Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Process Sample Analysis”

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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Final Scientific/Technical Report for DE-FG02-07ER64500 Study of Lignocellulosic Material Degradation with CARS Microscopy

The program of research undertaken by our Harvard group, in collaboration with Dr. Ding at the National Renewable Energy Laboratory (NREL) in Golden, CO, seeks to introduce, validate and apply a new analytical technique to study the conversion of lignocellulosic biomass into ethanol. This conversion process has been the subject of intense interest over the past few years because of its potential to provide a clean, renewable source of energy to meet increasing global demand. During the funding period, we have clearly demonstrated visualization of lignin and cellulose using intrinsic vibrational contrast with simulated Raman scattering (SRS) microscopy, developed at Harvard. Our approach offers high spatial resolution and time resolution that is sufficient to capture the kinetics of a pre‐treatment process. This is reflected by the publications listed below, as well as the use of SRS microscopy at NREL as a routine analysis tool for research on lignocellulosic biomass. In our original proposal, we envisioned moving to near‐field CARS imaging in order to perform chemical mapping at the nanoscale. However, given the dramatic progress made by our group in SRS imaging, we concentrated our efforts on using multi‐component SRS (lignin, cellulose, lipid, water, protein, deuterated metabolites, etc.) to quantitatively understand the spatially dispersed kinetics in a variety of plant samples under a variety of conditions. In addition, we built a next generation laser system based on fiber laser technology that allowed rugged and portable instrumentation for SRS microscopy. We also pursued new imaging approaches to improve the acquisition speed of SRS imaging of lignocellulose without sacrificing signal‐to‐noise ratio. This allowed us to image larger volumes of tissue with higher time resolution to get a more comprehensive picture of the heterogeneity of this chemical process from the submicron up to the centimeter scale.

09 BIOMASS FUELS↗
DOE OSTI2017

A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past the application of sensitivity analysis, such as Degree of Rate Control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. Here in this study we present an efficient and robust three stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using CO oxidation on RuO 2 (110) as a prototypical reaction. In a first step, we utilize the Fisher Information Matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally we adopt a method for sampling coupled finite differences for evaluating the sensitivity measure of lattice based models. This allows efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano scale design of heterogeneous catalysts.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A Statistical Framework for Evaluating Rain Microphysics in Model Simulations and Disdrometer Observations

Abstract Statistical analyses of a large disdrometer data set and a diverse set of model simulations for convection using the Regional Atmospheric Modeling System were conducted, with the mutual goal of providing insights into precipitation formation and microphysical processes. We demonstrate that a two‐moment bulk microphysical model successfully captures the dominant observed modes of variability in rainfall related to rainfall intensity and raindrop size distributions. The model reproduced the general distribution of observed precipitation groups (PGs) derived from Principal Component Analysis. The multi‐variable analysis also uncovered some shortcomings in the model as well as limitations of the disdrometer data. The model solutions were constrained in their predicted drop size distributions (DSDs) due to the fixed DSD parameters assumed in a two‐moment microphysics scheme. A case study from the Mid‐latitude Continental Clouds and Convection Experiment field project demonstrated how model results can be used to contextualize the disdrometer observations which are limited in sample size, spatial coherence, and detection of small drops and low drop concentrations. The case study also showed that the spatial patterns of the statistically derived PGs revealed by the model are consistent with the hypothesized microphysical processes that determine surface rain DSDs. This work demonstrates how leveraging the strengths of observations and models together can improve our understanding and representation of rain microphysical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Effect of Preheated Microstructure Vis-à-vis Process Parameters and Characterization of Orange Peel in Incremental Forming of AA1050 Sheets

The present investigation systematically analyzes and compares the influence of microstructure and crystallographic texture of AA1050 sheet to that of the most critical process parameters, namely tool dimension, and incremental step depth, in single-point incremental forming (SPIF) process. The sheet samples were preheated at different temperatures to reform the original, i.e., distorted and misoriented grain distribution. The results from experimental and statistical analyses report higher sensitivity of global spring back, surface topography and forming limits strains to variations in microstructure and texture than tool diameter and incremental step depth. The preheating of the sheets resulted in the formation of preferential texture by grain reformation, which leads to the increase in the fraction of homogeneous orientated grains. Such grains increase the maximum forming limit strains and reduce the global spring back in SPIF. Fractography analysis of the failed components revealed that improvement in formability due to grain homogenization (developed texture) may be attributed to larger average void diameter. Empirical models were also developed, and optimized levels of parameters were identified to maximize the efficiency of the SPIF process. Further, qualitative and quantitative characterization of orange peel roughness was carried out by segregating the external formed surface into surfaces subjected to orange peel roughness and tool-induced texture.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Commercial, industrial, and institutional discount rate estimation for efficiency standards analysis: Sector-level data 1998–2023

Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process relying on the Capital Asset Pricing Model (CAPM) to estimate a business’ cost of equity, and by adding a risk adjustment factor to the risk-free rate associated with long-term U.S. Treasury bonds to estimate their cost of debt. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: • Discount rate estimation methods and rationale • Data sources used and data limitations • Discount rate distributions for use in standards analysis • Discount rate estimation methods and distributions specific to the small business subgroup analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Coupling Ambient Pressure X-ray Photoelectron Spectroscopy with Density Functional Theory to Study Complex Surface Chemistry and Catalysis

Ambient pressure X-ray photoelectron spectroscopy (APXPS) experiments narrow the pressure and materials gaps between UHV surface science experiments and applications. Upon closing these gaps, ambiguity can enter the analysis of the spectra due to overlapping peaks from different elements or functional groups of both the sample and the gas phase. Additionally, reaction intermediates and mechanisms are often inaccessible from interpretation of APXPS data alone. In many cases, these issues can be overcome with the aid of density functional theory (DFT) calculations. Here, we outline our process of combining DFT calculations with APXPS experiments by describing our recent investigations of the adsorption of dimethyl methylphosphonate (DMMP) on MoO3 and CuO. We begin by showing the importance of the characterization of the isolated gas phase molecule before adsorption onto a surface. In particular, strong agreement between theory and experiment helps identify plausible decomposition pathways of the isolated molecule and provides a baseline for interpretation of spectra showing evidence of DMMP interaction with surfaces. The intact adsorption of DMMP on MoO3 offers an illustration of how moving beyond pristine single crystalline surfaces in calculations can enable better modeling of experimental trends that result from surface defects. Studies of DMMP adsorption on CuO exemplify the powerful synergy of APXPS combined with DFT for elucidation of complex reaction mechanisms on surfaces.

Chemistry↗
DOE OSTI2021

Microstructure and mechanical properties of friction stir welded Haynes 282

Advanced ultrasupercritical (A-USC) steam plants are designed to operate at high temperatures and pressures due to the necessity for higher operational efficiency. The extreme operating conditions of A-USC requires the deployment of precipitation strengthened Ni-base alloys that exhibit elevated temperature strength and good fabricability. Fusion welding of precipitation strengthened nickel alloys lead to solidification cracking in fusion zone and/or liquation cracking in heat affected zone. Therefore, an alternative non-melting welding technique is a necessity to efficiently join nickel alloys. In the current study, friction stir welding, a solid state joining technique was implemented on a precipitation strengthened nickel-based superalloy, Haynes 282. Detailed microstructural and mechanical properties characterization was carried out. The processed region exhibited wrought, fine-grained microstructure, absence of weld defects such as voids and cracks and absence of elemental segregation. Both hardness and cross-weld tensile tests demonstrated that the weld region was stronger than the base material. And the cross-weld tensile samples failed in the base material. Based on joint efficiency analysis, friction stir welded Haynes 282 outperformed fusion welds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

