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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Super-porous Pt/CuO/Pt hybrid platform for ultra-sensitive and selective H 2 O 2 detection

A super-porous Pt/CuO/Pt hybrid electrode is demonstrated with extremely high sensing performance parameters for the hydrogen peroxide (H 2 O 2 ) detection. A unique physiochemical approach is adapted for the fabrication of 3-D super-porous Pt/CuO/Pt sensing platform. Here, the super-porous Pt/CuO/Pt hybrid platform demonstrates a superior sensitivity of 16,694 µA mM -1 cm -2 with a limit of detection of 2.91 nM (S/N = 3). It also demonstrates an excellent selectivity against the interfering molecules such as NaCl, fructose, ascorbic acid, citric acid, dopamine and glucose with a wide linear range. The demonstrated performance ranks the Pt/CuO/Pt hybrid platform as one of the best H 2 O 2 sensors as summarized in the Table 2. The super-porous CuO layer is fabricated by a dynamic hydrogen bubbling technique of electrochemical deposition and metallic Pt NP decoration is achieved by the physical vapor deposition (PVD) and post-annealing. The super-porous CuO layer offers a drastically improved electrochemical active surface area, and the Pt NP decoration offers a significantly improved conductivity and improved charge accumulation for the H 2 O 2 reduction. The DFT simulations confirm the predominance of CuO over Cu 2 O and Pt over Pd for the H 2 O 2 detection based on the adsorption energy, density of states and charge accumulation calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Delivering Robust Proton-Only Sensing of Hyperpolarized [1,2- 13 C 2 ]-Pyruvate Using Broad-Spectral-Range Nuclear Magnetic Resonance Pulse Sequences

Hyperpolarized [1- 13 C]pyruvate is the leading hyperpolarized injectable contrast agent and is currently under evaluation in clinical trials for molecular imaging of metabolic diseases, including cardiovascular disease and cancer. One aspect limiting broad scalability of the technique is that hyperpolarized 13 C MRI requires specialized 13 C hardware and software that are not generally available on clinical MRI scanners, which employ proton-only detection. Here, we present an approach that uses pulse sequences to transfer 13 C hyperpolarization to methyl protons for detection of the 13 C– 13 C pyruvate singlet, employing proton-only excitation and detection only. The new pulse sequences are robust to the B 1 and B 0 magnetic field inhomogeneities. The work focuses on singlet-to-magnetization (S2M) and rotor-synchronized (R) pulses, both relying on trains of hard pulses with broad spectral width coverage designed to effectively transform hyperpolarized 13 C 2 -singlet hyperpolarization to 1 H polarization on the CH 3 group of [1,2- 13 C 2 ]pyruvate. Finally, this approach may enable a broader adoption of hyperpolarized MRI as a molecular imaging technique.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Front-End Design for SiPM-Based Monolithic Neutron Double Scatter Imagers

Neutron double scatter imaging exploits the kinematics of neutron elastic scattering to enable emission imaging of neutron sources. Due to the relatively low coincidence detection efficiency of fast neutrons in organic scintillator arrays, imaging efficiency for double scatter cameras can also be low. One method to realize significant gains in neutron coincidence detection efficiency is to develop neutron double scatter detectors which employ monolithic blocks of organic scintillator, instrumented with photosensor arrays on multiple faces to enable 3D position and multi-interaction time pickoff. Silicon photomultipliers (SiPMs) have several advantageous characteristics for this approach, including high photon detection efficiency (PDE), good single photon time resolution (SPTR), high gain that translates to single photon counting capabilities, and ability to be tiled into large arrays with high packing fraction and photosensitive area fill factor. However, they also have a tradeoff in high uncorrelated and correlated noise rates (dark counts from thermionic emissions and optical photon crosstalk generated during avalanche) which may complicate event positioning algorithms. We have evaluated the noise characteristics and SPTR of Hamamatsu S13360-6075 SiPMs with low noise, fast electronic readout for integration into a monolithic neutron scatter camera prototype. The sensors and electronic readout were implemented in a small-scale prototype detector in order to estimate expected noise performance for a monolithic neutron scatter camera and perform proof-of-concept measurements for scintillation photon counting and three-dimensional event positioning.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Blockchain based Communication Architectures with Applications to Private Security Networks

