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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Glycosylation of inositol phosphorylceramide sphingolipids is required for normal growth and reproduction in Arabidopsis

Sphingolipids are a major component of plant plasma membranes and endomembranes, and mediate a diverse range of biological processes. Study of the highly glycosylated glycosyl inositol phosphorylceramide (GIPC) sphingolipids has been slow as a result of challenges associated with the extractability of GIPCs, and their functions in the plant remain poorly characterized. We recently discovered an Arabidopsis GIPC glucuronosyltransferase, INOSITOL PHOSPHORYLCERAMIDE GLUCURONOSYLTRANSFERASE 1 (IPUT1), which is the first enzyme in the GIPC glycosylation pathway. Plants homozygous for the iput1 loss-of-function mutation were unobtainable, and so the developmental effects of reduced GIPC glucuronosylation could not be analyzed in planta. Using a pollen-specific rescue construct, we have here isolated homozygous iput1 mutants. The iput1 mutants show severe dwarfism, compromised pollen tube guidance, and constitutive activation of salicyclic acid-mediated defense pathways. The mutants also possess reduced GIPCs, increased ceramides, and an increased incorporation of short-chain fatty acids and dihydroxylated bases into inositol phosphorylceramides and GIPCs. The assignment of a direct role for GIPC glycan head groups in the impaired processes in iput1 mutants is complicated by the vast compensatory changes in the sphingolipidome; however, our results reveal that the glycosylation steps of GIPC biosynthesis are important regulated components of sphingolipid metabolism. In conclusion, this study corroborates previously suggested roles for GIPC glycans in plant growth and defense, suggests important role s for them in reproduction and demonstrates that the entire sphingolipidome is sensitive to their status.

Arabidopsis thaliana↗
DOE OSTI2020

Three-dimensional super line-localization in low signal-to-noise microscope images via prior-apprised unsupervised learning (PAUL)

Biological processes such as processive enzyme turnover and intracellular cargo tracking involve the dynamic motion of a small "article" along a curvilinear biopolymer track. To understand these processes that occur across multiple length and time scales, one must acquire both the trajectory of the particle and the position of the track along which it moves, possibly by combining high-resolution single-particle tracking with conventional microscopy. Yet, usually there is a significant resolution mismatch between these modalities: while the tracked particle is localized with a precision of 10 nm, the image of the surroundings is limited by optical difraction, with 200 nm lateral and 500 nm axial resolutions. Compared to the particle's trajectory, the surrounding curvilinear structure appears as a blurred and noisy image. This disparity in the spatial resolutions of the particle trajectory and the surrounding curvilinear structure image makes data reconstruction, as well as interpretation, particularly challenging. Analysis is further complicated when the curvilinear structures are oriented arbitrarily in 3D space. Here, we present a prior-apprised unsupervised learning (PAUL) approach to extract information from 3D images where the underlying features resemble a curved line such as a filament or microtubule. This three-stage framework starts with a Hessian-based feature enhancement, which is followed by feature registration, where local line segments are detected on repetitively sampled subimage tiles. In the final stage, statistical learning, segments are clustered based on their geometric relationships. Principal curves are then approximated from each segment group via statistical tools including principal component analysis, bootstrap and kernel transformation. This procedure is characterized on simulated images, where sub-voxel medium deviations from true curves have been achieved. The 3D PAUL approach has also been implemented for successful line localization in experimental 3D images of gold nanowires obtained using a multifocal microscope. Lastly, this work not only bridges the resolution gap between two microscopy modalities, but also allows us to conduct 3D super line-localization imaging experiments, without using super-resolution techniques.

