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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

U.S. advanced and novel accelerator beam test facilities

Demonstrating the viability of Advanced Accelerator Concepts (AAC) relies on experimental validation. Over the last three decades, the U.S. has maintained a portfolio of advanced and novel accelerator test facilities to support research critical to AAC. The facilities have enabled pioneering developments in a wide variety of beam and accelerator physics, including plasma-wakefield and structure-wakefield acceleration. This work provides an overview of the current portfolio of U.S. facilities possessing charged particle drive beams with high energies, on the order of tens of joules per pulse, or drive lasers with high peak powers, on the order of a petawatt, and are actively conducting AAC research.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Performance of a coarsely pixelated LAPPD photosensor for the SoLID gas Cherenkov detectors

The SoLID spectrometer's gas Cherenkov counters require photosensors that operate in a high luminosity and high background environment. The reference design features arrays of 9 or 16 tiled multi-anode photomultipliers (MaPMTs), distributed across 32 sectors, to serve the light-gas and heavy-gas Cherenkov counters, respectively. To assess the viability of a pixelated INCOM Large Area Picosecond Photodetector (LAPPD TM ) as an alternative photosensor to replace MaPMT arrays in either detector, we evaluated its performance under realistic SoLID running conditions in Hall C at the Thomas Jefferson National Accelerator Facility (Jefferson Lab). The results of this test confirmed that the coarse-pixelated (2.5 × 2.5 cm 2 pixel size) LAPPD is capable of handling the total projected signal and background rates of the three pillar SoLID experiments. The tested photosensor detected Cherenkov signals with the capability of separating single-electron events from pair production events while rejecting background. Although the design was not aimed at ring-imaging Cherenkov detectors, Cherenkov disk images were captured in two different gas radiators. Through a direct comparison with a GEANT4 simulation, we confirmed the experimental performance of the LAPPD.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Performance evaluation of an RFSoC operating in a 1.25 Tesla magnetic field

Here, the Belle II experiment at the SuperKEKB collider is preparing for an upgrade after 2027–2028 to handle higher luminosity and increased background rates. A Radio Frequency System-on-Chip (RFSoC) has been identified as a potential candidate for a common front-end upgrade for subsystems requiring high-speed waveform digitization. The RFSoC's ADC and DAC channels were tested across various magnetic field strengths and a few different field orientations. Power consumption and boot memory functionality were also assessed. Results indicate stable operation with negligible performance degradation, suggesting the RFSoC's viability for high-speed digitization tasks in high magnetic field environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

The pathfinder X-Ray axion telescope for the International Axion Observatory (IAXO) and axion searches at the CERN Axion Solar Telescope (CAST)

The axion, a hypothetical pseudo-scalar particle proposed by Peccei and Quinn to resolve the strong CP problem in quantum chromodynamics, remains one of the most compelling dark matter candidates. Axions and Axion-Like Particles (ALPs) are characterized by a broad and largely unconstrained parameter space in mass and coupling strength, motivating extensive experimental searches. The International Axion Observatory (IAXO) is a next-generation axion helioscope designed to achieve over an order of magnitude improvement in sensitivity to the axion-photon coupling constant gaγ relative to previous experiments such as the CERN Axion Solar Telescope (CAST). IAXO will employ large-scale superconducting magnets, precision x-ray optics, and ultra-low-background detectors to search for solar axions produced primarily via the Primakoff effect. This work presents the design and performance of the IAXO pathfinder x-ray optic, a technological demonstrator that validated the optical concepts for IAXO through axion searches at CAST. Comprehensive ray-tracing simulations and experimental measurements were conducted to assess the optic's effective area, detection efficiency, and background suppression capabilities. Deployed at CAST in conjunction with Micromegas and GridPix detectors, the Pathfinder demonstrated record-setting sensitivity to both gaγ and the axion-electron coupling gae, establishing the most stringent laboratory constraints on solar axions to date. These results confirm the viability of the IAXO optical design and detector concept, providing a critical technological benchmark that informs the ongoing development of the BabyIAXO and full-scale IAXO telescopes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Rapid curing dynamics of PEG-thiol-ene resins allow facile 3D bioprinting and in-air cell-laden microgel fabrication

