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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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A lab-on-paper biosensor using a two-step enzymatic amplification strategy for ultrasensitive detection of active BoNT/A in complex matrices
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Turning Outsiders into Insiders: A Call for Papers to Expand the Reach of National Laboratories’ Safety Successes, Challenges, Research, and Approaches
The most complex challenges facing the world today comprise the work of [Department of Energy’s] (DOE’s) 17 National Laboratories: [...] From furthering U.S. energy independence and leadership in clean technologies; to promoting innovation that advances U.S. economic competitiveness; to conducting research of the highest caliber in the physical, chemical, biological, materials, computational, and information sciences to advance understanding of the world around us-the Laboratories’ purview is expansive and further their contributions are indispensable.
In situ hemolysis in a three-dimensional paper-based device for quantification of intraerythrocytic analytes
Quantitative in situ hemolysis is achieved for samples of whole blood using a chemical treatment without additional user-steps or sample preparation.
Foreword to special issue: Papers from the 63rd annual meeting of the APS Division of Plasma Physics, November 8–12, 2021
The 63rd annual meeting of the APS Division of Plasma Physics (DPP) was held on November 8–12, 2021 in Pittsburgh at the David Lawrence Convention Center with both a live (in person) component and a virtual component. Following guidance from an APS COVID task force, all in-person attendees were fully vaccinated and masked. More than 800 physicists attended, safely, in-person. With both virtual and on-site participants, discussions were lively, and the research presentations showed unmatched mastery in the modern observation, theory, simulation, and manipulation of plasma. The presentations included four invited review talks, 97 invited talks, four tutorials, and four presentations from this year's prize and award recipients. There were more than 1200 contributed poster presentations and 725 contributed oral presentations. Including both in-person and remote attendees, DPP 2021 had a record of 2232 participants. As a hybrid meeting, in-person presentations of all invited presentations were broadcast live and were accompanied by a Q&A discussion. Contributed oral and poster presentations were prerecorded along with options to schedule in-person discussions on demand. Five mini-conferences were held: “Gatekeeper Workshop: Creating a Diverse, Equitable, and Inclusive Pipeline,” “Collisionless Shocks in Laboratory and Space Plasmas,” “The High Repetition Rate Frontier in High-Energy-Density Physics,” “Measuring and Modeling Plasma Surface Interactions,” and “The Second Mini-Conference on Machine Learning, Data Science and Artificial Intelligence in Plasma Research.” Finally, on the day before the official start of the meeting, an afternoon “for students, by students” included lightning talks, plasma trivia, and an informal occasion to connect with other students, learn how to get the most from the DPP Annual Meeting, and share successful ways to connect with colleagues and advance their professional careers.
Foreword: Selected papers from the 2020 Nuclear and Emerging Technologies for Space Topical Meeting (NETS 2020)
Humanity’s curiosity of and intrigue for exploring space has been with our species since we first looked up into the night sky. This age-old curiosity has driven humankind to innovate technologies for millennia, including efforts ranging from the construction of Stonehenge to track the annual movements of the sun to the investigation of advanced propulsion systems capable of transporting people to distant planets. Today’s technical communities dedicated to researching and developing innovative technologies for space exploration have seen a recent reinvigoration. Over the past few years, impressive progress made by industry, with exceptional support from government agencies, to reestablish and develop new capabilities has renewed confidence in humanity’s ability to reach the stars—a confidence that has not been present since the days of the Apollo program. Moreover, history shows that innovation and collaboration within the scientific and engineering communities reaches unparalleled pinnacles during periods of astrophilia. Finally, given the advancements in computational capacities for advanced modeling and simulation, unprecedented breakthroughs in commercializing advanced manufacturing techniques, and powerful collaborative relationships between industry and national scientific organizations, today we are limited only by our own imaginations.