42 ENGINEERING↗
DOE OSTI2017

Deep functional analysis of synII, a 770-kilobase synthetic yeast chromosome

INTRODUCTION Although much effort has been devoted to studying yeast in the past few decades, our understanding of this model organism is still limited. Rapidly developing DNA synthesis techniques have made a “build-to-understand” approach feasible to reengineer on the genome scale. Here, we report on the completion of a 770-kilobase synthetic yeast chromosome II (synII). SynII was characterized using extensive Trans-Omics tests. Despite considerable sequence alterations, synII is virtually indistinguishable from wild type. However, an up-regulation of translational machinery was observed and can be reversed by restoring the transfer RNA (tRNA) gene copy number. RATIONALE Following the “design-build-test-debug” working loop, synII was successfully designed and constructed in vivo. Extensive Trans-Omics tests were conducted, including phenomics, transcriptomics, proteomics, metabolomics, chromosome segregation, and replication analyses. By both complementation assays and SCRaMbLE (synthetic chromosome rearrangement and modification by loxP -mediated evolution), we targeted and debugged the origin of a growth defect at 37°C in glycerol medium. RESULTS To efficiently construct megabase-long chromosomes, we developed an I- Sce I–mediated strategy, which enables parallel integration of synthetic chromosome arms and reduced the overall integration time by 50% for synII. An I- Sce I site is introduced for generating a double-strand break to promote targeted homologous recombination during mitotic growth. Despite hundreds of modifications introduced, there are still regions sharing substantial sequence similarity that might lead to undesirable meiotic recombinations when intercrossing the two semisynthetic chromosome arm strains. Induction of the I- Sce I–mediated double-strand break is otherwise lethal and thus introduced a strong selective pressure for targeted homologous recombination. Since our strategy is designed to generate a markerless synII and leave the URA3 marker on the wild-type chromosome, we observed a tenfold increase in URA3 -deficient colonies upon I- Sce I induction, meaning that our strategy can greatly bias the crossover events toward the designated regions. By incorporating comprehensive phenotyping approaches at multiple levels, we demonstrated that synII was capable of powering the growth of yeast indistinguishably from wild-type cells (see the figure), showing highly consistent biological processes comparable to the native strain. Meanwhile, we also noticed modest but potentially significant up-regulation of the translational machinery. The main alteration underlying this change in expression is the deletion of 13 tRNA genes. A growth defect was observed in one very specific condition—high temperature (37°C) in medium with glycerol as a carbon source—where colony size was reduced significantly. We targeted and debugged this defect by two distinct approaches. The first approach involved phenotype screening of all intermediate strains followed by a complementation assay with wild-type sequences in the synthetic strain. By doing so, we identified a modification resulting from PCRTag recoding in TSC10 , which is involved in regulation of the yeast high-osmolarity glycerol (HOG) response pathway. After replacement with wild-type TSC10 , the defect was greatly mitigated. The other approach, debugging by SCRaMbLE, showed rearrangements in regions containing HOG regulation genes. Both approaches indicated that the defect is related to HOG response dysregulation. Thus, the phenotypic defect can be pinpointed and debugged through multiple alternative routes in the complex cellular interactome network. CONCLUSION We have demonstrated that synII segregates, replicates, and functions in a highly similar fashion compared with its wild-type counterpart. Furthermore, we believe that the iterative “design-build-test-debug” cycle methodology, established here, will facilitate progression of the Sc2.0 project in the face of the increasing synthetic genome complexity. SynII characterization. ( A ) Cell cycle comparison between synII and BY4741 revealed by the percentage of cells with separated CEN2-GFP dots, metaphase spindles, and anaphase spindles. ( B ) Replication profiling of synII (red) and BY4741 (black) expressed as relative copy number by deep sequencing. ( C ) RNA sequencing analysis revealed that the significant up-regulation of translational machinery in synII is induced by the deletion of tRNA genes in synII.

Shen, Yue↗
DOE OSTI2024

Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction

ABSTRACT Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Microbiology↗
DOE OSTI2026

