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DOE OSTI2025

Exascale granular microstructure reconstruction in 3D volumes of arbitrary geometries with generative learning

Reconstructing 3D granular microstructures within volumes of arbitrary geometries from limited 2D image data is crucial for predicting the material properties, as well as performances of structural components accounting for material microstructural effects. We present a novel generative learning framework that enables exascale reconstruction of granular microstructures within complex 3D geometric volumes. Building upon existing transfer learning techniques using pre-trained convolutional neural networks (CNN), we introduce several key innovations to overcome the difficulties inherent in arbitrary geometries. Our framework incorporates periodic boundary conditions using circular padding techniques, ensuring continuity and representativeness of the reconstructed microstructures. We also introduce a novel seamless transition reconstruction (STR) method that creates statistically equivalent transition zones to integrate multiple pre-existing 3D microstructure volumes. Based on STR, we propose a cost-effective strategy for reconstructing microstructures within complex geometric volumes, minimizing computational waste. Validation through numerical experiments using kinetic Monte Carlo simulations demonstrates accurate reproduction of grain statistics, including grain size distributions and morphology. A case study involving the reconstruction of a 4-blade propeller microstructure illustrates the method’s capability to efficiently handle complex geometries. In conclusion, the proposed framework significantly reduces computational demands while maintaining high reconstruction quality, paving the way for scalable microstructure reconstruction in materials design and analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗

DOE OSTI2025

Data-Driven Mapping of the Cesium Cadmium Bromide Phase Space Utilizing a Soft-Chemistry Approach

Soft-chemistry techniques provide a versatile approach to synthesizing inorganic materials under mild conditions, enabling access to compositions and structures that are challenging to achieve through traditional thermodynamically driven solid-state methods. However, these solution-based routes often result in phase competition, requiring precise control over reaction conditions to achieve selective product formation. While one-variable-at-a-time (OVAT) approaches have traditionally been used for phase selection, data-driven strategies are emerging as more efficient methods for navigating complex synthetic spaces. Ternary metal halides, such as cesium cadmium bromides (Cs–Cd–Br), are of growing interest due to their potential in wide and ultrawide band gap applications. Unlike the well-studied cesium lead halide phases, the compositional diversity and solution-based synthesis of ternary Cs–Cd–Br phases remain largely unexplored. This study systematically investigates the synthetic phase space of the Cs–Cd–Br system by constructing a data-driven phase map. Using a common set of precursors and a standardized experimental procedure, we successfully synthesize all four known Cs–Cd–Br phases—CsCdBr 3 , Cs 2 CdBr 4 , Cs 3 CdBr 5 , and Cs 7 Cd 3 Br 13 —each exhibiting distinct structures, morphologies, and optical properties. Our findings highlight the potential of soft-chemistry methods for expanding the library of ternary metal halides and provide key insights into the thermodynamic and kinetic factors governing phase formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Understanding the effect of density functional choice and van der Waals treatment on predicting the binding configuration, loading, and stability of amine-grafted metal organic frameworks

Metal organic frameworks (MOFs) are crystalline, three-dimensional structures with high surface areas and tunable porosities. Made from metal nodes connected by organic linkers, the exact properties of a given MOF are determined by node and linker choice. MOFs hold promise for numerous applications, including gas capture and storage. M2(4,4′-dioxidobiphenyl-3,3′-dicarboxylate)—henceforth simply M2(dobpdc), with M = Mg, Mn, Fe, Co, Ni, Cu, or Zn—is regarded as one of the most promising structures for CO2 capture applications. Further modification of the MOF with diamines or tetramines can significantly boost gas species selectivity, a necessity for the ultra-dilute CO2 concentrations in the direct-air capture of CO2. There are countless potential diamines and tetramines, paving the way for a vast number of potential sorbents to be probed for CO2 adsorption properties. The number of amines and their configuration in the MOF pore are key drivers of CO2 adsorption capacity and kinetics, and so a validation of computational prediction of these quantities is required to suitably use computational methods in the discovery and screening of amine-functionalized sorbents. In this work, we study the predictive accuracy of density functional theory and related calculations on amine loading and configuration for one diamine and two tetramines. In particular, we explore the Perdew–Burke–Ernzerhof (PBE) functional and its formulation for solids (PBEsol) with and without the Grimme-D2 and Grimme-D3 pairwise corrections (PBE+D2/3 and PBEsol+D2/3), two revised PBE functionals with the Grimme-D2 and Grimme-D3 pairwise corrections (RPBE+D2/3 and revPBE+D2/3), and the nonlocal van der Waals correlation (vdW-DF2) functional. We also investigate a universal graph deep learning interatomic potential’s (M3GNet) predictive accuracy for loading and configuration. These results allow us to identify a useful screening procedure for configuration prediction that has a coarse component for quick evaluation and a higher accuracy component for detailed analysis. Our general observation is that the neural network-based potential can be used as a high-level and rapid screening tool, whereas PBEsol+D3 gives a completely qualitatively predictive picture across all systems studied, and can thus be used for high accuracy motif predictions. We close by briefly exploring the predictions of relative thermal stability for the different functionals and dispersion corrections.

