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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
DOE OSTI2026

Graphical User Interface for a Biasing Board for the PSEC6

The PSEC6 is an application-specific integrated circuit (ASIC) designed for a readout system for a large area picosecond photodetector (LAPPD). The PSEC6 is currently in fabrication and pending testing. The testing system for the PSEC5, the previous iteration of the ASIC, required expensive and non-portable equipment, because the ASIC needs twelve adjustable reference voltages. The new testing system consists of an low-cost, open-source, cross-platform graphical user interface (GUI), a digital system, and a biasing board. The digital system is the interface between the GUI and biasing board, and can be implemented on a microcontroller or field-programmable gate array (FPGA). The biasing board contains twelve digital-to-analog converters (DACs) that are configurable via the GUI, which gives users the ability to write voltage values to all or specific DACs. The GUI was developed in C on Linux using the widget library GTK4 and cross-compiled for Windows compatibility. I2C and SPI protocols were implemented on an Adafruit Feather ESP32-S3 microcontroller to write commands to the DACs and PSEC6. A hardware implementation of the I2C protocol is in development on an FPGA. Since LAPPDs will be used by the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) at Fermilab, the PSEC6 testing system in this internship project can potentially benefit future neutrino research. The project is relevant to the Department of Energy’s microelectronics mission, because the PSEC6 is an ASIC that will handle fast time signals arriving from the detector for readout. It also provided experience with building a cross-platform user interface, practicing digital design and implementation in hardware description language (HDL), and using simulations to inform new design iterations.

Guerrero, Sasha Camila [North Central Coll.]↗
DOE OSTI2025

PickerXL, A Large Deep Learning Model to Measure Arrival Times from Noisy Seismic Signals

Precisely measuring seismic arrival times is a labor-intensive task but is critical for both earthquake monitoring and subsurface imaging. Recently published deep learning models have demonstrated superior performance compared to traditional automatic approaches for picking arrival times. Although existing deep learning models have shown promising results, further advancements are necessary as their performance is not yet satisfactory especially when applied to new regions and station networks. Increasing model size has led to improved performance in other machine learning applications. Here, we aimed to investigate whether enlarging deep learning models can increase performance on accepted benchmarks. We trained three models of varying sizes, small (1X), medium (4X), and large (16X), using globally distributed local and regional earthquake signals and background noise waveforms from a benchmark dataset, Stanford Earthquake Dataset. Our results indicate that the largest model (PickerXL) outperforms both the smaller models and Seisbench implementation of the PhaseNet model, which has the same number of parameters as our small model. The PickerXL model’s enhanced capacity to extract complex patterns from seismograms contributes to its superior arrival picking abilities compared to the smaller model.

Chai, Chengping [Oak Ridge National Laboratory (OR↗
DOE OSTI2025

Design of facilitated dissociation enables timing of cytokine signalling

Protein design has focused on the design of ground states, ensuring that they are sufficiently low energy to be highly populated. Designing the kinetics and dynamics of a system requires, in addition, the design of excited states that are traversed in transitions from one low-lying state to another. This is a challenging task because such states must be sufficiently strained to be poorly populated, but not so strained that they are not populated at all, and because protein design methods have focused on generating near-ideal structures. Here we describe a general approach for designing systems that use an induced-fit power stroke to generate a structurally frustrated and strained excited state, allosterically driving protein complex dissociation. X-ray crystallography, double electron–electron resonance spectroscopy and kinetic binding measurements show that incorporating excited states enables the design of effector-induced increases in dissociation rates as high as 5,700-fold. We highlight the power of this approach by designing rapid biosensors, kinetically controlled circuits and cytokine mimics that can be dissociated from their receptors within seconds, enabling dissection of the temporal dynamics of interleukin-2 signalling.

deformation dynamics↗
DOE OSTI2024

Hyperspectral acquisition with ScanImage at the single pixel level: application to time domain coherent Raman imaging

We present a comprehensive strategy and its practical implementation using the commercial ScanImage software platform to perform hyperspectral point scanning microscopy when a fast time-dependent signal varies at each pixel level. In the proposed acquisition scheme, the scan along the X-axis is slowed down while the data acquisition is maintained at a high pace to enable the rapid acquisition of the time-dependent signal at each pixel level. The ScanImage generated raw 2D images have a very asymmetric aspect ratio between X and Y, the X axis encoding both for space and time acquisition. The results are X-axis macro-pixel where the associated time-dependent signal is sampled to provide hyperspectral information. We exemplified the proposed hyperspectral scheme in the context of time-domain coherent Raman imaging, where a pump pulse impulsively excites molecular vibrations that are subsequently probed by a time-delayed probe pulse. In this case, the time-dependent signal is a fast acousto-optics delay line that can scan a delay of 4.5ps in 25 μ s at each pixel level. With this acquisition scheme, we demonstrate ultra-fast hyperspectral vibrational imaging in the low frequency range [10 cm −1 , 150 cm −1 ] over a 500 μm field of view (64 x 64 pixels) in 130ms (∼ 7.5 frames/s). The proposed acquisition scheme can be readily extended to other applications requiring the acquisition of a fast-evolving signal at each pixel level.

