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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Femtosecond Laser Desorption Postionization MS vs ToF-SIMS Imaging for Uncovering Biomarkers Buried in Geological Samples

The study of lipid molecular fossils by traditional biomarker analysis requires bulk sample crushing, followed by solvent extraction, and then the analysis of the extract by gas chromatography-mass spectrometry (GC–MS). This traditional analysis mixes all organic compounds in the sample regardless of their origins, with a loss of information on the spatial distribution of organic molecules within the sample. These shortcomings can be overcome using the chemical mapping of intact samples. Spectroscopic techniques such as UV fluorescence or Raman spectroscopy, laser ablation inductively coupled plasma mass spectrometry, and time-of-flight secondary ion mass spectrometry (ToF-SIMS) are among those elemental and molecular mapping techniques. This study employed femtosecond (fs) laser ablation combined with single-photon ionization, a method called fs-laser desorption postionization mass spectrometry (fs-LDPI-MS). In this work, a pulsed ~75 fs, 800 nm laser was used to ablate the geological sample, which was then photoionized after a few microseconds by a pulsed 7.9 eV vacuum ultraviolet laser. An organic carbon-rich geological sample was used for this study to map hydrocarbon biomarkers in sediments that were previously studied by GC–MS. The petrography of this sample was examined by optical and fluorescence microscopy. It is demonstrated here that fs-LDPI-MS combined with petrography for multimodal imaging can expose buried compounds within the sample via in situ layer removal. When used in conjunction with traditional organic geochemical analysis, this method has the potential to determine the spatial distribution of organic biomarkers in geological material. Finally, fs-LDPI-MS imaging data are compared with ToF-SIMS imaging that is commonly used for such studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling

Label-free quantitative proteomics has become an increasingly popular tool for profiling global protein abundances. However, one major weakness is the potential performance drift of the LC-MS platform over time, which in turn limits its utility for analyzing large-scale sample sets. To address this, in this work we introduce an experimental and data analysis scheme based on a block-design with common controls within each block for enabling LC-MS-based large-scale label-free quantification. In this scheme, a large number of samples (e.g., >100 samples) are analyzed in smaller, and more manageable blocks, minimizing instrument drift and variability within a block. Furthermore, each designated block also contains common controls (or reference) samples for normalization within and across blocks. We demonstrated the effectiveness of this method by profiling the proteome response of human macrophage THP-1 cells to 11 engineered nanomaterials (ENMs) at two different doses. A total of 116 samples were analyzed in six blocks, yielding an average coverage of 4500 proteins per sample. The data revealed consistent quantification of proteins across all six blocks, as shown by highly stable quantification of house-keeping proteins in all samples and high levels of quantification correlation among samples from different blocks. The data also demonstrated that label-free quantification is robust and accurate enough to quantify even very subtle abundance changes as well as large fold-changes without potential ratio compression as often encountered with isobaric labeling. Our streamlined workflow is easy to implement and can be readily adapted to other large cohort studies for reproducible label-free proteome quantification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Nanopipettes: probes for local sample analysis

Nanopipettes (pipettes with diameters <1 μm) were explored as pressure-driven fluid manipulation tools for sampling nanoliter volumes of fluids. The fundamental behavior of fluids confined in the narrow channels of the nanopipette shank was studied to optimize sampling volume and probe geometry. This method was utilized to collect nanoliter volumes (<10 nL) of sample from single Allium cepa cells and live Drosophila melanogaster first instar larvae. Matrix assisted laser desorption/ionization-mass spectrometry (MALDI-MS) was utilized to characterize the collected sample. The use of nanopipettes for surface sampling of mouse brain tissue sections was also explored. Lipid analyses were performed on mouse brain tissues with spatial resolution of sampling as small as 50 μm. Nanopipettes were shown to be a versatile tool that will find further application in studies of sample heterogeneity and population analysis for a wide range of samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Direct and rapid uranium isotopic analysis of environmental sample swipes via microextraction – LS-APGD/Orbitrap mass spectrometry