Thiol-norbornene photoclick hydrogels are highly efficient in tissue engineering applications due to their fast gelation, cytocompatibility, and tunability. In this work, we utilized the advantageous features of polyethylene glycol (PEG)-thiol-ene resins to enable fabrication of complex and heterogeneous tissue scaffolds using 3D bioprinting and in-air drop encapsulation techniques. We demonstrated that photoclickable PEG-thiol-ene resins could be tuned by varying the ratio of PEG-dithiol to PEG norbornene to generate a wide range of mechanical stiffness (0.5–12 kPa) and swelling ratios. Importantly, all formulations maintained a constant, rapid gelation time (<0.5 s). We used this resin in biological projection microstereolithography (BioPµSL) to print complex structures with geometric fidelity and demonstrated biocompatibility by printing cell-laden microgrids. Moreover, the rapid gelling kinetics of this resin permitted high-throughput fabrication of tunable, cell-laden microgels in air using a biological in-air drop encapsulation apparatus (BioIDEA). We demonstrated that these microgels could support cell viability and be assembled into a gradient structure. This PEG-thiol-ene resin, along with BioPµSL and BioIDEA technology, will allow rapid fabrication of complex and heterogeneous tissues that mimic native tissues with cellular and mechanical gradients. The engineered tissue scaffolds with a controlled microscale porosity could be utilized in applications including gradient tissue engineering, biosensing, and in vitro tissue models.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Droplet bioprinting of acellular and cell-laden structures at high-resolutions

Advances in digital light projection(DLP) based (bio) printers have made printing of intricate structures at high resolution possible using a wide range of photosensitive bioinks. A typical setup of a DLP bioprinter includes a vat or reservoir filled with liquid bioink, which presents challenges in terms of cost associated with bioink synthesis, high waste, and gravity-induced cell settling, contaminations, or variation in bioink viscosity during the printing process. Here, we report a vat-free, low-volume, waste-free droplet bioprinting method capable of rapidly printing 3D soft structures at high resolution using model bioinks and model cells. A multiphase many-body dissipative particle dynamics model was developed to simulate the dynamic process of droplet-based DLP printing and elucidate the roles of surface wettability and bioink viscosity. Process variables such as light intensity, photo-initiator concentration, and bioink formulations were optimized to print 3D soft structures (∼0.4–3 kPa) with a typical layer thickness of 50 µm, an XY resolution of 38 ± 1.5 μm and Z resolution of 237 ± 5.4 µm. To demonstrate its versatility, droplet bioprinting was used to print a range of acellular 3D structures such as a lattice cube, a Mayan pyramid, a heart-shaped structure, and a microfluidic chip with endothelialized channels. Droplet bioprinting, performed using model C3H/10T1/2 cells, exhibited high viability (90%) and cell spreading. Additionally, microfluidic devices with internal channel networks lined with endothelial cells showed robust monolayer formation while osteoblast-laden constructs showed mineral deposition upon osteogenic induction. Overall, droplet bioprinting could be a low-cost, no-waste, easy-to-use, method to make customized bioprinted constructs for a range of biomedical applications.

