Search NASA⌕ Search

SEARCH · Search NASA

Results for “Complex Framework Materials”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Commercial Fault Detection and Diagnostics Tools: What They Offer, How They Differ, and What's Still Needed

It is estimated that 5%-30% energy use in commercial buildings is wasted due to faults and errors in operations. Automated fault detection and diagnostics (AFDD) technologies can address this waste by identifying (detecting) deviations from normal or expected operation (faults), and resolving (diagnosing) the type of problem or its location, minimizing the need for complex manual analysis of operational data. Although currently underutilized, AFDD is a powerful approach to ensuring efficient building operations. AFDD offers the potential to greatly improve performance, and to do so cost effectively. There is currently a diverse landscape of AFDD technologies on the market, but no common framework exists to characterize such tools, or distinguish one offering from another. It is difficult to determine from vendor websites and marketing materials key technology features and capabilities, or the overall state of the technology. In this paper, we present an AFDD characterization framework, and findings from applying the framework to survey over a dozen technologies from today's market. This paper outlines the current state of the market, as well as outstanding needs in the industry, derived from direct engagement of, and technical assistance provided to users of AFDD technology. A core set of interrelated informational, organizational, and technical needs and barriers that must be addressed to realize the full potential of AFDD at scale are identified. Lastly, based on information gathered through a survey and discussion with both vendors and users, several opportunities to further advance the technology are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Superhydrophobic Phosphonium Modified Robust 3D Covalent Organic Framework for Preferential Trapping of Charge Dispersed Oxoanionic Pollutants

Abstract Charge dispersed and less hydrophilic anionic pollutants are often difficult to be preferentially captured by common cationic framework materials. A gamma radiation modification approach is employed to anchor a superhydrophobic phosphonium‐containing coating on a robust crystalline 3D covalent organic framework (COF). By regulating the surface hydrophobicity, the prepared 3DCOF‐ g ‐VBPPh 3 Cl is endowed with a strong affinity for charge dispersed and less hydrophilic oxoanions, such as MnO 4 − , TcO 4 − and ReO 4 − , to surmount the Hofmeister bias, which much favors remediation of oxoanionic pollutants in complex aqueous systems. Batch and column experiments with 3DCOF‐g‐VBPPh 3 Cl in both tap water and simulated groundwater are performed, and rapid sequestration is achieved with removal efficacy up to 99.995%, record‐high distribution coefficient of 1.0 × 10 8 mL g −1 , and desirable priority over competing anions such as Cl − , SO 4 2− , HCO 3 − , and NO 3 − , confirming promise for remediation of charge dispersed anionic pollutants. Theoretical calculations reveal a mechanism of preferential capture based on electrostatic and dispersion interaction between charge dispersed anions and 3DCOF‐g‐VBPPh 3 Cl that effectively competes with solvation of the aqueous anions.

Wang, Yue↗
DOE OSTI2022

hPIC2: A hardware-accelerated, hybrid particle-in-cell code for dynamic plasma-material interactions

The exascale era of high performance computing promises to bring the field of computational plasma physics ever closer to the goal of accurate multiscale modeling. Such computers will rely on hardware acceleration to offload work to dedicated components, notably general-purpose graphics processing units (GPUs). However, devices from different manufacturers require software to be written with different parallel programming models, greatly increasing the code maintenance burden of applications designed to perform on more than one such device. hPIC2 is a hybrid plasma simulation code developed with the Kokkos performance portability framework to target the architectures that will drive exascale computing for the foreseeable future. As a hybrid simulation code, hPIC2 investigates the simultaneous use of various plasma models on the same domain, at the same time. hPIC2 also optionally couples to RustBCA, which accurately models ion-material interactions using the binary collision approximation (BCA) method. In conclusion, hPIC2 therefore achieves scalable performance on a variety of computing architectures when simulating complex and diverse plasmas, particularly near plasma-material interfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Genetically encoded sensors enable real-time observation of metabolite production

