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All sources NASA NTRS DOE OSTI

DOE OSTI2026

Directing Assembly of Mesoscale Multi‐Shell Morphologies of DNA Origami Crystals

Nature builds hierarchically ordered materials, such as seashells, wood, and bones, through spatially and temporally regulated growth. Mimicking such a level of control in synthetic systems remains challenging, particularly in achieving multiscale organizations with prescribed nanoscale arrangements and desired material morphologies. In this study, we introduce a DNA-based self-assembly strategy for constructing diverse multi-shell mesoscale morphologies from nanoscale lattices, enabling prescribed structural, and compositional 3D material patterns. Using DNA origami frames as modular monomers, we direct anisotropic epitaxial growth through addressable DNA frame binding motifs and encapsulate nanoparticles (NPs) in desired 3D patterns. Sequential monomer addition under thermodynamically favorable conditions enables shell growth through heterogeneous nucleation while minimizing unwanted homogeneous nucleation. Here, we demonstrate that DNA-encoded addressability enables epitaxial shell growth along specific lattice directions, yielding crystals with multilayered mesoscale organization, including tube-like (sushi roll) and plate-like (macaron) morphologies. Shell-specific NP configurations and compositions are achieved through addressable and differentiated placement of NPs within each shell, as validated by small-angle x-ray scattering and cross-sectional scanning transmission electron microscopy. We further demonstrate addressable NP release and reveal that shells modulate release kinetics. Together, these findings establish a platform for fabricating DNA origami crystals with programmable mesoscale morphologies, nanoscale structure, composition, and transport properties.

3D patterning↗

DOE OSTI2026

Phosphoserine Charge State Drives Ion Condensation and Spatial Polyamine Presentation in Multirepeat Silaffin

Diatom silaffins direct silica biomineralization through heavily post-translationally modified repeat domains, yet how these modifications reshape the multirepeat conformational ensemble remains unknown. We report all-atom MD simulations of a 195-residue construct spanning repeats R1–R7 of Sil1p from Cylindrotheca fusiformis, carrying the full complement of native PTMs: phosphoserine (pSer), long-chain polyamines (LCPA), dimethyllysine (MLY), and trimethylhydroxylysine phosphate (TPL). We simulated three variants (Native, P1/singly deprotonated phosphate, and P2/doubly deprotonated phosphate) at two NaCl concentrations in triplicate for 500 ns each. All systems disorder from the AlphaFold 3 starting structure. Phosphate charge state, not ionic strength, is the dominant control of ensemble compaction and ion organization. Doubly deprotonated phosphate organizes an extensive Na + condensation shell (∼100 ions, 20% of box Na + ) and a heterogeneous bridging network that integrates both pSer and TPL phosphate groups. The resulting ensemble is compact with LCPA side chains exhibiting above-median solvent accessibility in 84% of simulation frames in P2 at 300 mM. This is higher than any other condition we simulated and indicates that polyamine groups are preferentially surface-presented in the most compact, ion-organized state. A charge-neutralization control confirms that this compact state is a structured intermediate maintained by the bridging network, not a simple collapsed globule. Here, this repeat-scale spatial organization is not captured by single-repeat peptide studies. Understanding the dynamics, mechanism, and spatial organization of PTM-rich silaffin at the repeat scale is a step closer to hierarchical biomimetic materials beyond simple silica morphologies.

Amines↗

DOE OSTI2024

Hierarchically porous and single Zn atom-embedded carbon molecular sieves for H2 separations

Abstract Hierarchically porous materials containing sub-nm ultramicropores with molecular sieving abilities and microcavities with high gas diffusivity may realize energy-efficient membranes for gas separations. However, rationally designing and constructing such pores into large-area membranes enabling efficient H 2 separations remains challenging. Here, we report the synthesis and utilization of hybrid carbon molecular sieve membranes with well-controlled nano- and micro-pores and single zinc atoms and clusters well-dispersed inside the nanopores via the carbonization of supramolecular mixed matrix materials containing amorphous and crystalline zeolitic imidazolate frameworks. Carbonization temperature is used to fine-tune pore sizes, achieving ultrahigh selectivity for H 2 /CO 2 (130), H 2 /CH 4 (2900), H 2 /N 2 (880), and H 2 /C 2 H 6 (7900) with stability against water vapor and physical aging during a continuous 120-h test.

