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At least 361 records · Page 20

Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”

Surface water and pore water samples were collected at five sites along a shoreline transect of the Columbia River, southeastern WA, USA in 2017. This dataset is comprised of (1) high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) and (2) a metadata csv file. The FTICR-MS files are .xml, and the data package includes instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user’s specific needs. The data are associated with the publication “Using community assembly metrics from metacommunity ecology to understand environmental metabolomes” that will be published in Nature Communications (Danczak et al.). The study aimed to investigate gaps in understanding the spatiotemporal organization of environmental metabolomes to improve the ability to predict ecosystem function. Associated sequencing data will be published via NCBI. The access information for NCBI and the publication DOI will be added to this abstract when they are available. Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.

54 ENVIRONMENTAL SCIENCES↗

Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces

These data are from Bandopadhyay et al., "Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces". This study aims to understand the soil microbial ecology along terrestrial-aquatic interfaces of a freshwater and estuarine region and how it relates to organic matter. We analyzed soil microbial (16S rRNA gene) and organic matter (Fourier-transform ion cyclotron resonance mass spectrometry, FTICR-MS) composition from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie (freshwater) and Chesapeake Bay (estuarine) regions. This dataset includes 16S rRNA gene amplicon data (only processed file types included here) and organic matter composition from FTICR-MS data (raw and processed files included here) from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie and Chesapeake Bay regions. These sites are part of the COMPASS-FME project (https://compass.pnnl.gov/FME/COMPASSFME). File formats and software needed to access files: 16S rRNA gene amplicon data: These files follow the format reported here https://ess-dive.gitbook.io/amplicon-sequencing-reporting-format#updates-in-v1.0.1. As per this format, there are four file types reported: 1. Taxon tables (also called sequence-by-sample or OTU (operational taxonomic unit)/ESV (exact sequence variant) tables) : available in a .txt file format and accessible using TextEdit or MS Excel. 2. Representative sequences (also called consensus sequences) : available in a .fasta format and accessible using TextEdit. 3. Sequencing metadata : available in a MS Excel workbook file format and CSV file format 4. Bioinformatic metadata : available in a MS Excel workbook file format and CSV file format FTICR-MS data: 1. Raw data converted to a processed file with intensities of the peaks in the given samples : available in a MS Excel CSV file format 2. Processed file used in analyses and visualizations (appended as icr_long_) : available in a MS Excel CSV file format 3. Metadata file for ICR features (appended as icr_meta) : available in a MS Excel CSV file format

54 ENVIRONMENTAL SCIENCES↗

Characterization and Understanding of Thermal Transport in Stationary and Moving Particle Beds for Concentrating Solar Power

Concentrating solar power (CSP) coupled with thermal energy storage (TES) is being considered as an appealing solution to deliver stable, dispatchable, and inexpensive electricity generation from renewable solar energy. The heat from the HTF is stored in a TES system that is significantly less expensive and more scalable than electrochemical storage, enabling electricity generation when the sunlight is unavailable. The general concentrating solar thermal technologies are being pushed to higher temperature for higher efficiency and lower cost in a diverse range application in electricity generation (in CSP), industrial heating, and thermochemical fuel productions. Inert and abundant solid particles are becoming increasingly more important for these emerging applications. Heat transfer in both stationary and moving particle beds have been studied for many decades, revealing a great deal of insights on the mechanisms. Yet, there are still several unresolved problems from both fundamental understanding and technological applications points of view. In this Chapter, we will attempt to provide an up-to-date picture of thermal transport in stationary and moving particle beds. In both cases, we will review historical and contemporary developments in the theoretical, computational, and experimental aspects of heat transfer and related behaviors in particle beds. Here, we will discuss both the advancements and limitations of the existing studies and point to future developments towards deeper fundamental understandings and better engineering applications.