Advances in biotechnology are enabling engineers to harness natural processes for the production of valuable new chemicals and materials. Cells engineered for chemical production act as renewable factories and redefine what is possible in industries as diverse as manufacturing, pharmaceuticals, and energy. Despite this potential, long and uncertain timelines for biobased product development hinder progress. Engineering cells for chemical production is challenging because the complexity of biology necessitates many attempted designs before an optimal combination of genetic elements or culture conditions is discovered. In this work, we develop a framework that allows design evaluation to be performed with fluorescence such that microbial chemical production can be monitored in real time without the need for sample preparation or laborious analytical techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A cellulose-derived supramolecule for fast ion transport

Supramolecular frameworks have been widely synthesized for ion transport applications. However, conventional approaches of constructing ion transport pathways in supramolecular frameworks typically require complex processes and display poor scalability, high cost, and limited sustainability. Here, we report the scalable and cost-effective synthesis of an ion-conducting (e.g., Na + ) cellulose-derived supramolecule (Na-CS) that features a three-dimensional, hierarchical, and crystalline structure composed of massively aligned, one-dimensional, and ångström-scale open channels. Using wood-based Na-CS as a model material, we achieve high ionic conductivities (e.g., 0.23 S/cm in 20 wt% NaOH at 25 °C) even with a highly dense microstructure, in stark contrast to conventional membranes that typically rely on large pores (e.g., submicrometers to a few micrometers) to obtain comparable ionic conductivities. This synthesis approach can be universally applied to a variety of cellulose materials beyond wood, including cotton textiles, fibers, paper, and ink, which suggests excellent potential for a number of applications such as ion-conductive membranes, ionic cables, and ionotronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2018

ExaTN

A challenging scientific problem that will benefit from exascale computing is predictive simulation of two- and three-dimensional quantum many-body Hamiltonians in condensed matter physics, together with the related strong entanglement problems in quantum chemistry and quantum computing. Efficient numerical simulations will require new insights into wavefunction compression algorithms that scale on extremely heterogeneous HPC architectures. To address this need, we propose to develop a scalable math library of parallel multi-linear algebraic numerical primitives for hierarchical tensor compression. Our library will subsequently be used for building an efficient, performance-portable HPC framework for simulating strongly correlated quantum systems. In particular, our will will be the first to deliver a massively parallel implementation of the multiscale entanglement renormalization ansatz (MERA), a hierarchical tensor decomposition quantum scheme capable of expressing local expectation values of strongly entangled higher-dimensional quantum systems efficiently. To address the extreme complexity and high computational cost of such schemes, we will automate their parallel implementation by delivering an integrated software framework, ExaTN (Exascale Tensor Networks), that will process hierarchical tensor representations on exascale HPC systems via an asymchronous task-based programming model. As a specific application, our framework will provide scientists with a capability of simulating strongly entangled quantum systems, thus positioning ORNL as a strategic leader in modeling of strongly correlated materials.

McCaskey, AlexanderJ↗
DOE OSTI2025

Depolarization self-compensation in high-power lasers enabled by a mid-cavity quartz rotator

Depolarization from thermal stress remains a major limitation in high-average-power laser amplifiers, often addressed by complex, costly active methods or by using magneto-optical effects to restore the polarization. We demonstrate a passive polarization self-compensation technique using a quartz rotator in a relay-imaged, multi-pass amplifier geometry. A detailed theoretical framework is presented and validated experimentally, showing a 47 × reduction in depolarized light in a relay-imaged 4-pass cavity. This approach employs a high-damage-threshold, reciprocal material and avoids the use of polarizers or active controls, thereby simplifying system design and reducing costs. Scalability is discussed for realistic inertial fusion energy driver designs, including effectiveness for broadband lasers and thick gain media.

