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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 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Machine learning-assisted design of metal–organic frameworks for hydrogen storage: A high-throughput screening and experimental approach

Various theoretical approaches, including big data and high-throughput screening techniques, have been explored in developing new materials due to their significant potential time-saving advantages. However, it remains a significant challenge to experimentally realize new materials that are predicted. In this study, we propose a novel materials design strategy that utilizes machine-learning (ML) techniques to predict new porous materials that show promise for hydrogen storage and are likely to be feasible to synthesize. By leveraging ML techniques and metal–organic framework (MOF) databases, we are able to predict the synthesizability of MOF structures. This is evidenced by the successful synthesis of a new vanadium-based MOF that exhibits excellent performance for cryogenic H 2 storage. Notably, the total gravimetric and volumetric H 2 uptakes are as high as 9.0 wt% and 50.0 g/L at 77 K and 150 bar. This ML-assisted materials design offers an efficient and promising approach for developing hydrogen storage materials.

08 HYDROGEN↗

NASA NTRS2005

Acoustic Liquid Manipulation Used to Enhance Electrochemical Processes

Working in concert with the NASA Technology Transfer and Partnership Office, the Great Lakes Industrial Technology Center, and Alchemitron Corporation of Elgin, Illinois, the NASA Glenn Research Center has applied nonlinear acoustic principles to industrial applications. High-intensity ultrasonic beam techniques employ the effects of acoustic radiation pressure and acoustic streaming to manipulate the behavior of liquids. This includes propelling liquids, moving bubbles, and ejecting liquids as droplets and fountains. Since these effects can be accomplished without mechanical pumps or moving parts, we are exploring how these techniques could be used to manipulate liquids in space applications. Some of these acoustic techniques could be used both in normal Earth gravity and in the microgravity of space.

Oeftering, Richard C.↗

DOE OSTI2024

Role of Tensile Stress in DNA Nanoresonators for Epigenetic Studies

The evaluation of epigenetic features such as DNA methylation is becoming increasingly important in many biochemical processes like gene expression and transcription as well as in several diseases like schizophrenia or diabetes. Here, in this work, we report that self-assembled nanomechanical resonators entirely composed of DNA molecules can be used to explore gross changes in DNA methylation levels (0–25–50%), while careful control of tensile stress is needed to reduce the variability of resonance frequency for rigorous quantification. The effect of the tensile stress retained by the suspended DNA nanoresonators on the application of the technique is extensively explored using a combination of laser Doppler vibrometry and atomic force spectroscopy. DNA nanoresonators are real-time, label-free sensors and could avoid chemical functionalization and sample amplification. Therefore, they may represent in the future a key complementary routine tool for global DNA methylation analysis needed to evaluate the consequences of environmental stresses on the human genome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2003

An Advanced Hierarchical Hybrid Environment for Reliability and Performance Modeling

The key issue we intended to address in our proposed research project was the ability to model and study logical and probabilistic aspects of large computer systems. In particular, we wanted to focus mostly on automatic solution algorithms based on a state-space exploration as their first step, in addition to the more traditional discrete-event simulation approaches commonly employed in industry. One explicitly-stated goal was to extend by several orders of magnitude the size of models that can be solved exactly, using a combination of techniques: 1) Efficient exploration and storage of the state space using new data structures that require an amount of memory sublinear in the number states; and 2) Exploitation of the existing symmetries in the matrices describing the system behavior using Kronecker operators. Not only we have been successful in achieving the above goals, but we exceeded them in many respects.

Ciardo, Gianfranco↗

DOE OSTI2019

“The development of a through-plane reactive excitation technique for detection of pinholes in membrane-containing MEA sub-assemblies”

As markets for polymer-electrolyte-membrane fuel cells (PEMFC) expand, there continues to be a need for the development and implementation of in-line quality inspection techniques to enable high-volume manufacturing methods for membrane-electrode assemblies (MEAs). These techniques mitigate the potential impact of poor quality on the cost of MEA components by real-time identification of process-induced irregularities, which can result from the manufacturing process or subsequent handling of the material during assembly into a full MEA. A particular type of irregularity known to impact MEA lifetime is loss of membrane integrity, e.g. via a pinhole. In this work, we focus on development of a technique to detect pinholes in membrane-containing MEA sub-assemblies - as opposed to in just the membrane - using a reactive excitation strategy coupled with infrared thermography for detection. A specialized device is introduced and, using various MEA sub-assemblies, is shown to enable detection of pinholes in stationary samples. Multi-physics modeling is utilized to understand and predict the impact of various design and operational parameters of this technique. The feasibility of the technique is demonstrated through both modeling and in-situ results. For example, a detectable (≥1 degree C) thermal response for a membrane pinhole of approximately 90 um in diameter is measured in a fraction of a second. The observed detection time is considered to be appropriate for further exploration of the technique in an in-line configuration.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