DLP↗
DOE OSTI2026

The ionomer as an oxygen evolution reaction promoter: piperidinium’s impact on mechanistic pathways on NiO, IrO 2 , and Fe–NiO

The commercial viability of anion exchange membrane (AEM) electrolysis requires optimization of various stack components, with specific catalyst-ionomer combinations often yielding higher current densities, lowered Tafel slopes, and improved mass activity. In this joint theoretical-experimental study, theoretical calculations detail the impact of Versogen’s piperidinium functional group on the complex, kinetically limiting oxygen evolution reaction, finding that the functional group can act as a promoter of specific steps (O*/O 2 * formation; H 2 O/O 2 desorption with reaction enthalpies ranging between 0.2–0.6 eV at higher coverages of O x H y intermediates) on NiO and NiFeO x catalysts. In particular, Fe sites on the NiFeO x catalyst facilitate concerted mechanisms of O*/O 2 * formation and H 2 O desorption with a low enthalpy of 0.5 eV; O 2 desorption alone requires only 0.3 eV. In contrast, Versogen-IrO 2 results in stronger Ir–O bonds, where the enthalpies for bond breaking (Ir–OH 2 and Ir–O 2 ) are considerably higher (1.4 eV and 1.6 eV, respectively). Rotating disk electrode studies utilized commercially available NiO and IrO 2 and synthesized 7.5 wt % Fe in NiFeO x catalysts in combination with Versogen, a common AEM ionomer, and Nafion, an alternative binder. Electrochemical testing validated the impact of these mechanistic changes on ionomer-catalyst combinations, finding that Versogen particularly activates NiO and NiFeO x compared to IrO 2 . Following a 13.5 h hold at 1.8 V, mass activities and Tafel slopes improved to 34 ± 13 A g −1 and 79 ± 2 mV dec −1 (NiO) and 82 ± 4.9 A g −1 and 72 ± 2 mV dec −1 (NiFeO x ). In contrast, Versogen-IrO 2 only reached 17 ± 2.9 A g −1 and 81 ± 3 mV dec −1 . Optimization of the ionomer-catalyst can yield significant increases in performance from initial activity and after an electrochemical conditioning procedure: this enhancement to the mass activity resulted in a 200.9 ± 106.1% improvement for Versogen-NiFeO x and 1284.2 ± 260.5% for Versogen-NiO. In contrast, Nafion-NiFeO x and -NiO offered moderate improvements of 39.1 ± 30.5% and 120.9 ± 59.1%, respectively.

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

Inferring dark matter substructure with astrometric lensing beyond the power spectrum

Abstract Astrometry—the precise measurement of positions and motions of celestial objects—has emerged as a promising avenue for characterizing the dark matter population in our Galaxy. By leveraging recent advances in simulation-based inference and neural network architectures, we introduce a novel method to search for global dark matter-induced gravitational lensing signatures in astrometric datasets. Our method based on neural likelihood-ratio estimation shows significantly enhanced sensitivity to a cold dark matter population and more favorable scaling with measurement noise compared to existing approaches based on two-point correlation statistics. We demonstrate the real-world viability of our method by showing it to be robust to non-trivial modeled as well as unmodeled noise features expected in astrometric measurements. This establishes machine learning as a powerful tool for characterizing dark matter using astrometric data.

convolutional neural networks (1938)↗
DOE OSTI2024

Unpaired image translation to mitigate domain shift in liquid argon time projection chamber detector responses

Deep learning algorithms often are developed and trained on a training dataset and deployed on test datasets. Any systematic difference between the training and a test dataset may severely degrade the final algorithm performance on the test dataset—what is known as the domain shift problem . This issue is prevalent in many scientific domains where algorithms are trained on simulated data but applied to real-world datasets. Typically, the domain shift problem is solved through various domain adaptation (DA) methods. However, these methods are often tailored for a specific downstream task, such as classification or semantic segmentation, and may not easily generalize to different tasks. This work explores the feasibility of using an alternative way to solve the domain shift problem that is not specific to any downstream algorithm. The proposed approach relies on modern Unpaired Image-to-Image (UI2I) translation techniques, designed to find translations between different image domains in a fully unsupervised fashion. In this study, the approach is applied to a domain shift problem commonly encountered in Liquid Argon Time Projection Chamber (LArTPC) detector research when seeking a way to translate samples between two differently distributed LArTPC detector datasets deterministically. This translation allows for mapping real-world data into the simulated data domain where the downstream algorithms can be run with much less domain-shift-related performance degradation. Conversely, using the translation from the simulated data to a real-world domain can increase the realism of the simulated dataset and reduce the magnitude of any systematic uncertainties. To evaluate the quality of the translations, we use both pixel-wise metrics and a downstream task to measure the effectiveness of UI2I methods for mitigating the domain shift problem. We adapted several popular UI2I translation algorithms to work on scientific data and demonstrated the viability of these techniques for solving the domain shift problem with LArTPC detector data. To facilitate further development of DA techniques for scientific datasets, the ‘Simple Liquid-Argon Track Samples’ dataset used in this study is also published.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Paired autoencoders for likelihood-free estimation in inverse problems

