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At least 613 records · Page 34

Trace detection of analytes using portable raman systems

Apparatuses and methods for in situ detection of a trace amount of an analyte are disclosed herein. In a general embodiment, the present disclosure provides a surface-enhanced Raman spectroscopy (SERS) insert including a passageway therethrough, where the passageway has a SERS surface positioned therein. The SERS surface is configured to adsorb molecules of an analyte of interest. A concentrated sample is caused to flow over the SERS surface. The SERS insert is then provided to a portable Raman spectroscopy system, where it is analyzed for the analyte of interest.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analytical Methods for Biomass Characterization during Pretreatment and Bioconversion

Lignocellulosic biomass has been introduced as a promising resource for alternative fuels and chemicals because of its abundance and complement for petroleum resources. Biomass is a complex biopolymer and its compositional and structural characteristics largely vary depending on its species as well as growth environments. Because of complexity and variety of biomass, understanding its physicochemical characteristics is a key for effective biomass utilization. Characterization of biomass does not only provide critical information of biomass during pretreatment and bioconversion, but also give valuable insights on how to utilize the biomass. For better understanding biomass characteristics, good grasp and proper selection of analytical methods are necessary. This chapter introduces existing analytical approaches that are widely employed for biomass characterization during biomass pretreatment and conversion process. Diverse analytical methods using Fourier transform infrared (FTIR) spectroscopy, gel permeation chromatography (GPC), and nuclear magnetic resonance (NMR) spectroscopy for biomass characterization are reviewed. In addition, biomass accessibility methods by analyzing surface properties of biomass are also summarized in this chapter.

accessibility↗

Semi-Analytical Benchmarks for MCNP6 [Slides]

This presentation begins with an Introduction and some background on semi-analytical benchmarks for MCNP6. Discussion topics include: verification & validation, MCNP history of V&V, semi-analytic benchmarks, numerical Results, comparison of semi-analytic to MCNP, and tips for proper comparison. This presentation ends with conclusions & future Work.

97 MATHEMATICS AND COMPUTING↗

On Concavity and Utilization Analytics of Wide-Area Network Transport Protocols

Wide-area data transfers in high-performance computing infrastructures and big data applications are increasingly carried over dynamically provisioned dedicated network connections, which provide high capacities with no competing traffic. Throughput of TCP and UDT over wide-area connections depends, often in a complex non-linear way, on the congestion control mechanism, buffer sizes, and the number of parallel streams. In addition, our extensive TCP and UDT throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs) show significant statistical and temporal variations. Consequently, parameter selection and optimization for transport methods require data analytics to complement analytical throughput models. We present analytics based on the concavity-convexity of throughput profiles which provide insights into peak throughput and superior/inferior trend compared to linear interpolations based on RTT. In particular, we propose the utilization-concavity coefficient, a scalar metric that incorporates both utilization and concavity profile to characterize the overall performance of a transport protocol. These measurements-based anaytics enable us to select a transport protocol and its parameters for a given host and connection configuration to achieve high throughput with statistical guarantees.

Rao, Nageswara↗

When Data Analytics Meet Site Operation: Benefits and Challenges

Demand for using data analytics for energy management in buildings is rising. Such analytics are required for advanced measurement and verification, commissioning, automated fault-detection and diagnosis, and optimal control. While novel analytics algorithms continue to be developed, bottlenecks and challenges arise when deploying them for demonstration, for a number of reasons that do not necessarily have to do with the algorithms themselves. It is important for developers of new technologies to be aware of the challenges and potential solutions during demonstration. Therefore, this paper describes a recent deployment of an automated, physical model-based, FDD and optimal control tool, highlighting its design and as-operated benefits that the tool provides. Furthermore, the paper presents challenges faced during deployment and testing along with solutions used to overcome these challenges. The challenges have been grouped into four categories: Data Management, Physical Model Development and Integration, Software Development and Deployment, and Operator Use. The paper concludes by discussing how challenges with this project generalize to common cases, how they could compare to other projects in their severity, and how they may be addressed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Rapid and continuous analyte processing in droplet microfluidic devices

The compositions and methods described herein are designed to introduce functionalized microparticles into droplets that can be manipulated in microfluidic devices by fields, including electric (dielectrophoretic) or magnetic fields, and extracted by splitting a droplet to separate the portion of the droplet that contains the majority of the microparticles from the part that is largely devoid of the microparticles. Within the device, channels are variously configured at Y- or T junctions that facilitate continuous, serial isolation and dilution of analytes in solution. The devices can be limited in the sense that they can be designed to output purified analytes that are then further analyzed in separate machines or they can include additional channels through which purified analytes can be further processed and analyzed.