Batysta, František [Lawrence Livermore National La↗
DOE OSTI2024

MOOSE-Workbench integration and MOOSE meshing capability enhancements to facilitate inputs and outputs for multiphysics modeling

The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source framework that supports many of the US Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) technical areas (TA). These TAs develop and use NEAMS physics and coupling modules in multiple ways to enable the research and development of complex physics models. In addition to the MOOSE framework, the NEAMS Workbench user interface provides a common analysis environment with user-interaction accelerators that streamline the tasks of model creation, review, execution, and out put inspection. In FY 2024, objectives were realized in the MOOSE framework application development support and user-oriented improvements. Application development improvements support both developers and users with an expanded Reactor Module and Mesh System, stateful material property support for mortar contact, and customizable convergence criteria. Additionally, new user-oriented features were implemented in the MOOSE framework language server, including autocompletion snippets, definition from source and find reference navigations, and syntax overrides. Lastly, improvements were made to the input interpreter necessary to support the MOOSE language server and the NEAMS Workbench so that they can interact with syntactically incomplete user inputs. These improvements and more were intended to address stakeholder feedback and improve developer and user ability to conduct advanced nuclear energy modeling and simulation in support of DOE and industry needs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Photoinduced Melting of V 4 O 7 Correlated State

The compound V 4 O 7 is one of the Magnéli phase (V n O 2n - 1 , n = 3, 4, …, 9) correlated vanadium oxides with distinct intriguing electronic and structural properties. The possibility to manipulate the phase state of V 4 O 7 on an ultrafast time scale by light makes this material promising for potential applications in photonics, optoelectronics, quantum, and neuromorphic circuit design. In this work, the ultrafast spectroscopy of V 4 O 7 reveals the second-order nature of the photoinduced insulator-to-metal transition, emphasizing electronic and lattice contributions. The findings reveal the influence of the laser excitation level and temperature on these dynamics, providing a comprehensive understanding of V 4 O 7 structural changes and response to external stimuli. The phenomenological model based on the Landau–Ginzburg formalism provides a robust framework for explaining the photoinduced transition dynamics, showing a detailed picture of the light interaction with the electronic and lattice subsystems. This integrated approach significantly enhances the understanding of V 4 O 7 complex behavior upon photoexcitation, opening new possibilities for developing new optoelectronic devices and noninvasive optical control of the phase transition pathways in vanadates.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Multi-scale computational analysis of unidirectional carbon fiber reinforced polymer composites under various loading conditions

In this study, a multi-scale computational analysis based on representative volume element (RVE) modeling and molecular dynamics (MD) simulations is developed to investigate the microscopic failure mechanisms of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The average properties of the 200-nm thickness interphase region between fiber and matrix are characterized through MD simulations and an analytical gradient model. The results demonstrate that the interphase region has higher Young’s modulus and strength, compared to the bulk matrix. This stiffened interphase region influences the composite response significantly. Specifically, the traditional two-phase model with zero-thickness interface fails to capture the stress-strain behavior compared to the experimental data. However, by adding the interphase region to a modified RVE model, the accuracy of simulation results will be improved significantly. Furthermore, a coupled experimental-computational micromechanics approach is adopted to calibrate and validate the cohesive parameters of the interface. By including the cohesive interface, our modified RVE model accurately captures the failure strength of the composites. Finally, different failure mechanisms for specimens are investigated using our multi-scale computational framework. In conclusion, the results show that the failure modes of UD CFRP composites are very complex and multiple failure mechanisms co-exist depending on the loading conditions, agreeing well with our experimental analyses.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Intercell moiré exciton complexes in electron lattices

Excitons, Coulomb-bound electron–hole pairs, play a crucial role in both optical excitation and correlated phenomena in solids. When excitons interact with other quasiparticles, few- and many-body excited states can appear. Here, in this work, we report an interaction between exciton and charges enabled by unusual quantum confinement in two-dimensional moiré superlattices, which results in many-body ground states composed of moiré excitons and correlated electron lattices. In an H-stacked (60 o -twisted) WS 2 /WSe 2 heterobilayer, we found an interlayer moiré exciton whose hole is surrounded by its partner electron’s wavefunction distributed among three adjacent moiré traps. This three-dimensional excitonic structure enables large in-plane electrical quadrupole moments in addition to the vertical dipole. Upon doping, the quadrupole facilitates the binding of interlayer moiré excitons to the charges in neighbouring moiré cells, forming intercell charged exciton complexes. Our work provides a framework for understanding and engineering emergent exciton many-body states in correlated moiré charge orders.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Deactivation of metastable single-crystal silicon hyperdoped with sulfur