Abstract We consider the solution of nonlinear inverse problems where the forward problem is a discretization of a partial differential equation. Such problems are notoriously difficult to solve in practice and require minimizing a combination of a data-fit term and a regularization term. The main computational bottleneck of typical algorithms is the direct estimation of the data misfit. Therefore, likelihood-free approaches have become appealing alternatives. Nonetheless, difficulties in generalization and limitations in accuracy have hindered their broader utility and applicability. In this work, we use a paired autoencoder framework as a likelihood-free estimator (LFE) for inverse problems. We show that the use of such an architecture allows us to construct a solution efficiently and to overcome some known open problems when using LFEs. In particular, our framework can assess the quality of the solution and improve on it if needed. We demonstrate the viability of our approach using examples from full waveform inversion and inverse electromagnetic imaging.

Chung, Matthias (ORCID:0000000178224539)↗
DOE OSTI2026

Microsecond-latency feedback at a particle accelerator by online reinforcement learning on hardware

The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution due to their ability to dynamically adapt to changing environments and consider delayed consequences. In many real-world applications, RL policies must produce actions in real time, often within microseconds to milliseconds, imposing significant constraints on system latency and computational overhead that conventional machine learning libraries are not designed to handle. To control phenomena in real time at these timescales, RL needs to be deployed on-the-edge, namely on dedicated hardware located near the system it controls, without relying on a host CPU or cloud-based inference. In this work we present the design and deployment of an experience accumulator system in a particle accelerator. In this system, deep-RL algorithms run using hardware acceleration and act within a few microseconds, enabling the use of RL for control of phenomena like beam instabilities. The training uses the collected data offline to reduce the number of operations carried out on the acceleration hardware. The proposed architecture was tested in real experimental conditions at the Karlsruhe research accelerator, a synchrotron light source, where the system was used to control artificially induced horizontal betatron oscillations in real-time, with a control loop period of just 2.7 μs. The results showed a performance comparable to the commercial feedback system available at the accelerator, demonstrating the viability and potential of this approach. Due to the self-learning and reconfiguration capability of this implementation, a seamless application to other control problems is possible. Applications range from particle accelerators to large-scale research and industrial facilities.

FPGA↗
DOE OSTI2023

Pan-Coronavirus CRISPR-CasRx Effector System Significantly Reduces Viable Titer in HCoV-OC43, HCoV-229E, and SARS-CoV-2

CRISPR-based technology has become widely used as an antiviral strategy, including as a broad-spectrum human coronavirus (HCoV) therapeutic. In this work, we have designed a CRISPR-CasRx effector system with guide RNAs (gRNAs) that are cross-reactive among several HCoV species. We tested the efficacy of this pan-coronavirus effector system by evaluating the reduction in viral viability associated with different CRISPR targets in HCoV-OC43, HCoV-229E, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We determined that several CRISPR targets significantly reduce viral titer, despite the presence of single nucleotide polymorphisms in the gRNA when compared with a non-targeting, negative control gRNA. CRISPR targets reduced viral titer between 85% and >99% in HCoV-OC43, between 78% and >99% in HCoV-229E, and between 70% and 94% in SARS-CoV-2 when compared with an untreated virus control. These data establish a proof-of-concept for a pan-coronavirus CRISPR effector system that is capable of reducing viable virus in both Risk Group 2 and Risk Group 3 HCoV pathogens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A cross-study analysis of drug response prediction in cancer cell lines