Strey, Helmut↗

Device and system for selective ionization and analyte detection and method of using the same

Disclosed herein are embodiments of a system for selectively ionizing samples that may comprise a plurality of different analytes that are not normally detectable using the same ionization technique. The disclosed system comprises a unique split flow tube that can be coupled with a plurality of ionization sources to facilitate using different ionization techniques for the same sample. Also disclosed herein are embodiments of a method for determining the presence of analytes in a sample, wherein the number and type of detectable analytes that can be identified is increased and sensitivity and selectivity are not sacrificed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Device and system for selective ionization and analyte detection and method of using the same

Disclosed herein are embodiments of a system for selectively ionizing samples that may comprise a plurality of different analytes that are not normally detectable using the same ionization technique. The disclosed system comprises a unique split flow tube that can be coupled with a plurality of ionization sources to facilitate using different ionization techniques for the same sample. Also disclosed herein are embodiments of a method for determining the presence of analytes in a sample, wherein the number and type of detectable analytes that can be identified is increased and sensitivity and selectivity are not sacrificed.

Denis, Elizabeth↗

Operational Focused Data Analytics for Optimizing Radiation Portal Monitor-Based Nuclear Smuggling Detection Systems at Global Ports of Entry

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence has deployed a fleet of radiation portal monitors (RPMs) across the world at global ports of entry including seaports, airports, and land border crossings. These RPMs are integrated into radiation detection systems (RDS) that also include fixed cameras, optical character recognition (OCR) systems, primary scanning systems (e.g., X-ray or gamma-ray), and secondary scanning systems (e.g., spectroscopic radiation portal monitors, portable radiation detection systems). The data from these sensing technologies is collected at the Central Alarm Station (CAS) where servers and computers reside to control and operate the system. Operators utilize the data collected by the CAS and declared cargo information to make decisions on how to respond to an alarm.This work explores the use of CAS-located data, looking at both the sensor data streams and operator inputs, to perform analysis which supports customs and border protection agencies to improve training capability and operational effectiveness. We focus on analyzing site level effectiveness and behavior by rolling up CAS-located data collected from individual occurrences. To-date, more than 15 sites (e.g., seaports, airports, border crossings) have been analyzed in this manner with the goal of understanding system operations to verify effectiveness and recommend potential improvements. This work first aims to provide background information on relevant CAS-located data sources and our current operational system analytics process including example results. After summarizing our current analytic techniques, we discuss how the future data analytics systems can provide key benefits to improving operational performance while minimizing the burden these detection systems place on operators.

Kuhn, Michael↗

Analytical Approach to Evaluate Uncertainty in Discharged Inventory Estimates at the Hanford Site - 19012

Many waste sites (>400) located within the Central Plateau portion of the Hanford Site received liquid discharges during the nuclear weapons material production mission (1944-1988). The Hanford Soil Inventory Model (SIM) is developed to quantitatively evaluate the discharged inventory for important radionuclides and chemicals at a given waste site to support fate and transport modeling of contaminants. An analytic approach was developed to estimate inventory and associated uncertainty. The approach was implemented for SIM and compared to a prior stochastic implementation applying a Monte-Carlo sampling approach. The analytic approach provides exact mean and variance results and the run times are much faster compared to the Monte-Carlo sampling approach. With the improved solution method using the analytical approach, it is feasible to run inventory updates and reduce associated uncertainty ranges. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Proposed Analytical Methods for Determining Filter Media Properties

High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Towards an Open (Data) Science Analytics-Hub for Reproducible Multi-Model Climate Analysis at Scale

Open Science is key to future scientific research and promotes a deep transformation in the whole scientific research process encouraging the adoption of transparent and collaborative scientific approaches aimed at knowledge sharing. Open Science is increasingly gaining attention in the current and future research agenda worldwide. To effectively address Open Science goals, besides Open Access to results and data, it is also paramount to provide tools or environments to support the whole research process, in particular the design, execution and sharing of transparent and reproducible experiments, including data provenance (or lineage) tracking. This work introduces the Climate Analytics-Hub, a new component on top of the Earth System Grid Federation (ESGF), which joins big data approaches and parallel computing paradigms to provide an Open Science environment for reproducible multi-model climate change data analytics experiments at scale. An operational implementation has been set up at the SuperComputing Centre of the Euro- Mediterranean Center on Climate Change, with the main goal of becoming a reference Open Science hub in the climate community regarding the multi-model analysis based on the Coupled Model Intercomparison Project (CMIP).

analytics-hub↗

Data review processes in the analytical laboratory

These documents contain information on the Analytical laboratory data review processes for the following analytical techniques: - alpha spectrometry - light elements analyses - gamma spectrometry - gas proportional flow counting - HR-ICP-MS - Q-ICP-MS - MC-ICP-MS - ICP OES - liquid scintillation counting

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A modified electrolyte non-random two-liquid model with analytical expression for excess enthalpy: Application to the MEA-H 2 O-CO 2 system

We report accurate thermodynamic properties of electrolyte systems are critical for the design and operation of many chemical processes. A comprehensive description of the thermodynamic framework for multi-electrolyte mixed solvent systems is presented, where the parameter structure of the symmetric electrolyte-Non-Random Two Liquid (e-NRTL) model is reformulated and a thermodynamically consistent and analytically derived formulation for the excess enthalpy is developed from the e-NRTL model. The refined parameter structure of the e-NRTL model avoids numerical singularities of the analytical formulation for the excess enthalpy in the absence of ionic species and extends the derived excess enthalpy formulation to non-electrolyte systems. The thermodynamic framework is demonstrated for the MEA-H 2 O-CO 2 case study using experimental data on thermodynamic quantities for the binary MEA-H 2 O system and the ternary MEA-H 2 O-CO 2 system. The model is implemented in Pyomo and will be available for release in the Institute for the Design of Advanced Energy Systems (IDAES) computational platform.