42 ENGINEERING↗

DOE OSTI2026

Phase-field model of freeze casting

Directional solidification of water-based solutions has emerged as a versatile technique for templating hierarchical porous materials. However, the underlying mechanisms of pattern formation remain incompletely understood. In this work, we present a detailed derivation and analysis of a quantitative phase-field model for simulating this nonequilibrium process. The phase-field model extends the thin-interface formulation of dilute binary alloy solidification with antitrapping to incorporate the highly anisotropic energetic and kinetic properties of the partially faceted ice-water interface. This interface is faceted in the basal plane normal to the ⟨0001⟩ directions and atomically rough in other directions within the basal plane. On the basal plane, the model reproduces a linear or nonlinear relationship between the interface growth rate and the kinetic undercooling that can be linked to experimental measurements. In both cases, spontaneous parity breaking of the solidification front is observed when the preferred growth direction is aligned with the temperature gradient. This phenomenon leads to the formation of partially faceted ice lamellae that drift laterally in one of the ⟨0001⟩ directions. Here, we demonstrate that the drifting velocity of the ice lamellae is controlled by the kinetics on the basal plane and converges as the thickness of the diffuse solid-liquid interface decreases. Furthermore, we examine the effect of the form of the kinetic anisotropy, which is chosen here such that the inverse of the kinetic coefficient varies linearly from a finite value in the ⟨0001⟩ directions to zero in all other directions within the basal plane, consistent with the assumption that the interface grows in local thermodynamic equilibrium in this plane. Our results indicate that the drifting velocity of ice lamellae is not affected by the slope of this linear relation, and the radius and undercooling at the tip of an ice lamella converge at relatively small slope values. Consequently, the phase-field simulations remain quantitative with computationally tractable choices of both the interface thickness and the slope assumed in the form of the kinetic anisotropy.

Materials science↗

DOE OSTI2026

Parity breaking at faceted crystal growth fronts during ice templating

Directional solidification of water-based solutions has emerged as a versatile technique to template hierarchical porous materials, but this nonequilibrium process remains incompletely understood. Here, in this study, we use phase-field simulations to shed light on the mechanism that selects the growth direction of the lamellar ice structure that templates those materials. Our results show that this selection can be understood within the general framework of spontaneous parity breaking, yielding quantitative predictions for the tilt angle of lamellae with respect to the thermal axis. The results provide a theoretical basis to interpret a wide range of experimental observations.

Materials science↗

NASA NTRSDate not supplied

Particle-Based Fiber Models of Woven Materials for Earth Entry Thermal Protection

Applications requiring materials with layer-to-layer strength, from basketry to thermal protection systems, use interlaced, three-dimensional woven materials. NASA is developing and deploying woven material heat shields for missions, including Artemis I (3D-MAT for compression pads) and potentially Mars Sample Return - Earth Entry System. These materials are complex, hierarchical and must protect from extreme environments and phenomena, such as deformation, impact and high-enthalpy heating. Woven material performance depends on microstructure, damage and weave geometry. Therefore, fiber-specific models are needed to simulate fiber contacts within the weave hierarchical geometry (fiber to tow to yarn to weave) and the inherent directionality of fibers. Explicit fiber models can simulate how weave microstructure evolution affects thermal and mechanical properties. We parameterize a discrete element bonded particle models (DEM-BPM) of fibers to capture thermal and mechanical behavior within and between fibers, with bonded and contact forces, respectively. We study the proportion of heat transfer and stress via the contact network, fiber bonds and the weave geometry, for example, with respect to yarn warp-weft identity (whether it interlaces weave layers). Our results demonstrate the importance of explicit fiber modeling for connecting microstructure with thermal and mechanical properties.

woven material↗

NASA NTRSDate not supplied

Particle-Based Fiber Models of Woven Materials for Earth Entry Thermal Protection

woven material↗

DOE OSTI2024

A Method for Producing Hierarchical and Statistically Calibrated Predictions of Nuclear Material Properties from Existing Models