Accurate and precise isotopic analysis of actinides collected on environmental sample swipes from within nuclear facilities is an important safeguarding measure for detecting undeclared materials and activities. Traditional isotope ratio (IR) analysis of actinides using a bulk digestion approach can be laborious and time-consuming. Recently, direct analysis of environmental swipe samples using a microextraction approach has been explored as an alternative to conventional bulk digestion methods. The present study further evaluates this approach for accurate and precise isotopic analysis of uranium (U) in cotton swipe samples using the liquid sampling-atmospheric pressure glow discharge (LS-APGD)/Orbitrap-FTMS Booster detection system. The instrumental parameters were optimized, and quantitative capabilities were demonstrated through excellent linearity (R2 = 0.99) across a deposited mass range of 1 to 500 ng, with a limit of detection of 90 pg (in a 2 × 4 mm region) for total U; well below typical U concentrations (ng–mg range) in environmental sample swipes. The 235U/238U ratio showed excellent accuracy (−0.3% relative difference from the certificate value), with ∼20× improvement over previous microextraction-Orbitrap methods. Precision (∼1% relative standard deviation) was also greatly enhanced by ∼5×. This study also demonstrates that figures of merit achieved with neat U solution were not highly degraded when various external interfering elements/matrices were introduced. Finally, the developed method was successfully applied to analyze practical swipe samples representative of laboratory and outdoor environments. The presented figures of merit and applicability to practical samples further validate the capability of the platform for rapid analysis (<7 minutes) of environmental swipe samples.

Shrestha, Suraj [Clemson University, SC]↗
DOE OSTI2013

Qualitative analysis of Pb liquid sample using laser-induced breakdown spectroscopy (LIBS)

Qualitative analysis of liquid sample containing 1,000 ppm of Pb was performed by using LIBS technique. In order to avoid splashing off of the liquid sample during laser irradiation, a sample pretreatment was done, namely the liquid sample was absorbed by using commercial available stomach medicine. Two kinds of absorbent materials were chosen in this experiment, first containing 125 mg activated carbon and second 600 mg activated attapulgite. These absorbent materials were used since carbon sample gives better absorption of infrared laser irradiation used in this experiment. In order to characterize the absorption process, three treatments were conducted in this experiment; first, without heating the sample but varying the absorption time before laser irradiation; second by varying the heating temperature after certain time of absorption process and third by varying the temperature only. The maximum emission intensity of Pb I 405.7 nm was found in the second treatment of heating the sample till 85°C after 30 minutes absorption of the liquid sample in both absorbent materials.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Case depth verification of hardened samples with Barkhausen noise sweeps

An interesting topic of recent Barkhausen noise (BN) method studies is the application of the method to case depth evaluation of hardened components. The utilization of BN method for this purpose is based on the difference in the magnetic properties between the hardened case and the soft core. Thus, the detection of case depth with BN can be achieved. The measurements typically have been carried out by using low magnetizing frequencies which have deeper penetration to the ferromagnetic samples than the conventional BN measurement. However, the penetration depth is limited due to eddy current damping of the signal. We introduce here a newly found sweep measurement concept for the case depth evaluation. In this study sweep measurements were carried out with various magnetizing frequencies and magnetizing voltages to detect the effect of different frequency and voltage and their correspondence to the actual case depth values verified from destructive characterization. Also a BN measurement device that has an implemented sweep analysis option was utilised. The samples were either induction or case-hardened samples and sample geometry contained both rod samples and gear axle samples with different case depth values. Samples were also further characterized with Xray diffraction to study the residual stress state of the surface. The detailed data processing revealed that also other calculated features than the maximum slope division of the 1st derivative of the BN signal could hold the information about the case depth value of the samples. The sweep method was able to arrange the axles into correct order according to the case depth value even though the axles were used.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Study on effect of annealing conditions on structural, magnetic and superconducting properties of MgB{sub 2} bulk samples

