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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mechanochromic Palettes Based on Optical Rotation in Cholesteric Liquid Crystal Elastomers for Visual Signalling

Mechanochromic photonic materials present promising prospects for enhancing diverse facets of human life. Cholesteric liquid crystal elastomers (CLCEs) present immediate mechanochromic properties, allowing their utility in various fields, including camouflages, textiles, and anticounterfeiting. Nonetheless, it is essential to provide differentiated color information corresponding to diverse types and degrees of deformation for practical use in real life. Herein, the mechanochromic responses of CLCEs are investigated using their optical rotation under compression and uniaxial stretching. The CLCEs exhibit the same reflection colors indistinguishable for compression and uniaxial stretching due to their contracted pitches. In contrast, the linearly polarized light passing through deformed CLCEs can be modulated by optical rotation, resulting in distinct transmission colors that can be discerned through mechanical deformations. A visual signaling system with color information derived from optical rotation is demonstrated. By comprehending and manipulating the mechanoresponsive behavior of CLCEs, these materials can be advanced into innovative solutions with enhanced functionality and performance, thereby broadening their applications for human life enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pulsar Movement Animation and its Corresponding Signal Visualization for Timing Source

The global positioning system, widely used for synchronization in energy systems, faces vulnerabilities, while Pulsars—natural cosmic clocks—offer long-term stability as potential backup timing sources. Existing research lacks sufficient exploration of Pulsar signal animation under astrophysical factors, limiting practical applications. This study establishes a mathematical model based on the rotation dynamics of dual-beam Pulsars and implements dynamic signal visualization through MATLAB. The model dynamically illustrates the relative motion between Pulsar beams and observers via timeline calculations, beam intensity modeling, and rotation matrix derivation. A case study on the millisecond Pulsar J1939+2134 reveals that observer angles influence signal peak timing, while beam widths determine signal duration, highlighting the critical role of parameter calibration for timing accuracy. Open-source code and animation results are publicly shared, providing tools for interdisciplinary research. This study validates the feasibility of Pulsar-based timing in energy systems, offering new insights to enhance synchronization robustness.

Wu, Ori [ORNL] (ORCID:0000000326723410)↗
DOE OSTI2024

Mechanochromic Palettes of Cholesteric Liquid Crystal Elastomers for Visual Signaling

Mechanochromic photonic materials present promising prospects for enhancing diverse facets of human life. Cholesteric liquid crystal elastomers (CLCEs) present immediate mechanochromic properties, allowing their utility in various fields, including camouflages, textiles, and anticounterfeiting. Nonetheless, it is essential to provide differentiated color information corresponding to diverse types and degrees of deformation for practical use in real life. Herein, we investigate the mechanochromic responses of CLCEs using their optical rotation under compression and uniaxial stretching. The CLCEs exhibit the same reflection colors indistinguishable for compression and uniaxial stretching due to their contracted pitches. In contrast, the linearly polarized light passing through deformed CLCEs can be modulated by optical rotation, resulting in distinct transmission colors that can be discerned through mechanical deformations. We demonstrate a visual signaling system with color information derived from optical rotation. By comprehending and manipulating the mechanoresponsive behavior of CLCEs, we can advance these materials into innovative solutions with enhanced functionality and performance, thereby broadening their applications for human life enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unique interface and dynamics of the complex of HSP90 with a specialized cochaperone AIPL1

Photoreceptor phosphodiesterase PDE6 is central for visual signal transduction. Maturation of PDE6 depends on a specialized chaperone complex of HSP90 with aryl hydrocarbon receptor-interacting protein-like 1 (AIPL1). Disruption of PDE6 maturation underlies a severe form of retina degeneration. Here, we report a 3.9 Å cryoelectron microscopy (cryo-EM) structure of the complex of HSP90 with AIPL1. This structure reveals a unique interaction of the FK506-binding protein (FKBP)-like domain of AIPL1 with HSP90 at its dimer interface. Unusually, the N terminus AIPL1 inserts into the HSP90 lumen in a manner that was observed previously for HSP90 clients. Deletion of the 7 N-terminal residues of AIPL1 decreased its ability to cochaperone PDE6. Multi-body refinement of the cryo-EM data indicated large swing-like movements of AIPL1-FKBP. Modeling the complex of HSP90 with AIPL1 using crosslinking constraints indicated proximity of the mobile tetratricopeptide repeat (TPR) domain with the C-terminal domain of HSP90. Our study establishes a framework for future structural studies of PDE6 maturation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Circular Trajectory Approach for Online Sinusoidal Signal Distortion Monitoring and Visualization

