interface involving a key guanine nucleotide. The host factor-induced structural transformation of protein structure in response to specific RNA triggers in the Ebola virus life cycle presents unique opportunities for therapeutic inhibition.

3′ UTR↗
DOE OSTI2024

Structural basis for self-discrimination by neoantigen-specific TCRs

T cell receptors (TCR) are pivotal in mediating tumour cell cytolysis via recognition of mutation-derived tumour neoantigens (neoAgs) presented by major histocompatibility class-I (MHC-I). Understanding the factors governing the emergence of neoAg from somatic mutations is a major focus of current research. However, the structural and cellular determinants controlling TCR recognition of neoAgs remain poorly understood. This study describes the multi-level analysis of a model neoAg from the B16F10 murine melanoma, H2-D b /Hsf2 p.K72N 68-76 , as well as its cognate TCR 47BE7. Through cellular, molecular and structural studies we demonstrate that the p.K72N mutation enhances H2-D b binding, thereby improving cell surface presentation and stabilizing the TCR 47BE7 epitope. Furthermore, TCR 47BE7 exhibited high functional avidity and selectivity, attributable to a broad, stringent, binding interface enabling recognition of native B16F10 despite low antigen density. Our findings provide insight into the generation of anchor-residue modified neoAg, and emphasize the value of molecular and structural investigations of neoAg in diverse MHC-I contexts for advancing the understanding of neoAg immunogenicity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A Comparison of Solidification Structures and Submicroscale Cellular Segregation in Rapidly Solidified Stainless Steels Produced via Two-Piston Splat Quenching and Laser Powder Bed Fusion

Fusion-based additive manufacturing techniques leverage rapid solidification (RS) conditions to create parts with complex geometries, unique microscale/nanoscale morphological features, and elemental segregation. Three custom composition stainless steel alloys with varying chromium equivalence to nickel equivalence ratio (Cr eq /Ni eq ) between 1.53 and 1.95 were processed using laser powder bed fusion (LPBF) and/or two-piston splat quenching (SQ) to produce solidification rates estimated between 0.4 and 0.8 m/s. Both scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were utilized to collect high-resolution images, electron backscatter diffraction (EBSD) phase identification, and measure cellular segregation. Similar features were observed in both LPBF and SQ samples including phase and microstructure, nanoscale oxide particles, cell size, and segregation behavior. However, dislocation pileup was observed along the cell boundaries only in the LPBF austenite solidified microstructure. Targeted adjustment of the SQ feedstock Cr and Ni concentrations, within the ASTM A240 specification for 316L resulted in no observable impact on the cell size, oxide particle size, or magnitude of segregation. Also, the amount of Ni segregation in the ferrite solidified microstructures did not significantly differ, regardless of Cr/Ni eq or processing technique. Here, SQ is demonstrated as capable of simulating RS rates and microstructures similar to LPBF for use as an alternative screening tool for new RS alloy compositions.

42 ENGINEERING↗
DOE OSTI2024

DECA: Discrete Event inspired Cellular Automata for grain structure prediction in additive manufacturing

Microstructure largely dictates macroscopic material properties and is strongly affected by processing. Therefore, the simulation of microstructure evolution in response to thermal fields during processing is of significant interest within the computational materials science community. Additive manufacturing (AM) has emerged as a technique for producing complex geometries and unique microstructures. Yet, complex and rapid thermal cycles in AM pose computational challenges for existing microstructure models. This work proposes a discrete event inspired cellular automata (CA) approach, titled DECA, to accelerate simulation of grain structure evolution in AM. In contrast to conventional time-stepped CA models, this model directly solves the times capture events would take place allowing for stepping in events rather than time (a technique also found in the field of discrete-event simulation). In comparison to purely serial discrete-event models, DECA allows for temporary violation of the causality constraint, but detects and corrects these violations, leading to an emergent phenomenon dubbed causality rippling, in which previously calculated capture events are overwritten. The amount of repeated calculations, defined by the capture ratio, is taken as a measure of computational inefficiency, and the model parameters that affect this ratio are evaluated. The new DECA approach was found to be more computationally efficient than conventional time-stepped CA models while guaranteeing an accurate solution, which can only be achieved in the conventional models for vanishingly small time steps. Finally, opportunities for parallelization and scaling of the new approach are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simulating Mixed‐Phase Open Cellular Clouds Observed During COMBLE: Evaluation of Parameterized Turbulence Closure

