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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

One Earth Energy FEED Process Design Basis

This report establishes the process design basis for the front-end engineering design (FEED) of a carbon capture and injection facility at One Earth Energy's (OEE) ethanol production plant in Gibson City, Illinois, developed as part of the Illinois Storage Corridor CarbonSAFE Phase III project. The facility is designed to compress and dehydrate up to approximately 458,000 metric tonnes of CO 2 per year, sourced directly from OEE's ethanol fermenters, for permanent injection into a saline aquifer approximately four miles from the plant. At normal operating conditions, the system will process 1,290 metric tonnes of CO 2 per day, assuming 355 operating days per year and an ethanol production rate of 160 million gallons per year. The proposed process trains a multistage centrifugal blower with a five-stage reciprocating compressor, delivering CO 2 to the injection wellhead at up to 1,500 psig. Triethylene glycol (TEG) dehydration, applied after the fourth compression stage, reduces water content to a target of 10 lb/MMscf, well within the 30 lb/MMscf injection limit. Beyond dehydration, no additional treatment is required; trace impurities including oxygen and nitrogen will remain in the injected stream. Key design considerations include the absence of spare cooling tower capacity at the site, necessitating new cooling infrastructure, and the need for a new electrical substation to support large motor loads. The facility is designed for continuous, largely unattended operation, monitored around the clock by existing OEE operations staff. This document serves as the foundational reference for all subsequent detailed engineering activities associated with the OEE CO 2 injection facility.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Optical-Gating of Spin-based Quantum States (Final Report)

This project developed a generalizable strategy for optical control of spin-based quantum states through the Photoisomerization-Induced Spin–Charge Excited State (PISCES) process, in which a photochromic spirooxazine ligand bound to an electronically bistable metal complex enables reversible, room-temperature optical switching of spin states in both dilute matrices and the solid state. A multidisciplinary team integrated synthesis, spectroscopy, theory, and surface science to establish design principles for opto-spintronic quantum materials. Systematic structure–property studies across four spirooxazine series revealed that donor–π–acceptor interactions govern thermal isomerization, which proceeds via a rotational pathway. Pulsed EPR measurements demonstrated millisecond-scale coherence times in cobalt-dioxolene-spirooxazine complexes, establishing their promise as optically addressable molecular qubits; the approach was extended to Cu(II), Ni(II), and lanthanide complexes, including optical modulation of zero-field splittings and clock transitions. Two-dimensional IR spectroscopy resolved picosecond ground-state population exchange dynamics, while ab initio calculations elucidated photoisomerization mechanisms and parametrized Hamiltonians for spin relaxation and decoherence. Toward device integration, the team fabricated 2D polymer scaffolds for covalent qubit organization, developed tip-enhanced Raman imaging of molecular monolayers, and demonstrated optical gating of gate voltage in spirooxazine-graphene field-effect transistors. The project produced numerous publications, dissertations, and presentations, and trained over 30 researchers.

2D polymers↗
DOE OSTI2026

Digital Silicon Photomultiplier Chip Testing

Silicon Photomultipliers (SiPMs) are highly sensitive photodetectors. Traditional analog SiPMs require complex external readout electronics. Digital SiPMs (dSiPMs) include digital readout circuitry directly on-chip, offering superior timing resolution, reduced power consumption and compact size, pixel-level masking for active noise reduction. The primary objectives of this study are to, verify digital logic integrity of the shift registers used for controlling the pixel masking circuit, and determine the dark count rate of individual pixels as a function of bias voltage and clock frequency. I observe and explain behavior of the shift register and counting circuit.

Graham, Bennett [U. Chicago (main)]↗
DOE OSTI2026

Captan+X Data Converter Integration

Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.

Espinoza, David [Illinois U., Urbana (main)]↗
DOE OSTI2026

Allan Variance is Bootstrap Aggregation for Spectral Estimation

Characterization of clocks and inertial sensors, such as accelerometers and gyroscopes, typically includes Allan variance analysis. Allan variance is ubiquitous in timing and navigation communities which may appear niche compared with generalized spectral analysis. This note provides some motivation for Allan Variance for audiences more familiar with spectral analysis.