The increasing complexity and uncertainties of modern power systems are placing significant demands on signal monitoring techniques. This work proposes the Circular Trajectory Approach (CTA) for online sinusoidal signal distortion monitoring and visualization. CTA can detect distortions of a sinusoidal signal. Compared with existing waveform anomaly detection techniques, CTA is faster in detection and less computation intensive. It thus supports edge devices and online applications. CTA also offers a new means of sinusoidal signal distortion visualization. It can reveal the distorted sections in a sinusoidal cycle and clearly display the distortions. The proposed approach is tested on real data from an open source EPRI dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Imaging system and method for enhanced visualization of near surface vascular structures

A sub-dermal structure visualization system and method is disclosed. The system may use an illumination module including: a near-infrared (NIR) light source adapted to substantially uniformly illuminate an imaged area including sub-dermal regions thereof with NIR light; and a first optical system including at least one optical element for controlling at least one of spectral and polarization properties of the NIR light prior to illuminating the imaged area. An imaging module rejects unwanted signals from an imaged area while passing desired optical signals that are to be received by an image acquisition module. The desired optical signals can comprise a vein visualization signal to assist in visualizing a vascular structure below a skin layer of a patient.

Demos, Stavros G.↗
DOE OSTI2022

Transience of the Retinal Output Is Determined by a Great Variety of Circuit Elements

Retinal ganglion cells (RGCs) encrypt stimulus features of the visual scene in action potentials and convey them toward higher visual centers in the brain. Although there are many visual features to encode, our recent understanding is that the ~46 different functional subtypes of RGCs in the retina share this task. In this scheme, each RGC subtype establishes a separate, parallel signaling route for a specific visual feature (e.g., contrast, the direction of motion, luminosity), through which information is conveyed. The efficiency of encoding depends on several factors, including signal strength, adaptational levels, and the actual efficacy of the underlying retinal microcircuits. Upon collecting inputs across their respective receptive field, RGCs perform further analysis (e.g., summation, subtraction, weighting) before they generate the final output spike train, which itself is characterized by multiple different features, such as the number of spikes, the inter-spike intervals, response delay, and the rundown time (transience) of the response. These specific kinetic features are essential for target postsynaptic neurons in the brain in order to effectively decode and interpret signals, thereby forming visual perception. We review recent knowledge regarding circuit elements of the mammalian retina that participate in shaping RGC response transience for optimal visual signaling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Developing Novel Performance Measures for Traffic Congestion Management and Operational Planning Based on Connected Vehicle Data

In this study, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers' clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles' abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%-15% of all moving vehicles in the Dallas-Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle's actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials - a common visualization of arterial signal performance for transportation planning and operations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Unsupervised multimodal fusion of in-process sensor data for advanced manufacturing process monitoring

Effective monitoring of manufacturing processes is crucial for maintaining product quality and operational efficiency. Modern manufacturing environments often generate vast amounts of complementary multimodal data, including visual imagery from various perspectives and resolutions, hyperspectral data, and machine health monitoring information such as actuator positions, accelerometer readings, and temperature measurements. However, fusing and interpreting this complex, high-dimensional data presents significant challenges, particularly when labeled datasets are unavailable or impractical to obtain. This paper presents a novel approach to multimodal sensor data fusion in manufacturing processes, inspired by the Contrastive Language-Image Pre-training (CLIP) model. We leverage contrastive learning techniques to correlate different data modalities without the need for labeled data, overcoming limitations of traditional supervised machine learning methods in manufacturing contexts. Our proposed method demonstrates the ability to handle and learn encoders for five distinct modalities: visual imagery, audio signals, laser position (x and y coordinates), and laser power measurements. By compressing these high-dimensional datasets into low-dimensional representational spaces, our approach facilitates downstream tasks such as process control, anomaly detection, and quality assurance. The unsupervised nature of our method makes it broadly applicable across various manufacturing domains, where large volumes of unlabeled sensor data are common. We evaluate the effectiveness of our approach through a series of experiments, demonstrating its potential to enhance process monitoring capabilities in advanced manufacturing systems. This research contributes to the field of smart manufacturing by providing a flexible, scalable framework for multimodal data fusion that can adapt to diverse manufacturing environments and sensor configurations. The proposed method paves the way for more robust, data-driven decision-making in complex manufacturing processes.