A physics-constrained neural ordinary differential equations approach for robust learning of stiff chemical kinetics

The high computational cost associated with solving for detailed chemistry poses a significant challenge for predictive computational fluid dynamics (CFD) simulations of turbulent reacting flows. While deep learning techniques have been explored to develop faster surrogate models, they often fail to integrate reliably with CFD solvers. This instability arises because traditional deep learning approaches optimize for training error without ensuring compatibility with ordinary differential equation (ODE) solvers, resulting in accumulation of errors over time. Recently, neuralODE (NODE) based approaches have been shown to be a promising technique to emulate and accelerate detailed chemistry computations. Here, in the present work, we extend this NODE framework for stiff chemical kinetics by incorporating mass conservation constraints directly into the loss function during training. This ensures that the total mass as well as the individual elemental species masses are conserved in an a-posteriori manner. Proof-of-concept studies are performed with the novel physics-constrained NODE (PC-NODE) approach for homogeneous autoignition of hydrogen-air mixture over a range of composition and thermodynamic conditions. It is demonstrated that the PC-NODE framework not only improves the physical consistency of the resulting data-driven model with respect to mass conservation criteria, but also improves training efficiency. PC-NODE is shown to achieve 2–100× speedup relative to the hydrogen-air detailed chemical mechanism depending on the type of the ODE solver (implicit or explicit) used during autoregressive inference tests. Lastly, a-posteriori studies are performed wherein the trained PC-NODE model is coupled with a CFD solver. It is shown that higher accuracy is achieved with PC-NODE relative to the purely data-driven NODE approach. Moreover, PC-NODE also exhibits robustness and generalizability to unseen initial conditions from within (interpolative capability) as well as outside (extrapolative capability) the training regime.

computational combustion↗

DOE OSTI2016

A SIMPLE METHOD FOR MEASURING THE ELECTRON-BEAM MAGNETIZATION

There are a number of projects that require magnetized beams, such as electron cooling or aiding in “flat” beam transforms. Here we explore a simple technique to characterize the magnetization, observed through the angular momentum of magnetized beams. These beams are produced through photoemission. The generating drive laser first passes through microlens arrays (fly-eye light condensers) to form a transversely modulated pulse incident on the photocathode surface [1]. The resulting charge distribution is then accelerated from the photocathode. We explore the evolution of the pattern via the relative shearing of the beamlets, providing information about the angular momentum. This method is illustrated through numerical simulations and preliminary measurements carried out at the Argonne Wakefield Accelerator (AWA) facility are presented.

43 PARTICLE ACCELERATORS↗

NASA NTRSDate not supplied

Developing Satellite-Assisted Particulate Matter (SAPM) Estimates over India for the MIRA Working Group

