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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 1,063 records · Page 59

Tuning the properties of metal–organic framework nodes as supports of single-site iridium catalysts: node modification by atomic layer deposition of aluminium

The metal–organic framework NU-1000, with Zr 6 -oxo, hydroxo, and aqua nodes, was modified by incorporation of hydroxylated Al( iii ) ions by ALD-like chemistry with [Al(CH 3 ) 2 (iso-propoxide)] 2 followed by steam (ALD = atomic layer deposition). Al ions were installed to the extent of approximately 7 per node. Single-site iridium diethylene complexes were anchored to the nodes of the modified and unmodified MOFs by reaction with Ir(C 2 H 4 ) 2 (acac) (acac = acetylacetonate) and converted to Ir(CO) 2 complexes by treatment with CO. Infrared spectra of these supported complexes show that incorporation of Al weakened the electron donor tendency of the MOF. Correspondingly, the catalytic activity of the initial supported iridium complexes for ethylene hydrogenation increased, as did the selectivity for ethylene dimerization. The results of density functional theory calculations with a simplified model of the nodes incorporating Al( iii ) ions are in qualitative agreement with some catalyst performance data.

catalysis (heterogeneous), materials and chemistry↗

Directing Nanoparticle Organization in Response to Diverse Chemical Inputs

Signaling cascades are crucial for transducing stimuli in biological systems, enabling multiple stimuli to regulate a downstream target with precisely controlled timing and amplifying signals through a series of intermediary reactions. Developing a robust signaling system with such capabilities would be pivotal for programming complex behaviors in synthetic DNA-based molecular devices. However, although “software” such as nucleic acid circuits could potentially be harnessed to relay signals to DNA-based nanostructure hardware, such explorations have been limited. Here, in this study, we develop a platform for transducing a variety of stimuli via messenger-mediated reactions to regulate the release and reloading of gold nanoparticles (AuNPs) in a 3D DNA framework. In the first step, an in vitro transcription circuit is engineered to sense and amplify chemical stimuli, including arbitrary DNA sequences and proteins, producing RNA. In the second step, the RNA releases the DNA-coated AuNPs from the DNA framework via a strand displacement reaction. AuNP reloading is controlled by a separate step driven by degradation of the RNA. Our platform holds promise for applications requiring dynamic multiagent control over DNA-based devices, offering a versatile tool for advanced molecular device engineering.

36 MATERIALS SCIENCE↗

Defect Thermodynamics and Transport Properties of Proton Conducting Oxide BaZr 1–x Y x O 3–δ (x ≤ 0.1) Guided by Density Functional Theory Modeling

Density functional theory-based thermodynamic modeling was performed to determine the effect of humidity and H 2 /O 2 gas pressure on the defect chemistry and transport properties of proton conducting oxide BaZr 1-x Y x O 3-δ (x ≤ 0.1) in the temperature range of 800–1200K, relevant for solid oxide fuel/electrolysis cell applications. The first-principles charge defect analysis was carried out to obtain the defect energetic ensembles as a function of Fermi level as well as the dependence of the hydration and oxidation reaction energies on complex defect-dopant configurations. It is shown that oxygen vacancies introduced to compensate for the extra Ba vacancies may cause a slight increase in the concentration of hydroxyl and proton species upon hydration of Ba deficient BaZr 1-x Y x O 3-δ , while the overall proton diffusivity is predicted to decrease with increased proton hopping barriers upon trapping near the Ba vacancies. The developed defect model is further demonstrated to be able to describe the bulk defect chemistry and transport properties of BaZr 0.9 Y 0.1 O 3-δ under the solid oxide cell operating conditions. Finally, the theoretical framework developed in this work further allows the inclusion of configurational, energetic and electronic characteristics of the defects that can be used as a complementary tool to experimental measurements for testing various mechanistic pathways or to provide essential mechanistic data.