Contrastive Learning↗
DOE OSTI2024

Dimensionally Aligned Signal Projection Algorithms Library

Dimensionally aligned signal projection (DASP) algorithms are used to analyze fast Fourier transforms (FFTs) and generate visualizations that help focus on the harmonics for specific signals. At a high level, these algorithms extract the FFT segments around each harmonic frequency center, and then align them in equally sized arrays ordered by increasing distance from the base frequency. This allows for a focused view of the harmonic frequencies, which, among other use cases, can enable machine learning algorithms to more easily identify salient patterns. This work seeks to provide an effective open-source implementation of the DASP algorithms proposed by Vann et al. (2018) as well as functionality to help explore and test how these algorithms work with an interactive dashboard and signal-generation tool. The DASP library is implemented in Python and contains four types of algorithms for implementing these feature engineering techniques: fixed harmonically aligned signal projection (HASP), decimating HASP, interpolating HASP, and frequency aligned signal projection (FASP). Each algorithm returns a numerical array, which can be visualized as an image. The HASP algorithms are variations of the algorithms originally presented by Vann et al. (2018). For consistency, FASP, which is the terminology used for the short-time Fourier transform (STFT), has been implemented as part of the library to provide a similar interface to the STFT of the raw signal. Additionally, the library contains an algorithm to generate artificial signals with basic customizations such as the base frequency, sample rate, duration, number of harmonics, noise, and number of signals. Finally, the library provides multiple interactive visualizations, each of which is implemented using IPyWidgets and works in a Jupyter environment. A dashboard-style visualization is provided, which contains some common signal-processing visual components (signal, FFT, spectogram) updating in unison with the HASP functions (see Figure 1 below). Separate from the dashboard, an independent visualization is provided for each of the DASP algorithms as well as for the artifical signal generator. These visualizations are included in the library to aid in developing an intuitive understanding how the algorithms are affected by different input signals and parameter selections.

harmonics↗
DOE OSTI2025

A single-cell atlas of the bobtail squid visual and nervous system highlights molecular principles of convergent evolution

Abstract The cephalopod and vertebrate visual systems are a textbook example of convergent evolution with unknown molecular underpinnings. Here we characterize 98,537 single-cell transcriptomes in the bobtail squidEuprymna berryito understand how the cephalopod retina and optic lobes relate to the vertebrate retina. We confirm the overall relative simplicity of the cephalopod retina but identify two related photoreceptor cell subtypes expressing distinct r-opsins. By contrast, the adult optic lobe contains a diverse repertoire of neuronal and glial cell types, with a predominance of dopaminergic neurons. We show that cephalopod-specific gene duplicates probably contributed to this cell type diversification. Comparing neuronal cell population in the optic lobes of hatchlings and adults, we reveal a switch towards dopaminergic neurotransmitter usage with age, indicative of a maturation process. We further identify an FMRF-amide-based retrograde signal from the optic lobe towards the retina that supports the functional analogy of the cephalopod optic lobe cortex and the vertebrate inner retina in visual signal processing from a molecular standpoint. Finally, comparative analyses with vertebrate and arthropod cells suggest a scenario in which two photoreceptor types and two neuronal populations may have already been present in the eye of the bilaterian ancestor.