Existing communication protocols in high consequence security networks are highly centralized. While this naively makes the controls easier to physically secure, external actors require fewer resources to disrupt the system because there are fewer points in the system can be destroyed or interrupted without the entire system failing. We present a solution to this problem using a proof-of-work-based blockchain implementation built on MultiChain. We construct a test-bed network containing two types of data input: visual imagers and microwave sensor information. These data types are ubiquitous in perimeter intrusion detection security systems and allow a realistic representation of a real-world network architecture. The cameras in this system use an object detection algorithm to nd important targets in the scene. The raw data from the camera and the outputs from the detection algorithm are then placed in a transaction on the distributed ledger. Similarly, microwave data is used to detect relevant events and are placed in a transaction. These transactions are then bundled into blocks and broadcast to the rest of the network using the Bitcoin-based MultiChain protocol. We develop five tests to examine the security metrics of our network. We performed the five security metric test using different sized networks from 7 to 39 nodes to determine how the metrics scale with respect to size. We nd that when compared to a centralized architecture our implementation provides a resiliency increase that is expected from a blockchain-based protocol without slowing the system so much that a human operator would notice. Furthermore, our approach is able to detect tampering in real time. Based on these results, we theorize that security networks in general could use a blockchain-based approach in a meaningful way.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Pluto's Ultraviolet Spectrum, Surface Reflectance, and Airglow Emissions

During the New Horizons spacecraft’s encounter with Pluto, the Alice ultraviolet spectrograph conducted a series of observations that detected emissions from both the interplanetary medium (IPM) and Pluto. In the direction of Pluto, the IPM was found to be 133.4 ± 0.6 R at Lyα, 0.24 ± 0.02 R at Lyβ, and <0.10 R at He i 584 Å. We analyzed 3900 s of data obtained shortly before closest approach to Pluto and detect airglow emissions from H i, N i, N ii, N{sub 2}, and CO above the disk of Pluto. We find Pluto’s brightness at Lyα to be 29.3 ± 1.9 R, in good agreement with preencounter estimates. The detection of the N ii multiplet at 1085 Å marks the first direct detection of ions in Pluto’s atmosphere. We do not detect any emissions from noble gases and place a 3σ upper limit of 0.14 R on the brightness of the Ar i 1048 Å line. We compare preencounter model predictions and predictions from our own airglow model, based on atmospheric profiles derived from the solar occultation observed by New Horizons, to the observed brightness of Pluto’s airglow. Although completely opaque at Lyα, Pluto’s atmosphere is optically thin at wavelengths longer than 1425 Å. Consequently, a significant amount of solar far-UV light reaches the surface, where it can participate in space weathering processes. From the brightness of sunlight reflected from Pluto, we find the surface has a reflectance factor (I/F) of 17% between 1400 and 1850 Å. We also report the first detection of a C{sub 3} hydrocarbon molecule, methylacetylene, in absorption, at a column density of ∼5 × 10{sup 15} cm{sup −2}, corresponding to a column-integrated mixing ratio of 1.6 × 10{sup −6}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Semi-supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost

Multireference (MR) diagnostics are common tools for identifying strongly correlated electronic structure that makes single-reference (SR) methods (e.g., density functional theory or DFT) insufficient for accurate property prediction. However, MR diagnostics typically require computationally demanding correlated wave function theory (WFT) calculations, and diagnostics often disagree or fail to predict MR effects on properties. To overcome these challenges, we introduce a semi-supervised machine learning (ML) approach with virtual adversarial training (VAT) of an MR classifier using 15 WFT and DFT MR diagnostics as inputs. In semi-supervised learning, only the most extreme SR or MR points are labeled, and the remaining point labels are learned. The resulting VAT model outperforms the alternatives, as quantified by the distinct property distributions of SR- and MR-classified molecules. Additionally, to reduce the cost of generating inputs to the VAT model, we leverage the VAT model’s robustness to noisy inputs by replacing WFT MR diagnostics with regression predictions in an MR decision engine workflow that preserves excellent performance. We demonstrate the transferability of our approach to larger molecules and those with distinct chemical composition from the training set. This MR decision engine demonstrates promise as a low-cost, high-accuracy approach to the automatic detection of strong correlation for predictive high-throughput screening.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Prompt Detection of Fast Optical Bursts with the Vera C. Rubin Observatory