14 SOLAR ENERGY↗

Strengthening the Security of Operational Technology: Understanding Contemporary Bill of Materials

The evolution of cyber-physical infrastructure has made its security more challenging. The last few years have witnessed a convergence of hardware and software segments in various domains, including operational technology (OT) which is responsible for carrying out critical tasks such as monitoring and controlling power grids, nuclear plants, transportation, and emergency services. Both hardware and software encapsulate numerous open source and proprietary subcomponents, making it crucial for end-users to understand the composition of the products they are using. For example, wind turbines incorporate thousands of lines of code (software) used for the turbine's design, planning, operation, and analytics in addition to the numerous hardware subcomponents that construct it. Due to the highly complex nature of software and hardware, knowledge of the components and subcomponents is required to mitigate cyber vulnerabilities and defend against cyberattacks. There has also been a transformation from a traditional linear supply chain into a global, dynamic, diverse, and interconnected system. The digitization of the supply chain makes it easier to find and exploit vulnerabilities. Critical infrastructures (e.g., power grids, oil, natural gas, water, and wastewater) rely on OT to function, and if the OT is compromised, equipment damage and potential interruption of services could result. A significant security measure to protect OT systems from disruption is to develop a supply chain bill of materials (BoM) corresponding to the software and hardware used in OT, along with attestations amongst vendors and asset owners. A supply chain BoM is a proactive way to understand the inherent vulnerabilities in the system and mitigate them in advance of being exploited. BoMs bolster the trust placed in the digital infrastructure and enhance software supply chain security by sustaining the management of component obsolescence and compliance, along with the seclusion of unsafe segments of a specific product. Adopting BoM tools is becoming increasingly important across various government sectors, as evidenced by the recent U.S. executive order on cybersecurity (NIST 2021). This paper aims to classify BoMs based on structure, functionality, component type, and architecture. The work also discusses case studies to further highlight the benefits of BoMs. In addition, it identifies missing pieces in existing BoM implementations so that future research may identify bounds on where it could expect to make improvements and directly enable researchers to identify promising areas for exploration. Further, the authors provide valuable recommendations to tool developers, researchers, and standardizing organizations (policymakers), additionally benefitting critical infrastructure owners and government executives. This aids in paving a path for future work, thereby, providing suggestions to determine a tool for consumers that best suit their needs.

97 MATHEMATICS AND COMPUTING↗

The East River, Colorado, Watershed: A Mountainous Community Testbed for Improving Predictive Understanding of Multiscale Hydrological–Biogeochemical Dynamics

Core Ideas Development of a 300‐km 2 mountainous headwater testbed began in 2016 in the East River. The testbed can be used to explore how watershed changes impact downgradient water availability and quality. System‐of‐system, scale‐adaptive approaches can potentially improve watershed dynamics simulation. We have new approaches to monitor and simulate water partitioning and system responses. The East River watershed has been developed as a “community” testbed. Extreme weather, fires, and land use and climate change are significantly reshaping interactions within watersheds throughout the world. Although hydrological–biogeochemical interactions within watersheds can impact many services valued by society, uncertainty associated with predicting hydrology‐driven biogeochemical watershed dynamics remains high. With an aim to reduce this uncertainty, an approximately 300‐km 2 mountainous headwater observatory has been developed at the East River, CO, watershed of the Upper Colorado River Basin. The site is being used as a testbed for the Department of Energy supported Watershed Function Project and collaborative efforts. Building on insights gained from research at the “sister” Rifle, CO, site, coordinated studies are underway at the East River site to gain a predictive understanding of how the mountainous watershed retains and releases water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, and other disturbances influence hydrological–biogeochemical watershed dynamics at seasonal to decadal timescales. A system‐of‐systems perspective and a scale‐adaptive simulation approach, involving the combined use of archetypal watershed subsystem “intensive sites” are being tested at the site to inform aggregated watershed predictions of downgradient exports. Complementing intensive site hydrological, geochemical, geophysical, microbiological, geological, and vegetation datasets are long‐term, distributed measurement stations and specialized experimental and observational campaigns. Several recent research advances provide insights about the intensive sites as well as aggregated watershed behavior. The East River “community testbed” is currently hosting scientists from more than 30 institutions to advance mountainous watershed methods and understanding.