Walker, Michael Ray [Sandia National Laboratories ↗
DOE OSTI2026

Calibration of the Nonlinear Viscoelastic SPECtacular Model for 828-CTBN/DEA/GMB and 828/Z/AlOx

Nonlinear viscoelastic model calibrations are developed for two filled epoxies: an adduct of Epon 828 DGEBA and CTBN cross-linked with diethanolamine (DEA) filled with glass microballoons, called 828-CTBN/DEA/GMB, and Epon 828 DGEBA cross-linked with Ancamine Z and filled with alumina, called 828/Z/AlOx. The thermo-mechanical responses of these materials are represented using the SPECtacular constitutive model, an extension of the Simplified Potential Energy Clock (SPEC) model. The model couples

Cundiff, Kenneth Noel [Sandia National Laboratorie↗
DOE OSTI2024

PPI DataHub Project Data Package: S. elongatus PCC 7942 Circadian Control Bioproduction Metabolomics (PB-DP5)

The purpose of this experiment was to evaluate how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942 in providing insights to strategies for enhanced bioproduction. Culture samples were collected at 0, 0.5, 1, 2, 4, 6, and 8 hours for extracellular sucrose analysis. Circadian metabolomics data was acquired using a Agilent single quadrupole gas chromatography-mass spectrometer and processed using Agilent Mass Hunter for targeted sucrose quantification. Metabolomic analysis of PCC 7942 light-dark cycle cultures transitioned to constant light revealed distinct temporal patterns in sucrose production. Processed metabolomic datasets are openly accessible from the PNNL DataHub project dataset download page and contain secondary processed GC-MS results files and supporting metadata materials linked to relevant source code information supporting data transparency and reuse.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

ARPA-E Grid Optimization (GO) Competition Challenge 1

The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each dataset consisted of a collection of power system network models of different sizes with associated operating scenarios (snapshots in time defining instantaneous power demand, renewable generation, generator and line availability, etc.). The datasets were of two types: Real-Time, which included starting-point information, and Online, which did not. Week-Ahead data is also provided for some cases but was not used in the Competition. Although most datasets were synthetic and generated by GRIDDATA, a few came from industry and were only used in the Final Event. All synthetic Input Data and Team Results for the GO Competition Challenge 1 for the Sandbox, Trial Events 1 to 3, and the Final Event along with problem, format, scoring and rules descriptions are available here. Data for industry scenarios will not be made public. Challenge 1, a minimization problem, required two computational steps. Solver 1 or Code 1 solved the base SCOPF problem under a strict wall clock time limit, as would be the case in industry, and reported the base case operating point as output, which was used to compute the Objective Function value that was used as the scenario score. The feasibility of the solution was provided by the Solver 2 or Code 2, which solves the power flow problem for all contingencies based on the results from Solver 1. This is not normally done in industry, so the time limits were relaxed. In fact, there were no time limits for Trial Event 1. This proved to be a mistake, with some codes running for more than 90 hours, and a time limit of 2 seconds per contingency was imposed for all other events. Entrants were free to use their own Solver 2 or use an open-source version provided by the Competition. Containers, such as Docker, were considered to improve the portability of codes, but none that could reliably support a multi-node parallel computing environment, e.g., MPI, could be found. For more information on the competition and challenge see the "GO Competition Challenge 1 Information" and "GO Competition Challenge 1 Additional Information" resources below.

ACOPF↗
DOE OSTI2025

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Unconventional compute methods and future challenges for superconducting digital computing

Superconducting digital computing (SDC) based on Josephson junctions (JJs) offers significant potential for enhancing compute throughput and reducing energy consumption compared to conventional room-temperature CMOS-based approaches. Current superconducting logic families exhibit diverse characteristics in clocking strategies, power management, and information encoding techniques. This paper reviews recent advancements in unconventional computing methods specifically designed for superconducting digital circuits, emphasizing temporal computing and pulse-train representations. Notable techniques include race logic (RL), temporal pulse train computing (U-SFQ), and temporal multipliers, each offering unique performance and area advantages suited to superconducting implementations. Additionally, this paper reviews innovations in superconducting coarse-grain reconfigurable architectures (CGRA), superconducting-specific on-chip communication architectures, cryogenic sensor interfaces, and quantum computing control electronics. Finally, we highlight research challenges that should be addressed to facilitate the widespread adoption of superconducting digital computing.