Effect of annealing conditions on structural, magnetic and superconducting properties of Magnesium Diboride (MgB{sub 2}) bulk superconductor samples prepared by solid state route method are compared. The samples are made by taking Magnesium and Boron powders in stoichiometric ratio, grounded well and pelletized at pressure of about 10Tonnes. These pellets are annealed in both Argon and vacuum environment separately up to 800°c for two hours. Both the samples show clear superconducting transition at Tc ∼ 38 k. This is further conformed by AC/DC magnetization (M-T), Resistivity [ρ (T, H)] measurements under magnetic field up to 14 Tesla as well. Rietveld refinement of X-ray diffraction of both samples conformed the MgB{sub 2} phase formation with P6/mmm space group symmetry. Scanning Electron Microscopy images of the surface revile more agglomeration of grains in case of Argon annealed samples. This result in more critical current density (J{sub c}) of Argon annealed samples than vacuum annealed one calculated from Bean's critical state model. This high Jc is explained in terms of more inter grain connectivity for Argon annealed sample than vacuum annealed sample.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A whole-path importance-sampling scheme for Feynman path integral calculations of absolute partition functions and free energies

Using Feynman path integrals, a molecular partition function can be written as a double integral with the inner integral involving all closed paths centered at a given molecular configuration, and the outer integral involving all possible molecular configurations. In previous work employing Monte Carlo methods to evaluate such partition functions, we presented schemes for importance sampling and stratification in the molecular configurations that constitute the path centroids, but we relied on free-particle paths for sampling the path integrals. At low temperatures, the path sampling is expensive because the paths can travel far from the centroid configuration. In this paper, we now present a scheme for importance sampling of whole Feynman paths based on harmonic information from an instantaneous normal mode calculation at the centroid configuration, which we refer to as harmonically guided whole-path importance sampling (WPIS). We obtain paths conforming to our chosen importance function by rejection sampling from a distribution of free-particle paths. Sample calculations on CH 4 demonstrate that at a temperature of 200 K, about 99.9% of the free-particle paths can be rejected without integration, and at 300 K, about 98% can be rejected. Finally, we also show that it is typically possible to reduce the overhead associated with the WPIS scheme by sampling the paths using a significantly lower-order path discretization than that which is needed to converge the partition function.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Quantitative comparison of adaptive sampling methods for protein dynamics

Adaptive sampling methods, often used in combination with Markov state models, are becoming increasingly popular for speeding up rare events in simulation such as molecular dynamics (MD) without biasing the system dynamics. Several adaptive sampling strategies have been proposed, but it is not clear which methods perform better for different physical systems. Here, we present a systematic evaluation of selected adaptive sampling strategies on a wide selection of fast folding proteins. The adaptive sampling strategies were emulated using models constructed on already existing MD trajectories. We provide theoretical limits for the sampling speed-up and compare the performance of different strategies with and without using some a priori knowledge of the system. The results show that for different goals, different adaptive sampling strategies are optimal. In order to sample slow dynamical processes such as protein folding without a priori knowledge of the system, a strategy based on the identification of a set of metastable regions is consistently the most efficient, while a strategy based on the identification of microstates performs better if the goal is to explore newer regions of the conformational space. Interestingly, the maximum speed-up achievable for the adaptive sampling of slow processes increases for proteins with longer folding times, encouraging the application of these methods for the characterization of slower processes, beyond the fast-folding proteins considered here.

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

Evaluating the effect of sample type on American alligator ( Alligator mississippiensis ) analyte values in a point-of-care blood analyser

The assessment of wildlife health has been enhanced by the ability of point-of-care (POC) blood analysers to provide biochemical analyses of non-domesticated animals in the field. However, environmental limitations (e.g. temperature, atmospheric humidity and rain) and lack of reference values may inhibit researchers from using such a device with certain wildlife species. Evaluating the use of alternative sample types, such as plasma, in a POC device may afford researchers the opportunity to delay sample analysis and the ability to use banked samples. In this study, we examined fresh whole blood, fresh plasma and frozen plasma (sample type) pH, partial pressure of carbon dioxide (PCO 2 ), bicarbonate (HCO 3 ₋), total carbon dioxide (TCO 2 ), base excess (BE), partial pressure of oxygen (PO 2 ), oxygen saturation (sO 2 ) and lactate concentrations in 23 juvenile American alligators (Alligator mississippiensis) using an i-STAT CG4+ cartridge. Our results indicate that sample type had no effect on lactate concentration values (F 2,65 = 0.37, P = 0.963), suggesting that the i-STAT analyser can be used reliably to quantify lactate concentrations in fresh and frozen plasma samples. In contrast, the other seven blood parameters measured by the CG4+ cartridge were significantly affected by sample type. In conclusion, we were able to collect blood samples from all alligators within 2 min of capture to establish preliminary reference ranges for juvenile alligators based on values obtained using fresh whole blood.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Application-Specific Graph Sampling for Frequent Subgraph Mining and Community Detection

