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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
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Habitability of Cloudy Worlds: Intersecting Constraints and Unknowns

"Follow the water" has long been a theme of astrobiology. Where there are terrestrial worlds with water, there are likely to be clouds. Earth's clouds carry active microbes, in addition to inactive life that comprises a significant minority of dry dust. Both Venus and Mars are believed to have had significant early water; on Venus, the limited water retained in the clouds has been suggested as a potential refuge for life, a parallel to Mars's subsurface water. Conversely, as microbes on Earth do not stay airborne for very long, a hypothetical exoplanet with more persistent cloud cover could be even more favorable to an airborne biosphere than Earth. Airborne microbiology is significant at a planetary scale for Earth. Effects include weather (microbes as condensation and ice nuclei), climate (alteration of cloud and surface albedo), and water and air chemistry (through metabolic processing). Some of these effects, if present on exoplanets, could be detectable through remote observation. Understanding the parameters that constrain the habitability of clouds is therefore necessary to help guide the search for life. Paper includes the extended abstract.

Habitability↗
DOE OSTI2025

Contrasting Time-Frequency Representations for Unknown Waveform Detection

In real-world applications like spectrum management and interference detection, dealing with unseen electromagnetic waveforms is critical. Although some methods attempt to simulate open set data using generator models, they face challenges in generating synthetic samples for open set while simultaneously selecting an optimal discriminator for accurate classification. This results in difficulties capturing distinctive features across classes, especially in dynamic scenarios where new classes emerge. To detect unseen waveforms, we propose combining time and frequency domain features with cosine similarity loss to enhance feature distinctiveness and enabling more accurate predictions. This approach efficiently captures more comprehensive information than single-domain representations or approaches without cosine loss. Additionally, our model avoids generic feature vectors by extracting class-specific features during training, resulting in improved class representation. The experiment results show that this combined feature approach with cosine loss outperforms single-domain models and improves accuracy by 10\% over models without cosine loss.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Contrasting Time-Frequency Representations for Unknown Waveform Detection

Identifying unseen electromagnetic waveforms is critical for many applications, like interference management, electronic warfare and spectrum management. Traditionally this is done using statistical methods for anomaly detection, which has evolved to deep learning models for identifying the unseen data, formally termed as open set recognition. Some prior methods use a generative model to emulate open set data, which face challenges in generating synthetic samples for open set while simultaneously selecting an optimal discriminator for accurate classification. To alleviate this issue, we propose a discriminative model that effectively combines time and frequency domain features of communication signals for accurate predictions. We further introduce a cosine similarity loss that makes the domain specific features unique to enhance the prediction rate. Additionally, our model avoids generic feature vectors by extracting class-specific features during training, resulting in improved class representation. The experiment results show that this combined feature approach with cosine loss outperforms single-domain models and improves accuracy by 10% over models without cosine loss.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Discovery of unknown posttranslational modifications by top-down mass spectrometry

Post-translational modifications can be important biomarkers of function within biological systems. Top-down mass spectrometry is a valuable tool for the characterization of combinatorial modifications on proteins such as histones that have a range of complex modifications. In this chapter, we present a top-down liquid chromatography-mass spectrometry experimental and data analysis workflow for the identification of novel modifications on proteins. The data analysis workflow presented here is reliant on the combination of proteoform searching using TopPIC and data visualization and fragment ion spectral confirmation using LcMsSpectator, part of the Informed-Proteomics package of software.

Wilson, Jesse W.↗
DOE OSTI2019

Solving a trillion unknowns per second with HPGMG on Sunway TaihuLight

Benchmarks for supercomputers are important tools, not only for evaluating and ranking modern supercomputers, but also for providing hints for future architecture design. As a new benchmark, HPGMG (high performance geometric multigrid) solves a linear equation set with a full geometric multi-grid algorithm. It involves computation on different scales, data movement with various volumes, global communication and neighbor communication with both large and small messages, etc., and is more correlated to real world applications than traditional benchmarks such as LINPACK. Therefore, it is desirable to examine how well HPGMG can perform on leadership supercomputers such as Sunway Taihulight. Sunway Taihulight, the No. 1 supercomputer in the Top 500 list from June 2016 to June 2018, which uses a specially designed many-core architecture SW26010, is of great interest to the community of high performance computing. With careful analysis and code design, we came up with an efficient implementation of HPGMG on SW26010 processors. We not only employed traditional optimization techniques such as 2.5D partitioning, double buffering, and collective data load, but also introduced a micro-benchmark to help with the choice of optimization direction and parameter tuning. Another contribution is that we proposed a new procedure for the major operations, by granulating and reordering the smooth function and the ghost exchange operation, leading to reduced memory copy and accelerated communication process. Our optimized implementation of HPGMG on Sunway TaihuLight achieved a ground-breaking performance of 1.036 × 10 12 Degrees of Freedom per second at the finest level, which is No. 1 on the HPGMG list of Nov 2017.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Pareto-Lognormal Modeling of Known and Unknown Metal Resources. II. Method Refinement and Further Applications