EDA tools↗
DOE OSTI2025

Gene network centrality analysis identifies key regulators coordinating day-night metabolic transitions in Synechococcus elongatus PCC 7942 despite limited accuracy in predicting direct regulator-gene interactions

Synechococcus elongatus PCC 7942 is a model organism for studying circadian regulation and bioproduction, where precise temporal control of metabolism significantly impacts photosynthetic efficiency and CO 2 -to-bioproduct conversion. Despite extensive research on core clock components, our understanding of the broader regulatory network orchestrating genome-wide metabolic transitions remains incomplete. We address this gap by applying machine learning tools and network analysis to investigate the transcriptional architecture governing circadian-controlled gene expression. While our approach showed moderate accuracy in predicting individual transcription factor-gene interactions - a common challenge with real expression data - network-level topological analysis successfully revealed the organizational principles of circadian regulation. Our analysis identified distinct regulatory modules coordinating day-night metabolic transitions, with photosynthesis and carbon/nitrogen metabolism controlled by day-phase regulators, while nighttime modules orchestrate glycogen mobilization and redox metabolism. Through network centrality analysis, we identified potentially significant but previously understudied transcriptional regulators: HimA as a putative DNA architecture regulator, and TetR and SrrB as potential coordinators of nighttime metabolism, working alongside established global regulators RpaA and RpaB. This work demonstrates how network-level analysis can extract biologically meaningful insights despite limitations in predicting direct regulatory interactions. The regulatory principles uncovered here advance our understanding of how cyanobacteria coordinate complex metabolic transitions and may inform metabolic engineering strategies for enhanced photosynthetic bioproduction from CO 2 .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Neutron-capture Element Abundances of 491 Stars in Milky Way Dwarf Satellite Galaxies from Medium-resolution Spectra

The chemical compositions of evolved stars in Local Group dwarf spheroidal galaxies (dSphs) provide insight into the galaxy’s past star formation and nucleosynthesis. Neutron-capture element abundances are especially interesting. In particular, s-process elements can provide a third chemical clock for resolving star formation histories in addition to core-collapse and Type Ia supernovae. Likewise, the primary sites of the r-process are still areas of extensive research. Until now, the number of stars with neutron-capture element abundances in dSphs has been limited by the need for stars bright enough for high-resolution spectroscopy. We present abundance measurements of the neutron-capture elements Sr, Y, Ba, and Eu with errors <0.4 dex—as well as new measurements of Mg—in 491 stars in Sculptor, Fornax, Draco, Sextans, and Ursa Minor. The large number of stars in our sample is possible because we used medium-resolution spectra from the DEIMOS spectrograph, assembling the largest homogeneous set of neutron-capture abundances in dSphs to date. By utilizing the abundances of both s- and r-process elements, we find evidence of an s-process contribution at early times in Sculptor from our measurements of [Ba/Fe]. This is a potential signature of s-process nucleosynthesis in fast-rotating massive stars. By comparing our measurements of [Eu/Fe] with [Mg/Fe], we show the need for an r-process source that has a short delay time to enrich stars in the dSphs. Thus, neutron star mergers are likely not the sole source of r-process material in dSphs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Spin-squeezed vector atomic magnetometry

Atomic magnetometers based on Zeeman shift measurement have the potential for high sensitivity and long-term stability. Like other atomic sensors, including atomic clocks and atom interferometers, the atomic magnetometer could, in principle, be augmented with spin squeezing for further sensitivity enhancement. However, existing atomic magnetometers are not compatible with spin squeezing because the atoms can hardly be in a pure quantum state during operation. Moreover, a natural challenge faced by an atomic magnetometer is the arbitrary direction of the magnetic field. In this paper, we propose a cold-atom-based magnetometer with spin squeezing that can measure both the magnitude and the direction of an arbitrary magnetic field. For experimentally accessible parameters, we show that the technique described above could potentially achieve a sensitivity nearly two orders of magnitude higher than that of the best existing magnetometers.