54 ENVIRONMENTAL SCIENCES↗

Understanding and Controlling Toughening Mechanisms in Nanotube Reinforced Ceramic Coatings

Research in this program is designed to understand mechanical behavior, particularly fracture toughness, in ceramics that are reinforced with carbon nanotubes (CNTs). In the past four years, emphasis was placed on: Synthesizing and characterizing ceramic nanocomposite materials reinforced with both multiwall carbon nanotubes (MWNTs) and single wall nanotubes (SWNTs); and Implementation and analysis of in situ mechanical testing methods to better understand and engineer the critical CNT/ceramic interfaces.

36 MATERIALS SCIENCE↗

Collaborative Research: Atmospheric Pressure Plasma-Biomaterial Surface Interactions - Bridging Understanding of APP Sources to Rational Modification of Biomolecules

The overriding objective of this work is to bridge the gap between understanding of atmospheric pressure plasma (APP) sources and predictive chemical modifications of biomolecules. A key aspect of this problem is to understand what oxidizing species are created in water adjacent to APP jets that would ultimately affect aqueous biomolecules. We report the production of highly oxidative species in solutions exposed to a self-pulsed corona discharge in air. We examine how the properties of the target solution (pH, conductivity) and the discharge power affect the discharge stability and the production of H2O2. Indigo carmine, a common organic dye, is used as an indicator of oxidative strength and in particular, hydroxyl radical (OH•) production. The observed rate of indigo oxidation in contact with the discharge far exceeds that predicted from reactions based on concentrations of species measured in the bulk solution. The generation of H2O2 and the oxidation of indigo carmine indicate a high concentration of highly oxidizing species such as OH• at the plasma-liquid interface. These results indicate that reactions at the air plasma-liquid interface play a dominant role in species oxidation during direct non-equilibrium atmospheric pressure plasma (NE-APP) treatment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding Litter Input Controls on Soil Organic Matter Turnover and Formation are Essential for Improving Carbon-Climate Feedback Predictions for Arctic, Tundra Ecosystems

The Arctic region stored vast amounts of carbon (C) in soils over thousands of years because decomposition has been limited by cold, wet conditions. Arctic soils now contain roughly as much C that is contained in all other soils across the globe combined. However, climate warming could unlock this oil C as decomposition accelerates and permafrost thaws. In addition to temperature-driven acceleration of decomposition, several additional processes could either counteract or augment warming-induced SOM losses. For example, increased plant growth under a warmer climate will increase organic matter inputs to soils, which could fuel further soil decomposition by microbes, but will also increase the production of new SOM. Whether Arctic ecosystems store or release carbon in the future depends in part on the balance between these two counteracting processes. By differentiating SOM decomposition and formation and understanding the drivers of these processes, we will better understand how these systems function. We did not find evidence of priming under current conditions, defined as an increase in the decomposition of native SOM stocks. This suggests that decomposition is unlikely to be further accelerated through this mechanism. We did find that decomposition of native SOM did occur when nitrogen was added to these soils, suggesting that nitrogen limits decomposition in these systems. Our results highlight the resilience and extraordinary C storage capacity of these soils, and suggest shrub expansion may partially mitigate C losses from decomposition of old SOM as Arctic soils warm.

54 ENVIRONMENTAL SCIENCES↗

Modeling of cellulose, hemicellulose and lignin-carbohydrate complex formation and regulation to understand plant cell wall structure

The goal of this project is to increase the fundamental understanding of the plant secondary cell wall in wood formation, using Populus trichocarpa as the model species. The project is built on a systematic transgenic strategy to perturb the expression of targeted cell-wall component genes and transcription factors (TFs). We used a systems biology approach that integrates this genome-wide transgenesis with full genome information to advance our understanding of wood formation and how to engineer woody plants to create robust feedstocks that maximize beneficial traits for biofuel and material production.