Salt supplementation-induced metabolic reprogramming in Streptomyces coelicolor

Members of the genus Streptomyces are major producers of a wide variety of secondary metabolites that serve as bioactive compounds. Many secondary metabolites are produced in response to environmental signals such as biotic and abiotic stresses. In this study, we identified salt supplementation as one of the stimuli activating secondary metabolism in the model Streptomyces species, Streptomyces coelicolor. Comparative metabolomics revealed overproduction of several known secondary metabolites, most notably undecylprodigiosin and coelimycin P1, in addition to their biosynthetic intermediates and derivatives, as well as many unknown metabolites. Transcriptomic analysis revealed activation of diverse biological processes including cation uptake, compatible solute production, and the phosphate limitation stress response through conserved and species-specific mechanisms, presumably to overcome the increased salinity. This response leads to activation of a variety of regulatory and metabolic pathways required for production of secondary metabolites including activation of conserved metabolic pathways for energy and substrate supply and species-specific secondary metabolite biosynthetic gene clusters. Furthermore, several promoter sequences contributing to upregulation of secondary metabolism induced by salt supplementation were identified. Overall, our data show how S. coelicolor copes with the increased salinity and tailors the cellular metabolism toward secondary metabolism in a conserved and species-specific manner.

Otani, Hiroshi [USDOE Joint Genome Institute (JGI)↗
DOE OSTI2018

Time-resolved Proteome Profiling of Normal Lung Development

The biochemical networks mediating normal lung development remain unclear with important implications for ameliorating morbidity and mortality in premature infants. Here we perform integrative proteomics and metabolomics analyses of murine lungs from embryonic to early adult ages to characterize the molecular networks mediating normal lung development. Multi-omics analysis identified 8,932 proteins and 158 polar metabolites providing a deep and comprehensive view of the lung proteome and metabolome during normal development. Analysis of the proteomics data revealed ten discrete expression modules driving lung development and the underlying regulatory and signaling network modulating these expression modules. Of interest our data suggest the action of protein ubiquitination in regulating lung development extends beyond the pseudoglandular stage previously described. Combined analysis of the proteomics and metabolomics supported the notion of increased cell proliferation earlier in lung development. Additionally, comparison of the proteomics data with a recent transcriptome analysis revealed biological processes under post-transcriptional control during lung development. Our study provides a unique resource for understanding normal lung development, and potentially avenues for developing strategies to address disrupted development.

computational network analysis, lung development, ↗
DOE OSTI2019

Integration of transcriptomic and proteomic data identifies biological functions in cell populations from human infant lung

Systems biology uses computational approaches to integrate diverse data types to understand cell and organ behavior. Data derived from complementary technologies, for example transcriptomic and proteomic analyses, are providing new insights into development and disease. We compared mRNA and protein profiles from purified endothelial, epithelial, immune, and mesenchymal cells from normal human lung tissue. Signatures for each cell type were identified and compared at both mRNA and protein levels. Cell specific biological processes and pathways were predicted by analysis of concordant and discordant RNA-protein pairs. Cell clustering and gene set enrichment comparisons identified shared versus unique processes associated with transcriptomic and/or proteomic data. Clear cell-cell correlations between mRNA and protein data were obtained from each cell type. Approximately 40% of RNA-protein pairs were coherently expressed. While the correlation between RNA and their protein products was relatively low (approximately 0.4), cell specific signature genes involved in functional processes characteristic of each cell type, were more highly correlated with their protein products. Consistency of cell specific RNA-protein signatures indicated an essential framework for the function of each cell type. Visualization and reutilization of the protein and RNA profiles are supported by a new web application, "LungProteomics," which is incorporated into the LGEA web portal and freely accessible at (https://research.cchmc.org/pbge/lunggens/lungProteomics/human_sorted_profiles.html).

human lung, sorted cells, integrated omics, Transc↗
DOE OSTI2019

A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan–Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Data sets for Unraveling Iron Oxides as Abiotic Catalysts of Organic Phosphorus Recycling in Soil and Sediment Matrices