Computer vision-based analysis of micrographs of nuclear materials is an emerging technique for property prediction, synthetic route identification, and other material analysis tasks. These analysis tasks play a pivotal role in many material characterization applications such as signature development for treaty verification, process optimization, etc. The backbone in many of the recent computer vision-based techniques is a deep learning model, which takes a fixed-size set of pixels and provides a class prediction for that set of pixels. For example, previous work developed a deep convolutional neural network (CNN) to predict the synthetic route from a 256 px x 256 px patch taken from a larger image of uranium ore concentrates. In this work, we present several methods for first calibrating these models in a manner that they can provide accurate probabilities of their predictions’ veracity, and several methods of combining these probabilities. Overall, the combination of these two steps into a pipeline allows for full-image and even full-sample (where a sample has many images) predictions with associated confidence values. Finally, we show that one can also use the patch predictions and confidence to produce a visualization to map predicted constituents through the image. Results and examples for predicting and mapping uranium ore concentrates’ synthetic process from imagery will be presented.

artificial intelligence↗

DOE OSTI2024

A Multiscale Inelastic Internal State Variable Corrosion Model

We present a corrosion internal state variable (ISV) damage model based upon the integrated computational materials engineering (ICME) hierarchical multiscale paradigm. Structure–property experiments for magnesium alloys were used where the only inputs were the volume fractions of each element of the periodic table. This macroscale ISV corrosion model finds its basis in Horstemeyer’s mechanical damage model, which includes three separate ISVs for damage nucleation, growth, and coalescence, as well as Walton’s inclusion of corrosion, which introduces five new ISVs for pit nucleation, growth, and coalescence, along with general corrosion and intergranular corrosion. While Walton’s corrosion ISVs are phenomenological in nature, herein we develop a multiscale physical basis for the corrosion ISVs. The parameters for the macroscale corrosion ISVs were garnered from the mesoscale Butler–Volmer equations. Pure magnesium with differing amounts of aluminum were used in corrosion tests to exemplify the different pitting, general corrosion, and intergranular corrosion rates, and the macroscale ISV model was calibrated with said data, in which the only inputs to the model are the volume percentages of the elements magnesium and aluminum. Although magnesium alloys were used to motivate and calibrate the model, the model is abstract enough to possibly capture other material systems as well.

Chemistry↗

DOE OSTI2025

Mesocrystal growth through oriented sliding and attachment of nanoplates

Oriented attachment is a critical, yet poorly understood, crystal growth pathway based on the self-assembly of nanocrystals. During oriented attachment, solvent-separated particles align and coalesce through forces that enable precise rotation and translation. While prior studies emphasized intragap forces driving crystallographic alignment, the forces enabling uniform stacking and superlattice formation remain unclear. Here, we demonstrate how macroscopic gibbsite mesocrystals emerge from nanoplates guided into staggered positions by directional sliding. Electron microscopy and X-ray scattering reveal the monoclinic superlattice structure, based on nanoplate stacking with a uniform ≈50° stagger along the gibbsite [010] direction. In situ liquid-cell TEM captures preferential sliding along the gibbsite [010] direction, decelerating with increasing particle overlap. Molecular dynamics simulations reveal that this staggered arrangement corresponds to a global free-energy minimum, rather than full alignment. The simulations also confirm that sliding along the [010] direction is energetically favored and provide insight into the role of interfacial water in achieving long-range ordered assemblies. These insights highlight the energy landscape’s role in oriented attachment, with implications for material synthesis and hierarchical structures in nature.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Post-Modification of Crystalline Peptoid Nanomembranes with Active Nanoparticles for Efficient Photooxidation of a Mustard Gas Simulant

