Search NASA⌕ Search

SEARCH · Search NASA

Results for “Analytical detection method”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Production and Evaluation of Fluorophore-Doped Polymer Substrates to Screen for Plastic-Degrading Enzymes

Fast and sensitive analytical methods are the key to efficient screening of plastic-degrading enzymes. Here, we present a streamlined and affordable approach to assess the enzymatic deconstruction of insoluble synthetic polymers by blending them with a fluorescent dye, rhodamine 6G, and we evaluate this screening method using poly(ethylene terephthalate) (PET) as a model material. Our results indicate that enzymatic depolymerization of the rhodamine-doped PET can be observed in a high-throughput fashion by following release of the fluorophore. The fluorescence data obtained during the hydrolysis of rhodamine-doped PET by 14 PET hydrolases, produced with a robotic platform, correlated with the quantitative chromatographic analysis of PET degradation products. Remarkably, the use of the rhodamine-loaded PET substrate resulted in negligibly low background signals even when detecting PETase activity in crude cell lysates, suggesting suitability for screening of a wide variety of samples. Encouraged by these results, we next produced a selection of polyethylene- and nylon-based materials loaded with rhodamine 6G. While rapid leaching of fluorophore observed with nylon substrates limits the utility of the method for detecting nylonase activity, the rhodamine-loaded polyethylene showed promising performance in passive diffusion tests, indicating that this latter substrate may be used to screen for polyolefin-degrading enzymes.

09 BIOMASS FUELS↗
NASA NTRS1992

X-Ray Microanalysis and Electron Energy Loss Spectrometry in the Analytical Electron Microscope: Review and Future Directions

This paper reviews and discusses future directions in analytical electron microscopy for microchemical analysis using X-ray and Electron Energy Loss Spectroscopy (EELS). The technique of X-ray microanalysis, using the ratio method and k(sub AB) factors, is outlined. The X-ray absorption correction is the major barrier to the objective of obtaining I% accuracy and precision in analysis. Spatial resolution and Minimum Detectability Limits (MDL) are considered with present limitations of spatial resolution in the 2 to 3 microns range and of MDL in the 0.1 to 0.2 wt. % range when a Field Emission Gun (FEG) system is used. Future directions of X-ray analysis include improvement in X-ray spatial resolution to the I to 2 microns range and MDL as low as 0.01 wt. %. With these improvements the detection of single atoms in the analysis volume will be possible. Other future improvements include the use of clean room techniques for thin specimen preparation, quantification available at the I% accuracy and precision level with light element analysis quantification available at better than the 10% accuracy and precision level, the incorporation of a compact wavelength dispersive spectrometer to improve X-ray spectral resolution, light element analysis and MDL, and instrument improvements including source stability, on-line probe current measurements, stage stability, and computerized stage control. The paper reviews the EELS technique, recognizing that it has been slow to develop and still remains firmly in research laboratories rather than in applications laboratories. Consideration of microanalysis with core-loss edges is given along with a discussion of the limitations such as specimen thickness. Spatial resolution and MDL are considered, recognizing that single atom detection is already possible. Plasmon loss analysis is discussed as well as fine structure analysis. New techniques for energy-loss imaging are also summarized. Future directions in the EELS technique will be the development of new spectrometers and improvements in thin specimen preparation. The microanalysis technique needs to be simplified and software developed so that the EELS technique approaches the relative simplicity of the X-ray technique. Finally, one can expect major improvements in EELS imaging as data storage and processing improvements occur.

Goldstein, J. I.↗
NASA NTRS2015

A Compact, Solid-State UV (266 nm) Laser System Capable of Burst-Mode Operation for Laser Ablation Desorption Processing

Compared to wet chemistry and pyrolysis techniques, in situ laser-based methods of chemical analysis provide an ideal way to characterize precious planetary materials without requiring extensive sample processing. In particular, laser desorption and ablation techniques allow for rapid, reproducible and robust data acquisition over a wide mass range, plus: Quantitative, spatially-resolved measurements of elemental and molecular (organic and inorganic) abundances; Low analytical blanks and limits-of-detection ( ng g-1); and, the destruction of minimal quantities of sample ( g) compared to traditional solution and/or pyrolysis analyses (mg).