09 BIOMASS FUELS↗

Next Generation Anodes for Lithium-ion Batteries: Thermodynamic Understanding and Abuse Performance

As we develop new materials to increase performance of lithium ion batteries for electric vehicles, the impact of potential safety and reliability issues become increasingly important. In addition to electrochemical performance increases (capacity, energy, cycle life, etc.), there are a variety of materials advancements that can be made to improve lithium-ion battery safety. Issues including energetic thermal runaway, electrolyte decomposition and flammability, anode SEI stability, and cell-level abuse tolerance behavior. Introduction of a next generation materials, such as silicon based anode, requires a full understanding of the abuse response and degradation mechanisms for these anodes. This work aims to understand the breakdown of these materials during abuse conditions in order to develop an inherently safe power source for our next generation electric vehicles.

25 ENERGY STORAGE↗

Fundamental Understanding of Creep-Fatigue Interactions in 9Cr-1MoV Steel Welds. Final Report

Ferritic-martensitic steels constitute a vital class of materials for current and future generation of nuclear reactors as well as ultra supercritical coal fired power plants due to their superior creep resistant properties. One particular ferritic-martensitic steel, 9Cr-1MoV (Grade 91) is one of five materials approved for high temperature use in nuclear service by the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC). Grade 91 is also a candidate material for proposed fission and fusion reactors such as the sodium cooled fast reactor (SFR). In service, Grade 91 components can be subjected to elevated temperatures and cyclic stresses, leading to the accumulation of creep-fatigue (CF) damage. While the monotonic creep properties of Grade 91 steels have been studied extensively, there is less knowledge concerning the mechanisms governing CF damage of this steel in the creep-dominated failure region. Moreover, the creep failure is especially pronounced in welded Grade 91 components, which are commonly joined using conventional arc welding techniques such as flux-cored arc welding (FCAW). In a Grade 91 weld, the creep failure typically occurs in the outer region of the heat affected zone (HAZ), specifically in the intercritical or fine-grained heat-affected zone (ICHAZ or FGHAZ), a phenomenon known as type IV failure. Currently, there exists a limited knowledge of CF damage mechanisms in Grade 91 welds. Improving the mechanistic understanding of the CF damage and failure of Grade 91 steel and its welds with inhomogeneous microstructure is crucial for the safety and design of key structural components in advanced, high-temperature reactors. The overall objectives of the project were to advance the state of knowledge and understanding of CF damage in both Grade 91 base metal and its welds, especially under loading conditions where creep is the dominant damage mechanism. Uncovering the mechanisms governing the creep-fatigue deformation and damage in Grade 91 base metal in creep-dominated region as well as type IV failure in Grade 91 welds contributes to a new knowledge that may lead to more accurate life prediction models than those currently in use. Moreover, the superior CF properties obtained by low heat input welding has a high potential to develop practical solutions to the premature failure of Grade 91 weld.

36 MATERIALS SCIENCE↗

Understanding the Evolution of Biomass Burning Particles in the Atmosphere: Analysis of BBOP Data, Laboratory Experiments, and Model Integration