In biogeochemical phosphorus cycling, iron oxide minerals are acknowledged as strong adsorbents of inorganic and organic phosphorus species. The dephosphorylation of organic phosphorus is attributed only to biological processes, but iron oxides could also catalyze this hydrolytic cleavage. Limited evidence of this abiotic catalysis has relied on monitoring inorganic phosphate in solution, thereby ignoring iron oxides as both catalysts and adsorbents. Here we apply high-resolution mass spectrometry and X-ray absorption spectroscopy to characterize dissolved and particulate phosphorus species, respectively. In soil and sediment samples reacted with ribonucleotides, we uncover the abiotic production of particulate inorganic phosphate associated specifically with iron oxides. Experiments with various organic phosphorus compounds revealed up to 12-fold greater catalytic and adsorption reactivities with iron oxides than with the silicate and aluminosilicate minerals identified in the environmental samples. Remarkably, we obtained dephosphorylation rates by the iron oxides that are within reported enzymatic rates in soils. However, phosphorus cycle models do not yet include a quantitative account of the abiotic evolution of inorganic phosphate from organic phosphorus trapped on iron oxides in environmental matrices. Our findings imply a missing abiotic axiom for organic phosphorus mineralization in the phosphorus cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Long-term stabilization of intensity-difference squeezing from four-wave mixing in rubidium vapor

Generation of quantum states of light through off-resonance four-wave mixing in rubidium vapor is a straightforward and well-established technique. However, achieving a sufficiently high and consistent level of intensity difference squeezing (IDS) and intrinsic quantum correlations between photon pairs over an extended timescale, necessary for quantum-light-based nonlinear optical spectroscopy and microscopy, remains challenging and largely unexplored. Here, we report a simple stabilization method combining an active periodic laser frequency retuning with an automatic control algorithm based on quantitatively assessing the factors affecting the IDS level and squeezed light intensity. Validation of our method was performed by acquiring data over a 5-hour period, and the results demonstrate a remarkably stable squeezing level of -7.8 dB in combination with a > 4× reduction of the standard deviation of IDS level from 0.46 dB to 0.10 dB. The achieved stabilization further enables us to quantitatively assess the IDS reduction due to the scattering in a polystyrene bead suspension as a function of sample transmission. Our approach should enable a variety of applications requiring an extended squeezing stability over multiple hours, especially for those following biological processes and chemical reactions in real time.

Allen, Christian Harry [Oak Ridge National Laborat↗
DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A rapid methods development workflow for high-throughput quantitative proteomic applications

Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes.

02 PETROLEUM↗
DOE OSTI2020

Investigating effects of soil chemicals on density of small mammal bioindicators using spatial capture-recapture models

Monitoring the ecological impacts of environmental pollution and the effectiveness of remediation efforts requires identifying relationships between contaminants and the disruption of biological processes in populations, communities, or ecosystems. Wildlife are useful bioindicators, but traditional comparative experimental approaches rely on a staunch and typically unverifiable assumption that, in the absence of contaminants, reference and contaminated sites would support the same densities of bioindicators, thereby inferring direct causation from indirect data. We demonstrate the utility of spatial capture-recapture (SCR) models for overcoming these issues, testing if community density of common small mammal bioindicators was directly influenced by soil chemical concentrations. By modeling density as an inhomogeneous Poisson point process, we found evidence for an inverse spatial relationship between Peromyscus density and soil mercury concentrations, but not other chemicals, such as polychlorinated biphenyls, at a site formerly occupied by a nuclear reactor. Although the coefficient point estimate supported Peromyscus density being lower where mercury concentrations were higher (β = –0.44), the 95% confidence interval overlapped zero, suggesting no effect was also compatible with our data. Estimated density from the most parsimonious model (2.88 mice/ha; 95% CI = 1.63–5.08), which did not support a density-chemical relationship, was within the range of reported densities for Peromyscus that did not inhabit contaminated sites elsewhere. Environmental pollution remains a global threat to biodiversity and ecosystem and human health, and our study provides an illustrative example of the utility of SCR models for investigating the effects that chemicals may have on wildlife bioindicator populations and communities.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presented to demonstrate the implementation details and system innovations.

58 GEOSCIENCES↗
DOE OSTI2024

Crystallization and assembly at interfaces: Celebrating the achievements of a vibrant research community

Crystallization is one of the cornerstones of modern materials science and engineering and plays a critical role in industries ranging from petroleum derivative manufacturing to microstructural engineering of structural materials and the defect-free growth of silicon single crystals for integrated chip technology. Also, in the realm of environmental and biological processes, the mineralization of diverse compounds has shaped the vast array of ecosystems we observe today. Conversely, understanding the crystallization and assembly of building blocks of various sizes at interfaces has broader impacts on materials synthesis, performance of energy storage devices, optimized processing conditions, and more.