Laser↗
NASA NTRS2009

Method for detection of selected chemicals in an open environment

The present invention relates to a space-invariant independent component analysis and electronic nose for detection of selective chemicals in an unknown environment, and more specifically, an approach to analysis of sensor responses to mixtures of unknown chemicals by an electronic nose in an open and changing environment. It is intended to fill the gap between an alarm, which has little or no ability to distinguish among chemical compounds causing a response, and an analytical instrument, which can distinguish all compounds present but with no real-time or continuous event monitoring ability.

Duong, Tuan↗
DOE OSTI2024

Algorithm 1049: The Delaunay Density Diagnostic

Accurate approximation of a real-valued function depends on two aspects of the available data: the density of inputs within the domain of interest and the variation of the outputs over that domain. There are few methods for assessing whether the density of inputs is sufficient to identify the relevant variations in outputs—i.e., the “geometric scale” of the function—despite the fact that sampling density is closely tied to the success or failure of an approximation method. In this article, we introduce a general purpose, computational approach to detecting the geometric scale of real-valued functions over a fixed domain using a deterministic interpolation technique from computational geometry. The algorithm is intended to work on scalar data in moderate dimensions (2–10). Our algorithm is based on the observation that a sequence of piecewise linear interpolants will converge to a continuous function at a quadratic rate (in L 2 norm) if and only if the data are sampled densely enough to distinguish the feature from noise (assuming sufficiently regular sampling). We present numerical experiments demonstrating how our method can identify feature scale, estimate uncertainty in feature scale, and assess the sampling density for fixed (i.e., static) datasets of input–output pairs. Finally, we include analytical results in support of our numerical findings and have released lightweight code that can be adapted for use in a variety of data science settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Method Validation Summary for L16.2 AD-ISO-0015 for ISO-17025 / NFAC Applications

Methods for the analysis of semi-volatile organic compounds are employed at Savannah River National Laboratory (SRNL) for routine and non-routine samples from tank waste, process control, waste acceptance, and a wide array of other process and research samples. A method has been developed by SRNL, based on existing methods for semi-volatile analysis, for the analysis of nitroaromatic high explosives by gas chromatography / mass spectrometry in soils and sediments. Relative to past work performed at SRNL on nitroaromatic explosives, this developed, optimized, and validated method can achieve lower limits of detection and quantitation, greater precision, lower bias, higher linearity, and accuracy across a greater linear range.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

The evolution of analytical techniques for multiplex analysis of protein biomarkers

Introduction: The landscape of biomarker development has evolved with advanced analytical technologies, particularly affinity- and mass spectrometry-based techniques. These advancements have deepened our understanding of disease mechanisms, enabling the development of precise diagnostic tools and personalized medicine. Protein biomarkers, which play pivotal roles in biological processes, have become invaluable in diagnosing and monitoring diseases, aided by their presence in various biological samples and the availability of established detection methods. Areas covered: This review covers the role of protein biomarkers in clinical practice, the development and dimensionality of protein biomarkers, advancements in detection technologies, a comparison of these technologies, and future directions in biomarker discovery and disease mechanism elucidation. Expert opinion: Advances in biomarker technologies have the potential to transform diagnostics and personalized treatment but face challenges such as high costs and technical complexity. Enhancing reproducibility and integrating multi-omics approaches may offer better insights. In conclusion, the field should evolve toward high-throughput, automated methods, continuously adapting research, and clinical practices.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quantitative Nonlinear Optical Polarimetry with High Spatial Resolution