Chemistry↗

NASA NTRS1984

Subbarrier absorption in a stationary superlattice

The calculation of the interband absorption coefficient was carried out in the classical case, when the frequency of light was assumed to bind two miniband subbarrier states of different bands. The influence of two dimensional Mott excitons on this absorption was studied and a comparison was made with the experiment. All of these considerations were done taking into account the photon wave vector (the phase spatial heterogeneity). The basic traits of the energy spectra of superlattice semiconductors, their kinetic and optical properties, and possible means of electromagnetic wave intensification were examined. By the density matrix method, a theory of electrical and electromagnetic properties of superlattices was suggested.

Arutyunyan, G. M.↗

NASA NTRS1984

Shear deformation plate continua of large double-layered space structures

The energy equivalence to construct equivalent continua for the actual lattice structure is described. An energy equivalent continuum is defined as that which has the same amount of strain and kinetic energies stored in it as the original lattice structure when both are subjected to the same loading conditions. The equivalent continuum is characterized by its strain and kinetic energies from which the constitutive relations and the equations of motion can be derived. A simple method to model large rigid jointed lattices as continuous media with couple stresses is presented. The transition from the discrete system to the continuous medium is achieved by expanding the displacements and the rotations of the nodal points in a Taylor series about a suitable chosen origin. Basic kinematic assumptions are introduced to insure that the assumptions used in deriving the governing equations of the modeled continuum are satisfied. The number of terms retained in the Taylor series expansion will depend upon the properties to be evaluated. This implies that the kind of continuum needed to model from the discrete lattice, before the actual properties are derived was to predetermined.

Hefzy, M. S.↗

NASA NTRS1987

ESR Analysis of Polymer Photo-Oxidation

Electron-spin resonance identifies polymer-degradation reactions and their kinetics. New technique enables derivation of kinetic model of specific chemical reactions involved in degradation of particular polymer. Detailed information provided by new method enables prediction of aging characteristics long before manifestation of macroscopic mechanical properties.

Kim, Soon Sam↗

NASA NTRS1995

Development of a two-equation turbulence model for hypersonic flows: Evaluation of a low Reynolds number correction to the Kappa - epsilon two equation compressible turbulence model - Volume 1

The objective of the current research is the development of an improved k-epsilon two-equation compressible turbulence model for turbulent boundary layer flows experiencing strong viscous-inviscid interactions. The development of an improved model is important in the design of hypersonic vehicles such as the National Aerospace Plane (NASP) and the High Speed Civil Transport (HSCT). Improvements have been made to the low Reynolds number functions in the eddy viscosity and dissipation of solenoidal dissipation of the k-epsilon turbulence mode. These corrections offer easily applicable modifications that may be utilized for more complex geometries. The low Reynolds number corrections are functions of the turbulent Reynolds number and are therefore independent of the coordinate system. The proposed model offers advantages over some current models which are based upon the physical distance from the wall, that modify the constants of the standard model, or that make more corrections than are necessary to the governing equations. The code has been developed to solve the Favre averaged, boundary layer equations for mass, momentum, energy, turbulence kinetic energy, and dissipation of solenoidal dissipation using Keller's box scheme and the Newton spatial marching method. The code has been validated by removing the turbulent terms and comparing the solution with the Blasius solution, and by comparing the turbulent solution with an existing k-epsilon model code using wall function boundary conditions. Excellent agreement is seen between the computed solution and the Blasius solution, and between the two codes. The model has been tested for both subsonic and supersonic flat-plate turbulent boundary layer flow by comparing the computed skin friction with the Van Driest II theory and the experimental data of Weighardt; by comparing the transformed velocity profile with the data of Weighardt, and the Law of the Wall and the Law of the Wake; and by comparing the computed results of an adverse pressure gradient with the experimental data of Fernando and Smits. Good agreement is obtained with the experimental correlations for all flow conditions.