36 MATERIALS SCIENCE↗
DOE OSTI2016

87 Sr/ 86 Sr Concentrations in the Appalachian Basin: A Review

This document reviews 87 Sr/ 86 Sr isotope data across the Appalachian Basin from existing literature to show spatial and temporal variation. Isotope geochemistry presents a means of understanding the geochemical effects hydraulic fracturing may have on shallow ground substrates. Isotope fractionation is a naturally occurring phenomenon brought about by physical, chemical, and biological processes that partition isotopes between substances; therefore, stable isotope geochemistry allows geoscientists to understand several processes that shape the natural world. Strontium isotopes can be used as a tool to answer an array of geological and environmental inquiries. In some cases, strontium isotopes are sensitive to the introduction of a non-native fluid into a system. This ability allows strontium isotopes to serve as tracers in certain systems. Recently, it has been demonstrated that strontium isotopes can serve as a monitoring tool for groundwater and surface water systems that may be affected by hydraulic fracturing fluids (Chapman et al., 2013; Kolesar Kohl et al., 2014). These studies demonstrated that 87 Sr/ 86 Sr values have the potential to monitor subsurface fluid migration in regions where extraction of Marcellus Shale gas is occurring. This document reviews publicly available strontium isotope data from 39 sample locations in the Appalachian Basin (Hamel et al., 2010; Chapman et al., 2012; Osborn et al., 2012; Chapman et al., 2013; Capo et al., 2014; Kolesar Kohl et al., 2014). The data is divided into two sets: stratigraphic (Upper Devonian/Lower Mississippi, Middle Devonian, and Silurian) and groundwater. ArcMap™ (ESRI, Inc.) was used to complete inverse distance weighting (IDW) analyses for each dataset to create interpolated surfaces in an attempt to find regional trends or variations in strontium isotopic values across the Appalachian Basin. 87 Sr/ 86 Sr varies up to ~ 0.011 across the Appalachian Basin, but the current publicly available data is limited in frequency and regional extent, causing artifacts and high uncertainty when interpolating data for locations far from sampling sites. These factors highlight the need for additional strontium isotope sampling across the region. Identifying potential contamination from hydraulic fracturing fluid in Appalachian Basin groundwater using strontium isotopes would require additional sampling. For a more comprehensive strontium isotope database, samples would need to be collected during prefracturing, syn-fracturing, and post-fracturing stages. This would add a temporal component to the spatial data and make tracing of fluid migration with strontium isotopes more accurate. Future research and modeling that incorporates subsurface geology and watershed data would also serve to increase the accuracy and certainty of the interpolations of these analyses. Prospective geospatial Appalachian Basin isotope studies would also benefit from the integration of geologic mapping because surface and subsurface geology influences observed strontium isotope values.

58 GEOSCIENCES↗
DOE OSTI2017

Identification of Promising Remediation Technologies for Iodine in the UP-1 Operable Unit

Iodine-129 (129I) generated at the U.S. Department of Energy (DOE) Hanford Site during plutonium production was released to the subsurface, resulting in several large, though dilute, plumes in the groundwater, including the plume in the 200-UP-1 operable unit (OU). Because 129I is an uncommon contaminant, relevant remediation experience and scientific literature are limited, though work is under way to better understand the fate and transport of 129I in the environment and the effectiveness of potential remediation technologies. The recent UP-1 Evaluation Plan for Iodine and report on the Conceptual Model of Iodine Behavior in the Subsurface at the Hanford Site provide information on the history of contamination in the 200-UP-1 OU, relevant controlling processes (biological and geochemical), risk, the conceptual site model, and potential remedial options, which provided a foundation for this study. In this study, available information was compiled and used to categorize potential remediation technologies, culminating in a recommendation of promising technologies for further evaluation. Approaches to improve the technical information about promising technologies are also recommended in this study so that a subsequent evaluation of potential remediation alternatives can assess these technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