Nonlinear optical microscopy such as in the optical second-harmonic generation (SHG) modality has become a popular tool today for probing materials in the physical and biological sciences. While imaging and spectroscopy are widely used in the microscopy mode, nonlinear polarimetry, which can shed light on materials’ symmetry and microstructure, is relatively underdeveloped. This is partly because quantitative analytical modeling of the optical SHG response for anisotropic crystals and films largely assumes low-numerical aperture (NA) focusing of light, where the plane-wave approximation is sufficient. Tight focusing provides unique benefits in revealing out-of-plane polarization responses, which cannot be detected by near-plane-wave illumination at normal incidence. Here, we outline a method for quantitatively analyzing SHG polarimetry measurements obtained under high-NA focusing within a microscope geometry. Experiments and simulations of a variety of standard samples, from single crystals to thin films, are in good agreement, including measured and simulated spatial SHG maps of ferroelectric domains. A solution to the inverse problem is demonstrated, where the spatial distribution of an SHG tensor with unknown tensor coefficient magnitudes is determined by experimentally measured polarimetry. The ability to extract the out-of-plane component of the nonlinear polarization in normal incidence is demonstrated, which can be valuable for high-resolution polarimetry of 2D materials, thin films, heterostructures, and uniaxial crystals with a strong out-of-plane response.

36 MATERIALS SCIENCE↗
NASA NTRS2011

High temperature ion channels and pores

The present invention includes an apparatus, system and method for stochastic sensing of an analyte to a protein pore. The protein pore may be an engineer protein pore, such as an ion channel at temperatures above 55.degree. C. and even as high as near 100.degree. C. The analyte may be any reactive analyte, including chemical weapons, environmental toxins and pharmaceuticals. The analyte covalently bonds to the sensor element to produce a detectable electrical current signal. Possible signals include change in electrical current. Detection of the signal allows identification of the analyte and determination of its concentration in a sample solution. Multiple analytes present in the same solution may also be detected.

Kang, Xiaofeng↗
NASA NTRS2008

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗
DOE OSTI2026

Carbamoylation as an Effective Tool in the Analysis of the Soman Nerve Agent Marker Pinacolyl Alcohol in Soil Matrices by EI-GC-MS and LC-HRMS

Pinacolyl alcohol (PA) is a Schedule 2 chemical commonly featured in most proficiency tests (PTs) administered by the Organisation for the Prohibition of Chemical Weapons (OPCW) due to its direct as well as forensic link to the nerve agent Soman. Therefore, its detection by Chemical Weapons Convention (CWC) inspection teams during on-site investigations is a strong indicator of the past or latent presence of Soman in the environment. Its small molecular weight (102), early elution time, and poor ionization profile make PA a challenging analyte to detect particularly at low concentrations (∼1–10 μg/g). In this work, 1,1′-carbonyldimidazole (CDI) has been used to effectively modify PA for the first time in two different soil matrices (Virginia type A soil and silt sediment) at two separate concentrations (1 and 10 μg/g) for its subsequent detection by EI-GC-MS and LC-HRMS methods. For the EI-GC-MS analysis, the PA carbamate derivative (PIC) exhibits improved chromatography relative to PA such as improved peak shape, increased molecular weight (196 for PIC and 102 for PA) and increased retention time (16.9 min for PIC and ∼4.1 min for PA). In addition, the derivatization also improves the detection of PA by LC-HRMS as the PIC product possesses protonation sites (i.e., imidazole ring) relative to none exhibited by PA. More importantly, the carbamoylation proceeds under mild conditions (55 °C, no base) and rapidly (3 h), characteristics that make it an appealing protocol for the analysis of PA during OPCW PTs or real case scenarios particularly in instances where it is present at low concentrations. It is anticipated that the protocol can be applied to the forensic analysis of this important Soman marker in various environmental matrices.