Silicon supersaturated with sulfur by ion implantation and pulsed laser melting exhibits broadband optical absorption of photons with energies less than silicon's band gap. However, this metastable, hyperdoped material loses its ability to absorb sub-band gap light after subsequent thermal treatment. We explore this deactivation process through optical absorption and electronic transport measurements of sulfur-hyperdoped silicon subject to anneals at a range of durations and temperatures. The deactivation process is well described by the Johnson-Mehl-Avrami-Kolmogorov framework for the diffusion-mediated transformation of a metastable supersaturated solid solution, and we find that this transformation is characterized by an apparent activation energy of E{sub A}=1.7 ± 0.1 eV. Using this activation energy, the evolution of the optical and electronic properties for all anneal duration-temperature combinations collapse onto distinct curves as a function of the extent of reaction. We provide a mechanistic interpretation of this deactivation based on short-range thermally activated atomic movements of the dopants to form sulfur complexes.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Assembly of dicobalt and cobalt–aluminum oxide clusters on metal–organic framework and nanocast silica supports

NU-1000, a mesoporous metal–organic framework (MOF) featuring hexazirconium oxide nodes and 3 nm wide channels, was infiltrated with a reactive dicobalt complex to install dicobalt active sites onto the MOF nodes. The anchoring of the dicobalt complex onto NU-1000 occurred with a nearly ideal stoichiometry of one bimetallic complex per node and with the cobalt evenly distributed throughout the MOF particle. To access thermally robust multimetallic sites on an all-inorganic support, the modified NU-1000 materials containing either the dicobalt complex, or an analogous cobalt–aluminum species, were nanocast with silica. The resulting materials feature Co 2 or Co–Al bimetallated hexazirconium oxide clusters within a silica matrix. The cobalt-containing materials are competent catalysts for the selective oxidation of benzyl alcohol to benzaldehyde. Catalytic activity depends on the number of cobalt ions per node, but does not vary significantly between the NU-1000 and silica supports. Hence, the multimetallic oxide clusters remain site-isolated and substrate-accessible within the nanocast materials.

catalysis (heterogeneous), materials and chemistry↗
DOE OSTI2018

Distributed X-ray photon correlation spectroscopy data reduction using Hadoop MapReduce

Multi-speckle X-ray photon correlation spectroscopy (XPCS) is a powerful technique for characterizing the dynamic nature of complex materials over a range of time scales. XPCS has been successfully applied to study a wide range of systems. Recent developments in higher-frame-rate detectors, while aiding in the study of faster dynamical processes, creates large amounts of data that require parallel computational techniques to process in near real-time. Here, an implementation of the multi-tau and two-time autocorrelation algorithms using the Hadoop MapReduce framework for distributed computing is presented. In conclusion, the system scales well with regard to the increase in the data size, and has been serving the users of beamline 8-ID-I at the Advanced Photon Source for near real-time autocorrelations for the past five years.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Dara: Automated Multiple-Hypothesis Phase Identification and Refinement from Powder X-ray Diffraction