Marine cold-air outbreaks, or CAOs, are airmass transformations whereby relatively cold boundary layer (BL) air is transported over relatively warm water. To more deeply understand BL and mixed-phase cloud properties during CAO conditions, the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) took place from late 2019 into early 2020. During COMBLE, the U.S. Department of Energy's first Atmospheric Radiation Measurement Mobile Facility (AMF1) was deployed to Andenes, Norway, far downstream (~1,000 km) from the Arctic pack ice. This study examines the two most intense CAOs sampled at the AMF1 site. The observed BL structures are open cellular with high (~3–5 km) and cold (–30 to –50 °C) cloud tops, and they often have pockets of high liquid water paths (LWPs; up to ~1,000 g m –2 ) associated with strong updrafts and enhanced turbulence. We use a high-resolution mesoscale model to explore how well four turbulence closure methods represent open cellular clouds. After applying a radar simulator to model outputs for direct evaluation, cloud top properties agree well with AMF1 observations (within ~10%), but radar reflectivity and LWP agreement is more variable. Results suggest that the turbulent Prandtl number may play an important role for the simulated BL and cloud properties. All simulations produce enhanced precipitation rates that are well-correlated with a cloud transition. Finally, the eddy-diffusivity/mass-flux approach produces the deepest cloud layer and therefore the largest and most coherent cellular structures. Furthermore, we recommend the use of a non-local turbulence closure approach to better capture turbulent processes in intense CAOs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A conserved viral RNA fold enables nuclease resistance across kingdoms of life

Abstract Viral exoribonuclease-resistant RNA (xrRNA) structures block cellular nucleases to produce subgenomic viral RNAs during infection. High sequence variability among xrRNAs from distantly related viruses raises questions about the shared molecular features that enable these RNAs to withstand the strong unwinding forces of exoribonucleases. Here, we present the first structure of a plant-virus xrRNA in its active conformation and uncover universal principles of xrRNA folding. Comparison with the structure of a human-pathogenic flavivirus xrRNA reveals that both share a core structural motif—a protective ring encircling the RNA’s 5′ end—despite lacking sequence similarity. Disrupting this core motif through targeted mutagenesis eliminates exoribonuclease-resistance and attenuates viral infection. We identify hundreds of related structures across multiple virus families, supporting the conservation of this mechanism. Our study demonstrates how distantly related RNA viruses have converged on a common structural strategy to inhibit cellular nucleases, with a universal ring topology as the defining feature of viral xrRNAs.

Biochemistry & Molecular Biology↗
DOE OSTI2020

CELLULAR COFFERDAMS AS PERMANENT HYDROPOWER DAM STRUCTURES

This paper presents the results of a comprehensive study on the potential use of cellular cofferdams as basis for the design and construction of water retaining structures to sustainably and cost-effectively harness hydropower. Previously, cellular cofferdams have been widely used mainly as temporary water exclusion devices to permit dry construction of in-water structures such as dams, locks, bridge footings and piers, and hydroelectric power plants. Design and construction requirements for cellular cofferdams are less stringent than for hydropower dams. To make cellular cofferdams suitable for permanent hydropower use, different design concepts that utilize cellular cofferdams as the main or core element of the water-retaining dam structure are proposed. One particular key design concept is the so-called “dry construction technique” in which the granular fill in cofferdam cells and the downstream berm are permanently kept dry in contrast to the wet construction technique for temporary use of cellular cofferdams. The viability of the proposed permanent cellular cofferdam design concepts is demonstrated using well-established structural and geotechnical design procedures and computational modeling. The improved performance of the proposed design concepts, particularly in combination with the dry construction technique, show cellular cofferdams have the potential to be used as basis for the construction of permanent hydropower dam structures that are versatile, with less impact on the environment, and will cost less to build than conventional hydropower dams.