Chemistry↗
DOE OSTI2021

Advances in the electron diffraction characterization of atomic clusters and nanoparticles

Nanoparticles and metallic clusters continue to make a remarkable impact on novel and emerging technologies. In recent years, there have been impressive advances in the controlled synthesis of clusters and their advanced characterization. One of the most common ways to determine the structures of nanoparticles and clusters is by means of X-ray diffraction methods. However, this requires the clusters to crystallize in a similar way to those used in protein studies, which is not possible in many cases. Novel methods based on electron diffraction have been used to efficiently study individual nanoparticles and clusters and these can overcome the obstacles commonly encountered during X-ray diffraction methods without the need for large crystals. These novel methodologies have improved with advances in electron microscopy instrumentation and electron detection. Here, we review advanced methodologies for characterizing metallic nanoparticles and clusters using a variety of electron diffraction procedures. These include selected area electron diffraction, nanobeam diffraction, coherent electron diffraction, precession electron diffraction, scanning transmission electron microcopy diffraction, and high throughput data analytics, which leverage deep learning to reduce the propensity for data errors and translate nanometer and atomic scale measurements into material data.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Soil Sampling Results for Closure of a Portion of Solid Waste Management Unit #16

The U.S. Department of Energy/National Nuclear Security Administration (DOE/ NNSA) and National Technology & Engineering Solutions of Sandia, LLC (NTESS), the management and operating contractor for Sandia National Laboratories/California (SNL/CA), has prepared this soil sampling results report for closure of a portion of Solid Waste Management Unit (SWMU) #16. The entire network of SNL/CA sanitary sewer lines, including building laterals, was identified as SWMU #16 under a Resource Conservation and Recovery Act (RCRA) Facility Assessment conducted for SNL/CA in April 1991 (DOE 1992). Along with the previous SWMU #16 investigation results (SNL/CA 2019), the results of this investigation are intended to support closure decisions by the San Francisco Bay Regional Water Quality Control Board (RWQCB), as discussed below. SNL/CA personnel completed upgrading its sanitary sewer discharge network in 2019. These upgrades included installing new sections of underground lines and decommissioning certain sections of the old piping system by capping in place. To date, several sections of the sewer line have been abandoned-in-place by capping as new sewer lines were installed or flow was rerouted to other existing lines. To formally close these abandoned sections of the sewer line, the RWQCB required that SNL/CA personnel collect soil samples to be analyzed for contaminants potentially released from the sewer lines. SNL/CA personnel hired Weiss Associates (Weiss) of Emeryville, California to prepare a sampling and analysis plan, implement the sampling plan and report the results of the investigation under Purchase Order #2166257. The Sampling and Analysis Plan for Partial Closure of Solid Waste Management Unit #16 (SAP) was submitted to the RWQCB on August 14, 2020 by Weiss on behalf of SNL/CA. The RWQCB approved the SAP on September 30, 2020 after Weiss updated the method detection limit and reporting limits for total polychlorinated biphenyls (PCBs) and individual aroclors. Soil sampling was conducted in accordance with the SAP except that fewer locations were sampled due to site constraints, as discussed below. This report presents the results of the sampling effort and documents all associated field activities including borehole clearing, soil sample collection, storage and transportation to the analytical laboratories, borehole backfilling and surface restoration, and storage of investigation-derived waste (IDW) for future profiling and disposal by SNL/CA waste management personnel.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2012

The Atacama Cosmology Telescope: A Measurement of the Thermal Sunyaev-Zel'dovich Effect Using the Skewness of the CMB Temperature Distribution

We present a detection of the unnormalized skewness (T(sup ~)(sup 2)(n(circumflex)) induced by the thermal Sunyaev-Zel'dovich (tSZ) effect in filtered Atacama Cosmology Telescope (ACT) 148 GHz cosmic microwave background temperature maps. Contamination due to infrared and radio sources is minimized by template subtraction of resolved sources and by constructing a mask using outlying values in the 218 GHz (tSZ-null) ACT maps. We measure (T(sup ~)(sup 3) (n(circumflex)) = -31 plus or minus 6 micro-K(sup 3) (measurement error only) or plus or minus 14 micro-K(sup 3) (including cosmic variance error) in the filtered ACT data, a 5sigma detection. We show that the skewness is a sensitive probe of sigma(sub 8), and use analytic calculations and tSZ simulations to obtain cosmological constraints from this measurement. From this signal alone we infer a value of sigma(sub 8) = 0.78 sup +0.03 sub -0.04 (68% C.L.) sup +0.05 sub -0.16. Our results demonstrate that measurements of nonGaussianity can be a useful method for characterizing the tSZ effect and extracting the underlying cosmological information.