Monoethanolamine↗

Chiral Separation of G-type Chemical Warfare Nerve Agents via Analytical Supercritical Fluid Chromatography: SEPARATION OF G-TYPE CHEMICAL WARFARE NERVE AGENTS

Chemical warfare nerve agents (CWNAs) are extremely toxic organophosphorus compounds that contain a chiral phosphorus center. Undirected synthesis of G-type CWNAs produces stereoisomers of tabun, sarin, soman, and cyclosarin (GA, GB, GD, and GF, respectively). Analytical-scale methods were developed using a supercritical fluid chromatography (SFC) system in tandem with a mass spectrometer for the separation, quantitation, and isolation of individual stereoisomers of GA, GB, GD, and GF. Screening various chiral stationary phases (CSPs) for the capacity to provide full baseline separation of the CWNAs revealed that a Regis WhelkO1 (SS) column was capable of separating the enantiomers of GA, GB, and GF, with elution of the P(+) enantiomer preceding elution of the corresponding P(–) enantiomer; two WhelkO1 (SS) columns had to be connected in series to achieve complete baseline resolution. The four diastereomers of GD were also resolved using two tandem WhelkO1 (SS) columns, with complete baseline separation of the two P(+) epimers. A single WhelkO1 (RR) column with inverse stereochemistry resulted in baseline separation of the GD P(–) epimers. The analytical methods described can be scaled to allow isolation of individual stereoisomers to assist in screening and development of countermeasures to organophosphorus nerve agents

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

What can we learn from N 2 O isotope data? – Analytics, processes and modelling

The isotopic composition of nitrous oxide (N 2 O) provides useful information for evaluating N 2 O sources and budgets. Due to the co–occurrence of multiple N 2 O transformation pathways, it is, however, challenging to use isotopic information to quantify the contribution of distinct processes across variable spatiotemporal scales. Here, we present an overview of recent progress in N 2 O isotopic studies and provide suggestions for future research, mainly focusing on: analytical techniques; production and consumption processes; and interpretation and modelling approaches. Comparing isotope–ratio mass spectrometry (IRMS) with laser absorption spectroscopy (LAS), we conclude that IRMS is a precise technique for laboratory analysis of N 2 O isotopes, while LAS is more suitable for in situ/inline studies and offers advantages for site–specific analyses. When reviewing the link between the N 2 O isotopic composition and underlying mechanisms/processes, we find that, at the molecular scale, the specific enzymes and mechanisms involved determine isotopic fractionation effects. In contrast, at plot–to–global scales, mixing of N 2 O derived from different processes and their isotopic variability must be considered. We also find that dual isotope plots are effective for semi–quantitative attribution of co–occurring N 2 O production and reduction processes. More recently, process–based N 2 O isotopic models have been developed for natural abundance and 15 N–tracing studies, and have been shown to be effective, particularly for data with adequate temporal resolution. Here, despite the significant progress made over the last decade, there is still great need and potential for future work, including development of analytical techniques, reference materials and inter–laboratory comparisons, further exploration of N 2 O formation and destruction mechanisms, more observations across scales, and design and validation of interpretation and modelling approaches. Synthesizing all these efforts, we are confident that the N 2 O isotope community will continue to advance our understanding of N 2 O transformation processes in all spheres of the Earth, and in turn to gain improved constraints on regional and global budgets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Cameron-Storvick Theorem for Analytic Feynman Integrals on Product Abstract Wiener Space and Applications

In this paper we derive a Cameron-Storvick theorem for the analytic Feynman integral of functionals on product abstract Wiener space B{sup 2}. We then apply our result to obtain an evaluation formula for the analytic Feynman integral of unbounded functionals on B{sup 2}. We also present meaningful examples involving functionals which arise naturally in quantum mechanics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optical-property coefficient estimation of bulky medium in experiments with a succinctly analytical calculation

Diffuse optical imaging enables to reconstruct distribution of optical properties, absorption and scattering coefficients, in tissue for breast cancer detection based on diffusion equation with the help of the initial guess obtained from measured data. To estimate the initial guess of the optical-property coefficients, an analytical solution of diffusion equation can be used and compared with the measured data. The analytical solution for a homogeneous infinite medium can be obtained in the frequency domain, expressing that the photon intensity and the phase lag relative to the distance between source and detector in a linear relationship. In this study, a succinct calculation using the trigonometric relation is proposed to estimate the optical-property coefficients. A tank-type and a cylinder Lipovenoes phantoms with two concentrations of 1.25% and 2.5% are employed and measured for verification. It is found that the method proposed here shows better results and results in estimation errors of 0–14.81% for μ{sub a} and 20–42% for μ{sub s}′.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