Metais, Samuel↗
DOE OSTI2025

DNN-based Signal Processing for Liquid Argon Time Projection Chambers

We investigate a deep learning-based signal processing for liquid argon time projection chambers (LArTPCs), a leading detector technology in neutrino physics. Identifying regions of interest (ROIs) in LArTPCs is challenging due to signal cancellation from bipolar responses and various detector effects observed in real data. We approach ROI identification as an image segmentation task, and employ a U-ResNet architecture. The network is trained on samples that incorporate detector geometry information and include a range of detector variations. Our approach significantly outperforms traditional methods while maintaining robustness across diverse detector conditions. This method has been adopted for signal processing in the Short-Baseline Neutrino program and provides a valuable foundation for future experiments such as the Deep Underground Neutrino Experiment.

Bhat, Avinay [Chicago U.]↗
DOE OSTI2024

Detecting dark matter substructures on small scales with fast radio bursts

The matter power spectrum is only weakly constrained on subgalactic scales, while physics beyond the Standard Model can leave unique imprints, especially on sub-parsec scales. We propose measuring the arrival-time difference of fast radio bursts (FRBs) along two adjacent sightlines as a new probe to dark matter substructures on scales down to ∼ 1 AU . We discuss two observational scenarios in which it may be possible to place interesting constraints on such models through the monitoring of repeating FRB sources: (i) By sending radio receivers to space to form a baseline of tens of AU or more and measuring the temporal variation of the arrival-time difference between receivers. (ii) By measuring the temporal variation of the arrival-time difference between two lensed images of one strongly lensed repeater. In both scenarios, obtaining interesting constraints requires correlating the voltage time series to measure the radio signal arrival time to sub-nanosecond precision. We find that two radio dishes separated by 20 AU may be sensitive to the enhancement of small-scale structures at ∼ 10 - 8 M ⊙ masses in the QCD axion dark matter scenario, or from an early epoch of matter domination with a reheating temperature up to 60 MeV. Other dark matter models, such as those composed of ∼ 10 - 13 M ⊙ primordial black holes produced during inflation, would also be probed by this method. We further show that a strong lensing situation of multiple images provides an equivalent ∼ 2000 AU ( σ v / 10 3 km s - 1 ) ( δ t / 10 yr ) baseline, for a typical velocity of dark matter substructures σ v and an observational time span δ . This is much more sensitive, but with the uncertainty that intervening decoherence from the interstellar medium may degrade the timing precision, and that spatial variation in the FRB emission spot may result in confounding signals. We show that the lensing magnifications of Type Ia supernovae constrain a similar quantity to such FRB timing, with present limits being equivalent to ruling out the same parameter space that would be probed by a 0.14 AU baseline.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Deep Multi-Agent Reinforcement Learning for Real-World Signalized Traffic Corridor Control

Signalized traffic control problem has been addressed recently with deep Reinforcement Learning (RL) approaches involving diverse state, action, and reward structures. While significant progress has been noted in the literature, open challenges still remain in the areas of adaptive signal phase timing, coordination in a multi-intersection corridor setting, and consideration of real-world traffic conditions. In the context of deep RL-based problem framing, extensions are needed that enable adaptive signal phase timings in an intersection agent's action space, computationally efficient information sharing among neighboring signalized intersection agents along a corridor, and experimentation in realistic simulation environments. In this paper, we develop a deep Advantage Actor Critic (A2C) multi-agent RL (MARL) approach capturing the research extensions above and apply it within a real-world calibrated Aimsun Next traffic corridor simulation model based on traffic data from the City of Coral Gables, Florida. For a multi-intersection corridor control setting, our numerical simulation experiments with a decentralized A2C MARL algorithm applied at different time periods led to a total average corridor travel delay reduction (expressed in seconds/mile averaged over vehicles) from 4.9% to 19.9% compared to state-of-the-art actuated control.