Graph mining is an important data analysis methodology, but struggles as the input graph size increases. The scalability and usability challenges posed by such large graphs make it imperative to sample the input graph and reduce its size. The critical challenge in sampling is to identify the appropriate algorithm to insure the resulting analysis does not suffer heavily from the data reduction. Predicting the expected performance degradation for a given graph and sampling algorithm is also useful. In this paper, we present different sampling approaches for graph mining applications such as Frequent Subgrpah Mining (FSM), and Community Detection (CD). We explore graph metrics such as PageRank, Triangles, and Diversity to sample a graph and conclude that for heterogeneous graphs Triangles and Diversity perform better than degree based metrics. We also present two new sampling variations for targeted graph mining applications. We present empirical results to show that knowledge of the target application, along with input graph properties can be used to select the best sampling algorithm. We also conclude that performance degradation is an abrupt, rather than gradual phenomena, as the sample size decreases. We present the empirical results to show that the performance degradation follows a logistic function.

Purohit, Sumit↗
DOE OSTI2023

In Vitro Thrombogenicity Testing of Biomaterials in a Dynamic Flow Loop: Effects of Length and Quantity of Test Samples

Abstract The results of in vitro dynamic thrombogenicity testing of biomaterials and medical devices can be significantly impacted by test conditions. To develop and standardize a robust dynamic in vitro thrombogenicity tool, the key test parameters need to be appropriately evaluated and optimized. We used a flow loop test system previously developed in our laboratory to investigate the effects of sample length and the number of samples per test loop on the thrombogenicity results. Porcine blood heparinized to a donor-specific target concentration was recirculated at room temperature through polyvinyl chloride (PVC) tubing loops containing test materials for 1 h at 200 mL/min. Four test materials (polytetrafluoroethylene (PTFE), latex, PVC, and silicone) with various thrombotic potentials in two sample lengths (12 and 18 cm) were examined. For the 12-cm long materials, two different test configurations (one and two samples per loop) were compared. Thrombogenicity was assessed through percent thrombus surface coverage, thrombus weight, and platelet count reduction in the blood. The test system was able to effectively differentiate the thrombogenicity profile of the materials (latex > silicone > PVC ≥ PTFE) at all test configurations. Increasing test sample length by 50% did not significantly impact the test results as both 12 and 18 cm sample lengths were shown to equally differentiate thrombotic potentials between the materials. The addition of a second test sample to each loop did not increase the test sensitivity and may produce confounding results, and thus a single test sample per loop is recommended.

Engineering↗
DOE OSTI2013

Ultra-trace determination of Strontium-90 in environmental soil samples from Qatar by collision/reaction cell-inductively coupled plasma mass spectrometry (CRC-ICP-MS/MS)

Because of the very low level of {sup 90}Sr in the environmental soil samples and its determination by beta counting may take several weeks, we developed a procedure for ultra-trace determination of {sup 90}Sr using collision reaction cell-inductively coupled plasma tandem mass spectrometry (CRC-ICP-MS/MS, Agilent 8800). Soil samples were dried at 105 deg. C and then heated in a furnace at 550 deg. C to remove any organics present. 500 g of each soil samples were aliquoted into 2000 ml glass beakers. Each Soils samples were soaked in 2 ppm Sr solution carrier to allow determination of chemical yield. The solid to liquid ratio was 1:1. Finally the soil samples were dried at 105 deg. C. Five hundred milliliters concentrated nitric acid and 250 ml hydrochloric acid volumes were added on 500 g soil samples. The samples were digested on hot plate at 80 deg. C to prevent spraying with continuous manual mixing. The leachate solution was separated. The solids were rinsed with 500 ml deionized water, warmed on a hot plate and the leachate plus previous leachate were filtered and the total volume was reduced to 500 ml by evaporation. Final leachate volume was transferred to a centrifuge tubes. The centrifuge tubes were centrifuged at 3,500 rpm for 10 min. The leachate was transferred to a 1 L beaker and heated on a hot plate to evaporate the leachate to dryness. The reside was re-dissolved in 100 ml of 2% HNO{sub 3} and reduced by evaporation to 10 mL. The solution was measured directly by CRC-ICP-MS/MS by setting the first quadruple analyzer to m/z 90 and introducing oxygen gas into the reaction cell for elimination isobar interference from zirconium-90. The method was validated by measurements of standard reference materials and applied on environmental soil samples. The overall time requirement for the measurement of strontium-90 by CRC-ICP-MS/MS is 2 days, significantly shorter than any radioanalytical protocol currently available. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Hierarchical Gaussian Random Field Sampling for Multilevel Markov Chain Monte Carlo: Coupling Stochastic Partial Differential Equation and the Karhunen–Loève Decomposition