New methods for trace analysis of gamma-irradiated pentaerythritol tetranitrate

High explosives (HEs) are used in a diverse range of applications in which they could be exposed to various radiation levels that may cause potential chemical changes. This study further evaluated pentaerythritol tetranitrate (PETN) that was previously aged with a low-level 2 kGy dose of gamma irradiation in order to understand chemical changes caused by irradiation. Both unirradiated PETN and gamma-irradiated PETN were analyzed using ultra high-pressure liquid chromatography coupled to quadrupole time of flight mass spectrometry (UHPLC-QTOF). The resulting data were processed in a non-targeted manner using Fisher's ratio analysis and multivariate curve resolution-alternating least squares (MCR-ALS) to aid in discovery and identification of the chemical changes brought about by irradiation without a priori knowledge. The application of using UHPLC-QTOF in combination with chemometric techniques for the analysis of irradiated samples has not previously been performed. Here, in this work, we show how to use this method to provide chemical information that would otherwise not be discernible, such as the discovery of degradation of the various homologues of PETN. Major differences identified with radiolytic aging of the PETN sample included decomposition products that resulted from the degradation of the trigger linkage – the O–NO 2 bonds – resulting in the formation of alcohol and aldehyde groups. Similar degradation was also observed in the PETN homologues as well as interconversion from one homologue to another.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Adaptive Data-Driven Deep-Learning Surrogate Model for Frontal Polymerization in Dicyclopentadiene

Frontal polymerization (FP) is a self-sustaining curing process that enables rapid and energy-efficient manufacturing of thermoset polymers and composites. Computational methods conventionally used to simulate the FP process are time-consuming, and repeating simulations are required for sensitivity analysis, uncertainty quantification, or optimization of the manufacturing process. Here, in this work, we develop an adaptive surrogate deep-learning model for FP of dicyclopentadiene (DCPD), which predicts the evolution of temperature and degree of cure orders of magnitude faster than the finite-element method (FEM). The adaptive algorithm provides a strategy to select training samples efficiently and save computational costs by reducing the redundancy of FEM-based training samples. The adaptive algorithm calculates the residual error of the FP governing equations using automatic differentiation of the deep neural network. A probability density function expressed in terms of the residual error is used to select training samples from the Sobol sequence space. The temperature and degree of cure evolution of each training sample are obtained by a 2D FEM simulation. The adaptive method is more efficient and has a better prediction accuracy than the random sampling method. With the well-trained surrogate neural network, the FP characteristics (front speed, shape, and temperature) can be extracted quickly from the predicted temperature and degree-of-cure fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

X-ray Emission Spectroscopy of Single Protein Crystals Yields Insights into Heme Enzyme Intermediates

Enzyme reactivity is often enhanced by changes in oxidation state, spin state, and metal-ligand covalency of associated metallocofactors. The development of spectroscopic methods for studying these processes coincidentally with structural rearrangements is essential for elucidating metalloenzyme mechanisms. Herein, we demonstrate the feasibility of collecting X-ray emission spectra of metalloenzyme crystals at a third-generation synchrotron source. In particular, we report the development of a von Hamos spectrometer for the collection of Fe Kβ emission optimized for analysis of dilute biological samples. Here, we further showcase its application in crystals of the immunosuppressive heme-dependent enzyme indoleamine 2,3-dioxygenase. Spectra from protein crystals in different states were compared with relevant reference compounds. Complementary density functional calculations assessing covalency support our spectroscopic analysis and identify active site conformations that correlate to high- and low-spin states. These experiments validate the suitability of an X-ray emission approach for determining spin states of previously uncharacterized metalloenzyme reaction intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

High spatial resolution imaging of biological tissues using nanospray desorption electrospray ionization mass spectrometry

Mass spectrometry imaging (MSI) enables label-free spatial mapping of hundreds of biomolecules in tissue sections. This capability provides valuable information on tissue heterogeneity that is difficult to obtain using population-averaged assays. Despite substantial developments in both instrumentation and methodology, MSI of tissue samples at single-cell resolution remains challenging. In our research, we describe a protocol for robust imaging of tissue sections with a high (better than 10-μm) spatial resolution using nanospray desorption electrospray ionization (nano-DESI) mass spectrometry, an ambient ionization technique that does not require sample pretreatment before analysis. In this protocol, mouse uterine tissue is used as a model system to illustrate both the workflow and data obtained in these experiments. We provide a detailed description of the nano-DESI MSI platform, fabrication of the nano-DESI and shear force probes, shear force microscopy experiments, spectral acquisition, and data processing. A properly trained researcher (e.g., technician, graduate student, or postdoc) can complete all the steps from probe fabrication to data acquisition and processing within a single day. We further describe a new strategy for acquiring both positive- and negative-mode imaging data in the same experiment. This is achieved by alternating between positive and negative data acquisition modes during consecutive line scans. Using our imaging approach, hundreds of high-quality ion images were obtained from a single uterine section. This protocol enables sensitive and quantitative imaging of lipids and metabolites in heterogeneous tissue sections with high spatial resolution, which is critical to understanding biochemical processes occurring in biological tissues.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