36 MATERIALS SCIENCE↗

Hydrothermal synthesis and structural characterization of several complex rare earth tantalates: Ln 2 TaO 5 (OH) (Ln = La, Pr) and Ln 3 Ta 2 O 9 (OH) (Ln = Pr, Nd)

Reactions are reported of early rare earth oxides, RE 2 O 3 (RE = La, Pr, Nd) with Ta 2 O 5 under hydrothermal conditions (650 °C, 1.5 kbar) in concentrated aqueous hydroxide (20–30 M KOH) as a mineralizer. Under various stoichiometries several members of two new structure types were isolated, Ln 2 TaO 5 (OH) (Ln = La, Pr) and Ln 3 Ta 2 O 9 (OH) (Ln = Pr, Nd). The analogous niobate La 2 NbO 5 (OH) was also obtained. Both structure types were characterized by single crystal X-ray diffraction and contain pentavalent tantalatum oxide octahedra and complex rare earth oxide frameworks. The Ln 2 TaO 5 (OH) structure type contains Ln–O 8 and Ln–O 9 building blocks and TaO 6 octahedra in a 3-D framework. It contains a 3-D rare earth oxide framework formed by from zig-zag chains of rare earth oxides linking sheets of rare earth oxides. The tantalates form edge-shared Ta 2 O 10 dimers occupying gaps in the rare earth oxide frameworks. The structure of Ln 3 Ta 2 O 9 (OH) contains two types of 2-D rare earth oxide slabs built of seven and eight coordinate rare earth metals. The tantalate units form 2-D slabs through a multiple corner-sharing scheme of TaO 6 octahedra. The Ln 3 Ta 2 O 9 (OH) structure type has an interesting close structural relationship to the previously reported rare earth titanate La 5 Ti 4 O 15 (OH), which is discussed. The presence of hydroxide in the lattice is confirmed by IR spectroscopy and the H atom locations are assigned unambiguously using bond valence sums.

36 MATERIALS SCIENCE↗

Attentional Ptycho-Tomography (APT) for three-dimensional nanoscale X-ray imaging with minimal data acquisition and computation time

Abstract Noninvasive X-ray imaging of nanoscale three-dimensional objects, such as integrated circuits (ICs), generally requires two types of scanning: ptychographic, which is translational and returns estimates of the complex electromagnetic field through the IC; combined with a tomographic scan, which collects these complex field projections from multiple angles. Here, we present Attentional Ptycho-Tomography (APT), an approach to drastically reduce the amount of angular scanning, and thus the total acquisition time. APT is machine learning-based, utilizing axial self-Attention for Ptycho-Tomographic reconstruction. APT is trained to obtain accurate reconstructions of the ICs, despite the incompleteness of the measurements. The training process includes regularizing priors in the form of typical patterns found in IC interiors, and the physics of X-ray propagation through the IC. We show that APT with ×12 reduced angles achieves fidelity comparable to the gold standard Simultaneous Algebraic Reconstruction Technique (SART) with the original set of angles. When using the same set of reduced angles, then APT also outperforms Filtered Back Projection (FBP), Simultaneous Iterative Reconstruction Technique (SIRT) and SART. The time needed to compute the reconstruction is also reduced, because the trained neural network is a forward operation, unlike the iterative nature of these alternatives. Our experiments show that, without loss in quality, for a 4.48 × 93.2 × 3.92 µm 3 IC (≃6 × 10 8 voxels), APT reduces the total data acquisition and computation time from 67.96 h to 38 min. We expect our physics-assisted and attention-utilizing machine learning framework to be applicable to other branches of nanoscale imaging, including materials science and biological imaging.

47 OTHER INSTRUMENTATION↗

Applications of fuzzy logic and best-worst method for tritium sensor selection

Accurate assessment of tritium as a fuel source is critical in fusion reactions, necessitating effective sensor evaluation methods. This study investigates a multi-criteria decision-making framework for selecting tritium sensors, integrating fuzzy logic to enhance decision quality. Initial attempts at applying fuzzy logic were found to be too elementary and failed to capture the complexity of multi-criteria selection; this prompted a refined approach that incorporated expert insights and advanced ranking techniques for sensor evaluation. The research used a two-stage methodology. In the first stage, important criteria and sub-criteria for sensor performance were identified and defined. These criteria were then weighted and scored using a fuzzy best-worst method, drawing upon expert opinions to ensure relevance and validity. The second stage involved interpreting information about varying sensors to rank them based on their overall criteria scores, encouraging the selection of the most suitable options. The result of the study is a proposed method for effective sensor selection in fusion reactors, which in turn will significantly improve the reliability of tritium monitoring in fusion applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A layered 2D computational framework: Theory and applications to nuclear fuel behavior