Abstract The transient optical sky has remained largely unexplored on very short timescales. While there have been some experiments searching for optical transients from minutes to years, none have had the capability to distinguish millisecond fast optical bursts (FOBs). Such very fast transients could be the optical counterparts of fast radio bursts, the prompt emission from γ -ray bursts, or other previously unknown phenomena. Here, we investigate a novel approach to the serendipitous detection of FOBs, which relies on searching for anomalous spatial images. In particular, due to their short duration, the seeing-distorted images of FOBs should look characteristically different than those of steady sources in a standard optical exposure of finite duration. We apply this idea to simulated observations with the Vera C. Rubin Observatory, produced by tracing individual photons through a turbulent atmosphere, and down through the optics and camera of the Rubin telescope. We compare these simulated images to steady-source star simulations in 15 s integrations, the nominal Rubin exposure time. We report the classification accuracy results of a neural network classifier for distinguishing FOBs from steady sources. From this classifier, we derive constraints in duration–intensity parameter space for unambiguously identifying FOBs in Rubin observations. We conclude with estimates of the total number of detections of FOB counterparts to FRBs expected during the 10 yr Rubin Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Using the optimal combined index weight ratio to improve the probability of anomaly detection in big area additive manufacturing

Big Area Additive Manufacturing (BAAM) of composites requires significant time, energy, and material, so it is critical to reduce production inefficiencies to make functional parts without multiple iterations. Statistical process control coupled with Principal Component Analysis (PCA) is a powerful technique that provides a quick, computationally inexpensive, and intuitive way for operators to detect defects that form in a manufacturing process without massive datasets. Recently, a combined index that is a weighted sum of the Hotelling's T 2 and squared residual error statistics has been proposed that can be monitored in one chart, improving interpretation accuracy and simplicity. However, the literature does not offer a formal method to optimise the weights. Here, we introduce two new approaches to the traditional weight selection approach using simulated and BAAM image data. Approach 1 uses a theoretically motivated optimum inspired by probabilistic principal component analysis. Approach 2 systematically varies the ratio of the weights to find the optimum. We show that approach 1 delivers optimal anomaly detection performance in select cases while approach 2 fares better in practice. Surprisingly, we also show that choosing a more complex PCA model has a minimal negative impact on anomaly detection performance compared to a more simplistic model.

3-dimensional printing↗
DOE OSTI2021

An ensemble method for nuclei detection of overlapping cervical cells

The Pap test is a preventive approach that requires specialized and labor-intensive examination of cytological preparations to track potentially cancerous cells from the internal and external cervix surface. A cytopathologist must analyze many microscopic fields while screening for abnormal cells. Therefore the expectation is that a support decision system could assist with screening the most relevant cells, for example, by identifying sub-cellular abnormalities, such as changes in the nuclei features. Here, this work proposes a computational method for cervical nuclei detection aimed to reduce the workload of cytopathologists.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Detection of Stealthy False Data Injection Attacks in Unobservable Distribution Networks

In this paper, a composite scheme is proposed for detecting stealthy data manipulation attacks on distribution system which is unobservable with standard least squares based state estimators. This technique has three stages where the process of data imputation, voltage phasor estimation and the bad data detection are carried out in a systematic manner. The proposed approach is then integrated with moving target defense strategies which perturbs the network parameters to reveal stealthy false data injection attacks. The proposed approach is tested is validated on a three-phase, unbalanced 37-node distribution system and its results are presented. It is shown that the proposed approach has the ability to accurately detect the presence of FDI attacks using limited measurements (i.e., the test system is unobservable).

Rajasekaran, James K.↗
DOE OSTI2021

Contrast and Temperature Dependence of Multi-epoch High-resolution Cross-correlation Exoplanet Spectroscopy

While high-resolution cross-correlation spectroscopy (HRCCS) techniques have proven effective at characterizing the atmospheres of transiting and nontransiting hot Jupiters, the limitations of these techniques are not well understood. We present a series of simulations of one HRCCS technique, which combines the cross-correlation functions from multiple epochs, to place temperature and contrast limits on the accessible exoplanet population for the first time. We find that planets approximately Saturn-sized and larger within ∼0.2 au of a Sun-like star are likely to be detectable with current instrumentation in the L band, a significant expansion compared with the previously studied population. Cooler (T {sub eq} ≤ 1000 K) exoplanets are more detectable than suggested by their photometric contrast alone as a result of chemical changes that increase spectroscopic contrast. The L-band CH{sub 4} spectrum of cooler exoplanets enables robust constraints on the atmospheric C/O ratio at T {sub eq} ∼ 900 K, which have proven difficult to obtain for hot Jupiters. These results suggest that the multi-epoch approach to HRCCS can detect and characterize exoplanet atmospheres throughout the inner regions of Sun-like systems with existing high-resolution spectrographs. We find that many epochs of modest signal-to-noise ratio (S/N{sub epoch} ∼ 1500) yield the clearest detections and constraints on C/O, emphasizing the need for high-precision near-infrared telluric correction with short integration times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Securing Inverter Communication: Proactive Intrusion Detection and Mitigation System to Tap, Analyze, and Act