Submicron particles in the atmosphere can have a profound influence on Earth’s climate [Stocker et al., 2013]. Particulate matter (PM) affects climate via both direct effects (scattering or absorption of radiation) and indirect effects (changes to the formation and properties of clouds). Biomass burning (BB) is the largest global source of submicron, carbonaceous particles [Wiedinmyer et al., 2011]. Field campaigns have shown that BB aerosol (BBA) can evolve through rapid transformations and removal processes in the atmosphere, with changing radiative and hygroscopic properties, but these processes are not well characterized. Better understanding of the evolution of biomass burning PM in the atmosphere is critical for improving the accuracy of regional to global climate models. In order to address uncertainties in the initial physical, chemical and radiative forcing of BBA and the evolution of these parameters, DOE ASR conducted an airborne field campaign, the Biomass Burning Observation Project (BBOP), during the summer and fall of 2013 to make measurements in the plumes of northwest U.S. wildfires and southeast U.S. agricultural burns. BBOP provided unique, extremely detailed trace gas and particle measurements in fresh biomass burning plumes and captured large, rapid downwind transformations within a few hours of the sources. These fast changes in properties have also been observed in laboratory-generated BB smoke in a smog chamber, but in general the controlling factors and most likely outcomes in the real atmosphere are still not clear. The goals of this project were to 1) analyze and interpret the BBOP measurements in detail, 2) conduct laboratory experiments to explore the formation of tar balls, and 3) to incorporate our findings into improved models of biomass burning emissions and aging. This research focuses on understanding the chemical, physical and optical properties and transformations of BB emissions in the near-field within hours downwind of the burn and on a more regional scale and, in turn, how BB emissions relate to climate forcing. Analysis of the BBOP data paid particular attention to relating SOA production, changes in size distribution, and mixing state to the environmental conditions (gas-phase precursors, relative humidity, radiation, oxidants, NO x , etc.). This project included subcontracts and unfunded collaborations with many of the key participants in the BBOP campaign. Professor Robert Yokelson at the University of Montana is an expert on biomass burning fuels and emissions and participated in BBOP as an unfunded collaborator. Professor Peter Buseck at Arizona State University collected particle samples during BBOP and analyzed some of them as part of this project. Unfunded collaborators include Dr. Arthur Sedlacek, III at Brookhaven National Laboratory (BNL) and Dr. Rahul Zaveri at the Pacific Northwest National Laboratory (PNNL) who were both principal investigators in the BBOP campaign, focusing on measurements and modeling, respectively. We are also working closely with Prof. Qi Zhang at UC Davis to coordinate analysis of BBOP flight data and data from the Mt. Bachelor Observatory (MBO), and with Dr. Kouji Adachi at the Meteorological Institute (Japan) to analyze laboratory-generated tar ball samples.

09 BIOMASS FUELS↗

Final report: Understanding influence of thermal history and glass chemistry on kinetics of phase separation and crystallization in borosilicate glass-ceramic waste forms for aqueous reprocessed high level waste

This report provides an overview of the research activities conducted over the three-year period, October 1, 2015 to September 30, 2018. The project consisted of the US DOE component and a parallel project funded by the UK’s EPSRC. The US project is reported here, with some overview of the UK project results. The project was designed to be highly collaborative, including work in the US by Washington State University and Rutgers University, and in the UK by the University of Sheffield and the University of Warwick. Pacific Northwest National Laboratory supported the US project with some synthesis and some characterization. The overall program had two aims: (Aim 1) Understand fundamental mechanisms of the phase transitions leading to the conversion of melt to multiphase glass-ceramic as a function of composition and cooling rate; (Aim 2) Understand influence of glass chemistry on kinetics of phase separation and crystallization. This report includes the summary of the project objectives, approaches, results and deliverables.

36 MATERIALS SCIENCE↗

Species-specific Susceptibility to Scale Loss: Using Simulated Shear to Understand Among Species Differences in Turbine Passage Injury