Li, Jinyang [Northwestern U.] (ORCID:0000000194328↗
DOE OSTI2025

In-situ mid-circuit qubit measurement and reset in a single-species trapped-ion quantum computing system

We implement in-situ mid-circuit measurement and reset (MCMR) operations on a trapped-ion quantum computing system by using metastable qubit states in $^{171}\textrm{Yb}^+$ ions. We introduce and compare two methods for isolating data qubits from measured qubits: one shelves the data qubit into the metastable state and the other drives the measured qubit to the metastable state without disturbing the other qubits. We experimentally demonstrate both methods on a crystal of two $^{171}\textrm{Yb}^+$ ions using both the $S_{1/2}$ ground state hyperfine clock qubit and the $S_{1/2}$-$D_{3/2}$ optical qubit. These MCMR methods result in errors on the data qubit of about $2\%$ without degrading the measurement fidelity. With straightforward reductions in laser noise, these errors can be suppressed to less than $0.1\%$. The demonstrated method allows MCMR to be performed in a single-species ion chain without shuttling or additional qubit-addressing optics, greatly simplifying the architecture.

Atomic Physics (physics.atom-ph)↗
DOE OSTI2026

Identification and mitigation of memory block timing issue in ITk ABCStar during ASIC production

The ABCStar is a mixed-signal front-end readout ASIC for the strips sensor portion of the ATLAS ITk detector being developed as part of the High-Luminosity LHC upgrade. In pre-production testing, a subtle design flaw was uncovered in the ABCStar that was reducing wafer yields in some manufactured lots from the expected 90% to as low as 2%. The root cause was determined to be a timing issue in the logic synthesized to control previously silicon proven memory blocks re-used for this ASIC. The solutions proposed included manufacturing process changes by the wafer foundry, changes to the operating parameters for the ABCStar in the detector, and the possibility that a redesign might be required. The two mitigation efforts were undertaken in parallel, with the process modification route a less desirable solution since already manufactured wafers would need to be scrapped in favour of the new ones. Based on a knowledge of the existing process, and testing done on the worst performing wafers, it was proposed that raising the core operating voltage of the ABCStar from 1.20V to 1.25V could address the timing issue by sufficiently speeding up its transistors. An extensive testing program that included the effects of temperature and radiation expected over the lifetime of the ITk detector was conducted to validate that approach. Those tests and studies proved that even the worst performing wafers would have yields over 80% with the 1.25V core voltage, and neither the modified process nor redesign would be required for ensuring reliable operation of the ITk. Based on testing, a further timing mitigation was implemented to provide an additional margin of reliability by increasing the duty cycle of the clock to the ABCStar. Testing of all ABCStar wafers has been completed and the production of the detector modules using these ASICs is now well underway as a result of the efforts detailed herein.

FOS: Physical sciences↗
DOE OSTI2026

Zooming in: SCREAM at 100 m using regional refinement over the San Francisco Bay Area

Pushing global climate models to large-eddy simulation (LES) scales over complex terrain has remained a major challenge. This study presents the first known implementation of a global model – SCREAM (Simple Cloud-Resolving E3SM Atmosphere Model) – at 100 m horizontal resolution using a regionally refined mesh (RRM) over the San Francisco Bay Area. Two hindcast simulations were conducted to test performance under both strong synoptic forcing and weak, boundary-layer-driven conditions. We demonstrate that SCREAM can stably run at LES scales while realistically capturing topography, surface heterogeneity, and coastal processes. The 100 m SCREAM-RRM substantially improves near-surface wind speed, temperature, humidity, and pressure biases compared to the baseline 3.25 km simulation, and better reproduces fine-scale wind oscillations and boundary-layer structures. These advances leverage SCREAM's scale-aware SHOC turbulence parameterization, which transitions smoothly across scales without tuning. Performance tests show that while CPU-only simulations remain costly, GPU acceleration with SCREAMv1 on NERSC's Perlmutter system enables two-day hindcasts to complete in under two wall-clock days. Our results open the door to LES-scale studies of orographic flows, boundary-layer turbulence, and coastal clouds within a fully comprehensive global modeling framework.

Geosciences↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Reusable Verification Components for High-Energy Physics readout ASICs

Verification is a critical aspect of designing front-end (FE) readout ASICs for High-Energy Physics (HEP) experiments. These ASICs share several similar functional features, resulting in similar verification objectives, which can be addressed using comparable verification strategies. This contribution presents a set of re-usable verification components for addressing common verification tasks, such as clock generation, reset handling, configuration, as well as hit and fault injections. The components were developed as part of the CHIPS initiative and they have been successfully used in the verification of multiple HEP ASICs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