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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Tale of Two Trimers from Two Different Worlds: A COF-Inspired Synthetic Strategy for Pore-Space Partitioning of MOFs

The introduction of a symmetry- and size-matching pore-partitioning agent in the form of either a molecular ligand, such as 2,4,6-tri(4-pyridinyl)-1,3,5-triazine ( tpt ), or a metal-complex cluster, into the hexagonal channels of MIL-88/MOF-235-type (the acs net) to create pacs -type (partitioned acs ) crystalline porous materials is an effective strategy to develop high-performance gas adsorbents. We have developed here an integrated COF–MOF coassembly strategy as a new method for pore-space partitioning through the coassembly of [(M 3 (OH) 1- x (O) x (COO) 6 ] MOF-type and [B 3 O 3 (py) 3 ] COF-type trimers. With this strategy, the coordination-driven assembly of the acs framework occurred concurrently and synergistically with the COF-1-type condensation of pyridine-4-boronic acid into a C 3 -symmetric trimeric boroxine molecule. Furthermore, the resulting boroxine-based pacs materials exhibited dramatically enhanced gas-sorption properties as compared to nonpartitioned acs -type materials and are among the most efficient NH 3 -sorption materials

36 MATERIALS SCIENCE↗
DOE OSTI2019

Integrated Simulation Framework for Additively Manufactured Ti-6Al-4V: Melt Pool Dynamics, Microstructure, Solid-State Phase Transformation, and Microelastic Response

In this work, to accelerate the establishment of fundamental understanding of the additive manufacturing (AM) process and its influence on microstructural evolution and related properties, we develop a multiphysics and multiscale modeling framework that integrates: (1) a high-fidelity powder-scale three-dimensional simulation of transient heat transfer and melt flow dynamics, (2) cellular automaton simulation of solidification grain structure and texture, (3) phase-field modeling of precipitation and dissolution of second-phase precipitate during repeated thermal cycles, and (4) microstructure-based micro- and mesoscopic elastic response calculation. Using Ti-6Al-4V as a model system, we demonstrate the application of the integrated framework to simulate complex microstructure evolution during a single-track laser powder bed fusion process and the associated mechanical response. Our modeling framework successfully captures the solidification β grain structure as a function of laser power and scanning speed, α precipitation upon subsequent cooling with different rates, and elastic response of the resulting (α + β) two-phase microstructure. The key features of solidification and second-phase precipitate microstructures, and their dependence on processing parameters, agree well with existing experimental observations. Finally, the established modeling framework is generally applicable to other metallic materials fabricated by AM.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Magnetic and electronic properties unveil polaron formation in Eu$$_5$$In$$_2$$Sb$$_6$$

Abstract The intermetallic compound Eu $$_5$$ 5 In $$_2$$ 2 Sb $$_6$$ 6 , an antiferromagnetic material with nonsymmorphic crystalline structure, is investigated by magnetic, electronic transport and specific heat measurements. Being a Zintl phase, insulating behavior is expected. Our thermodynamic and magnetotransport measurements along different crystallographic directions strongly indicate polaron formation well above the magnetic ordering temperatures. Pronounced anisotropies of the magnetic and transport properties even above the magnetic ordering temperature are observed despite the Eu $$^{2+}$$ 2 + configuration which testify to complex and competing magnetic interactions between these ions and give rise to intricate phase diagrams discussed in detail. Our results provide a comprehensive framework for further detailed study of this multifaceted compound with possible nontrivial topology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Long-range correlation energy calculated from coupled atomic response functions