Wilson, Michael J.↗
DOE OSTI2021

Revealing the Chemical Bonding in Adatom Arrays via Machine Learning of Hyperspectral Scanning Tunneling Spectroscopy Data

The adatom arrays on surfaces offer an ideal playground to explore the mechanisms of chemical bonding via changes in the local electronic tunneling spectra. While this information is readily available in hyperspectral scanning tunneling spectroscopy data, its analysis has been considerably impeded by a lack of suitable analytical tools. Here we develop a machine learning based workflow combining supervised feature identification in the spatial domain and unsupervised clustering in the energy domain to reveal the details of structure-dependent changes of the electronic structure in adatom arrays on the Co 3 Sn 2 S 2 cleaved surface. This approach, in combination with first-principles calculations, provides insight for using artificial neural networks to detect adatoms and classifies each based on their local neighborhood comprised of other adatoms. These structurally classified adatoms are further spectrally deconvolved. The unexpected inhomogeneity of electronic structures among adatoms in similar configurations is unveiled using this method, suggesting there is not a single atomic species of adatoms, but rather multiple types of adatoms on the Co 3 Sn 2 S 2 surface. This is further supported by a slight contrast difference in the images (or slight size variation) of the topography of the adatoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

Spacelab Charcoal Analyses

This report describes analytical methods and results obtained from chemical analysis of 31 charcoal samples in five sets. Each set was obtained from a single scrubber used to filter ambient air on board a Spacelab mission. Analysis of the charcoal samples was conducted by thermal desorption followed by gas chromatography/mass spectrometry (GC/MS). All samples were analyzed using identical methods. The method used for these analyses was able to detect compounds independent of their polarity or volatility. In addition to the charcoal samples, analyses of three Environmental Control and Life Support System (ECLSS) water samples were conducted specifically for trimethylamine.

Slivon, L. E.↗
NASA NTRS1995

Automated Performance Prediction of Message-Passing Parallel Programs

The increasing use of massively parallel supercomputers to solve large-scale scientific problems has generated a need for tools that can predict scalability trends of applications written for these machines. Much work has been done to create simple models that represent important characteristics of parallel programs, such as latency, network contention, and communication volume. But many of these methods still require substantial manual effort to represent an application in the model's format. The NIK toolkit described in this paper is the result of an on-going effort to automate the formation of analytic expressions of program execution time, with a minimum of programmer assistance. In this paper we demonstrate the feasibility of our approach, by extending previous work to detect and model communication patterns automatically, with and without overlapped computations. The predictions derived from these models agree, within reasonable limits, with execution times of programs measured on the Intel iPSC/860 and Paragon. Further, we demonstrate the use of MK in selecting optimal computational grain size and studying various scalability metrics.

Block, Robert J.↗
NASA NTRS1997

High precision computing with charge domain devices and a pseudo-spectral method therefor

The present invention enhances the bit resolution of a CCD/CID MVM processor by storing each bit of each matrix element as a separate CCD charge packet. The bits of each input vector are separately multiplied by each bit of each matrix element in massive parallelism and the resulting products are combined appropriately to synthesize the correct product. In another aspect of the invention, such arrays are employed in a pseudo-spectral method of the invention, in which partial differential equations are solved by expressing each derivative analytically as matrices, and the state function is updated at each computation cycle by multiplying it by the matrices. The matrices are treated as synaptic arrays of a neural network and the state function vector elements are treated as neurons. In a further aspect of the invention, moving target detection is performed by driving the soliton equation with a vector of detector outputs. The neural architecture consists of two synaptic arrays corresponding to the two differential terms of the soliton-equation and an adder connected to the output thereof and to the output of the detector array to drive the soliton equation.

Barhen, Jacob↗