Peptoids (or poly-N-substituted glycines) hold immense potential for assembling into hierarchically structured functional materials via controlled molecular interactions. To create self-assembled materials with tailored functionalities, peptoid sequences are often conjugated with reactive or recognition motifs to enable applications including specific binding, biomimetic catalysis, and fluorescence imaging. However, the direct integration of bulky functional motifs into peptoid sequences can disrupt assembly processes and structural outcomes. Herein, we present a post-modification strategy for functionalizing pre-formed 2D crystalline assemblies. Through introducing clickable active sites, such as azide, alkyne, or thiol groups into a peptoid sequence, site-specific conjugation is achieved post-assembly via efficient “click”-type reactions. This strategy enables the ordered alignment of functional groups and gold nanoparticles (Au NPs) on the surface of 2D peptoid nanomaterials with controlled density, while preserving their high crystallinity and structural integrity. Furthermore, we demonstrated that nanomembranes functionalized with both Au NPs and porphyrins enhance the efficiency and selectivity of the photooxidation of 2-chloroethyl ethyl sulfide, a simulant of sulfur mustard. This innovative strategy lays the groundwork for advancing peptoid-based functional materials across diverse applications, from catalysis to biomedicine.

Chemistry↗

NASA NTRS2002

Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems

This document contains the proceedings of the Training Workshop on Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems held at NASA Langley Research Center, Hampton, Virginia, March 5 - 6, 2002. The workshop was jointly sponsored by Old Dominion University's Center for Advanced Engineering Environments and NASA. Workshop attendees were from NASA, other government agencies, industry, and universities. The objectives of the workshop were to give overviews of the diverse activities in hierarchical approach to material modeling from continuum to atomistics; applications of multiscale modeling to advanced and improved material synthesis; defects, dislocations, and material deformation; fracture and friction; thin-film growth; characterization at nano and micro scales; and, verification and validation of numerical simulations, and to identify their potential for future aerospace systems.

Noor, Ahmed K.↗

NASA NTRS2010

Developing a Logistics Data Process for Support Equipment for NASA Ground Operations

The United States NASA Space Shuttle has long been considered an extremely capable yet relatively expensive rocket. A great part of the roughly US $500 million per launch expense was the support footprint: refurbishment and maintenance of the space shuttle system, together with the long list of resources required to support it, including personnel, tools, facilities, transport and support equipment. NASA determined to make its next rocket system with a smaller logistics footprint, and thereby more cost-effective and quicker turnaround. The logical solution was to adopt a standard Logistics Support Analysis (LSA) process based on GEIA-STD-0007 http://www.logisticsengineers.org/may09pres/GEIASTD0007DEXShortIntro.pdf which is the successor of MIL-STD-1388-2B widely used by U.S., NATO, and other world military services and industries. This approach is unprecedented at NASA: it is the first time a major program of programs, Project Constellation, is factoring logistics and supportability into design at many levels. This paper will focus on one of those levels NASA ground support equipment for the next generation of NASA rockets and on building a Logistics Support Analysis Record (LSAR) for developing and documenting a support solution and inventory of resources for. This LSAR is actually a standards-based database, containing analyses of the time and tools, personnel, facilities and support equipment required to assemble and integrate the stages and umbilicals of a rocket. This paper will cover building this database from scratch: including creating and importing a hierarchical bill of materials (BOM) from legacy data; identifying line-replaceable units (LRUs) of a given piece of equipment; analyzing reliability and maintainability of said LRUs; and therefore making an assessment back to design whether the support solution for a piece of equipment is too much work, i.e., too resource-intensive. If one must replace or inspect an LRU too much, perhaps a modification of the design of the equipment can make such operational effort unnecessary. Finally, this paper addresses processes of tying resources to a timeline of tasks performed in ground operations: this enables various overarching analyses, e.g., a summarization of all resources used for a given piece of equipment. Quality Control of data will also be discussed: importing and exporting data from product teams, including spreadsheets-todatabase or data exchange between databases.

Chakrabarti, Suman↗

NASA NTRS2019

TPSAS-NF1676L-32791-DND

Accelerate adoption of 3D printing in aerospace by investigating issues involving part quality, material compatibility, and hierarchical structures.

John M Gardner↗

NASA NTRSDate not supplied

A Partitioned -Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a “plug and play” software package that allows users to conduct massively multiscale modeling of hierarchical and nonlinear materials. This work extends the scalability and improves the High Performance Computing friendliness of NASMAT by adopting a Partitioned Task-Parallel approach. Interoperability of NASMAT with external software is enhanced through preCICE, a open source library for multiphysics coupling in a partitioned manner. Enhancement through preCICE allows for easy integration of NASMAT to other macro solvers and dissociates the parallelization strategy adopted within NASMAT from the macro solver. The task-parallel framework based on Master-Worker approach is implemented as the parallelization scheme. The scheme accounts for hierarchy of multiple scales (task-dependence) and heterogeneous nature (dynamic load balancing) of computations. The applicability and scalability of the framework will be evaluated by analyzing large scale engineering problems through massively multiscale methods.