Some of the History Surrounding the Oliphant et al. Discovery of dd Fusion and an Inference of the d(d,p)t Cross Section from This 1934 Paper
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Sphingobium lignivorans sp. nov., isolated from river sediment downstream of a paper mill
Here, a bacterial isolate, B1D3A T , was isolated from river sediment collected from the Hiwassee River near Calhoun, TN, by enrichment culturing with a model 5–5' lignin dimer, dehydrodivanillate, as its sole carbon source. B1D3A T was also shown to utilize several model lignin-derived monomers and dimers as sole carbon sources in a variety of minimal media. Cells were Gram-stain-negative, aerobic, motile, rod-shaped and formed yellow/cream-coloured colonies on rich agar. Optimal growth occurred at 30°C, pH 7–8, and in the absence of NaCl. The major fatty acids of B1D3A T were C 18:1 ω7c and C 17:1 ω6c. The predominant hydroxy fatty acids were C 14: 0 2-OH and C 15:0 2-OH. The polar lipid profile consisted of a mixture of phosphatidylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, phosphatidyldimethylethanolamine and sphingoglycolipid. B1D3A T contained spermidine as the only major polyamine. The major isoprenoid quinone was Q-10 with minor amounts of Q-9 and Q-11. The genomic DNA G+C content of B1D3A T was 65.6mol%. Phylogenetic analyses based on 16S rRNA gene sequences and coding sequences of 49 core, universal genes defined by Clusters of Orthologous Groups gene families indicated that B1D3A T was a member of the genus Sphingobium. B1D3A T was most closely related to Sphingobium sp. SYK-6, with a 100% 16S rRNA gene sequence similarity. B1D3A T showed 78.1–89.9%average nucleotide identity and 19.5–22.2% digital DNA–DNA hybridization identity with other type strains from the genus Sphingobium. On the basis of phenotypic and genotypic properties and phylogenetic inference, strain B1D3A T should be classified as representing a novel species of the genus Sphingobium, for which the name Sphingobium lignivorans sp. nov. is proposed. The type strain is strain B1D3A T (ATCC TSD-279 T =DSM 111877 T ).
FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper
The outbreak of the global COVID-19 pandemic emphasizes the importance of collaborative drug discovery for high effectiveness; however, due to the stringent data regulation, data privacy becomes an imminent issue needing to be addressed to enable collaborative drug discovery. In addition to the data privacy issue, the efficiency of drug discovery is another key objective since infectious diseases spread exponentially and effectively conducting drug discovery could save lives. Advanced Artificial Intelligence (AI) techniques are promising to solve these problems: (1) Federated Learning (FL) is born to keep data privacy while learning data from distributed clients; (2) graph neural network (GNN) can extract structural properties of molecules whose underlying architecture is the connected atoms; and (3) generative adversarial network (GAN) can generate novel molecules while retaining the properties learned from the training data. In this work, we make the first attempt to build a holistic collaborative and privacy-preserving FL framework, namely FL- DISCO, which integrates GAN and GNN to generate molecular graphs. Experimental results demonstrate the effectiveness of FL- DISCO on: (1) IID data for ESOL and QM9, where FL-DISCO can generate highly novel compounds with high drug-likeliness, uniqueness and LogP scores compared to the baseline; (2) non- IID data for ESOL and QM9, where FL-DISCO generates 100% novel compounds with high validity and LogP scores compared to the baseline. We also demonstrate how different fractions of clients, generator and discriminator architectures affect our evaluation scores.
Guest Editorial Special Issue on Plenary, Invited, and Tutorial Papers From ICOPS 2022
The IEEE International Conference on Plasma Science (ICOPS) is an annual meeting of plasma physics researchers with an emphasis on various applications of plasma science and technology. This meeting is organized by the Plasma Science and Application Committee (PSAC) of the IEEE Nuclear and Plasma Sciences Society (NPSS).
Quantum Engineering With Hybrid Magnonic Systems and Materials (Invited Paper)
Quantum technology has made tremendous strides over the past two decades with remarkable advances in materials engineering, circuit design and dynamic operation. In particular, the integration of different quantum modules has benefited from hybrid quantum systems, which provide an important pathway for harnessing the different natural advantages of complementary quantum systems and for engineering new functionalities. This review focuses on the current frontiers with respect to utilizing magnetic excitations or magnons for novel quantum functionality. Magnons are the fundamental excitations of magnetically ordered solid-state materials and provide great tunability and exibility for interacting with various quantum modules for integration in diverse quantum systems. The concomitant rich variety of physics and material selections enable exploration of novel quantum phenomena in materials science and engineering. In addition, the relative ease of generating strong coupling and forming hybrid dynamic systems with other excitations makes hybrid magnonics a unique platform for quantum engineering. We start our discussion with circuit-based hybrid magnonic systems, which are coupled with microwave photons and acoustic phonons. Subsequently, we are focusing on the recent progress of magnon-magnon coupling within confined magnetic systems. Next we highlight new opportunities for understanding the interactions between magnons and nitrogen-vacancy centers for quantum sensing and implementing quantum interconnects. Lastly, we focus on the spin excitations and magnon spectra of novel quantum materials investigated with advanced optical characterization.