Knight, Doyle D.↗

NASA NTRS1999

Quantitative Species Measurements in Microgravity Combustion Flames using Near-Infrared Diode Lasers

Understanding the physical phenomena controlling the ignition and spread of flames in microgravity has importance for space safety as well as for characterizing dynamical and chemical combustion processes which are normally masked by buoyancy and other gravity-related effects. Unfortunately, combustion is highly complicated by fluid mechanical and chemical kinetic processes, requiring the use of numerical modeling to compare with carefully designed experiments. More sophisticated diagnostic methods are needed to provide the kind of quantitative data necessary to characterize the properties of microgravity combustion as well as provide accurate feedback to improve the predictive capabilities of the models. Diode lasers are a natural choice for use under the severe conditions of low gravity experiments. Reliable, simple solid state operation at low power satisfies the operational restrictions imposed by drop towers, aircraft and space-based studies. Modulation wavelength absorption spectroscopy (WMS) provides a means to make highly sensitive and quantitative measurements of local gas concentration and, in certain cases, temperature. With near-infrared diode lasers, detection of virtually all major combustion species with extremely rapid response time is possible in an inexpensive package. Advancements in near-infrared diode laser fabrication technology and concurrent development of optical fibers for these lasers led to their use in drop towers. Since near-infrared absorption line strengths for overtone and combination vibrational transitions are weaker than the mid-infrared fundamental bands, WMS techniques are applied to increase detection sensitivity and allow measurement of the major combustion gases. In the first microgravity species measurement, Silver et al. mounted a fiber-coupled laser at the top of the NASA 2.2-sec drop tower and piped the light through a single-mode fiber to the drop rig. A fiber splitter divided the light into eight channels that directed the laser beam across a methane or propane diffusion jet flame. The light beams were recaptured by a set of gradient index lenses, coupled back into separate fiber optic lines, and transmitted back to detectors and electronics in the instrument package. In these experiments a 6-mm od fiber cable (containing the nine optical fibers) fell with the drop rig. Using separate detection and demodulation channels, spatial and temporal (up to 20 Hz) maps of water vapor and methane concentrations were obtained at differing heights in the flames. While this apparatus was useful from a demonstration standpoint, several drawbacks needed attention before useful scientific measurements could be obtained. First, eight lines of sight are somewhat insufficient for detailing the spatial profiles of the gas. Second, multiple detection channels operating in parallel are both expensive and present a challenge for accurate calibration. As a result, a newer scanning system was developed in our first contract under this program. The primary characteristic of this system is that it contains a single detection channel and achieves "continuous" spatial resolution by scanning the laser beam across the flame region, then directing this beam onto a single detector. Thus spatial measurements are converted to a temporal series of data. The true spatial resolution is limited only by the beam diameter and width of the sweep. In these experiments the beam is focused to about 1-mm diameter and scans across a region up to 4-cm wide.