An accurate determination of the electron correlation energy is an essential prerequisite for describing the structure, stability, and function in a wide variety of systems. Therefore, the development of efficient approaches for the calculation of the correlation energy (and hence the dispersion energy as well) is essential and such methods can be coupled with many density-functional approximations, local methods for the electron correlation energy, and even interatomic force fields. In this work, we build upon the previously developed many-body dispersion (MBD) framework, which is intimately linked to the random-phase approximation for the correlation energy. We separate the correlation energy into short-range contributions that are modeled by semi-local functionals and long-range contributions that are calculated by mapping the complex all-electron problem onto a set of atomic response functions coupled in the dipole approximation. We propose an effective range-separation of the coupling between the atomic response functions that extends the already broad applicability of the MBD method to non-metallic materials with highly anisotropic responses, such as layered nanostructures. Application to a variety of high-quality benchmark datasets illustrates the accuracy and applicability of the improved MBD approach, which offers the prospect of first-principles modeling of large structurally complex systems with an accurate description of the long-range correlation energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Enabling accurate chemical modeling of shocked energetic materials using a machine learning interatomic potential

Understanding the complex chemistry of organic materials under dynamic compression is important for many applications, but it is challenging due to the large number of reactions occurring at various time scales. Here, in this study, we develop a machine learning potential based on Chebyshev polynomials to study the insensitive energetic material 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) under detonation. We discuss a strategy for constructing diverse training data needed to capture the complex chemistry of TATB. Our potential demonstrates strong transferability across a wide range of thermodynamic conditions and other explosives, enabling accurate and reliable chemical modeling of organic materials under extreme conditions. The efficiency of our approach allows for simulations over several nanoseconds and for large system sizes, providing detailed insights into the chemistry of shocked TATB. The model accurately reproduces experimental Hugoniot equation of state data, and our simulations reveal the rapid formation of nitrogen-rich carbon clusters following shock. The methods and datasets developed here offer a robust framework for accurate chemical modeling of other shocked organic energetic materials.

Chemistry↗
DOE OSTI2023

A probabilistic-phase field model for the fracture of brittle materials

Abstract We develop a computational method to determine the failure probability of brittle materials under general mechanical loading conditions. The method is a combination of two parts: (1) numerical simulations of materials with multiple cracks using phase field theory, where the complete fracture process is viewed as ‘damage percolation’ along critical paths or clusters of cracks, rather than the traditional weak-link failure mechanism of Weibull, and (2) an extension of the Batdorf statistical theory of fracture to finite domains, where it is implemented within the finite element framework. The results of phase-field simulations at the ‘percolation threshold’ are used as failure data in the Batdorf theory to determine the overall probability of failure. The input to this approach is the size distribution of cracks in a pristine material. An example is shown, where alumina samples that were previously tested by Abe and coworkers (Abeet al2003J. Am. Ceram. Soc.861019–21) in four-point loading are compared to the results of our numerical simulations. The approach developed here has the advantage of being extendable to more complex thermomechanical loading.

Materials Science↗
DOE OSTI2016

Adaptive Visual Sort and Summary of Micrographic Images of Nanoparticles for Forensic Analysis

Forensic analysis of nanoparticles is often conducted through the collection and identifi- cation of electron microscopy images to determine the origin of suspected nuclear material. Each image is carefully studied by experts for classification of materials based on texture, shape, and size. Manually inspecting large image datasets takes enormous amounts of time. However, automatic classification of large image datasets is a challenging problem due to the complexity involved in choosing image features, the lack of training data available for effective machine learning methods, and the availability of user interfaces to parse through images. Therefore, a significant need exists for automated and semi-automated methods to help analysts perform accurate image classification in large image datasets. We present INStINCt, our Intelligent Signature Canvas, as a framework for quickly organizing image data in a web based canvas framework. Images are partitioned using small sets of example images, chosen by users, and presented in an optimal layout based on features derived from convolutional neural networks.

active canvas↗
DOE OSTI2025

Development of Automated Atom Probe Tomography capability to study the influence of applied voltage and laser power on the final apparent composition of the analyzed specimen