13 HYDRO ENERGY↗
DOE OSTI2024

Hierarchical Composites Patterned via 3D Printed Cellular Fluidics

Additive manufacturing of freeform structures containing multiple materials with deterministic spatial arrangement and interactions remains a challenge for most 3D printing processes, due to complex fabrication tool requirements and limitations in printability of some material classes. Here, in this paper, a versatile method is reported to produce architected composites using the concept of cellular fluidics, in which lattices of unit cells are used as templating scaffolds to guide flowable infill materials in a programmed spatial pattern, upon which they are cured in place to produce a deterministically ordered multimaterial solid. The lattice design relies on the unit cell size, type, strut diameter, surface wetting, and distribution of cellular structures to control liquid flow and retention. Individual unit cells are tuned to achieve reliable infilling and combined into higher-order architectures to achieve multiscale composite materials with disparate mechanical properties, including those considered non-printable. Lattice design considerations for leveraging capillary phenomena and demonstrate several methods of patterning polymers in 3D-printed cellular fluidic structures are presented. The concept of tuning the compressive response of an architected composite using a flexible-elastomer as the lattice and a stiff-epoxy as the infill material is illustrated.

36 MATERIALS SCIENCE↗
DOE OSTI2025

SwinCell: a 3D transformer and flow-based framework for improved cell segmentation

Segmentation of three-dimensional (3D) cellular images is fundamental for studying and understanding cell structure and function. However, 3D cellular segmentation is challenging, particularly for dense cells and tissues. This challenge arises mainly from the complex contextual information within 3D images, anisotropic properties, and the sensitivity to internal cellular structures, which often lead to incorrect segmentation. In this work, we introduce SwinCell, a 3D transformer-based framework that leverages Swin-transformer to predict flow and differentiate individual cell instances. We demonstrate SwinCell’s utility in the segmentation of nuclei, colon tissue cells, and densely cultured cells. SwinCell strikes a balance between maintaining detailed local feature recognition and understanding broader contextual information. Through extensive testing with both public and in-house 3D cell imaging datasets, SwinCell shows utility in segmenting dense cells, making it a valuable tool for 3D segmentation in cellular analysis that could expedite research in cell biology and tissue engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Sparse thermal data for cellular automata modeling of grain structure in additive manufacturing

Grain growth in the wake of the melt pool formed during alloy-based additive manufacturing (AM) is complex and multifaceted, depending on parameters governing heat transport, fluid flow, and solidification itself. Cellular automata (CA) models have proven effective in providing computationally efficient and physically sound predictions of grain structure for several AM problems, but their efficiency is tied to the performance of heat transport models. CA models use only a small portion of the problem's temperature data (near the moving melt pool boundary), and much of the CA calculations do not affect the final result due to re-melting of material. Coupling of and communication between heat transport and solidification models, and eliminating operations irrelevant towards final grain structure prediction, will be necessary for using these methods for efficient simulation of large parts. In this work, we introduce a procedure of decoupling the CA from temperature field simulation, using files of relevant temperature data written by the heat transport model. This approach is validated against the standard coupling approach using data obtained through the computational fluid dynamics software OpenFOAM. Negligible differences are seen in grain size, volume, and texture distributions for multilayer simulation of test problems, while the quantity of temperature data for these test problems was reduced by four orders of magnitude (from 100s of GB to 10s of MB) and the code performance sped up by a factor of around 50. Furthermore, variability in microstructure as a function of cell size, substrate, time step, and nucleation parameters is studied, and it is found that cell sizes less than or equal to 1.67 μm and sufficiently small time steps yield Αstatistically equivalent microstructures. Finally, a potential use case for this CA approach—the layer-wise convergence in grain structure starting from extremes in initial grain size—is examined. This approach's ability to simulate expected trends in nucleation and epitaxial grain growth for large regions of microstructure, simulated independently of heat transport models themselves, should prove useful for investigation of various microstructure uncertainties and prediction of part-scale experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Structural basis for aminoacylation of cellular modified tRNALys3 by human lysyl-tRNA synthetase

