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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Numerical modeling for an electric-field hyperthermia applicator

Hyperthermia, in conjunction with radiation and chemotherapy for treatment of cancers, is an area of current concern. Experiments have shown that hyperthermia can increase the potency of many chemotherapy drugs and the effectiveness of radiation for treating cancer. A combination of whole body or regional hyperthermia with chemotherapy or radiation should improve treatment results. Conventional methods for inducing whole body hyperthermia, such as exposing a patient in a radiant cabinet or under a hot water blanket, conduct heat very slowly from the skin to the body core. Thus a more efficient system, such as the three-plate electric-field hyperthermia applicator (EHA), is developed. This three-plate EHA has one top plate over and two lower plates beneath the patient. It is driven at 27.12 MHz with 500 Watts through a matching circuit. Using this applicator, a 50 kg pig was successfully heated to 42 C within 45 minutes. However, phantom and animal studies have indicated non-uniform heating near the side of the body. In addition, changes in the size and distance between the electrode plates can affect the heating (or electromagnetic field) pattern. Therefore, numerical models using the method of moments (MOM) or the finite difference time domain (FDTD) technique are developed to optimize the heating pattern of this EHA before it is used for human trials. The accuracy of the numerical modeling has been achieved by the good agreement between the MOM and FDTD results for the three-plate EHA without a biological body. The versatile FDTD technique is then applied to optimize the EHA design with a human body. Both the numerical and measured data in phantom blocks will be presented. The results of this study will be used to design an optimized system for whole body or regional hyperthermia.

Wu, Te-Kao↗
NASA NTRS1976

Geochemistry of biomolecules

A highly sensitive fluorometric technique is developed for the determination of biological and geo-organic compounds in ancient sediments and extraterrestrial samples. This technique is used to establish chemical evidence for fossil pigments in an extraterrestrial sample. Also developed is a highly sensitive and specific fluorometric method for the determination of total primary amine nitrogen in soil samples.

Bonner, J.↗
NASA NTRS2002

Machine Learning for Biological Trajectory Classification Applications

Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.

Sbalzarini, Ivo F.↗
NASA NTRS1989

Initial Scientific Assessment of the EOS Data and Information System (EOSDIS)

Crucial to the success of the Earth Observing System (Eos) is the Eos Data and Information System (EosDIS). The goals of Eos depend not only on its instruments and science investigations, but also on how well EosDlS helps scientists integrate reliable, large-scale data sets of geophysical and biological measurements made from Eos data, and on how successfully Eos scientists interact with other investigations in Earth System Science. Current progress in the use of remote sensing for science is hampered by requirements that the scientist understand in detail the instrument, the electromagnetic properties of the surface, and a suite of arcane tape formats, and by the immaturity of some of the techniques for estimating geophysical and biological variables from remote sensing data. These shortcomings must be transcended if remote sensing data are to be used by a much wider population of scientists who study environmental change at regional and global scales.

Source record↗
DOE OSTI2025

Structural and Mechanistic Advances in the Chemistry of Methyl-Coenzyme M Reductase (MCR)