The electric grid has undergone rapid, revolutionary changes in recent years; from the addition of advanced smart technologies to the growing penetration of distributed energy resources (DERs) to increased interconnectivity and communications. However, these added communications, access interfaces, and third-party software to enable autonomous control schemes and interconnectivity also expand the attack surface of the grid. To address the gap of DER cybersecurity and secure the grid-edge to motivate a holistic, defense-in-depth approach, a proactive intrusion detection and mitigation system (PIDMS) device was developed to secure PV smart inverter communications. The PIDMS was developed as a distributed, flexible bump-in-the-wire (BITW) solution for protecting PV smart inverter communications. Both cyber (network traffic) and physical (power system measurements) are processed using network intrusion monitoring tools and custom machinelearning algorithms for deep packet analysis and cyber-physical event correlation. The PIDMS not only detects abnormal events but also deploys mitigations to limit or eliminate system impact; the PIDMS communicates with peer PIDMSs at different locations using the MQTT protocol for increased situational awareness and alerting. The details of the PIDMS methodology and prototype development are detailed in this report as well as the evaluation results within a cyber-physical emulation environment and subsequent industry feedback.

14 SOLAR ENERGY↗
DOE OSTI2020

Probabilistic Look-ahead Contingency Analysis Integration with Commercial Tool and Practical Data

This paper presents an initial effort of integrating a smart sampling-based probabilistic look-ahead contingency analysis algorithm with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool as a proof-of-concept for a seamless research tool integration using real world large-scale grid data. With the increasing impact of random forces such as variable generation and load, their stochastic behaviors cannot be ignored. However, the current practices are still dominated by deterministic tools. They are becoming increasingly inadequate for the future grid. The developed look-ahead contingency analysis algorithm incorporates forecast errors of variable energy and load to address the challenges brought by the increasing uncertainty of power system. The algorithm can reveal the potential violations caused by the variance of variable energy and load that are not normally detected by traditional deterministic approaches. To test its performance under practical environments ( real data with real commercial tool), significant efforts have been made to prepare test cases, modify GE EMS tool, and adapt an extreme value distribution algorithm to analyze the GE EMS’s violation-only outputs. The test results clearly demonstrate the effectiveness of the developed algorithm as new transformer violations that were not previously detected have been identified. This performance provides better situational awareness to engineers for their decision-making process under uncertainty. Moreover, with the discussion of computational performance and future work, this paper has shown a clear path for integrating the probabilistic algorithm with commercial tools to make us better equipped for the changing power system.

Modeling and simulation of power systems, constrai↗
DOE OSTI2021

Interaction of amphiphilic lipoarabinomannan with host carrier lipoproteins in tuberculosis patients: Implications for blood-based diagnostics

Lipoarabinomannan (LAM), an amphiphilic lipoglycan of the Mycobacterium tuberculosis cell wall, is a diagnostic target for tuberculosis. Previous work from our laboratory and others suggests that LAM is associated with host serum lipoproteins, which may in turn have implications for diagnostic assays. Our team has developed two serum assays for amphiphile detection: lipoprotein capture and membrane insertion. The lipoprotein capture assay relies on capture of the host lipoproteins, exploiting the biological association of host lipoprotein with microbial amphiphilic biomarkers to “concentrate” LAM. In contrast, the membrane insertion assay is independent of the association between pathogen amphiphiles and host lipoprotein association, and directly captures LAM based on its thermodynamic propensity for association with a supported lipid membrane, which forms the functional surface of an optical biosensor. In this manuscript, we explored the use of these assays for the detection of LAM in sera from adults whose tuberculosis status had been well-characterized using conventional microbiological tests, and endemic controls. Using the lipoprotein capture assay, LAM signal/noise ratios were >1.0 in 29/35 (83%) individuals with culture-confirmed active tuberculosis, 8/13 (62%) individuals with tuberculosis symptoms, but no positive culture for M . tuberculosis , and 0/6 (0%) symptom-free endemic controls. To evaluate serum LAM levels without bias associated with potential differences in circulating host lipoprotein concentrations between individuals, we subsequently processed available samples to liberate LAM from associated host lipoprotein assemblies followed by direct detection of the pathogen biomarker using the membrane insertion approach. Using the membrane insertion assay, signal/noise for detection of serum LAM was greater than that observed using the lipoprotein capture method for culture-confirmed TB patients (6/6), yet remained negative for controls (2/2). Taken together, these results suggest that detection of serum LAM is a promising TB diagnostic approach, but that further work is required to optimize assay performance and to decipher the implications of LAM/host lipoprotein associations for diagnostic assay performance and TB pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Detecting anomalous SRF cavity behavior with unsupervised learning

