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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns

A technique, associated system and program code, for retrieving depth information about at least one surface of an object. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the object; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

Hassebrook, Laurence G.↗
NASA NTRS2010

System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns

A technique, associated system and program code, for retrieving depth information about at least one surface of an object, such as an anatomical feature. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the anatomical feature; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

Hassebrook, Laurence G.↗
DOE OSTI2024

Zircon-to-reidite phase transition enhanced by minor radiation damage: Implications for hypervelocity impacts

Reidite, a high-pressure phase of zircon, is increasingly identified at terrestrial impact sites. Despite its growing recognition, the potential applications for estimating minimum impact pressure face impediments due to existing discrepancies in the condition of zircon-reidite transformation, controversial models governing the transformation mechanism, and unclear effects of pre-existing radiation damage on reidite formation. Here, we show enhanced reidite formation by synchrotron X-ray diffraction, Raman spectroscopy, and transmission electron microscopy analyses of zircon grains that have experienced different alpha-decay doses from U and Th impurities and subsequent pressurization in diamond anvil cells. Below ~1 × 10 18 α-decay events/g, the α-decay-induced isolated point defects in the still crystalline zircon facilitate the minor atomic readjustments required for reidite formation. However, above this dose, the loss of long-range periodicity in severely damaged or even metamict zircon inhibits the transformation. The enhanced reidite formation by minor radiation damage coincides with the more common occurrence of reidite at impact sites for which the precursor zircon has a relatively lower alphadecay- event dose before the impact event. In addition, the detailed atomic-scale structures of twinned reidite provide unambiguous evidence for a characteristic internal stress-induced martensitic transition. Furthermore, these findings have important implications for interpreting the formation conditions of natural reidite due to the convergence of pressure from the static, shockwave, and natural reidite samples.

58 GEOSCIENCES↗
NASA NTRS2005

Artificial Immune System for Recognizing Patterns

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Huntsberger, Terrance↗
NASA NTRS2015

NASA's Vision for Potential Energy Reduction from Future Generations of Propulsion Technology

Through a robust partnership with the aviation industry, over the past 50 years NASA programs have helped foster advances in propulsion technology that enabled substantial reductions in fuel consumption for commercial transports. Emerging global trends and continuing environmental concerns are creating challenges that will very likely transform the face of aviation over the next 20-40 years. In recognition of this development, NASA Aeronautics has established a set of Research Thrusts that will help define the future direction of the agency's research technology efforts. Two of these thrusts, Ultra-Efficient Commercial Vehicles and Transition to Low-Carbon Propulsion, serve as cornerstones for the Advanced Air Transport Technology (AATT) project. The AATT project is exploring and developing high-payoff technologies and concepts that are key to continued improvement in energy efficiency and environmental compatibility for future generations of fixed-wing, subsonic transports. The AATT project is primarily focused on the N+3 timeframe, or 3 generations from current technology levels. As should be expected, many of the propulsion system architectures technologies envisioned for N+3 vary significantly from todays engines. The use of batteries in a hybrid-electric configuration or deploying multiple fans distributed across the airframe to enable higher bypass ratios are just two examples of potential advances that could enable substantial energy reductions over current propulsion systems.

Airbreathing Propulsion↗
NASA NTRS1997

Effects of Orientation on Recognition of Facial Affect

The ability to discriminate facial features is often degraded when the orientation of the face and/or the observer is altered. Previous studies have shown that gross distortions of facial features can go unrecognized when the image of the face is inverted, as exemplified by the 'Margaret Thatcher' effect. This study examines how quickly erect and supine observers can distinguish between smiling and frowning faces that are presented at various orientations. The effects of orientation are of particular interest in space, where astronauts frequently view one another in orientations other than the upright. Sixteen observers viewed individual facial images of six people on a computer screen; on a given trial, the image was either smiling or frowning. Each image was viewed when it was erect and when it was rotated (rolled) by 45 degrees, 90 degrees, 135 degrees, 180 degrees, 225 degrees and 270 degrees about the line of sight. The observers were required to respond as rapidly and accurately as possible to identify if the face presented was smiling or frowning. Measures of reaction time were obtained when the observers were both upright and supine. Analyses of variance revealed that mean reaction time, which increased with stimulus rotation (F=18.54, df 7/15, p (is less than) 0.001), was 22% longer when the faces were inverted than when they were erect, but that the orientation of the observer had no significant effect on reaction time (F=1.07, df 1/15, p (is greater than) .30). These data strongly suggest that the orientation of the image of a face on the observer's retina, but not its orientation with respect to gravity, is important in identifying the expression on the face.