Powder X-ray diffraction (XRD) is a foundational technique for characterizing crystalline materials. However, the reliable interpretation of XRD patterns, particularly in multiphase systems, remains a manual and expertise-demanding task. As a characterization method that only provides structural information, multiple reference phases can often be fit to a single pattern, leading to potential misinterpretation when alternative solutions are overlooked. To ease humans’ efforts and address the challenge, we introduce Dara (data-driven automated Rietveld analysis), a framework designed to automate the robust identification and refinement of multiple phases from powder XRD data. Dara performs an exhaustive tree search over all plausible phase combinations within a given chemical space and validates each hypothesis using the BGMN Rietveld refinement routine. Key features include structural database filtering, automatic clustering of isostructural phases during tree expansion, and peak-matching-based scoring to identify promising phases for refinement. When ambiguity exists, Dara generates multiple hypothesis which can then be decided between by human experts or with further characterization tools. By enhancing the reliability and accuracy of phase identification, Dara enables scalable analysis of realistic complex XRD patterns and provides a foundation for integration into multimodal characterization workflows, moving toward fully self-driving materials discovery.

Biological databases↗
DOE OSTI2015

Current limitations and challenges in nanowaste detection, characterisation and monitoring

Highlights: • First review on detection of nanomaterials in complex waste samples. • Focus on nanoparticles in solid, liquid and gaseous waste samples. • Summary of current applicable methods for nanowaste detection and characterisation. • Limitations and challenges of characterisation of nanoparticles in waste. - Abstract: Engineered nanomaterials (ENMs) are already extensively used in diverse consumer products. Along the life cycle of a nano-enabled product, ENMs can be released and subsequently accumulate in the environment. Material flow models also indicate that a variety of ENMs may accumulate in waste streams. Therefore, a new type of waste, so-called nanowaste, is generated when end-of-life ENMs and nano-enabled products are disposed of. In terms of the precautionary principle, environmental monitoring of end-of-life ENMs is crucial to allow assessment of the potential impact of nanowaste on our ecosystem. Trace analysis and quantification of nanoparticulate species is very challenging because of the variety of ENM types that are used in products and low concentrations of nanowaste expected in complex environmental media. In the framework of this paper, challenges in nanowaste characterisation and appropriate analytical techniques which can be applied to nanowaste analysis are summarised. Recent case studies focussing on the characterisation of ENMs in waste streams are discussed. Most studies aim to investigate the fate of nanowaste during incineration, particularly considering aerosol measurements; whereas, detailed studies focusing on the potential release of nanowaste during waste recycling processes are currently not available. In terms of suitable analytical methods, separation techniques coupled to spectrometry-based methods are promising tools to detect nanowaste and determine particle size distribution in liquid waste samples. Standardised leaching protocols can be applied to generate soluble fractions stemming from solid wastes, while micro- and ultrafiltration can be used to enrich nanoparticulate species. Imaging techniques combined with X-ray-based methods are powerful tools for determining particle size, morphology and screening elemental composition. However, quantification of nanowaste is currently hampered due to the problem to differentiate engineered from naturally-occurring nanoparticles. A promising approach to face these challenges in nanowaste characterisation might be the application of nanotracers with unique optical properties, elemental or isotopic fingerprints. At present, there is also a need to develop and standardise analytical protocols regarding nanowaste sampling, separation and quantification. In general, more experimental studies are needed to examine the fate and transport of ENMs in waste streams and to deduce transfer coefficients, respectively to develop reliable material flow models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Crystallographic Mapping and Tuning of Water Adsorption in Metal–Organic Frameworks Featuring Distinct Open Metal Sites

Crucial steps toward designing water sorption materials and fine-tuning their properties for specific applications include precise identification of adsorption sites and establishment of rigorous molecular-level insight into the water adsorption process. We report stepwise crystallographic mapping and DFT computations of adsorbed water molecules in ALP-MOF-1, a metal-organic framework decorated with distinct open metal sites and carbonyl functional groups that serve as water anchoring sites for seeding the nucleation of a complex water network. Identification of an unusual water adsorption step in ALP-MOF-1 motivated the tuning of metal ion composition to carefully adjust water uptake. These studies provide direct evidence that the identity of the open metal sites in MOFs can dramatically affect water adsorption behavior between 0 and ~20% RH and that multiple proximal water anchoring sites along the MOF skeleton facilitate water uptake steps which could be potentially useful for applications requiring rapid and energetically facile water sorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