Nuclear fuel performance computer codes have been developed over the last 50 years to analyze fuel behavior under various operating conditions. Traditionally, these codes used quasi-two-dimensional (also commonly known as 1.5D) representations of the fuel rod, which model the rod using a set of one-dimensional axisymmetric models that represent the behavior at specific axial positions on the rod. Modern fuel performance codes have the ability to investigate full three-dimensional (3D) effects and couple to other physics-based codes for true multiphysics simulations. However, with increasing complexity comes increasing computational costs. Many phenomena of interest involve azimuthally-varying behavior that cannot be represented using the aforementioned quasi-two-dimensional approach, but do not require the use of a full 3D model. To efficiently address these problems, there is a need for a computational framework that provides a compromise between the quasi-two-dimensional and full 3D models. In this paper, we present a new quasi-three-dimensional approach that represents the fuel as a set of 2D planar models that represent the behavior of the fuel cross-section at various axial positions. Presented here are the theory behind the methodology, test cases to illustrate proper implementation, and practical applications of its use in the BISON fuel performance code for a variety of cases in nuclear fuel analysis, such as fuel fracture, axial fuel relocation, and cladding distension and oxidation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Asymmetric Cracking in Mar-M247 Alloy Builds During Electron Beam Powder Bed Fusion Additive Manufacturing

In the electron beam powder bed fusion (EB-PBF) process, a substantial number of high-gamma prime Ni-based superalloys are considered as non-printable due to a high propensity to form cracks. In this research, we focused on computational modeling framework to predict solidification-related cracking phenomena in EB-PBF processes. The cracking analysis was performed on cylindrical overhang structures where the cracks are observed only on one side of the part. Comprehensive microstructural characterization correlated the cracking tendency to low-melting point liquid-film formation along columnar grain boundaries with high misorientation angles due to partitioning of alloying elements. Uncoupled numerical thermal and mechanical models were used to rationalize the relationship between process parameters, build geometry, and cracking. The simulations showed asymmetric temperature distributions and associated asymmetric tensile thermal stresses over a cross section due to differences in section modulus and periodic changes in beam scanning directions. Here, the results provide a potential pathway based on spatially varying beam scanning strategies to reduce the cracking tendency during additive manufacturing of complex geometries on the overhang structure in high-gamma prime nickel-based superalloys.

36 MATERIALS SCIENCE↗

Mesoscopic finite-size effects of unconventional electron transport in PdCoO 2

A wide range of unconventional transport phenomena has recently been observed in single-crystal delafossite metals. Here, we present a theoretical framework to elucidate electron transport using a combination of first-principles calculations and numerical modeling of the anisotropic Boltzmann transport equation. Using PdCoO 2 as a model system, we study different microscopic electron and phonon scattering mechanisms and establish the mean free path hierarchy of quasiparticles at different temperatures. We treat the anisotropic Fermi surface explicitly to numerically obtain experimentally-accessible transport observables, which bridge between the “diffusive,” “ballistic,” and “hydrodynamic” transport regime limits. Further, we illustrate that the distinction between the “quasiballistic” and “quasihydrodynamic” regimes is challenging and often needs to be quantitative in nature. From first-principles calculations, we populate the resulting transport regime plots and demonstrate how the Fermi surface orientation adds complexity to the observed transport signatures in micrometer-scale devices. Our work provides key insights into microscopic interaction mechanisms on open hexagonal Fermi surfaces and establishes their connection to the macroscopic electron transport in finite-size channels.

36 MATERIALS SCIENCE↗

Data Assimilation - Advances and Applications

This presentation provides an overview of data assimilation (model calibration) for complex computer experiments. Calibration refers to the process of probabilistically constraining uncertain physics/engineering model inputs to be consistent with observed experimental data. An initial probability distribution for these parameters is updated using the experimental information. Utilization of surrogate models and empirical adjustment for model form error in code calibration form the basis for the statistical methodology considered. The role of probabilistic code calibration in supporting code validation is discussed. Incorporation of model form uncertainty in rigorous uncertainty quantification (UQ) analyses is also addressed. Design criteria used within a batch sequential design algorithm are introduced for efficiently achieving predictive maturity and improved code calibration. Predictive maturity refers to obtaining stable predictive inference with calibrated computer codes. These approaches allow for augmentation of initial experiment designs for collecting new physical data. A standard framework for data assimilation is presented and techniques for updating the posterior distribution of the state variables based on particle filtering and the ensemble Kalman filter are introduced.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Extended Finite Element Based Approach in Additive Manufacturing Modeling for Optimizing Highly Complex Manifold in Protonic Ceramic Electrochemical Cells