In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)
Human mobility data science using trajectories or check-ins of individuals has many applications. Recently, we have seen a plethora of research efforts that tackle these applications. However, research progress in this field is limited by a lack of large and representative datasets. The largest and most commonly used dataset of individual human trajectories captures fewer than 200 individuals, while datasets of individual human check-ins capture fewer than 100 check-ins per city per day. Thus, it is not clear if findings from the human mobility data science community would generalize to large populations. Since obtaining massive, representative, and individual-level human mobility data is hard to come by due to privacy considerations, the vision of this work is to embrace the use of data generated by large-scale socially realistic microsimulations. Informed by both real data and leveraging social and behavioral theories, massive spatially explicit microsimulations may allow us to simulate entire megacities at the person level. The simulated worlds, which do not capture any identifiable personal information, allow us to perform “in silico” experiments using the simulated world as a sandbox in which we have perfect information and perfect control without jeopardizing the privacy of any actual individual. In silico experiments have become commonplace in other scientific domains such as chemistry and biology, permitting experiments that foster the understanding of concepts without any harm to individuals. This work describes challenges and opportunities for leveraging massive and realistic simulated alternate worlds for in silico human mobility data science.
Dataset for the paper titled "Investigating the relationship between bolide entry angle and apparent direction of infrasound signal arrivals"
This dataset includes outputs generated for the journal publication titled: "Investigating the relationship between bolide entry angle and apparent direction of infrasound signal arrivals". The outputs include .csv files with model-generated synthetic trajectories of asteroids entering Earth at a variety of impact and approach (azimuthal) angles. All outputs are based on hypothetical but realistic scenarios.
Time-Based CAN IDS Paper Results Code
Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface which is vulnerable to message injection attacks. These injections change the overall timing characteristics of messages on the bus, and thus, to detect these malicious messages, time-based intrusion detection systems (IDSs) have been proposed. However, time-based IDSs are usually trained and tested on low-fidelity datasets with unrealistic, labeled attacks. This makes difficult the task of evaluating, comparing, and validating IDSs. Here we detail and benchmark four time-based IDSs against the newly published ROAD dataset, the first open CAN IDS dataset with real (non-simulated) stealthy attacks with physically verified effects. We found that methods that perform hypothesis testing by explicitly estimating message timing distributions have lower performance than methods that seek anomalies in a distribution related statistic. In particular, these “distribution-agnostic” based methods outperform “distribution-based” methods by at least 55% in area under the precision-recall curve (AUC-PR). Our results expand the body of knowledge of CAN time-based IDSs by providing details of these methods and reporting their results when tested on datasets with real advanced attacks. Finally, we develop an after-market plug-in detector using lightweight hardware, which can be used to deploy the best performing IDS method on nearly any vehicle.
MIST_paper
Code to reproduce results from and implement functionality described in "A Bayesian error model for synthesis and sequencing of oligonucleotides", Marrs, FW, Gratz, D, and Erkkila, TH.
EGS Collab Experiment 1: SIMFIP Notch-164 GRL Paper
Characterizing the stimulation mode of a fracture is critical to assess the hydraulic efficiency and the seismic risk related to deep fluid manipulations. We have monitored the three-dimensional displacements of a fluid-driven fracture during water injections in a borehole at ~1.5 km depth in the crystalline rock of the Sanford Underground Research Facility (USA). The fracture initiates at 61% of the minimum horizontal stress by micro-shearing of the borehole on a foliation plane. As the fluid pressure increases further, borehole axial and radial displacements increase with injection time highlighting the opening and sliding of a new hydrofracture growing ~10 m away from the borehole, in accordance with the ambient normal stress regime and in alignment with the microseismicity. Our study reveals how fluid-driven fracture stimulation can be facilitated by a mixed-mode process controlled by the complex hydromechanical evolution of the growing fracture. The data presented in this submission refer to the SIMFIP measurements and analyses of the stimulation tests conducted on the 164 ft (50 m) notch of the Sanford Underground Research Facility (SURF), during the EGS-Collab test 1. In addition to the datafiles, there is the draft of a manuscript submitted to Geophysical Research Letters (GRL).