Methane represents 34% of U.S. energy consumption and is a major greenhouse gas related to the global carbon cycle and energy production. However, current industrial practices significantly increase atmospheric methane levels, necessitating a deeper understanding of its biosynthesis and oxidation. Methyl-coenzyme M reductase (MCR) is central to biological methane metabolism, catalyzing the final step of methanogenesis and the first step in anaerobic methane oxidation. It is also a key target for strategies to capture and transform methane into value-added chemicals.The active site of MCR is a buried Ni-based cofactor only accessible by the substrates via a 50 Å long tunnel. Although the Ni(I) state is required to initiate catalysis, capturing this state remains a challenge for the current structural techniques. Recent advances in structural biology using X-ray Free-Electron Laser serial crystallography have provided insights into MCR's inactive Ni(II) state at room temperature and show promise for capturing its active Ni(I) form.Our team has established several critical aspects of the MCR mechanism using a combination of experimental and computational studies. MCR uses CH 3 -SCoM and CoBSH as substrates, producing methane and a disulfide product CoMSSCoB. Kinetic analysis showed that productive substrate binding requires CH 3 -SCoM to bind first, inducing conformational changes that optimize the active site for subsequent CoBSH binding. Following substrate binding, four proposed methane production/oxidation mechanisms were examined, establishing whether the reaction proceeds through an organometallic methyl-nickel(III), methyl anion ion, or methyl radical intermediate. Experimental measurements using CoBSH analogs successfully slowed the reaction, allowing for mechanistic insight that demonstrated the methyl radical pathway, where the initial interactions involve homolytic cleavage of the methyl-sulfur bond, generating a methyl radical that quickly abstracts the thiol hydrogen atom of CoBSH to form methane. Computational studies further confirmed that, compared to other mechanisms, the methyl radical mechanism is thermodynamically more favorable and accessible under physiological conditions.Spectroscopic and computational studies challenged the conventional understanding of substrate binding in MCR by proposing an alternative positioning of CH 3 -SCoM and CoMSSCoB in the active site pocket. The research suggested that CH 3 -SCoM (substrate) and CoMSSCoB (product) bind via their sulfonate groups to the Ni(I) center of cofactor F 430 . This binding allows for the reaction without substrate reorganization in the pocket but would require a long-range electron transfer. Altogether, the work summarized in this review reflects our current understanding of the enzyme's catalytic mechanism and structural dynamics. This is essential for developing efficient methane conversion technologies that could mitigate its environmental impact while harnessing energy-storage properties.

03 NATURAL GAS↗
NASA NTRS1975

Sample detection and analysis techniques for electrophoretic separation

Methods for detecting and analyzing biological agents suitable for space flight operations were studied primarily by literature searches which were conducted of cell separation techniques. Detection methods discussed include: photometrometric, electric, radiometric, micrometry, ultrasonic, microscopic, and photographic. A bibliography, and a directory of vendors are included along with an index of commercial hardware.

Falb, R. D.↗
NASA NTRS1992

New developments of a knowledge based system (VEG) for inferring vegetation characteristics

An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

Kimes, D. S.↗
NASA NTRS1996

An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.

Non-NASA Center↗
DOE OSTI2020

High-Temperature and High-Pressure In Situ Magic Angle Spinning Nuclear Magnetic Resonance Spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy represents an important technique to understand the structure and bonding environment of molecules. There exists a drive to conduct characterization experiment under conditions relevant to the chemical process of interest. To address this, in situ high-temperature, high-pressure MAS NMR methods have been developed to enable the observation of chemical interactions over a range of pressures (vacuum to several hundred bar) and temperatures (well below 0°C to 250°C). Further, the chemical identity of the samples can be comprised of solids, liquids, and gases or mixtures of the three. The method incorporates all-zirconia NMR rotors (sample holder for MAS NMR) which can be sealed using a threaded cap to compress an O-ring. This rotor exhibits great chemical resistance, temperature compatibility, low NMR background, and can withstand high pressures. These factors combined enable its use in a wide range of system combinations which permit its use in diverse fields as carbon sequestration, catalysis, material science, geochemistry, and biology. The flexibility of this technique makes it an attractive option for scientists from numerous disciplines.

Nuclear Magnetic Resonance, NMR, in situ, spectros↗
DOE OSTI2020

Preventing Bio-Bloopers and XFEL Follies: Best Practices from your Friendly Instrument Staff

Serial Femtosecond Crystallography (SFX) at X-ray Free electron Lasers (XFELs) is a relatively new field promising to deliver unparalleled spatial and temporal resolution on biological systems and there dynamics. Over the past decade, though, there have been a handful of results that have truly delivered on these promises. Why? SFX has many paradigm shifting techniques not seen in typical structural biology arenas, such as creating a concentrated slurry of microcrystals rather than a handful of loopable prisms worthy of a catalog photo. Then taking that slurry and high speed jetting them towards the vacuum or helium interation region to destroy less than 1% of your sample and waste the other 99. The literature is full of techniques and methods promising to cure what ails your experiment, yet as an instrument scientist will tell you –and a first author might admit after a few drinks at the conference happy hour—is that there are a lot more failures than the success we published, results may vary. We will walk through a best practices on how to prepare your sample and chose a sample delivery technique that will amerliorate your studies rather than undermine your hardwork and hopefully lead to better experimental planning and execution, inching you closer to that scientific goal and that call from Stockholm. This will be written in a more editorialized fashion and is meant to give the reader an idea of what to try or how they should be thinking. Welcome to SFX, now what?