The Models, In Situ, and Remote Sensing of Aerosols (MIRA) Working Group is an international collective that encourages collaboration among researchers from these three atmospheric aerosol communities. MIRA currently comprises five interdisciplinary and independently funded Topic Groups, each with specific goals, and involves requests for additional scientific datasets. The Satellite-Assisted Particulate Matter (SAPM) Topic Group, as part of MIRA, focuses on studying particulate matter smaller than 2.5 microns in diameter (PM2.5) due to its significant contribution to air pollution and its harmful effects on human health. While the annual mean PM2.5 levels are typically low (~5-15 μg/m³) across most of the contiguous United States (CONUS), other countries experience much higher concentrations (e.g., India). SAPM aims to compare different methods and techniques for obtaining surface PM2.5 proxies using spaceborne passive and active remote sensors, aerosol models, and in situ measurements. Ultimately, SAPM aims to provide more extensive coverage of PM2.5 concentrations than what is currently available from in situ ground stations, which are limited in some parts of the CONUS and large regions worldwide. Current SAPM members are exploring PM2.5 estimation techniques using active sensors. This presentation offers an overview of these techniques and highlights the strengths and limitations of each approach. These techniques include 1) spaceborne lidar (CALIOP: Cloud-Aerosol Lidar with Orthogonal Polarization) alone, and 2) a combination of spaceborne lidar (CATS: Cloud Aerosol Transport System) and a global aerosol transport model (GEOS: Goddard Earth Observing System). Additionally, we present a case study featuring our SAPM research in India, a country with high levels of PM2.5 concentrations (i.e., state-level annual means of ~100-200 μg/m³). Consistent spatial patterns in PM2.5 over India are found from the in situ data, CALIOP-based, and CATS/model-based methods, with the highest concentrations found in northern India near New Delhi. The gridded PM2.5 analysis yields high R values between in situ and CATS/model (~0.7) and between in situ and CALIOP nighttime (~0.9), as well as good agreement between CATS/model and CALIOP nighttime PM2.5 estimates (R = ~0.8 and slope = ~0.9). For current and future efforts, the SAPM Topic Group is actively seeking new collaborators, especially those working with in situ aerosol measurements, and is interested in acquiring additional aerosol datasets to improve and validate the PM2.5 proxies.

Travis D Toth↗

DOE OSTI2024

Bridging length scales in hard materials with ultra-small angle X-ray scattering – a critical review

Owing to their exceptional properties, hard materials such as advanced ceramics, metals and composites have enormous economic and societal value, with applications across numerous industries. Understanding their microstructural characteristics is crucial for enhancing their performance, materials development and unleashing their potential for future innovative applications. However, their microstructures are unambiguously hierarchical and typically span several length scales, from sub-ångstrom to micrometres, posing demanding challenges for their characterization, especially for in situ characterization which is critical to understanding the kinetic processes controlling microstructure formation. This review provides a comprehensive description of the rapidly developing technique of ultra-small angle X-ray scattering (USAXS), a nondestructive method for probing the nano-to-micrometre scale features of hard materials. USAXS and its complementary techniques, when developed for and applied to hard materials, offer valuable insights into their porosity, grain size, phase composition and inhomogeneities. We discuss the fundamental principles, instrumentation, advantages, challenges and global status of USAXS for hard materials. Using selected examples, we demonstrate the potential of this technique for unveiling the microstructural characteristics of hard materials and its relevance to advanced materials development and manufacturing process optimization. We also provide our perspective on the opportunities and challenges for the continued development of USAXS, including multimodal characterization, coherent scattering, time-resolved studies, machine learning and autonomous experiments. Our goal is to stimulate further implementation and exploration of USAXS techniques and inspire their broader adoption across various domains of hard materials science, thereby driving the field toward discoveries and further developments.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Imaging moiré excited states with photocurrent tunnelling microscopy

Moiré superlattices provide a highly tuneable and versatile platform to explore novel quantum phases and exotic excited states ranging from correlated insulators to moiré excitons. Scanning tunnelling microscopy has played a key role in probing microscopic behaviours of the moiré correlated ground states at the atomic scale. However, imaging of quantum excited states in moiré heterostructures remains an outstanding challenge. In this report we develop a photocurrent tunnelling microscopy technique that combines laser excitation and scanning tunnelling spectroscopy to directly visualize the electron and hole distribution within the photoexcited moiré exciton in twisted bilayer WS 2 . The tunnelling photocurrent alternates between positive and negative polarities at different locations within a single moiré unit cell. This alternating photocurrent originates from the in-plane charge transfer moiré exciton in twisted bilayer WS 2 , predicted by our GW-Bethe–Salpeter equation calculations, that emerges from the competition between the electron–hole Coulomb interaction and the moiré potential landscape. Our technique enables the exploration of photoexcited non-equilibrium moiré phenomena at the atomic scale.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Book: Advanced Nano and Micro materials for Photovoltaics: future and emerging technologies, Chapter 11: "Multifunctional Optical Coatings and Light Management for Photovoltaics"