Abstract To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm development efforts have relied on cross-validation within a single study to assess model accuracy. While an essential first step, cross-validation within a biological data set typically provides an overly optimistic estimate of the prediction performance on independent test sets. To provide a more rigorous assessment of model generalizability between different studies, we use machine learning to analyze five publicly available cell line-based data sets: National Cancer Institute 60, ancer Therapeutics Response Portal (CTRP), Genomics of Drug Sensitivity in Cancer, Cancer Cell Line Encyclopedia and Genentech Cell Line Screening Initiative (gCSI). Based on observed experimental variability across studies, we explore estimates of prediction upper bounds. We report performance results of a variety of machine learning models, with a multitasking deep neural network achieving the best cross-study generalizability. By multiple measures, models trained on CTRP yield the most accurate predictions on the remaining testing data, and gCSI is the most predictable among the cell line data sets included in this study. With these experiments and further simulations on partial data, two lessons emerge: (1) differences in viability assays can limit model generalizability across studies and (2) drug diversity, more than tumor diversity, is crucial for raising model generalizability in preclinical screening.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Metagenomic investigation of African dust events in the Caribbean

ABSTRACT African dust from the Sahara and Sahel regions of Northern Africa is blown intercontinental distances and is the highest portion of atmospheric dust generated each year. During the Northern Hemisphere summer months (boreal summer), these dust events travel into the Caribbean and southern United States. While viability assays, microscopy and bacterial amplicon analyses have shown that dust-associated microbes may be diverse, the specific microbial taxa that are transported intercontinental distances with these dust events remain poorly characterized. To provide new insights into these issues, five metagenomes of Saharan dust events occurring in the Caribbean, collected in the summer months of 2002 and 2008, were analyzed. The data revealed that similar microbial composition existed between three out of the five of the distinct dust events and that fungi were a prominent feature of the metagenomes compared to other environmental samples. These results have implications for better understanding of microbial transport through the atmosphere and may implicate that the dust-associated microbial load transiting the Atlantic with Saharan dust is similar from year to year.

Waters, Samantha Marie↗
DOE OSTI2023

Towards the usage of quarry blasts as an active seismic source for subsurface characterization and imaging

SUMMARY Active or man-made seismic sources are often used to delineate subsurface geological structures via seismic imaging techniques. Although conventional controlled seismic sources have provided high-resolution subsurface images, the high cost of data acquisition necessitates improved use of cheaper alternative seismic sources for subsurface imaging, such as traffic noise, quarry blasts and earthquakes. Here, we explore the potential use of quarry blasts as an active seismic source for subsurface imaging. The goal of our study is to demonstrate the utility of quarry blasts as seismic sources for investigating subsurface structure with a field experiment in Mill Creek, southern Oklahoma. We deployed a 7455-m-long receiver line of 72 receivers (105 m spacing) extending away from a quarry, with a recording time of 28 d. We analyse similarities between blasts, wave types, origin time and excitation location of quarry blasts, which is important information for using such signal as an active source. Given a relative homogeneous geological condition in the study area, we could not observe clear reflected waves. However, the use of P- and S-wave velocities led to the delineation of a major basement damage zone in the study area, which further demonstrates the viability of quarry blasts as a useful seismic source for subsurface geological imaging.