A new combined nuclear magnetic resonance and Raman spectroscopic probe applied to in situ investigations of catalysts and catalytic processes

Both Raman and nuclear magnetic resonance (NMR) spectroscopies are valuable analytical techniques capable of providing mechanistic information and thereby providing insights into chemical processes, including catalytic reactions. Since both techniques are chemically sensitive, they yield not only structural information but also quantitative analysis. In this work, for the first time, the combination of the two techniques in a single experimental apparatus is reported. This entailed the design of a new experimental probe capable of recording simultaneous measurements on the same sample and/or system of interest. The individual datasets acquired by each spectroscopic method are compared to their unmodified, stand-alone equivalents on a single sample as a means to benchmark this novel piece of equipment. The application towards monitoring reaction progress is demonstrated through the evolution of the homogeneous catalysed metathesis of 1‑hexene, with both experimental techniques able to detect reactant consumption and product evolution. This is extended by inclusion of magic angle spinning (MAS) NMR capabilities with a custom made MAS 7 mm rotor capable of spinning speeds up to 1600 Hz, quantified by analysis of the spinning sidebands of a sample of KBr. The value of this is demonstrated through an application involving heterogeneous catalysis, namely the metathesis of 2-pentene and ethene. This provides the added benefit of being able to monitor both the reaction progress (by NMR spectroscopy) and also the structure of the catalyst (by Raman spectroscopy) on the very same sample, facilitating the development of structure-performance relationships.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Enhancement of stability of aqueous suspension of alumina nanoparticles by femtosecond laser irradiation

In this work, we report substantially enhanced colloidal stability of aqueous nanoparticle suspensions by ultrashort laser pulse irradiation. A Ti:Sapphire femtosecond laser (wavelength: 800 nm; pulse duration: 50 fs at full width at half maximum) was used to modify the electrochemical properties of nanoparticle suspensions at laser fluences below the particle ablation threshold. The colloidal stability of the suspension was evaluated by zeta potential and dynamic light scattering (DLS). The DLS results along with the images from transmission electron microscopy revealed that the laser irradiation caused no distinct morphological change to the individual alumina particles, but a substantial portion of the clustered particles was fragmented by the laser pulses, decreasing the apparent size of the suspended particles. Also, X-ray photoelectron spectroscopy analysis indicates that the laser irradiation modified the surface chemistry of the alumina particles. The stabilizing capability of the proposed technique was turned out to be better than that of conventional ultrasonic treatments. The stability of the laser-treated sample with no added surfactant was maintained for up to 30 days, without requiring an additional homogenizing process such as magnetic stirring.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Multi-Collector Inductively Coupled Plasma Mass Spectrometer – Operational Performance Report

The INL made an assessment of the commercially available inductively coupled plasma mass spectrometers (ICPMS) for actinide analysis; emphasizing low detection limits for plutonium. INL scientists subsequently determined if plutonium was present on a swipe, at a 10 million atom decision level. This report describes the evaluation of ICPMS instruments and the operational testing of a new process for the dissolution, separation and analysis via ICPMS of swipes for plutonium and uranium. The swipe dissolution, plutonium and uranium isolation, separation and purification are wet chemistry methods following established procedures. The ICPMS is a commercially available multi-collector magnetic sector mass spectrometer that utilizes five ion counting detectors operating simultaneously. The instrument includes a sample introduction system allowing for sample volumes of < 1 mL to be reproducibly injected into the instrument with minimal waste of the sample solution, while maximizing the useable signal. The performance of the instrument was measured using SRM 996 ( 244 Pu spike) at concentrations of 12 parts per quadrillion (ppq, fg/mL) and with SRM 4350B Columbia River Sediment samples spiked onto swipes at the 10 million atom level. The measured limit of detection (LOD, defined as 3s) for 239 Pu is 310,000 atoms based upon the instrument blank data. The limit of quantification (LOQ defined as 10 s) for 239 Pu is 105,000 atoms. The measured limit of detection for 239 Pu from the SRM 4350B spiked onto a swipe was 2.7 million atoms with the limit of quantification being 9.0 million atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