This work introduces structure preserving hierarchical decompositions for sampling Gaussian random fields (GRFs) within the context of multilevel Bayesian inference in high-dimensional space. Existing scalable hierarchical sampling methods, such as those based on stochastic partial differential equations (SPDEs), often reduce the dimensionality of the sample space at the cost of accuracy of inference. Other approaches, such that those based on Karhunen-Loève (KL) expansions, offer sample space dimensionality reduction but sacrifice GRF representation accuracy and ergodicity of the Markov chain Monte Carlo (MCMC) sampler and are computationally expensive for high-dimensional problems. The proposed method integrates the dimensionality reduction capabilities of KL expansions with the scalability of SPDE-based sampling, thereby providing a robust, unified framework for high-dimensional uncertainty quantification (UQ) that is scalable and accurate, preserves ergodicity, and offers dimensionality reduction of the sample space. The hierarchy in our multilevel algorithm is derived from the geometric multigrid hierarchy. By constructing a hierarchical decomposition that maintains the covariance structure across the levels in the hierarchy, the approach enables efficient coarse-to-fine sampling while ensuring that all samples are drawn from the desired distribution. The effectiveness of the proposed method is demonstrated on a benchmark subsurface flow problem, demonstrating its effectiveness in improving computational efficiency and statistical accuracy. Furthermore, our proposed technique is more efficient and accurate and displays better convergence properties than existing methods for high-dimensional Bayesian inference problems.

Gaussian random fields↗
DOE OSTI2024

AGS-GNN: Attribute-guided Sampling for Graph Neural Networks

We propose AGS-GNN, a novel attribute-guided sampling algorithm for Graph Neural Networks (GNNs) that exploits node features and connectivity structure of a graph while simultaneously adapting for both homophily and heterophily in graphs. (In homophilic graphs vertices of the same class are more likely to be connected, and vertices of different classes tend to be linked in heterophilic graphs.) While GNNs have been successfully applied to homophilic graphs, their application to heterophilic graphs remains challenging. The best-performing GNNs for heterophilic graphs do not fit the sampling paradigm, suffer high computational costs, and are not inductive. We employ samplers based on feature-similarity and feature-diversity to select subsets of neighbors for a node, and adaptively capture information from homophilic and heterophilic neighborhoods using dual channels. Currently, AGS-GNN is the only algorithm that we know of that explicitly controls homophily in the sampled subgraph through similar and diverse neighborhood samples. For diverse neighborhood sampling, we employ submodularity, which was not used in this context prior to our work. The sampling distribution is pre-computed and highly parallel, achieving the desired scalability. Using an extensive dataset consisting of 35 small (<=100K nodes) and large (>100K nodes) homophilic and heterophilic graphs, we demonstrate the superiority of AGS-GNN compare to the current approaches in the literature. AGS-GNN achieves comparable test accuracy to the best-performing heterophilic GNNs, even outperforming methods using the entire graph for node classification. AGS-GNN also converges faster compared to methods that sample neighborhoods randomly, and can be incorporated into existing GNN models that employ node or graph sampling.

artificial intelligence↗
DOE OSTI2022

Leaf structural and chemical traits, and BNL field campaign sample details, San Lorenzo, Panama, 2020