NASMAT↗

DOE OSTI2026

Structural and Mechanical Analysis of Individual Mineralized Collagen Fibrils Using In Situ Transmission Electron Microscopy

Bone serves as an example of nature’s architectured material with its characteristic blend of strength and toughness, all at a lightweight design. Given the hierarchical nature of these materials, it is essential to understand the governing mechanisms and organization of their constituents across length scales for bioinspired structural design. Despite recent advances in transmission electron microscopy (TEM) that have allowed us to witness the hierarchical arrangement of bone at micro-down to the nanoscale, we are still missing the details about the structural organization and mechanical properties of the main building blocks of bone─mineralized collagen fibrils (MCFs). Here, we present a method to extract individual MCFs from nature’s model material, mineralized turkey leg tendon, using a dropcasting procedure. By isolating the MCFs onto TEM supporting grids, we visualized the arrangement of organic and mineral phases within individual MCFs at the nanoscale. Using a four-dimensional scanning transmission electron microscopy (4D-STEM) approach, the orientation of individual mineral crystals within the MCFs was examined. Furthermore, we conducted in situ tensile experiments, revealing exceptional tensile strains of at least 8%, demonstrating the intricate relationship between structural organization and the mechanical behavior of MCFs. These insights into the ultrastructure of mineralized tissue building blocks, as well as the proposed sample-extraction method compatible with in situ mechanical testing, provide a strong basis for research into nature-inspired material design.

4D-STEM↗

DOE OSTI2025

Hierarchical Gaussian process-based Bayesian optimization for materials discovery in high entropy alloy spaces

Bayesian optimization (BO) is a powerful and data-efficient method for iterative materials discovery and design, particularly valuable when prior knowledge is limited, underlying functional relationships are complex or unknown, and the cost of querying the materials space is significant. Traditional BO methodologies typically utilize conventional Gaussian Processes (cGPs) to model the relationships between material inputs and properties, as well as correlations within the input space. However, cGP-BO approaches often fall short in multi-objective optimization scenarios, where they are unable to fully exploit correlations between distinct material properties. Leveraging these correlations can significantly enhance the discovery process, as information about one property can inform and improve predictions about others. Here, this study addresses this limitation by employing advanced kernel structures to capture and model multi-dimensional property correlations through multi-task (MTGPs) or deep Gaussian Processes (DGPs), thus accelerating the discovery process. We demonstrate the effectiveness of MTGP-BO and DGP-BO in rapidly and robustly solving complex materials design challenges that occur within the context of complex multi-objective optimization over FCC FeCrNiCoCu high entropy alloy (HEA) spaces, where traditional cGP-BO approaches fail. Furthermore, we highlight how the differential costs associated with querying various material properties can be strategically leveraged to make the materials discovery process more cost-efficient.

36 MATERIALS SCIENCE↗

NASA NTRS2013

Fibrillar Adhesive for Climbing Robots

A climbing robot needs to use its adhesive patches over and over again as it scales a slope. Replacing the adhesive at each step is generally impractical. If the adhesive or attachment mechanism cannot be used repeatedly, then the robot must carry an extra load of this adhesive to apply a fresh layer with each move. Common failure modes include tearing, contamination by dirt, plastic deformation of fibers, and damage from loading/ unloading. A gecko-like fibrillar adhesive has been developed that has been shown useful for climbing robots, and may later prove useful for grasping, anchoring, and medical applications. The material consists of a hierarchical fibrillar structure that currently contains two levels, but may be extended to three or four levels in continuing work. The contacting level has tens of thousands of microscopic fibers made from a rubberlike material that bend over and create intimate contact with a surface to achieve maximum van der Waals forces. By maximizing the real area of contact that these fibers make and minimizing the bending energy necessary to achieve that contact, the net amount of adhesion has been improved dramatically.

Pamess, Aaron↗