Cohen, M. M.↗
DOE OSTI2024

Manipulating symmetry-breaking charge separation employing molecular recognition

The exploration of symmetry-breaking charge separation (SB-CS) is imperative when designing functional light-harvesting materials. Past explorations, however, have been confined to covalent systems, more often than not requiring complicated/demanding syntheses and facing inconvenient regulation of charge transfer processes. Here, in this work, we present a concept that regulates the efficiency of SB-CS through molecular recognition utilizing a pyridinium-based cyclophane as a host. This host undergoes photo-driven excited-state SB-CS. By employing different guests with distinct frontier molecular orbital energy levels, we have achieved comprehensive control of electron transfer pathways in the cyclophane, modulating between accelerated (>10-fold) intramolecular SB-CS involving superexchange and direct intermolecular electron transfer between the host and guest. The improvement in SB-CS efficiency results in catalytic activity for the photo-oxidation of a sulfur-mustard simulant. This research offers an opportunity for tuning SB-CS by utilizing molecular recognition, which holds the potential for achieving precise regulation without complicated organic syntheses.

charge transfer↗
DOE OSTI2025

Contrasting Time-Frequency Representations for Unknown Waveform Detection

Identifying unseen electromagnetic waveforms is critical for many applications, like interference management, electronic warfare and spectrum management. Traditionally this is done using statistical methods for anomaly detection, which has evolved to deep learning models for identifying the unseen data, formally termed as open set recognition. Some prior methods use a generative model to emulate open set data, which face challenges in generating synthetic samples for open set while simultaneously selecting an optimal discriminator for accurate classification. To alleviate this issue, we propose a discriminative model that effectively combines time and frequency domain features of communication signals for accurate predictions. We further introduce a cosine similarity loss that makes the domain specific features unique to enhance the prediction rate. Additionally, our model avoids generic feature vectors by extracting class-specific features during training, resulting in improved class representation. The experiment results show that this combined feature approach with cosine loss outperforms single-domain models and improves accuracy by 10% over models without cosine loss.

99 - GENERAL AND MISCELLANEOUS↗
NASA NTRS2010

Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

neural network↗
NASA NTRS1992

Ninth Annual NASA/Contractors Conference on Quality and Productivity. World Class Excellence: The Journey Continues. Keynote presentations

This coference provided an excellent forum for the members of the NASA community to share their experience and expertise in an effort to continuously improve the quality of the US space program. The topics covered include the following: NASA's approach to continual improvement; commitment to total quality; total quality at AlliedSignal Aerospace; organizational TQM; recognition of the 1992 Low Trophy Finalists; announcement of the 1992 Low Trophy Recipients; and the changing face of aerospace contracting.

Templeton, Geoffrey B.↗
NASA NTRS2006

Pattern-Recognition Processor Using Holographic Photopolymer

proposed joint-transform optical correlator (JTOC) would be capable of operating as a real-time pattern-recognition processor. The key correlation-filter reading/writing medium of this JTOC would be an updateable holographic photopolymer. The high-resolution, high-speed characteristics of this photopolymer would enable pattern-recognition processing to occur at a speed three orders of magnitude greater than that of state-of-the-art digital pattern-recognition processors. There are many potential applications in biometric personal identification (e.g., using images of fingerprints and faces) and nondestructive industrial inspection. In order to appreciate the advantages of the proposed JTOC, it is necessary to understand the principle of operation of a conventional JTOC. In a conventional JTOC (shown in the upper part of the figure), a collimated laser beam passes through two side-by-side spatial light modulators (SLMs). One SLM displays a real-time input image to be recognized. The other SLM displays a reference image from a digital memory. A Fourier-transform lens is placed at its focal distance from the SLM plane, and a charge-coupled device (CCD) image detector is placed at the back focal plane of the lens for use as a square-law recorder. Processing takes place in two stages. In the first stage, the CCD records the interference pattern between the Fourier transforms of the input and reference images, and the pattern is then digitized and saved in a buffer memory. In the second stage, the reference SLM is turned off and the interference pattern is fed back to the input SLM. The interference pattern thus becomes Fourier-transformed, yielding at the CCD an image representing the joint-transform correlation between the input and reference images. This image contains a sharp correlation peak when the input and reference images are matched. The drawbacks of a conventional JTOC are the following: The CCD has low spatial resolution and is not an ideal square-law detector for the purpose of holographic recording of interference fringes. A typical state-of-the-art CCD has a pixel-pitch limited resolution of about 100 lines/mm. In contrast, the holographic photopolymer to be used in the proposed JTOC offers a resolution > 2,000 lines/mm. In addition to being disadvantageous in itself, the low resolution of the CCD causes overlap of a DC term and the desired correlation term in the output image. This overlap severely limits the correlation signal-to-noise ratio. The two-stage nature of the process limits the achievable throughput rate. A further limit is imposed by the low frame rate (typical video rates) of low- and medium-cost commercial CCDs.