Hydropower is the largest source of utility-scale, renewable electricity (e.g., 44% of all renewable energy) in the USA to date (U.S. Energy Information Administration (USEIA), 2017); however, dam installation and operation have impacted natural upstream and downstream fish passage and altered connectivity of riverine fish communities throughout the USA (Čada, 1998; Čada et al., 2006; Pracheil et al., 2016a). Fish ladders and exclusion devices (among others) allow fish to safely circumvent and avoid passage through the turbines altogether (Čada, 2001), but are rarely 100% effective. At many dams, passage through turbines is unavoidable, and stressors like collision with structures or blade strike, barotrauma or cavitation, turbulence, and exposure to shear forces may cause injury or mortality to entrained fish (Čada, 2001; Neitzel et al., 2004; Pracheil et al., 2016a). Passage injury and mortality may be a consequence of exposure to the entire suite of stressors, while the exact role of each is difficult to ascertain and link to individuals (Colotelo et al., 2017). Contributing complicating factors to understanding mortality include turbine type, variation in fish size (i.e., life stages), and the marked morphological diversity of freshwater fishes (Pracheil et al., 2016a; Colotelo et al., 2017). Laboratory studies aimed to understand the effects of turbine passage have quantified each stressor separately to determine appropriate dose-response relationships based on fish size, species, etc. Establishing dose-response relationships by stressor for priority species that interact with hydropower dams is one of the primary objectives of the Biologicallybased Design and Evaluation (BioDE) project being conducted at Oak Ridge National Laboratory (ORNL) and Pacific Northwest National Laboratory (PNNL). At its core, BioDE is focused on empirically driven research that quantifies fish responses to stressors at exposure levels similar to those experienced during turbine passage so that Biological Performance Assessment (BioPA) models can be developed. The BioPA model informs hydropower turbine design modifications based on predicted injury and mortality in response to various stressor exposures, e.g., blade strike, shear, and barotrauma. Stress exposure is defined by computational fluid dynamics models of the turbine environment. Fish response relationships are determined through laboratory studies like the one reported in this document. The BioPA model will aid turbine manufactures, plant operators, and dam owners with design of lower impact turbines and modify operating procedures to maximize survival of entrained fishes.

13 HYDRO ENERGY↗

Understanding and Controlling Toughening Mechanisms in Nanotube Reinforced Ceramic Coatings (Final Report)

Research in this program is designed to understand mechanical behavior, particularly fracture toughness, in ceramics that are reinforced with carbon nanotubes (CNTs). In the past four years, emphasis was placed on: Synthesizing and characterizing ceramic nanocomposite materials reinforced with both multiwall carbon nanotubes (MWNTs) and single wall nanotubes (SWNTs) and implementation and analysis of in situ mechanical testing methods to better understand and engineer the critical CNT/ceramic interfaces.

36 MATERIALS SCIENCE↗

Pathways to Carbon Liberation: A Systems Approach to Understanding Carbon Transformations and Losses from Thawing Permafrost