Silver, Joel A.↗

NASA NTRS1997

Analysis, Repair, and Management of the Total Ozone Mapping Spectrometer Database

In the ensuing period we were able to demonstrate that the origin of these filamentous patterns resulted from the action of synoptic-scale vortical velocity field on the global-scale background gradient of ozone concentration in the meridional direction. Hyperbolic flow patterns between long-lived atmospheric vortices bring together air parcels from different latitudes, thus creating large gradients along the separatrices leaving the hyperbolic (stagnation) point. This result is further confirmed by the KL analysis of the ozone field in the equatorial region, where the background concentration gradient vanishes. The spectral slope in this region has been found to lie close to -1, in agreement with Batchelor's prediction. Another outcome of this result is that it at least provides indirect evidence about the kinetic energy spectrum of the atmospheric turbulence in the range of scales approximately 200 to 2000 km. Namely, Batchelor's analysis is based on the assumption that the velocity field is large-scale, that is the kinetic energy spectrum decays as O(k(sup -3)) or steeper. Since the scalar spectrum is confirmed, this also supports this form of the kinetic energy spectrum. The study of equatorial regions of TOMS data revealed the efficiency of the KL method is in detecting and separating a wave-like measurement artifact inherently present in the dataset due to the non-perfect correction for cross-track bias. Just two to three eigenfunctions represent the error, which makes it possible to enhance the data by reconstituting it from the data by eliminating the subspace of artifactual eigenfunctions. This represents a highly efficient means for achieving an improved rendering of the data. This has been implemented on the database. A wide range of techniques and algorithms have been developed for the repair and extension of the TOMS database.

Sirovich, Lawrence↗

NASA NTRS1998

The evolution of chromosomal instability in Chinese hamster cells: a changing picture?

PURPOSE: To investigate the kinetics of chromosomal instability induced in clones of Chinese hamster cells following X-irradiation. MATERIALS AND METHODS: X-irradiated clones of GM10115, human-hamster hybrid cells containing a single human chromosome 4 (HC4), have been previously established. These clones were defined as unstable if they contained > or = three subpopulations of cells with unique rearrangements of HC4 as detected by FISH. Stable and unstable clones were analysed by FISH and Giemsa staining at various times post-irradiation. RESULTS: While most of the stable clones continued to show chromosomal stability of HC4 over time, one became marginally unstable at approximately 45 population doublings post-irradiation. Clones exhibiting chromosomal instability had one of several fates. Many of the unstable clones were showed similar levels of instability over time. However, one unstable clone became stable with time in culture, while another became even more unstable over time. Cytogenetic analyses of all clones after Giemsa staining indicated that in some clones the hamster chromosomes were rearranged independent of HC4, demonstrating increased frequencies of chromatid breaks and dicentric chromosomes. The majority of the unstable clones also had higher yields of chromatid gaps. CONCLUSIONS: These data demonstrate the dynamic nature of chromosomal instability as measured by two different cytogenetic assays.

Non-NASA Center↗

NASA NTRS2018

Growth of Bio Sensor Materials by Physical Vapor Transport Method

Recently there is a big thrust on bio-inspired sensors and there has been a large rise in the investment and expectations for nanotechnology to meet these goals. For in situ sensor development materials deposition on substrate is essential part of device development. Physical vapor deposition (PVD), chemical vapor deposition (CVD) and molecular organic vapor deposition methods have developed for growth of semiconductor bulk and thin film growth with some modifications have been used for these materials. Oxides and other elements of the VI group such as sulfides and selenides are key components in the skins of many species. Growth of ordered structures containing these elements have been achieved by using PVD method. This paper describes effect of growth parameters during PVD growth on the quality of materials. Growth kinetics and mechanism will be discussed for the vertical and horizontal growth reactors. Since most of the efficient materials systems are multinary and in many cases non-congruent, PVD provides a pathway to grow materials below melting temperature.

Sachs, David↗

NASA NTRSDate not supplied

Interpretable Tree-Based and Graph Neural Network Approaches for Novel Solid State Electrolyte Design

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes simultaneously possessing high ionic conductivity and good chemical and electrochemical stabilities has proven to be a challenge. I will present our informatics approach to explore the Li compound space for promising solid electrolytes using high-throughput multi-property screening and interpretable machine learning. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds. We use tree-based ensemble learning methods and graph neural network approaches to accurately learn relationships between crystal structures and corresponding thermodynamic and kinetic properties, with interpretability being a major focus. Our models give us the ability to enable rapid discovery and design of novel solid-state battery chemistries.