The objective of this project is to develop a novel numerical approach based on the extended finite element method (XFEM) for modeling moving boundaries of material deposited in additive manufacturing (AM) process with improved accuracy and reduced computational cost. One of the major challenges in simulating AM processes is that the boundaries of the computational domain need to change as material is deposited. Previous approaches have achieved this by activating new finite elements, but this requires a high level of mesh refinement to capture small movement of the boundary. XFEM allows the solution boundary to move independently of the mesh, permitting smooth representation of the evolution of the boundary as material is deposited. As a result, this new method will significantly improve the simulation accuracy while reducing the computational cost compared with existing approaches. Furthermore, this project will bring significant improvements for the design and AM process optimization in an iterative fashion among numerical simuation, parameter optimization, and experimental validation. Specifically, this project will support the protonic ceramic electrochemical cells (PCEC) stack development at INL by providing insights into the density, residual stress, thermal and mechanical properties of the PCEC manifold and interconnect, which is critical in enhancing the system lifetime and reducing the overall cost. Upon the success of proposed development and validation of the proposed approach, simulation will be applied to determine an optimal set of AM process parameters for the PCEC manifold production. This project will consolidate Idaho National Laboratory (INL)’s simulation capabilities provided by the MOOSE framework and the Valhalla AM simulation application, with encouraging expansion to emerging PCEC applications and AM technologies at INL and beyond.

97 MATHEMATICS AND COMPUTING↗

Enhancing Pore-Environment Complexity Using a Trapezoidal Linker: Toward Stepwise Assembly of Multivariate Quinary Metal–Organic Frameworks

Multicomponent metal–organic frameworks (MOFs) promise the precise placement of synergistic functional groups with atomic-level precision, capable of promoting fascinating developments in basic sciences and applications. However, the complexity of multicomponent systems poses a challenge to their structural design and synthesis. Herein, we show that linkers of low symmetry can bring new opportunities to the construction of multicomponent MOFs. A carbazole-tetracarboxylate linker of C s point group symmetry was designed and combined with an 8-connected Zr 6 cluster to generate a low-symmetry MOF, PCN-609. PCN-609 contains coordinatively unsaturated Zr sites arranged within a lattice with three crystallographically distinct pockets, which can accommodate linear linkers of different lengths. Sequential linker installation was carried out to postsynthetically insert three linear linkers into PCN-609, giving rise to a quinary MOF. At last, functionalization of each linker from the quinary MOF system creates multivariate pore environments with unprecedented complexity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cross-domain digital twin architecture for predictive maintenance via machine learning and Large Language Models

This research introduces a comprehensive framework for creating and deploying a digital twin platform for continuous monitoring and predictive maintenance within industrial settings. Through utilizing advanced technologies, including Unreal Engine 5, Unity 3D, the Message Queue Telemetry Transport protocol, Random Forest machine learning algorithms, and Large Language Models (LLMs), we establish a platform that digitally reproduces physical equipment and translates digital controls into real-world actions. This facilitates preventive maintenance approaches and improves operational effectiveness. The digital twin platform gathers sensor data from operational equipment, analyzes it using machine learning, and delivers practical insights to prevent potential malfunctions and enhance equipment performance. Furthermore, the incorporation of a web portal enables efficient monitoring and access to historical data, educational materials, and equipment status information. Preliminary findings indicate that digital twins can transform industrial equipment management and maintenance methodologies.

97 MATHEMATICS AND COMPUTING↗

Polarization screening-induced magnetic phase gradients at complex oxide interfaces

Thin-film oxide heterostructures show great potential for use in spintronic memories, where electronic charge and spin are coupled to transport information. Here we use a La 0.7 Sr 0.3 MnO 3 (LSMO)/PbZr 0.2 Ti 0.8 O 3 (PZT) model system to explore how local variations in electronic and magnetic phases mediate this coupling. We present direct, local measurements of valence, ferroelectric polarization and magnetization, from which we map the phases at the LSMO/PZT interface. We combine these experimental results with electronic structure calculations to elucidate the microscopic interactions governing the interfacial response of this system. We observe a magnetic asymmetry at the LSMO/PZT interface that depends on the local PZT polarization and gives rise to gradients in local magnetic moments; this is associated with a metal–insulator transition at the interface, which results in significantly different charge-transfer screening lengths. This work establishes a framework to understand the fundamental asymmetries of magnetoelectric coupling in oxide heterostructures.