Environmental Sciences & Ecology↗
DOE OSTI2026

A non-intrusive framework using acoustic signals and deep learning for boiling diagnostics in visual-limited environments

Accurate monitoring of boiling heat transfer is critical for safeguarding high-power systems operating in environments where conventional optical diagnostics are hindered by radiation fields or restricted visual accessibility. This study presents a non-intrusive framework that integrates hydroacoustic sensing with deep learning to infer near-wall boiling characteristics and enable predictive thermal assessment without visual access. In a prototypical subcooled flow-boiling facility representative of the Isotope Production Facility (IPF) at Los Alamos, hydrophones capture boiling-induced acoustic emissions that are transformed into background-removed Short-Time Fourier Transform (STFT) spectrograms. A convolutional neural network (CNN) then regresses heat flux, wall superheat, and key bubble parameters directly from these spectrograms. The CNN achieved predictive accuracy under nominal conditions and demonstrated robustness and generalization under acoustic noise for Signal-to-Noise Ratios (SNRs) down to approximately 0 dB. When integrated into an ANSYS CFX wall-boiling model, the acoustically inferred parameters reproduced boiling curve and critical heat flux (CHF) values consistent with image-based benchmarks. Furthermore, the model retained reliable performance under moderate variations in bulk temperature, flow rate, and hydrophone placement, confirming its generalizability across practical boundary conditions. These results demonstrate the feasibility of hydroacoustic-based deep learning as a viable path toward real-time, radiation-tolerant boiling diagnostics and predictive thermal safety assessment in inaccessible systems such as the IPF.

42 ENGINEERING↗
DOE OSTI2023

Retina-inspired narrowband perovskite sensor array for panchromatic imaging

The retina is the essential part of the human visual system that receives light, converts it to neural signal, and transmits to brain for visual recognition. The red, green, and blue (R/G/B) cone retina cells are natural narrowband photodetectors (PDs) sensitive to R/G/B lights. Connecting with these cone cells, a multilayer neuro-network in the retina provides neuromorphic preprocessing before transmitting to brain. Inspired by this sophistication, we develop the narrowband (NB) imaging sensor combining R/G/B perovskite NB sensor array (mimicking the R/G/B photoreceptors) with a neuromorphic algorithm (mimicking the intermediate neural network) for high-fidelity panchromatic imaging. Compared to commercial sensors, we use perovskite “intrinsic” NB PD to exempt the complex optical filter array. In addition, we use an asymmetric device configuration to collect photocurrent without external bias, enabling a power-free photodetection feature. These results display a promising design for efficient and intelligent panchromatic imaging.

42 ENGINEERING↗
DOE OSTI2021

Interactive Web Application for Traffic Simulation Data Management and Visualization

As traffic simulation software becomes more effective for realistically simulating and analyzing traffic dynamics and vehicle interactions on the mesoscopic and microscopic level, the management, dissemination, and collaborative visualization of traffic simulation results produced by individual transportation planners presents a significant challenge. Existing online content management systems have a very limited capability in allowing users to query specific traffic simulation scenarios and geospatially visualize simulation results through shareable and interactive web interfaces. This paper presents a web-based application for promoting the archiving, sharing, and visualization of large-scale traffic simulation outputs. The application is developed to enhance cyber-physical controls, communications, and public education for collaborative transportation planning. Unique features of the web application include: (a) allowing users to upload their new traffic simulation scenarios (parameters and outputs), as well as search existing scenarios using easily accessible interfaces; (b) optimizing simulation output files with heterogeneous data formats and projected coordinate systems for web-based storage and management using a scalable and searchable data/metadata standard; (c) standardizing user-uploaded simulation outputs using web interfaces and data processing libraries with parallel computing capacity; and (d) providing shareable web visual interfaces for visualizing the traffic flow and signal information stored in simulation outputs (e.g., regional traffic patterns and individual vehicle interactions) and visually comparing multiple simulation outputs both spatially and temporally. Furthermore, the paper presents the conceptual design and implementation of this application, and demonstrates the application’s performance for sharing, comparing, and visualizing simulation outputs from VISSIM and SUMO, two commonly used traffic simulation software programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