Chao, Tien-Hsin↗
DOE OSTI2025

Component Identification of Solid Biomass Fuels Using Reflected Light Microscopy: Interlaboratory Study 2

As nations transition toward sustainable energy systems, biomass has become a vital component of global energy portfolios. Derived from organic materials such as wood, agricultural residues, forestry byproducts, and organic waste, biomass is a renewable energy source with significant environmental and economic benefits. Responsible biomass energy production can improve waste management, reduce emissions of greenhouse gases, and mitigate environmental pollution. However, as the diversity of biomass-derived fuels increases, robust quality assessment methods are essential to ensure their efficiency, safety, and minimal environmental impact. Reflected light microscopy (RLM) is one such technique with the potential to complement conventional physico-chemical analyses by enabling a rapid identification of material constituents and impurities. To refine this methodology and evaluate the reproducibility of solid biomass component identification using RLM, an interlaboratory study (ILS) was conducted. The study involved the recognition of 58 components across 45 photomicrographs, with the participation of 65 scientists and students from 25 countries. The participants faced high difficulty identifying some of the marked components, and as a result, the percentage of correct answers ranged from 19.0 % to 98.3 %, with an average correct identification rate of 62.7 %. The most challenging aspects of the identification process included distinguishing between woody and non-woody (agro) biomass, accurately identifying petroleum-derived materials, and differentiating agro biomass from inorganic matter. The results suggest that while RLM is an important tool for characterizing solid biomass, further development of methodology guidelines and training are necessary to enhance its effectiveness. Future research should prioritize preparing detailed, image-rich, microscopic morphological descriptions of biomass fuel components, which could improve the accuracy and reliability of using RLM in biomass fuel characterization.

09 BIOMASS FUELS↗
DOE OSTI2025

A continental scale analysis reveals widespread root bimodality

An improved understanding of root vertical distribution is crucial for assessing plant-soil-atmosphere interactions and their influence on the land carbon sink. Here, we analyze a continental-scale dataset of fine roots reaching 2 meters depth, spanning from Alaskan tundra to Puerto Rican forests. Contrary to the expectation that fine root abundance decays exponentially with depth, we found root bimodality at ~20% of 44 sites, with secondary biomass peaks often below 1m. Root bimodality was more likely in areas with low total fine root biomass and was more frequent in shrublands than grasslands. Notably, secondary peaks coincided with high soil nitrogen content at depth. Our analyses suggest that deep soil nutrients tend to be underexploited, while root bimodality offers plants a mechanism to tap into deep soil resources. Our findings add to the growing recognition that deep soil dynamics are systematically overlooked, and calls for more research attention to this deep frontier in the face of global environmental change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Fingerprinting Interactions between Proteins and Ligands for Facilitating Machine Learning in Drug Discovery

Molecular recognition is fundamental in biology, underpinning intricate processes through specific protein–ligand interactions. This understanding is pivotal in drug discovery, yet traditional experimental methods face limitations in exploring the vast chemical space. Computational approaches, notably quantitative structure–activity/property relationship analysis, have gained prominence. Molecular fingerprints encode molecular structures and serve as property profiles, which are essential in drug discovery. While two-dimensional (2D) fingerprints are commonly used, three-dimensional (3D) structural interaction fingerprints offer enhanced structural features specific to target proteins. Machine learning models trained on interaction fingerprints enable precise binding prediction. Recent focus has shifted to structure-based predictive modeling, with machine-learning scoring functions excelling due to feature engineering guided by key interactions. Notably, 3D interaction fingerprints are gaining ground due to their robustness. Various structural interaction fingerprints have been developed and used in drug discovery, each with unique capabilities. This review recapitulates the developed structural interaction fingerprints and provides two case studies to illustrate the power of interaction fingerprint-driven machine learning. The first elucidates structure–activity relationships in β2 adrenoceptor ligands, demonstrating the ability to differentiate agonists and antagonists. The second employs a retrosynthesis-based pre-trained molecular representation to predict protein–ligand dissociation rates, offering insights into binding kinetics. Despite remarkable progress, challenges persist in interpreting complex machine learning models built on 3D fingerprints, emphasizing the need for strategies to make predictions interpretable. Binding site plasticity and induced fit effects pose additional complexities. Interaction fingerprints are promising but require continued research to harness their full potential.