This study presents the development and implementation of an autonomous Bayesian optimization (BO) framework for controlling and optimizing experimental parameters in Atom Probe Tomography (APT). Using commercial silicon needle samples as a benchmark system, we demonstrate that BO can efficiently navigate the complex parameter space of voltage and laser power to achieve target charge state ratios (specifically Si + /(Si + +Si 2+ )) with minimal experimental evaluations. Our implementation integrates Gaussian Process modeling with the CAMECA atom probe control framework, enabling autonomous adjustment of experimental conditions in real-time. Results show that the algorithm successfully converges to target ratios under different scenarios: maintaining a reference ratio, increasing the ratio (favoring Si 1+ ), and decreasing the ratio (favoring Si 2+ ). The system adapts to specimen evolution during analysis, compensating for changes in apex geometry while maintaining optimization targets. This work establishes a proof of concept for AI-driven optimization in APT, addressing the traditional challenges of manual parameter tuning and paving the way for applications to more complex materials where compositional accuracy is critical.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Effects of Atomic-Scale Structure on the Fracture Properties of Amorphous Carbon - Carbon Nanotube Composites

The fracture of carbon materials is a complex process, the understanding of which is critical to the development of next generation high performance materials. While quantum mechanical (QM) calculations are the most accurate way to model fracture, the fracture behavior of many carbon-based composite engineering materials, such as carbon nanotube (CNT) composites, is a multi-scale process that occurs on time and length scales beyond the practical limitations of QM methods. The Reax Force Field (ReaxFF) is capable of predicting mechanical properties involving strong deformation, bond breaking and bond formation in the classical molecular dynamics framework. This has been achieved by adding to the potential energy function a bond-order term that varies continuously with distance. The use of an empirical bond order potential, such as ReaxFF, enables the simulation of failure in molecular systems that are several orders of magnitude larger than would be possible in QM techniques. In this work, the fracture behavior of an amorphous carbon (AC) matrix reinforced with CNTs was modeled using molecular dynamics with the ReaxFF reactive forcefield. Care was taken to select the appropriate simulation parameters, which can be different from those required when using traditional fixed-bond force fields. The effect of CNT arrangement was investigated with three systems: a single-wall nanotube (SWNT) array, a multi-wall nanotube (MWNT) array, and a SWNT bundle system. For each arrangement, covalent bonds are added between the CNTs and AC, with crosslink fractions ranging from 0-25% of the interfacial CNT atoms. The SWNT and MWNT array systems represent ideal cases with evenly spaced CNTs; the SWNT bundle system represents a more realistic case because, in practice, van der Waals interactions lead to the agglomeration of CNTs into bundles. The simulation results will serve as guidance in setting experimental processing conditions to optimize the mechanical properties of CNT composites.

Jensen, Benjamin D.↗
DOE OSTI2015

Ionic liquid-mediated synthesis of meso-scale porous lanthanum-transition-metal perovskites with high CO oxidation performance

Lanthanum-transition-metal perovskites with robust meso-scale porous frameworks (meso-LaMO 3 ) are synthesized through use of ionic liquids. The resultant samples demonstrate a rather high activity for CO oxidation, by taking advantage of unique nanostructure-derived benefits. This synthesis strategy opens up a new opportunity for preparing functional mesoporous complex oxides of various compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Self-learning quantum Monte Carlo method in interacting fermion systems

We present the self-learning Monte Carlo method is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we extend it to an interacting fermion quantum system in the framework of the widely used determinant quantum Monte Carlo. This method can generally reduce the computational complexity and moreover can greatly suppress the autocorrelation time near a critical point. This enables us to simulate an interacting fermion system on a $100 × 100$ lattice even at the critical point and obtain critical exponents with high precision.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An atomistic survey of shear coupling in asymmetric tilt grain boundaries and interpretation using the disconnections framework