We present an unsupervised learning framework for detecting anomalous superconducting radio-frequency (SRF) cavity behavior at the Continuous Electron Beam Accelerator Facility (CEBAF), emphasizing its initial performance and effectiveness. Key to the system’s success was the development of data acquisition systems (DAQs) that capture fast-sampled, information-rich signals, essential for detecting transient effects. The approach involves creating daily cavity-specific models using principal component analysis to handle variations in rf signal behavior and mitigate performance degradation from data drift. This unsupervised method eliminates the need for expensive labeling by continuously updating models with recent data. Deployed and operational for 3 months before a scheduled shutdown, the system successfully identified several issues with DAQ signals, confirming its effectiveness. Despite access to only a fraction of CEBAF’s SRF cavity signals, the framework efficiently detected several instances requiring intervention, demonstrating a significant improvement over traditional, labor-intensive methods of manual plot inspection. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Metagenome-Guided Proteomic Quantification of Reductive Dehalogenases in the Dehalococcoides mccartyi -Containing Consortium SDC-9

At groundwater sites contaminated with chlorinated ethenes, fermentable substrates are often added to promote reductive dehalogenation by indigenous or augmented microorganisms. Contemporary bioremediation performance monitoring relies on nucleic acid biomarkers of key organohalide-respiring bacteria, such as Dehalococcoides mccartyi (Dhc). In this work, metagenome sequencing of the commercial, Dhc-containing consortium, SDC-9, identified 12 reductive dehalogenase (RDase) genes, including pceA (two copies), vcrA, and tceA, and allowed for specific detection and quantification of RDase peptides using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Shotgun (i.e., untargeted) proteomics applied to the SDC-9 consortium grown with tetrachloroethene (PCE) and lactate identified 143 RDase peptides, and 36 distinct peptides that covered greater than 99% of the protein-coding sequences of the PceA, TceA, and VcrA RDases. Quantification of RDase peptides using multiple reaction monitoring (MRM) assays with 13 C-/ 15 N-labeled peptides determined 1.8 × 10 3 TceA and 1.2 × 10 2 VcrA RDase molecules per Dhc cell. Ultimately, the MRM mass spectrometry approach allowed for sensitive detection and accurate quantification of relevant Dhc RDases and has potential utility in bioremediation monitoring regimes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An Active Detection Scheme for Sensor Spoofing in Grid-tied PV Systems

In this paper an active detection scheme for sensor spoofing (manipulated externally via a cyber attack) in grid-tied PV systems is discussed. The core of the proposed active detection scheme is to introduce a private (secret) watermarking signal into the control inputs of the DC-DC converter and DC-AC inverter stages to detect any malicious spoofing (manipulation) of voltage/current sensor measurements controlling both the DC-DC converter maximum power point tracking (MPPT) stage and the DC-AC inverter of the grid-tied PV system. Several types of possible spoofing mechanisms (attack models) are discussed. The proposed sensor spoofing attack detector system consists of injecting a small magnitude of digital watermarking signal (DWS) and conduct three statistical watermark tests on the reported sensor measurements to determine if a) the proposed system is healthy and operating as expected b) if sensor signals were spoofed (manipulated) externally or c) if a particular sensor is malfunctioning due to a faulty hardware. It is shown via extensive simulations that the proposed DWS approach is robust in detecting malicious external manipulation of sensors controlling the grid tied PV system. A testing platform is currently under development and the experimental results will be discussed in the conference presentation.

Ibrahim, Hasan↗
DOE OSTI2021

Multiplexing of frequency-modulation spectroscopy by spread-spectrum codes, demonstrated in continuous-wave LIDAR

Frequency-modulation spectroscopy (FMS) is generally suited to code-division multiplexing, and we demonstrate that capacity in a form of continuous-wave LIDAR, utilizing a sharp CO 2 absorption transition at 1.6 µm in simple ranging setups. The approach retains the advantages of FMS, including coherent detection and good rejection of broad absorption backgrounds. Extensions of this multiplexed approach to the continuous, simultaneous detection of several transitions would come by transmitting an encoded combination of frequency-modulated carriers, each tuned to detect a unique absorption transition. Signal analysis at the receiver involves a simple process of de-multiplexing that, in a general application, reveals targets at various distances and the absorption-related FMS signals in between.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