Pareto-lognormal modeling of worldwide metal deposit size–frequency distributions was proposed in an earlier paper (Agterberg in Nat Resour 26:3–20, 2017). In the current paper, the approach is applied to four metals (Cu, Zn, Au and Ag) and a number of model improvements are described and illustrated in detail for copper and gold. The new approach has become possible because of the very large inventory of worldwide metal deposit data recently published by Patiño Douce (Nat Resour 25:97–124, 2016c). Worldwide metal deposits for Cu, Zn and Ag follow basic lognormal size–frequency distributions that form straight lines on lognormal Q–Q plots. Au deposits show a departure from the straight-line model in the vicinity of their median size. Both largest and smallest deposits for the four metals taken as examples exhibit hyperbolic size–frequency relations and their Pareto coefficients are determined by fitting straight lines on log rank–log size plots. As originally pointed out by Patiño Douce (Nat Resour Res 25:365–387, 2016d), the upper Pareto tail cannot be distinguished clearly from the tail of what would be a secondary lognormal distribution. The method previously used in Agterberg (2017) for fitting the bridge function separating the largest deposit size–frequency Pareto tail from the basic lognormal is significantly improved in this paper. A new method is presented for estimating the approximate deposit size value at which the upper tail Pareto comes into effect. Although a theoretical explanation of the proposed Pareto-lognormal distribution model is not a required condition for its applicability, it is shown that existing double Pareto-lognormal models based on Brownian motion generalizations of the multiplicative central limit theorem are not applicable to worldwide metal deposits. Neither are various upper tail frequency amplification models in their present form. Although a physicochemical explanation remains possible, it is argued that preferential mining of the largest and smallest orebodies can have economic historical reasons. The size–frequency distribution of uranium can be regarded as lognormal without Pareto tails. At the end of the paper, it is shown that original copper deposit size data can be used for forward projection of discovery trends toward the end of this century.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

BCL-2 proteins and apoptosis: Recent insights and unknowns

Highlights: • The pro-apoptotic BCL-2 proteins can commit cells to apoptosis. • BAX and BAK are regulated by dynamic shuttling between mitochondria and cytosol of healthy cells. • BH3-only proteins, regulators of BAX and BAK, are not required for BAX activation. • Recent super-resolution microscopy studies provide novel insights into the active BAX complex. Proteins of the B-cell lymphoma-2 (BCL-2) family control the intrinsic apoptosis pathway. The pro-apoptotic BCL-2 proteins BAX and BAK can commit a cell to its programmed death by permeabilizing the outer mitochondrial membrane (OMM) and subsequent initiation of the caspase cascade. Therefore, the activities of BAX and BAK are precisely controlled by a complex network of proteins inside and outside the BCL-2 family. Cells survive by constant control of dynamic translocation and retrotranslocation of BAX and BAK to the mitochondria and back into the cytosol. Recent insights into BAX/BAK shuttling, BCL-2 protein interactions, the role of BH3-only proteins in apoptosis signaling and the active BAX complex set the stage for the development of novel strategies in cancer therapy and the analysis of cellular predisposition to apoptosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Nuclear forensic analysis of an unknown uranium ore concentrate sample seized in a criminal investigation in Australia

In early 2009, a state policing agency raided a clandestine drug laboratory in a suburb of a major city in Australia. While searching the laboratory, they discovered a small glass jar labelled “Gamma Source” and containing a green powder. The powder was radioactive. This paper documents the detailed nuclear forensic analysis undertaken to characterize and identify the material and determine its provenance. Isotopic and impurity content, phase composition, microstructure and other characteristics were measured on the seized sample, and the results were compared with similar material obtained from the suspected source (ore and ore concentrate material). While an extensive range of parameters were measured, the key ‘nuclear forensic signatures’ used to identify the material were the U isotopic composition, Pb and Sr isotope ratios, and the rare earth element pattern. These measurements, in combination with statistical analysis of the elemental and isotopic content of the material against a database of uranium ore concentrates sourced from mines located worldwide, led to the conclusion that the seized material (a uranium ore concentrate of natural isotopic abundance) most likely originated from Mary Kathleen, a former Australian uranium mine.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Quantitative Separation of Unknown Organic–Metal Complexes by Liquid Chromatography–Inductively Coupled Plasma-Mass Spectrometry

Dissolved organic matter (DOM) is widely recognized to control the solubility and reactivity of trace metals in the environment. However, the mechanisms that govern metal-DOM complexation remain elusive, primarily due to the analytical challenge of fractionating and quantifying metal–organic species within the complex mixture of organic compounds that comprise DOM. Here, we describe a quantitative method for fractionation and element-specific detection of organic–metal complexes using liquid chromatography with online inductively coupled plasma mass spectrometry (LC–ICP-MS). The method implements a post-column compensation gradient to stabilize ICP–MS elemental response across the LC solvent gradient, thereby overcoming a major barrier to achieving quantitative accuracy with LC–ICP-MS. With external calibration and internal standard correction, the method yields concentrations of organic–metal complexes that were consistently within 6% of their true values, regardless of the complex’s elution time. We used the method to evaluate the effects of four stationary phases (C18, phenyl, amide, and pentafluoroylphenyl propyl) on the recovery and separation of environmentally relevant trace metals (Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in Suwannee River Fulvic Acid and Suwannee River Natural Organic Matter. The C18, amide, and phenyl phases generally yielded optimal metal recoveries (>75% for all metals except Pb), with the phenyl phase separating polar species to a greater extent than C18 or amide. We also fractionated organic-bound Fe, Cu, and Ni in oxidized and reduced soils, revealing divergent metal-DOM speciation across soil redox environments. Finally, by enabling quantitative fractionation of DOM-bound metals, our method offers a means for advancing a mechanistic understanding of metal–organic complexation throughout the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