Grain Boundaries (GB) play an important role in determining the behavior of polycrystalline materials. While the mechanisms of motion and associated shear response for symmetric tilt grain boundaries (STGBs) are well studied, the same is not true for asymmetric tilt grain boundaries (ATGBs) despite their greater prevalence in polycrystals. Here, this study aims to investigate the shear response of a large collection of asymmetric tilt grain boundaries (ATGBs) using molecular dynamics (MD) simulations and interpret the data using a discrete disconnections model that works remarkably well for STGBs. MD simulations of shear-driven ATGBs show that the plastic shear (shear coupling factor) in the region swept by a GB exhibits a complex dependence on the inclination angle, and this dependence changes with the misorientation of the GB. In addition, the shear response was observed to be highly sensitive to the applied shear rate and temperature. Recognizing the spatial and temporal scale limitations of MD simulations, we extended the discrete disconnections mesoscale model of Khateret al. (2012) to calculate the nucleation barriers of disconnection modes and predict the effective shear coupling of an ATGB. We observed that the mesoscale model’s predictions of the shear coupling factor of ATGBs do not agree with those observed in MD simulations. Finally, we examine the hypotheses of our mesoscale model that contribute to disagreements between MD simulations and the mesoscale model and propose improvements to the mesoscale model for future work.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Zinc(II) and Cadmium(II) coordination polymers constructed from phenylenediacetate ligands

ABSTRACT: A series of new coordination polymers {[Zn(μ-opda)(μ-bpa)]·2H_2O}{sub n} (1), [Zn(μ{sub 3}-ppda)(μ-bpa)]{sub n} (2), [Cd(μ{sub 3}-ppda)(μ-bpa)]{sub n} (3), [Cd(μ{sub 3}-mpda)(μ-bpa)]{sub n} (4) and [Cd(μ{sub 3}-mpda)(μ-bipy)]{sub n} (5), (o/m/ppda=1,2/1,3/1,4-phenylenediacetate, bpa=1,2-bi(4-pyridyl)ethane, bipy=4,4′-bipyridine) were synthesized. Their structures were characterized by elemental analysis, IR spectroscopy, single-crystal and powder X-ray diffraction. Furthermore, the effect of metal sources (zinc acetate and zinc oxide) and acidity of the solution on the structure of the coordination polymers was discussed for complexes 1 and 5, respectively. The single-crystal X-ray crystallographic studies revealed that complexes 1, 3, 4 and 5 are uninodal (4)-connected 2D frameworks and display sql topology with the point symbol of (4{sup 4}.6{sup 2}). Complex 2 is 3D coordination polymer and exhibits pcu topology with the point symbol of (4{sup 12}.6{sup 3}). In addition, the luminescent properties and thermal behavior of all complexes were also investigated. - Graphical abstract: Scheme 1. Topologies of Coordination Polymers Reported in This Paper.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Mg[(UO2)2(Ge2O6(OH)2]·(H2O)4.4, a novel compound with mixed germanium coordination: cation disordering and topological features of β-U3O8 type sheets

Abstract A novel hydrated magnesium uranyl germanate, Mg[(UO 2 ) 2 (Ge 2 O 6 (OH) 2 )]·(H 2 O) 4.4 , has been synthesized under hydrothermal conditions at 200 °C. The orthorhombic unit-cell parameters are a =10.829(6), b =7.625(4), c =16.888(10) Å, V =1394.5(1) Å 3 , space group Cmcm , Z =4. The crystal structure is based on β-U 3 O 8 -type sheets of corner- and edge-sharing U 6+ O 7 pentagonal bipyramids. The GeO 3 (OH) tetrahedra and GeO 4 (OH) trigonal bipyramids are linked to form [Ge 2 φ 8 ] diortho groups that fill the hexagonal-shaped windows within the sheets. The uranyl germanate layers are connected through Mgφ 6 octahedra. The disorder of the [Ge 2 φ 8 ] diortho groups leads to different local structure types with layered- and framework-like characters. A review of the crystal structures of uranyl minerals and actinide-bearing synthetic compounds based on β-U 3 O 8 topological-type sheets is provided. Structural complexity parameters ( I G,total =176.19 bits/unit cell) indicate that the title compound is one of the simplest actinyl compounds among this family.

nuclear (including radiation effects), materials a↗
DOE OSTI2019

A robust process-structure model for predicting the joint interface structure in impact welding