In this chapter, we present a discussion of three main topics in coatings and light management for PV. First, we will cover the basic principles behind light management and broadly discuss approaches that can be used to mitigate reflective losses. Additionally, we build further on this topic by exploring the specific antireflection techniques used by PV glass and module manufacturers. Next, we explore antisoiling coatings, a relatively understudied area until recently. We comment on the distinctly different approaches to antisoiling coatings currently being explored by the PV community and the pros and cons of each. In addition, antisoiling coatings can also serve as antireflective coatings, providing a route to multifunctional coatings. Finally, we comment briefly on possible rich areas for new research efforts that we believe will provide a meaningful impact on solar module efficiency, reliability, and durability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Search for Catalysts by Inverse Design: Artificial Intelligence, Mountain Climbers, and Alchemists

In silico catalyst design is a grand challenge of chemistry. Traditional computational approaches have been limited by the need to compute properties for an intractably large number of possible catalysts. Recently, inverse design methods have emerged, starting from a desired property and optimizing a corresponding chemical structure. Techniques used for exploring chemical space include gradient-based optimization, alchemical transformations, and machine learning. Though the application of these methods to catalysis is in its early stages, further development will allow for robust computational catalyst design. This review provides an overview of the evolution of inverse design approaches and their relevance to catalysis. In conclusion, the strengths and limitations of existing techniques are highlighted, and suggestions for future research are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Use of micro-photoluminescence as a contactless measure of the 2D electron density in a GaAs quantum well

We compare micro-photoluminescence (μPL) as a measure of the electron density in a clean, two-dimensional (2D) system confined in a GaAs quantum well (QW) to the standard magneto-transport technique. Our study explores the PL shape evolution across a number of molecular beam epitaxy-grown samples with different QW widths and 2D electron densities and notes its correspondence with the density obtained in magneto-transport measurements on these samples. We also measure the 2D density in a top-gated quantum well sample using both PL and transport and find that the two techniques agree to within a few percent over a wide range of gate voltages. We find that the PL measurements are sensitive to gate-induced 2D density changes on the order of 109 electrons/cm 2 . The spatial resolution of the PL density measurement in our experiments is 40 μm, which is already substantially better than the millimeter-scale resolution now possible in spatial density mapping using magneto-transport. Our results establish that μPL can be used as a reliable high spatial resolution technique for future contactless measurements of density variations in a 2D electron system.

42 ENGINEERING↗

DOE OSTI2021

DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.14

Sandia's Dakota software supports science and engineering transformation through advanced exploration of simulations. Specifically, Dakota manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-10468 O

Adams, BrianM.↗

DOE OSTI2021

DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.16

Adams, BrianM.↗

DOE OSTI2015

Design Analysis Kit for Optimization and Terascale Applications 6.0

Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers.

Source record↗

NASA NTRS2004

Advanced X-Ray Inspection of Reinforced Carbon Composite Materials on the Orbiter Leading Edge Structural Subsystem (LESS)

The post return-to-flight (RTF) inspection methodology for the Orbiter Leading Edge Structural Subsystem (LESS) is currently being defined. Numerous NDT modalities and techniques are being explored to perform the flight-to-flight inspections of the reinforced carbon/carbon (RCC) composite material for impact damage, general loss of mass in the bulk layers, or other anomalous conditions that would pose risk to safe return upon re-entry. It is possible to have an impact upon ascent that is not visually observable on the surface, yet causes internal damage. Radiographic testing may be a useful NDT technique for such occurrences. The authors have performed radiographic tests on full-sized mock samples of LESS hardware with embedded image quality phantoms. Digitized radiographic film, computed radiography and flat panel digital real-time radiography was acquired using a GE Eresco 200 x-ray tube, and Se-75 and Yb-169 radioisotopes.

Hernandez, Jose M.↗

DOE OSTI2023

Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing

One of the commonly used chemical-inspired approaches in variational quantum computing is the unitary coupled-cluster (UCC) ansatze. Despite being a systematic way of approaching the exact limit, the number of parameters in the standard UCC ansatze exhibits unfavorable scaling with respect to the system size, hindering its practical use on near-term quantum devices. Efforts have been taken to propose some variants of UCC ansatze with better scaling. In this paper we explore the parameter redundancy in the preparation of unitary coupled-cluster singles and doubles (UCCSD) ansatze employing spin-adapted formulation, small amplitude filtration, and entropy-based orbital selection approaches. Numerical results of using our approach on some small molecules have exhibited a significant cost reduction in the number of parameters to be optimized and in the time to convergence compared with conventional UCCSD-VQE simulations. Further, we also discuss the potential application of some machine learning techniques in further exploring the parameter redundancy, providing a possible direction for future studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