This data package includes leaf traits, canopy traits and sample details for leaves from 71 species sampled from the San Lorenzo forest canopy crane site, Panama (PA-SLZ) during the BNL field campaign in January to March 2020. Each leaf sample is described with species, phenological stage and location within vertical canopy profiles. Leaf area index (LAI) and height is presented for each canopy profile location. Leaf mass per area (LMA), leaf water content (LWC) and leaf carbon and nitrogen content are included for a subset of the samples. This data package includes sample details, processed data for leaf traits and LAI (*.csv), LAI raw data (compressed as *.zip) and digital camera images (*.jpg, compressed as *.zip) of the leaf samples. Metadata files include data descriptions (_dd.csv) for tabular data, a list of all species sampled during the campaign (*.csv) and a detailed description of the field campaign protocol and methods (*.pdf). See related datasets for leaf gas exchange, leaf water potential and leaf spectral measurements made on the samples described here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A Surrogate-based Adaptive Sampling Approach for History Matching and Uncertainty Quantification

A critical procedure in reservoir simulations is history matching (or data assimilation in a broader sense), which calibrates model parameters such that the simulation results are consistent with field measurements, and hence improves the credibility of the predictions given by the simulations. Often there exist non-unique combinations of parameter values that all yield the simulation results matching the measurements. For such ill-posed history matching problems, Bayesian theorem provides a theoretical foundation to represent different solutions and to quantify the uncertainty with the posterior PDF. Lacking an analytical solution in most situations, the posterior PDF may be characterized with a sample of realizations, each representing a possible scenario. A novel sampling algorithm is presented here for the Bayesian solutions to history matching problems. We aim to deal with two commonly encountered issues: 1) as a result of the nonlinear input-output relationship in a reservoir model, the posterior distribution could be in a complex form, such as multimodal, which violates the Gaussian assumption required by most of the commonly used data assimilation approaches; 2) a typical sampling method requires intensive model evaluations and hence may cause unaffordable computational cost. In the developed algorithm, we use a Gaussian mixture model as the proposal distribution in the sampling process, which is simple but also flexible to approximate non-Gaussian distributions and is particularly efficient when the posterior is multimodal. Also, a Gaussian process is utilized as a surrogate model to speed up the sampling process. Furthermore, an iterative scheme of adaptive surrogate refinement and re-sampling ensures sampling accuracy while keeping the computational cost at a minimum level. The developed approach is demonstrated with an illustrative example and shows its capability in handling the above-mentioned issues. Multimodal posterior of the history matching problem is captured and are used to give a reliable production prediction with uncertainty quantification. The new algorithm reveals a great improvement in terms of computational efficiency comparing previously studied approaches for the sample problem.

Li, Weixuan↗
DOE OSTI2018

Portable Automation of Static Chamber Sample Collection for Quantifying Soil Gas Flux

Quantification of soil gas flux using the static chamber method is labor intensive. The number of chambers that can be sampled is limited by the spacing between chambers and the availability of trained research technicians. An automated system for collecting gas samples from chambers in the field would eliminate the need for personnel to return to the chamber during a flux measurement period and would allow a single technician to sample multiple chambers simultaneously. This study describes Chamber Automated Sampling Equipment (FluxCASE) to collect and store chamber headspace gas samples at assigned time points for the measurement of soil gas flux. The FluxCASE design and operation is described, and the accuracy and precision of the FluxCASE system is evaluated. In laboratory measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) concentrations of a standardized gas mixture, coefficients of variation associated with automated and manual sample collection were comparable, indicating no loss of precision. In the field, soil gas fluxes measured from FluxCASEs were in agreement with manual sampling for both N2O and CO2. Slopes of regression equations were 1.01 for CO2 and 0.97 for N2O. The 95% confidence limits of the slopes of the regression lines included the value of one, indicating no bias. Additionally, an expense analysis found a cost recovery ranging from 0.6 to 2.2 yr. Implementing the FluxCASE system is an alternative to improve the efficiency of the static chamber method for measuring soil gas flux while maintaining the accuracy and precision of manual sampling.

Davis, Morgan P.↗