The impact welding is gaining popularity in joining of dissimilar metals as any intermetallics are often very thin or discontinous with little to no heat affected zone resulting from the process. This work focuses on a recently developed impact welding technique, known as the Vaporizing Foil Actuator Welding (VFAW), which uses the pressure created from the electrically driven rapid vaporization of a thin metallic conductor to drive the flyer. A typical characteristic of an impact-welded joint is the wavy weld interface which is attributed to the complex interfacial kinematics resulting from the high-speed oblique impact of the metal plates. A numerical simulation framework based on the finite element method (FEM) with Eulerian formalism is developed to model the high-speed impact between the metal plates. The model accounts for the thermomechanical interactions in the process and captures the complex interfacial deformations. A thorough validation of the model is achieved by comparing the wave characteristics obtained from numerical simulations with the experimental results from vaporizing foil actuator welding. The amplitude and wavelength of the interfacial waves and the resulting joint microstructure is shown to be strongly dependent on the process conditions and the specific material system, which is well captured by the model.

42 ENGINEERING↗
DOE OSTI2023

Tailoring light-induced charge transfer and intersystem crossing in FeCO using time-dependent spin–orbit configuration interaction

Real-time (RT) electronic structure methods provide a natural framework for describing light–matter interactions in arbitrary time-dependent electromagnetic fields (EMF). Optically induced excited state transitions are of particular interest, which require tuned EMF to drive population transfer to and from the specific state(s) of interest. Intersystem crossing, or spin-flip, may be driven through shaped EMF or laser pulses. These transitions can result in long-lived “spin-trapped” excited states, which are especially useful for materials requiring charge separation or protracted excited state lifetimes. Time-dependent configuration interaction (TDCI) is unique among RT methods in that it may be implemented in a basis of eigenstates, allowing for rapid propagation of the time-dependent Schrödinger equation. The recent spin–orbit TDCI (TD-SOCI) enables a real-time description of spin-flip dynamics in an arbitrary EMF and, therefore, provides an ideal framework for rational pulse design. The present study explores the mechanism of multiple spin-flip pathways for a model transition metal complex, FeCO, using shaped pulses designed to drive controlled intersystem crossing and charge transfer. These results show that extremely tunable excited state dynamics can be achieved by considering the dipole transition matrix elements between the states of interest.

Chemistry↗
DOE OSTI2014

Pervasive Restart In MOOSE-based Applications

Multiphysics applications are inherently complicated. Solving for multiple, interacting physical phenomena involves the solution of multiple equations, and each equation has its own data dependencies. Feeding the correct data to these equations at exactly the right time requires extensive effort in software design. In an ideal world, multiphysics applications always run to completion and produce correct answers. Unfortunately, in reality, there can be many reasons why a simulation might fail: power outage, system failure, exceeding a runtime allotment on a supercomputer, failure of the solver to converge, etc. A failure after many hours spent computing can be a significant setback for a project. Therefore, the ability to “continue” a solve from the point of failure, rather than starting again from scratch, is an essential component of any high-quality simulation tool. This process of “continuation” is commonly termed “restart” in the computational community. While the concept of restarting an application sounds ideal, the aforementioned complexities and data dependencies present in multiphysics applications make its implementation decidedly non-trivial. A running multiphysics calculation accumulates an enormous amount of “state”: current time, solution history, material properties, status of mechanical contact, etc. This “state” data comes in many different forms, including scalar, tensor, vector, and arbitrary, application-specific data types. To be able to restart an application, you must be able to both store and retrieve this data, effectively recreating the state of the application before the failure. When utilizing the Multiphysics Object Oriented Simulation Environment (MOOSE) framework developed at Idaho National Laboratory, this state data is stored both internally within the framework itself (such as solution vectors and the current time) and within the applications that use the framework. In order to implement restart in MOOSE-based applications, the total state of the system (both within the framework and without) must be stored and retrieved. To this end, the MOOSE team has implemented a “pervasive” restart capability which allows any object within MOOSE (or within a MOOSE-based application) to be declared as “state” data, and handles the storage and retrieval of said data.

97 MATHEMATICS AND COMPUTING↗