47 OTHER INSTRUMENTATION↗
NASA NTRS2008

Cell-Detection Technique for Automated Patch Clamping

A unique and customizable machinevision and image-data-processing technique has been developed for use in automated identification of cells that are optimal for patch clamping. [Patch clamping (in which patch electrodes are pressed against cell membranes) is an electrophysiological technique widely applied for the study of ion channels, and of membrane proteins that regulate the flow of ions across the membranes. Patch clamping is used in many biological research fields such as neurobiology, pharmacology, and molecular biology.] While there exist several hardware techniques for automated patch clamping of cells, very few of those techniques incorporate machine vision for locating cells that are ideal subjects for patch clamping. In contrast, the present technique is embodied in a machine-vision algorithm that, in practical application, enables the user to identify good and bad cells for patch clamping in an image captured by a charge-coupled-device (CCD) camera attached to a microscope, within a processing time of one second. Hence, the present technique can save time, thereby increasing efficiency and reducing cost. The present technique involves the utilization of cell-feature metrics to accurately make decisions on the degree to which individual cells are "good" or "bad" candidates for patch clamping. These metrics include position coordinates (x,y) in the image plane, major-axis length, minor-axis length, area, elongation, roundness, smoothness, angle of orientation, and degree of inclusion in the field of view. The present technique does not require any special hardware beyond commercially available, off-the-shelf patch-clamping hardware: A standard patchclamping microscope system with an attached CCD camera, a personal computer with an imagedata- processing board, and some experience in utilizing imagedata- processing software are all that are needed. A cell image is first captured by the microscope CCD camera and image-data-processing board, then the image data are analyzed by software that implements the present machine-vision technique. This analysis results in the identification of cells that are "good" candidates for patch clamping (see figure). Once a "good" cell is identified, a patch clamp can be effected by an automated patchclamping apparatus or by a human operator. This technique has been shown to enable reliable identification of "good" and "bad" candidate cells for patch clamping. The ultimate goal in further development of this technique is to combine artificial-intelligence processing with instrumentation and controls in order to produce a complete "turnkey" automated patch-clamping system capable of accurately and reliably patch clamping cells with a minimum intervention by a human operator. Moreover, this technique can be adapted to virtually any cellular-analysis procedure that includes repetitive operation of microscope hardware by a human.

McDowell, Mark↗
DOE OSTI2022

Revisiting the K-edge X-ray absorption fine structure of Si, Ge–Si alloys, and the isoelectronic series: CuBr, ZnSe, GaAs, and Ge

Extended X-ray absorption fine structure (EXAFS) has evolved into an unprecedented local-structure technique that is routinely used to study materials’ problems in the biological, chemical, and physical sciences. Like many other experimental techniques, EXAFS also requires that several key atomic parameters must be known a priori before structural information can be quantitatively determined. Utilizing current analytical methods, we revisit the isoelectronic series CuBr, ZnSe, GaAs, and Ge originally studied by Stern et al. during the early development of EXAFS. We demonstrate that the ab initio EXAFS code FEFF accurately predicts the atomic phase shifts and backscattering amplitudes that are primarily functions of the sum of atomic numbers Z along an EXAFS scattering path. We also investigate quantitative fitting and first- and second-shell phase transferability together with problems that arise if a backscattering atom is identified incorrectly in an EXAFS fitting model. Features in the near-edge region, on the other hand, are shown to require a comprehensive treatment of the band structure and density-of-states, including effects of the screened Coulomb interaction between the photoelectron and core hole. Here, we demonstrate that the Bethe–Salpeter equation (BSE) accurately captures the NEXAFS (or XANES) portion of the spectrum for the isoelectronic series in addition to Si and Ge–Si alloys, including within a few eV of the absorption edge, where band structure and excitonic effects are most important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Recurrent and convolutional neural networks for sequential multispectral optoacoustic tomography ( MSOT ) imaging

Abstract Multispectral optoacoustic tomography (MSOT) is a beneficial technique for diagnosing and analyzing biological samples since it provides meticulous details in anatomy and physiology. However, acquiring high through‐plane resolution volumetric MSOT is time‐consuming. Here, we propose a deep learning model based on hybrid recurrent and convolutional neural networks to generate sequential cross‐sectional images for an MSOT system. This system provides three modalities (MSOT, ultrasound, and optoacoustic imaging of a specific exogenous contrast agent) in a single scan. This study used ICG‐conjugated nanoworms particles (NWs‐ICG) as the contrast agent. Instead of acquiring seven images with a step size of 0.1 mm, we can receive two images with a step size of 0.6 mm as input for the proposed deep learning model. The deep learning model can generate five other images with a step size of 0.1 mm between these two input images meaning we can reduce acquisition time by approximately 71%.