36 MATERIALS SCIENCE↗

Establishing mesh topology in multi-material cells: enabling technology for robust and accurate multi-material simulations

Real world problems are typically multi-material, combining materials such as gases, liquids and solids that have very different properties. The material interfaces may be fixed in time or can be a part of the solution, as in fluid-structure interactions or air-water dynamics, and therefore move and change shape. In such problems the computational mesh may be non-conformal to interfaces due to complexity of these interfaces, presence of small fractions of materials, or because the mesh does not move with the flow, as in the arbitrary Lagrangian–Eulerian (ALE) methods. In order to solve problems of interest on such meshes, interface reconstruction methods are usually used to recover an approximation of material regions within the cells. For a cell intersecting multiple material regions, these approximations of contained subregions can be considered as single-material subcells in a local mesh that we call a minimesh. In this paper, we discuss some of the requirements that discretization methods have on topological information in the resulting hierarchical meshes and present an approach that allows incorporating the buildup of sufficiently detailed topology into the nested dissections based PLIC-type reconstruction algorithms (e.g. Volume-of-Fluid, Moment-of-Fluid) in an efficient and robust manner. Specifically, we describe the X-MOF interface reconstruction algorithm in 2D, which extends the Moment-Of-Fluid (MOF) method to include the topology of minimeshes created inside of multi-material cells and parent-child relations between corresponding mesh entities on different hierarchy levels. X-MOF retains the property of being local to a cell and not requiring external communication, which makes it suitable for massively parallel applications. Here, we demonstrate some scaling results for the X-MOF implementation in Tangram, a modern interface reconstruction framework for exascale computing.

97 MATHEMATICS AND COMPUTING↗

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↗

Interaction of Water with Carbon Fiber Reinforced Polymer Laminates under Dynamic Loading Conditions

With the aim of simulating the real conditions during the navigation, in this framework, impact tests were performed by loading CFRP laminates immersed in the water from the front side. The specimens, made by vinyl ester matrix because of the lower moisture absorption compared to the other epoxy systems, are in the presence of the water to accurately simulate the incidental impact on the hull of the vessel, immersed or partially immersed, during the navigation. It can be caused by the ice in the Arctic Ocean, by a projectile due to a terroristic attack or by debris from an explosion. The results are compared with the ones obtained by loading the laminates in pure traditional impact tests in the air. The influence of the clamping device has been tested too. The exciting results obtained on carbon fiber laminates in the air (pure traditional impact tests), water-backed (with water on the back side) and waterfront (water only on the front side) conditions at room temperature are here reported and compared. They highlighted the critical role played by the complex fluid–structure interaction.

36 MATERIALS SCIENCE↗

A Verification Framework for Runtime Assurance of Autonomous UAS

Runtime Assurance (RTA) is a design-time architecture for safety-critical systems where an internal monitor acts upon detecting a violation of a property. The simplex architecture is an instance of RTA, where the action taken is to hand control of the overall system to a trusted controller when an untrusted one violates a safety property. Simplex RTA is emerging as a method for allowing AI/ML and other unverified software to be integrated into safety-critical applications like aircraft. To this end, the American Society for Testing and Materials (ASTM) and NASA have each published guidelines on the use of RTA in such systems. In the simplex RTA framework, a system has an advanced controller (AC) and a reversionary controller (RC). The system is allowed to operate with the AC until a runtime monitor detects that some property has been violated and then the RC takes over. Assuming that the sample rate of the monitor will detect improper functioning with enough time for the RC to correct the impending problem, and that the RC is trusted, the system will operate as intended. This use of the simplex RTA framework can allow for the integration of untrusted, but possibly more performant, controllers in a safe way. This paper presents a formalization of a simplex RTA framework in the Prototype Verification System (PVS) theorem prover using an embedding of differential dynamic logic (DDL) called Plaidypvs. A novel feature of this framework is that it can be instantiated at different levels of abstraction. This feature allows for the formal verification of a system with an untrusted black box component, such as an AI/ML controller. This paper does not address the many difficulties in deploying RTA in an industrial-level system. Instead, the focus is on the formal verification of the simplex RTA framework in the language of hybrid programs. Hybrid programs are programs that include both discrete and continuous dynamics and can be used to model complex cyber-physical systems. Plaidypvs is a tool that enables formalization of hybrid programs in the PVS theorem prover. Plaidypvs enables the verification of the general simplex RTA framework and then, by specializing some components of the hybrid program, verifying instances of the framework while treating the untrusted component as a black box. A selection of Unmanned Aircraft Systems (UAS) operations are shown as instances of the general RTA framework in PVS. This offers the benefit of design time verification of relevant safety properties to the system, and it also gives requirements on the sample rate of sensors that determine the time interval in which the ‘switch’ property of the RTA framework is checked.

PVS↗