FY-16 Technology Gap Study Technical Report: Analysis of Undissolved Anode Materials of Mark-IV Electrorefiner

The Experimental Breeder Reactor II (EBR-II) is a sodium cooled fast reactor developed at Argonne National Laboratory (ANL). The used fuels from the EBR-II are currently being treated in the Fuel Conditioning Facility (FCF) at the Idaho National Laboratory (INL). The Mark IV (Mk-IV) electrorefiner (ER) is a unit process in the FCF, which is primarily assigned to treating the used driver fuels. The stainless steel anode baskets hold the chopped spent driver fuel segments. During electrorefining, the anode baskets are immersed into the electrolyte and the used fuel is dissolved electrochemically. Perforated sides and bottoms allow the flow of the electrolyte into and out of the anode baskets. The steel cathode is also immersed into the electrolyte and collects the reduced products. The active metal contents in the used fuel (e.g., Cs, Sr, lanthanides, Pu, etc.) reacts with uranium cations in the electrolyte and progressively reports to the electrolyte. Noble metals are mostly retained in the cladding hulls. Varying quantities of zirconium are retained in the cladding hulls depending on the operational conditions of the Mk-IV ER. The undissolved anode materials are removed from the anode baskets and stored for subsequent metal waste form processing. These undissolved materials typically include undissolved fuels, stainless steel cladding, and adhering electrolyte. A couple of hulls are retrieved for chemical analysis and used for estimating the composition of the entire undissolved anode materials. The mass balance attempt based on this practice of estimating the undissolved anode materials has been a challenge due to inherently high sampling errors associated with heterogeneous undissolved material compositions. Responding to the prescribed challenge, this report investigates chemical analysis data as a whole and finds noticeable trends in the compositions of undissolved anode material samples with respect to the mass of the whole undissolved anode materials. Based upon this discovery, an empirical model is proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Demonstration of microfluidics for synthesis of sol-gel feedstocks

This report details the design and processing conditions for producing hydrous cerium oxide surrogate microspheres using a microfluidics-based approach. Variables such as microfluidic chip design, exit tubing diameter, temperature, and flow rate continue to be investigated. A washing and drying procedure to remove gelation media, unreacted starting material, and unwanted reaction byproducts is under development. Samples are imaged and characterized for analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Agilent CRADA (Abstract)

The CRADA between Agilent Technologies Inc. and Battelle will focus on five software components as listed below: Prototype 4D Feature Finding functionality with a particular focus on recovering low level features and extending the bottom end dynamic range of IM-MS technology. Compare and contrast developments to current 4D Feature Finding capabilities. Highlight important algorithmic aspects employed. Implement the PNNL saturation correction algorithm. Agilent will give PNNL the needed data file access API and assistance in understanding it implementation and any needed instrumental aspects. Supported high resolution products to include Agilent’s TOF, QTOF and IM-QTOF mass spectrometers. PNNL will then work with Agilent to benchmark performance. Implementation of the PNNL Hadamard de-multiplexing algorithm. Agilent will give provide PNNL the needed date file access API access and as needed assistance in understanding the current Agilent multiplexed IM offering. PNNL will then work with Agilent on benchmark performance. Add ion mobility collision cross sections to existing and new metabolomic libraries for data analysis with Agilent’s informatics program MPP/ID Browser. PNNL will work with Agilent to create a software pipeline that takes data from chemical and metabolic standards and properly formats it for inclusion in MPP accessible libraries, using the collision cross section as a new separation dimension. Improvements of MPP multidimensional matching to identify metabolomic features using multiple characteristics beyond retention time and accurate mass. Most significantly matching will include analyte collision cross section with proposed support for sample fraction or RapidFire cartridge and fragmentation spectra. PNNL will work with Agilent to modify and improve the current MPP analysis pipeline to allow for creating, aligning, and identifying MS features defined by accurate mass, collision cross section and chromatographic retention time. As additional criteria such as fraction or RapidFire cartridge type are supported in the identification process, then they also will become part of the automation workflow. This includes the automation of said system to work with command line program (i.e. not a GUI) sufficient for programmatic execution in a pipeline.

97 MATHEMATICS AND COMPUTING↗