Juhong, Aniwat↗
DOE OSTI2020

Effects of sodium and calcium chloride ionic stresses on model yeast membranes revealed by molecular dynamics simulation

As efforts to move a renewable economy grow, it will be necessary to make use of microbial conversion strategies for the production of novel materials or the upgrading of waste to high-value products. One critical technical challenge currently limiting waste upgrading remains the difficulty in obtaining single-pot conversion techniques where physical, chemical, and biological conversion are performed in a single step. To overcome this challenge, a detailed understanding of how different stresses impact microbial membrane stability will be necessary. In this work, using all-atom molecular dynamics simulations, we examine the impacts of moderate concentrations of NaCl and CaCl 2 on a model yeast plasma membrane. Weak, though statistically significant, changes in membrane morphology and dynamics functions are observed that are consistent with swelling and stiffening. Additionally, an examination of the ion-lipid contacts and the behavior of water at the water-membrane interface suggests that the impacts of these common salts may, in part, be mediated through changes to water-membrane hydrogen-bonding and hydration water dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Advances in mass spectrometry-enabled multiomics at single-cell resolution

We report biological organisms are multifaceted, intricate systems where slight perturbations can result in extensive changes in gene expression, protein abundance and/or activity, and metabolic flux. These changes occur at different timescales, spatially across cells of heterogeneous origins, and within single-cells. Hence, multimodal measurements at the smallest biological scales are necessary to capture dynamic changes in heterogeneous biological systems. Of the analytical techniques used to measure biomolecules, mass spectrometry (MS) has proven to be a powerful option due to its sensitivity, robustness, and flexibility with regard to the breadth of biomolecules that can be analyzed. Recently, many studies have coupled MS to other analytical techniques with the goal of measuring multiple modalities from the same single-cell. It is with these concepts in mind that we focus this review on MS-enabled multiomic measurements at single-cell or near-single- cell resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Terahertz EPR spectroscopy using a 36-tesla high-homogeneity series-connected hybrid magnet

Electron Paramagnetic Resonance (EPR) is a powerful technique to study materials and biological samples on an atomic scale. High-field EPR in particular enables extracting very small g-anisotropies in organic radicals and half-filled 3d and 4f metal ions such as Mn II (3d 5 ) or Gd III (4f 7 ), and resolving EPR signals from unpaired spins with very close g-values, both of which provide high-resolution details of the local atomic environment. Before the recent commissioning of the high-homogeneity Series Connected Hybrid magnet (SCH, superconducting + resistive) at the National High Magnetic Field Laboratory (NHMFL), the highest-field, high-resolution EPR spectrometer available was limited to 25 T using a purely resistive “Keck” magnet at the NHMFL. Herein, we report the first EPR experiments performed using the SCH magnet capable of reaching the field of 36 T, corresponding to an EPR frequency of 1 THz for g = 2. The magnet’s intrinsic homogeneity (25 ppm, that is 0.9 mT at 36 T over 1 cm diameter, 1 cm length cylinder) was previously established by NMR. We characterized the magnet’s temporal stability (5 ppm, which is 0.2 mT at 36 T over one-minute, the typical acquisition time) using 2,2-diphenyl-1-picrylhydrazyl (DPPH). This high resolution enables resolving the weak g-anisotropy of 1,3-bis(diphenylene)-2-phenylallyl (BDPA), Δg = 2.5 × 10 –4 obtained from measurements at 932 GHz and 33 T. Subsequently, we recorded EPR spectra at multiple frequencies for two Gd III complexes with potential applications as spin labels. In conclusion, we demonstrated a significant reduction in line broadening in Gd[DTPA], attributed to second order zero field splitting, and a resolution enhancement of g-tensor anisotropy for Gd[sTPATCN]-SL.

47 OTHER INSTRUMENTATION↗