Shuvo, Salman S. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2024

Progress Toward Fast Decay Energy Spectroscopy for Actinide Analysis

Decay energy spectroscopy (DES) is an increasingly popular technique for measuring isotopic composition of actinide samples for nuclear safeguards applications. Current approaches for actinide DES utilize milligram-scale external gold absorbers (> 0.1 nJ/K) that are integrated with actinide samples through mechanical kneading and are thermally connected to microcalorimeters using indium or gold wire bonds. This leads to relatively slow sensor rise time and, consequently, limits counting speed to a few counts per second. We are developing faster metallic magnetic calorimeter-based DES by integrating actinide samples with magnetic sensor materials. This reduces signal rise time and enables high counting speed while maintaining the ability to knead the radioactive source with the absorber. We have measured signal rise time of 0.7 μs with a 1.5 mg external gold absorber using this approach. Here, we also demonstrated online DES operation using an Ortec DSPEC 50, a commercially available data acquisition system developed for semiconductor detectors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Systems and methods for optical measurement of cross-wind

Various technologies pertaining to optical measurement of cross-wind are described herein. A beam of light is emitted along a trajectory through a shooting space from a location of a shooter to a target using a laser. The beam is reflected by the target, and the beam is received at two optical detectors. Due to changes in the index of refraction of air along the path of the beam, an envelope signal atmospherically encoded on the beam is received at each of the two apertures at different times. A signal analyzer receives a signal from each of the detectors and outputs data indicative of an average speed of the cross-wind along the trajectory in the shooting space based upon a time delay between the signals.

Bagwell, Brett↗
DOE OSTI2024

The ETROC2 prototype for CMS MTD Endcap Timing Layer (ETL) upgrade

The ETROC2 prototype for CMS MTD Endcap Timing Layer (ETL) upgrade 520__ $$aThe Endcap Timing ReadOut Chip (ETROC) is designed to process LGAD signals with time resolution down to about 40-50ps per hit. The ETROC2 is the first full size (16x16) prototype design with the front-end based on and scaled up from the ETROC1 (4x4). The readout designs at pixel and global level and the system interfaces are all new and are compatible with the final chip specifications in terms of functionality. The ETROC2 is intended as a learning chip, as a stepstone to the ETROC3 which is intended as the pre-production design. The ETROC2 design and test results will be presented.

Gong, Datao↗
DOE OSTI2025

Multifrequency eddy-current detection of fast transient thermal signatures for in situ monitoring applications

Eddy-current (EC) nondestructive evaluation has a long history of use in a variety of ex situ defect monitoring applications because of its exquisite sensitivity to local material variations. Due to the relationship between a material's conductivity and its temperature, EC methods have also been used to investigate quasistatic, long-range temperature variations in casting applications. However, these techniques remain underutilized for the measurement of rapidly varying, spatially nonuniform temperature distributions. In this work, we construct a model system capable of generating repeatable temperature transients in steel plates and measure real-time eddy-current signals with millisecond time resolution and spatial resolution of the order of 1 mm. Using a combination of Multiphysics simulations, fast thermal imaging, and time-resolved holographic interferometry, we tease apart contributions to the eddy-current signals arising from temperature variations and transient plate deformation. Finally, we perform a systematic study in which we vary the plate thickness and the eddy-current excitation frequency to demonstrate that eddy-current techniques can provide information about a three-dimensional, time-varying, subsurface thermal distribution, which is inaccessible to the traditional thermal imaging techniques.

Rosenberg, Ethan R. [Lawrence Livermore National L↗
DOE OSTI2025

Modeling the differential rate for signal interactions in coincidence with noise fluctuations or large rate backgrounds

The characteristic energy of a relic dark matter interaction with a detector scales strongly with the putative dark matter mass. Consequently, experimental search sensitivity at the lightest masses will always come from interactions whose size is similar to noise fluctuations and low energy backgrounds in the detector. In this paper, we correctly calculate the net change in measured differential event rate due to low rate signal interactions that overlap in time with noise and backgrounds, accounting for both periods of time when the signal is coincident with noise/backgrounds and for the decreased amount of time in which only noise/backgrounds occur and we show that the introduction of random simulated signal events into the continuous raw data stream (a form of “salting”) provides a correct and practical implementation to estimate this net linear signal sensitivity. Unfortunately this does not apply to the situation with non negligible pileups as we show through explicit examples. Consequently, this exclusion technique should be complemented by less sensitive techniques that can separately exclude large rate, high pileup signal parameter space. An analysis threshold above the Gaussian-like noise component of the measured differential rate spectrum should also likely produce conservative limits. Though previous light mass dark matter searches did not correctly account for decreased background only live time effects in their signal sensitivity, conservative analysis choices likely protected their published limits from being nonconservative.