3D structural interaction fingerprints↗
DOE OSTI2023

Structural basis of promiscuous substrate transport by Organic Cation Transporter 1

Organic Cation Transporter 1 (OCT1) plays a crucial role in hepatic metabolism by mediating the uptake of a range of metabolites and drugs. Genetic variations can alter the efficacy and safety of compounds transported by OCT1, such as those used for cardiovascular, oncological, and psychological indications. Despite its importance in drug pharmacokinetics, the substrate selectivity and underlying structural mechanisms of OCT1 remain poorly understood. Here, we present cryo-EM structures of full-length human OCT1 in the inward-open conformation, both ligand-free and drug-bound, indicating the basis for its broad substrate recognition. Comparison of our structures with those of outward-open OCTs provides molecular insight into the alternating access mechanism of OCTs. We observe that hydrophobic gates stabilize the inward-facing conformation, whereas charge neutralization in the binding pocket facilitates the release of cationic substrates. These findings provide a framework for understanding the structural basis of the promiscuity of drug binding and substrate translocation in OCT1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Water Structure and Dynamics Near the Surfaces of Silicalite-1

Zeolites are crystalline microporous aluminosilicates that are commonly used as industrial sorbents and membranes. Solvent structuring and dynamics near zeolite crystal surfaces are thought to influence interfacial transport and molecular recognition processes, as well as fundamental aspects of their crystallization from solution. Here, in this work, we use molecular dynamics (MD) simulations to investigate the behavior of interfacial water near the exposed (010), (100), and (101) crystal faces of silicalite-1, one of the most widely studied zeolites. The MD simulations reveal that water’s translational and orientational order is strongly influenced by the distinct corrugations, pore apertures, and functional group distributions presented on each surface. Specifically, we observe two distinct hydration layers near each surface. Water molecules in the contact layer are hydrogen bonded to two or three exposed surface silanol groups. The relative populations of water molecules that are doubly and triply hydrogen bonded to the surface strongly depend on the distribution of the exposed silanols. The interactions with exposed surface silanols also influence water’s local orientational order and distribution across each surface. We also show that the structuring of the solvent near the different faces of silicalite-1 strongly impacts the interfacial dynamics. The translational and orientational relaxation dynamics of water are slowest in the contact layers and correlate with structural ordering near each face.

42 ENGINEERING↗
DOE OSTI2025

An Application of Molecular Recognition for the Efficient Removal of Cesium from Hanford Nuclear Waste by Modular Solvent Extraction

In this work, experimental results leading to flowsheet design are presented showing how a calixarene-crown ether based solvent-extraction process can meet the challenge of cesium removal from nuclear tank wastes stored at the US Department of Energy Hanford site. Cleanup of legacy Cold War nuclear waste stored in underground tanks represents one of the greatest environmental challenges facing the US Department of Energy in terms of risk, cost, and effectiveness of applicable science and technology. Planning for the cleanup at the Hanford Site calls for the removal of the radioactive fission product 137Cs from its alkaline salt waste, including the use of modular processes that can be deployed near the tank farms. To meet the resulting need for extremely high selectivity, the Next-Generation Caustic-Side Solvent Extraction (NG-CSSX) process employing a calix[4]arene-crown ether in modified kerosene has been adapted to remove sub-millimolar cesium in competition with molar sodium and potassium in a high-nitrate alkaline matrix. Potassium loading in the solvent was determined in extraction, scrubbing, and stripping, leading to an empirical model closely approximating cesium distribution ratios for a variety of Hanford waste types. Process chemistry has been developed based on this molecular-recognition approach, focusing on the competitive effect of potassium loading and the mitigating process modifications needed, including extending the scrub section. The result is a modular flowsheet design that can achieve cesium decontamination factors well in excess of 15,000 even for the worst-case Hanford waste.

Williams, Neil [ORNL] (ORCID:000000023159226X)↗
NASA NTRS2006

Laboratory Simulation of Impacts upon Aluminum Foils of the Stardust Spacecraft: Calibration of Dust Particle Size from Comet Wild 2

Metallic aluminium alloy foils exposed on the forward, comet-facing surface of the aerogel tray on the Stardust spacecraft are likely to have been impacted by the same cometary particle population as the dedicated impact sensors and the aerogel collector. The ability of soft aluminium alloy to record hypervelocity impacts as bowl-shaped craters offers an opportunistic substrate for recognition of impacts by particles of a wide potential size range. In contrast to impact surveys conducted on samples from low Earth orbit, the simple encounter geometry for Stardust and Wild 2, with a known and constant spacecraft-particle relative velocity and effective surface-perpendicular impact trajectories, permits closely comparable simulation in laboratory experiments. For a detailed calibration programme we have selected a suite of spherical glass projectiles of uniform density and hardness characteristics, with well-documented particle size range from 10 microns to nearly 100 microns. Light gas gun buckshot firings of these particles at approximately 6km s)exp -1) onto samples of the same foil as employed on Stardust have yielded large numbers of craters. Scanning electron microscopy of both projectiles and impact features has allowed construction of a calibration plot, showing a linear relationship between impacting particle size and impact crater diameter. The close match between our experimental conditions and the Stardust mission encounter parameters should provide another opportunity to measure particle size distributions and fluxes close to the nucleus of Wild 2, independent of the active impact detector instruments aboard the Stardust spacecraft.

Kearsley, A. T.↗