Abstract The average eukaryotic transfer ribonucleic acid (tRNA) contains 13 post-transcriptional modifications; however, their functional impact is largely unknown. Our understanding of the complex tRNA aminoacylation machinery in metazoans also remains limited. Herein, using a series of high-resolution cryo-electron microscopy (cryo-EM) structures, we provide the mechanistic basis for recognition and aminoacylation of fully modified cellular tRNALys3 by human lysyl-tRNA synthetase (h-LysRS). The tRNALys3 anticodon loop modifications S34 (mcm5s2U) and R37 (ms2t6A) play an integral role in recognition by h-LysRS. Modifications in the T-, variable-, and D-loops of tRNALys3 are critical for ordering the metazoan-specific N-terminal domain of LysRS. The two catalytic steps of tRNALys3 aminoacylation are structurally ordered; docking of the 3′-CCA end in the active site cannot proceed until the lysyl–adenylate intermediate is formed and the pyrophosphate byproduct is released. Association of the h-LysRS–tRNALys3 complex with a multi-tRNA synthetase complex-derived peptide shifts the equilibrium toward the 3′-CCA end “docked” conformation and allosterically increases h-LysRS catalytic efficiency. The insights presented here have broad implications for understanding the role of tRNA modifications in protein synthesis, the human aminoacylation machinery, and the growing catalog of metabolic and neurological diseases linked to it.

Devarkar, Swapnil C. (ORCID:000000029271243X)↗
DOE OSTI2026

Influence of cellular redox reactions on the structure and function of light harvesting and photosystems

Photosynthesis enables the conversion of one of the most abundant and free forms of energy, sunlight, into chemical bonds through the utilization of highly tailored protein complexes. These enzymes work in unison to absorb, convert, and transform light into high-energy electrons which are used for various functions important to metabolism and cellular protection. Over the last ∼50 years, photosynthetic organisms, such as cyanobacteria, have been adapted and engineered to produce valuable compounds like hydrogen and ethylene, among others. Often this is performed by removing native and/or adding in exogenous energy utilization pathways so that light energy is re-directed towards the synthesis of desired compounds. However, the interplay between primary light capture, conversion reactions, and the downstream electron utilization sinks is not fully understood. Further complicating these strategies are the plethora of compensatory mechanisms that facilitate steady electron flow and the maintenance of photosynthesis under dynamic conditions. This manifests as structural and functional plasticity of the photosynthetic machinery, often seen in modulations of oligomeric compositions or changes in protein-protein interactions and coupling with redox enzymes. Understanding these mechanisms is crucial to biotechnology applications because re-engineering electron utilization sinks has profoundly different effects on the light capture and conversion reactions of photosynthesis. Optimization requires a molecular-level understanding of the functional interrelationships between electron sinks and photosynthetic components that influence photosynthetic efficiencies to realize potential improvements in product yields. Here, we aim to highlight how perturbation of reductive reactions is revealing the functional plasticity in key components of the photosynthetic energy transduction pathway.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

In-situ radiation response of additively manufactured modified Inconel 718 alloys

Here in this study, a novel alloy of modified Inconel 718 produced by laser powder bed fusion is studied before and after in-situ Kr irradiation up to 3 dpa at 200 and 450 °C. Before irradiation, the microstructure consists of dislocation cells having a misorientation angle less than 5° and with an average size of ~500 nm. There are also second phase particles of MC type carbides, Laves phase and oxides such as Y-O, Y-(Ti)-Al-O. While the microstructure consists of stacking fault tetrahedra, faulted and perfect loops after irradiation at 200 °C, dislocation loops are the primary defects at 450 °C. With increasing dose, the size of the defects remains similar at 200 °C while it increases at 450 °C. This has been attributed to the existence of vacancy type defects at 200 °C and the different defect transport mechanisms at different temperatures. Moreover, matrix and second phase particle compositions seem to be similar after irradiation. The sink strengths of the structures have been calculated and superior radiation resistance of this alloy has been attributed to the existence of fine cell boundaries stabilized by the second phase particles produced by additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multi-scale microstructural investigation of a laser 3D printed Ni-based superalloy

The heterogeneous microstructure of a laser 3D printed Ni-based superalloy was examined at multiple length scales. The sub-millimeter-sized columnar crystal grains are composed of micron-sized cellular colonies. The crystal grains grow in epitaxy with the substrate under the large temperature gradient and high cooling rate. The cell boundaries, decorated with γ/γ' eutectics, μ-phase precipitates and high density of dislocations, show enrichment of γ' forming elements and low-angle misorientations. Dislocations trapped in the intra-cellular regions are characterized as statistically stored dislocations with no detectable contribution to lattice curvature, and are the results of the interaction between dislocations and γ' precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