Materials discovery↗

NASA NTRSDate not supplied

Interpretable ML Approaches for Novel Solid State Electrolyte Design

Shreyas J Honrao↗

NASA NTRSDate not supplied

Machine Learning for Dynamic Test Sensor Placement

There are multiple different algorithms to perform modal test sensor placement optimization: effective independence, residual kinetic energy, iterative Guyan reduction, genetic algorithms, or a brute-force methodology. However, any of these methods may be computationally expensive, especially for structural models with a large number of degrees of freedom. Given the high-cost and the need to optimize the solution, modal sensor placement is a great application for machine learning (ML) algorithms. In this paper, we will apply ML algorithms to determine the optimal sensor locations for simple and complex structures. We will also discuss the benefits and drawbacks of using machine learning over other sensor placement algorithms.

Kelsey Buckles↗

DOE OSTI2025

Additive manufacturing of metal matrix composites

Although Metal matrix composites (MMCs) are superior to most sought-after metallic alloys, their challenging fabricability has limited their widespread use in bulk-form applications. Among the many advanced fabrication techniques, Additive Manufacturing (AM), owing to its unique capabilities to produce near-net shapes, has drawn significant traction in the past two decades, especially for materials that are difficult to process using traditional methods. However, unlike pure metal/alloy systems, MMCs are highly sensitive to the processing conditions prevailing in AM techniques due to factors such as the high melting point of reinforcement particles and the potential for in-situ reactions. Therefore, it may be a while before metal matrix composites are commercially produced via AM. This review will discuss the current state-of-the-art design, fabricability, and performance of various additively manufactured MMCs. A particular focus will be on microstructural evolution and microstructure-property relationships. The most employed AM techniques, such as directed energy deposition, powder bed fusion, binder jetting, sheet lamination, and solid-state friction stir processing, are fundamentally different in terms of thermo-kinetics, forming the perspective for this review. A detailed comparison of microstructural evolution and process parameter optimization, including feedstock preparation methods and the role of machine learning and modeling among the different AM processes, is also presented. Finally, a critical evaluation of emerging AM technologies for MMCs is also provided, highlighting their potential advantages and challenges.

36 - MATERIALS SCIENCE↗

NASA NTRS1991

Modified ICED-ALE method for astrogeophysical plasma flows

The Implicit-Continuous-Eulerian-Difference Mesh-Arbitrary-Lagrangian-Eulerian (ICED-ALE) algorithm of Brackbill and Pracht (1973) is modified for the study of astrophysical plasma flows in which dynamical effects are important. In the present study the general-energy-conservation law is directly applied to the iteration process, with the total (kinetic-, specific-internal-, and magnetic-) energy density being obtained implicitly at the end of the process. An example is computed in which the convergence speed of the latter method is substantially faster than that of the former. The initializing calculation, or explicit phase, in which the electric current density, magnetic diffusion of field, energy augmentation, and zero-order approximation of the flow velocity are given, is described. Consideration is given to the iteration process, or implicit phase, from which the exact Lagrangian solution for energy density, velocity, and a magnetic field is obtained.

Wu, S. T.↗

DOE OSTI2025

Microscale Metal Additive Manufacturing by Solid‐State Impact Bonding of Shaped Thin Films

The deposition of device-grade inorganic materials is one key challenge toward the implementation of additive manufacturing (AM) in microfabrication, and to that end, a broad range of physico-chemical principles has been explored for 3D fabrication with micro- and nanoscale resolution. Yet, for metals, a process that achieves material quality rivalling that of established thin-film deposition methods, and at the same time, has the potential to combine high throughput production with a broad palette of processable materials, is still lacking. Here, the kinetic, solid-state bonding of metal thin films for the additive assembly of high-purity, high-density metals with micrometer-scale precision is introduced. Indirect laser ablation accelerates micrometer-thick gold films to hundreds of meters per second without their heating or ablation. Their subsequent impact on the substrate above a critical velocity forms a permanent, metallic bond in the solid state. Stacked layers are of high density (>99%). By defining thin-film layers with established lithographic methods prior to launch, a variable feature size (2–50 µm), arbitrary shape of bonded layers, and parallel transfer of up to 36 independent film units in a single shot, is demonstrated. Thus, the solid-state kinetic bonding principle as a viable and potentially versatile route for micro-scale AM of metals is established.

3D printing↗