Li, Xinran↗
DOE OSTI2025

Computational Prediction of Infrasound Arrival Times and Directions from Stationary and Moving Impulsive Sources

This report addresses the need to predict infrasound signal arrival times and back azimuths at monitoring stations, enabling more focused and efficient searches within recorded waveform data. The primary challenge is estimating expected signal arrival windows for stationary and moving acoustic sources, such as chemical explosions, volcanic eruptions, meteoroids, and spacecraft re-entry events. To address this challenge, a reproducible methodology is described that uses simplified propagation speeds for boundary layer, tropospheric, stratospheric, and thermospheric atmospheric waveguides. While the Python source code itself is not freely available, this document provides detailed, step-by-step instructions, and equations enabling users to replicate and adapt the method independently. The method reliably predicts signal arrival intervals and back azimuths, thereby supporting rapid detection and accurate interpretation of infrasound events. Results demonstrate that this method effectively identifies plausible signal arrival intervals and directions, facilitating faster event detection and more reliable interpretation. This methodology directly supports atmospheric monitoring, planetary defense, and forensic analysis of explosive atmospheric events.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Discovery of an unconventional quantum echo by interference of Higgs coherence

Detecting photon echoes from superconducting Higgs modes is challenging due to the necessity of preserving and retrieving phase coherence encoded in multiple Higgs and quasiparticle (QP) excitations. Here, we demonstrate the emergence of a Higgs echo in niobium superconductors. This approach disentangles unique quantum pathways involving the Higgs mode and QP excitations. Using Higgs echo spectroscopy, we also uncover unconventional echo formation caused by inhomogeneous broadening and “soft” QP bands, which dynamically evolve under terahertz (THz) driving. Specifically, THz pulse pairs modulate the superconducting gap, imprinting coherence and forming a temporal “Higgs grating.” This grating produces echoes with distinctive characteristics: (i) echo rephasing spectral peaks at superconducting gap frequencies, (ii) asymmetric echo formation delays unlike those observed in atoms or semiconductors, and (iii) negative-time echo signals stemming from Higgs-QP anharmonic interactions. Combined with advanced time-frequency analysis, these findings distinguish Higgs from QP responses and clarify their intricate interactions in THz-driven superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

PySolate : A Python‐Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform

PySolate is a Python‐based toolset that implements the continuous wavelet transform and nonlinear thresholding operations to denoise or designal seismic data, following Langston and Mousavi (2019). This filtering approach can remove microseismic noise to isolate intermediate‐period seismic signals that are key to enabling full‐waveform modeling and analysis of smaller‐magnitude regional events. This approach is best for the application to signals with frequency or time separation of signal and noise, in contrast to Fourier analysis, which is effective when signal and noise are separated in frequency. We demonstrate the Python toolset using the six announced Democratic People’s Republic of Korea declared nuclear tests, showing the effectiveness of isolating the seismic signal compared to standard bandpass filtering. In conclusion, we also demonstrate the ease of using the toolset with any Python processing tools.

Asia↗
DOE OSTI2025

Integrating vehicle trajectory planning and arterial traffic management to facilitate eco-approach and departure deployment

Eco-approach and departure (EAD) enable continuous vehicle motion in urban signalized corridors. Since such a motion can extend to the EAD vehicles’ followers, it makes EAD a promising technology to benefit the traffic flow where automated vehicles and conventional vehicles coexist. Most existing EAD studies envision an ideal setting that neglects real-world operational conditions such as lane changes, multi-movement intersection configuration, partially automated fleet, and/or limited traffic state awareness. This study aims to fill the gap by designing an EAD algorithm considering real-world traffic operation constraints. The proposed algorithm uses a model predictive controller to minimize vehicle speed reduction and variation based on the real-time traffic signal control plan and measured queues at the intersection. The required inputs are readily available at many modern intersections. We observed that the proposed controller’s performance might degrade because of lane-changing maneuvers and lead-left turn traffic signals. These observations motivated our development of a lane change management strategy and a signal control implementation strategy to facilitate the EAD implementation. The lane change management strategies separate the EAD operations and lane-changing maneuvers in time and space. The signal control implementation strategy applies lag-left turn signals to enable EAD operation for both the through and left-turn vehicles. Compared to the non-EAD case, our EAD approach produces 2.5% to 7.8% energy savings while keeping similar intersection mobility. Notably, this approach brings about 2.5% to 3.6% energy savings in a 2% CAV case. This result demonstrates the feasibility of deploying EAD at low connected automated vehicle penetration rates.

Arterial corridor management↗