58 GEOSCIENCES↗
DOE OSTI2025

Climate history modulates stress responses of common soil bacteria under experimental drought

Soil drying challenges microbial viability and survival, with bacteria employing various mechanisms to respond to shifts in osmolarity, including dormancy or metabolic upregulation of osmoprotectants. However, the extent to which these responses are shaped by an organism's phylogeny, or the climate history of a given environment is poorly understood. This study examines the responses of phylogenetically similar bacteria from semi-arid and humid tropical forest soils to osmotic and matric stress using synchrotron radiation-based Fourier Transform Infrared spectromicroscopy. This non-destructive approach depicts the biochemical phenotype for whole cells under control and stress conditions. We observed that, under osmotic stress, bacteria upregulated cell-signaling pathways, rapidly turned over lipid-storage compounds, and increased osmolyte production. In contrast, matric stress induced a more muted response, typically elevating the production of carbohydrate stress compounds, such as glycine betaine and trehalose. Whereas phylogenetically similar bacteria showed comparable biochemistry under control conditions, climate history played an important role in regulating responses to stress, whereby a stronger metabolic response was observed from semi-arid relative to tropical forest isolates. We conclude that bacterial stress response to drought can be more diverse than previously observed and regulated by both phylogeny and climate history.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Actinomycetota isolated from the sponge Hymeniacidon perlevis as a source of novel compounds with pharmacological applications: diversity, bioactivity screening, and metabolomic analysis

Abstract Aims To combat health conditions, such as multi-resistant bacterial infections, cancer, and metabolic diseases, new drugs need to be urgently found and, in this respect, marine Actinomycetota have a high potential to produce secondary metabolites with pharmacological importance. We aimed to study the cultivable Actinomycetota community associated with a marine sponge from the Portuguese coast, Hymeniacidon perlevis, and investigate the potential of the retrieved isolates to produce compounds with antimicrobial, anticancer and anti-obesity properties. Methods and results The analysis of the 16S rRNA gene revealed 79 Actinomycetota isolates affiliated with 12 genera—Brachybacterium, Dietzia, Glutamicibacter, Gordonia, Micrococcus, Micromonospora, Nocardia, Nocardiopsis, Paenoartrhobacter, Rhodococcus, Streptomyces, and Tsukamurella, most of which affiliated with the genus Streptomyces. The screening of antimicrobial activity revealed 13 strains, all belonging to the Streptomyces genus, capable of inhibiting the growth of Candida albicans, Bacillus subtilis, or Staphylococcus aureus. Forty-three extracts exhibited cytotoxic activity against at least one tested cell line (HepG2, HCT-116, and hCMEC-D3). Three extracts that were active against the two cancer cell lines tested, did not reduce the viability of the non-cancer endothelial cell line, hCMEC-D3. One Gordonia strain exhibited anti-obesity activity, revealed by its ability to reduce the neutral lipids in zebrafish larvae. Mass spectrometry-based dereplication analysis of active extracts identified several compounds associated with known Actinomycetota natural products. Nonetheless, five clusters contained metabolites that did not match any annotated natural products, suggesting they may represent new bioactive molecules. Conclusions This work contributed to increase the knowledge on the diversity and bioactive potential of Actinomycetota associated with H. perlevis.

Fonseca, Ana C.↗
DOE OSTI2024

Application of functional genomics for domestication of novel non-model microbes

Abstract With the expansion of domesticated microbes producing biomaterials and chemicals to support a growing circular bioeconomy, the variety of waste and sustainable substrates that can support microbial growth and production will also continue to expand. The diversity of these microbes also requires a range of compatible genetic tools to engineer improved robustness and economic viability. As we still do not fully understand the function of many genes in even highly studied model microbes, engineering improved microbial performance requires introducing genome-scale genetic modifications followed by screening or selecting mutants that enhance growth under prohibitive conditions encountered during production. These approaches include adaptive laboratory evolution, random or directed mutagenesis, transposon-mediated gene disruption, or CRISPR interference (CRISPRi). Although any of these approaches may be applicable for identifying engineering targets, here we focus on using CRISPRi to reduce the time required to engineer more robust microbes for industrial applications. One-Sentence Summary The development of genome scale CRISPR-based libraries in new microbes enables discovery of genetic factors linked to desired traits for engineering more robust microbial systems.

59 BASIC BIOLOGICAL SCIENCES↗