Our objective in this project was to discover how microbial communities mediate the fate of carbon in thawing permafrost under climate change. We proposed a systems approach integrating (a) molecular microbial and viral ecology, (b) molecular organic chemistry and stable and radiocarbon isotopes, and (c) state-of-the-art modeling, along a chronosequence of permafrost thaw in subarctic Sweden. The fate of carbon (C) in thawing permafrost is an outstanding challenge of modern biogeochemistry and climate change. Permafrost C pools are large (~1700 PgC), and C dynamics of thawing permafrost complex: old C decomposes as it is liberated from thawing permafrost as CO 2 or CH 4 , with a significant fraction cycling through lake sediments, even as new C accumulates due to thaw-initiated ecological succession. Our work is allowing better prediction of the net effect of these processes. Microbes mediate C dynamics in thawing permafrost, but a mechanistic understanding of how to scale microbial population dynamics, genomic potential, and expression to ecosystem-scale processes has been missing. A key question was: What is the interplay of microbial communities and organic matter chemical structure in the decomposition/preservation of organic C across a thaw gradient? And intriguingly, what (if any) is the role of phage (viruses that infect prokaryotic cells) in mediating these processes? Viruses appear to play a large role in driving oceanic function, but these phenomena are virtually unstudied in terrestrial systems. This endeavor linking microbial and viral dynamics, organic geochemistry and trace gas production will improve models of C cycling in permafrost systems, and clarify the fate of C under future climates. Technical Approach – We conducted a study at Stordalen Mire, Sweden, along a permafrost thaw chronosequence encompassing permafrost palsas and their initial collapse stage, thawing bog sites (dominated by Sphagnum moss), fully-thawed and inundated fen sites (dominated by Eriophorum spp or Carex spp.), and lakes. Our project used cutting edge technologies in both biogeochemistry and molecular microbial ecology to advance systems biology research on microbial carbon cycling through: (a) systems-level mapping of chemical states and ages of organic matter (via FT-ICR-MS and 14 C analysis) along thaw gradients to associated microbial communities, biochemical potentials, and activities (via meta-genomics, -transcriptomics, –proteomics, and viral genomics), and to CO 2 and CH 4 fluxes; (b) experimental incubations using Quantum Dot Probing, to test key hypotheses, arising from (a), about particular microbially-driven biochemical degradation pathways; (c) bioinformatics designed to simultaneously enhance the DOE Knowledgebase, and (d) integrated ecosystem C-cycle modeling testable by soil organic chemical and microbial data. Results from this project spanned 4 categories: (i) integrative across disciplines, and disciplinarily-focused in (ii) microbiology, (iii) biogeochemistry, and (iv) modeling. In integrated understanding of the system, we answered the questions posed above, mapping resident microbes to carbon transformations to reveal a carbon-processing shift with permafrost thaw, and discovering abundant, diverse and habitat-specific viruses that appear to be impacting carbon cycling, while also relating microbial communities to modeled processes. In microbiology-specific papers, we dug into viromes, microbial community networks, and informatic methods, while also introducing a new permafrost-associated phylum and its ecogenomic context. Relevance to DOE FOA - With a focus on discovering how microbial communities mediate the fate of old and new carbon in permafrost systems with climate change, our work directly responds to the call for “–omics driven basic research on the contribution of... microbial communities to C cycling processes in terrestrial ecosystems.” We bridge all three of the focal areas of the call, including (i) “Systems biology studies”, and development of –omics approaches (ii) “to investigate microbial community functional processes”, and (iii) “for imaging and analysis of microbially-mediated carbon cycling.”

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular-scale Understanding of Selective Oxidative Transformations of Alcohols Promoted by Au and Au-based Alloys

This project developed a molecular-scale mechanistic framework for complex selective oxidation of alcohols and amines on O-covered Au and Ag-Au alloys that guides the design of selective and energy efficient processes. Our work has led to the discovery of new classes of reactions. We have also bridged a wide range of pressures and materials complexity by demonstrating catalytic activity using nanoporous Au catalysts. The selective oxidation of alcohols with each other and with other reactants, such as CO or amines, were focused on in this work because it is a key technology for large-scale chemical synthesis. Theory and experiment were combined to understand selective oxidation reactions on Au. Significant accomplishments are: (i) development of molecular-scale mechanisms for selective alcohol oxidation over Au surfaces; (ii) discovery of two new classes of reactions on O/Au—amide synthesis from amines and aldehydes and carbonylation of alcohols; and, (iii) demonstration that the mechanisms derived from our fundamental work predict the conditions for efficient catalysis using nanoporous Au catalysts under flow conditions at atmospheric pressure. This work has made an unprecedented connection between fundamental surface science studies and their implementation under catalytic conditions. This research fits squarely in the DOE-BES mission articulated in several BES Basic Research Needs (BRN) reports. “Catalysis for Energy” emphasizes the need to fabricate, design, characterize, and assemble new structures, including nanoscale alloys, and to understand and model their chemical behavior for energy-related applications. Our studies of nanoporous materials also exploit unique mesoscale phenomena to address complex energy-related issues (http://www.meso2012.com/).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding the Hierarchy of Dense Subgraphs in Stationary and Temporally Varying Setting

Graphs are widely used to model relationships in a wide variety of domains such as sociology, bioinformatics, infrastructure, the WWW, to name a few. One of the key observations is that while real-world graphs are often globally sparse, they are locally dense. In other words, the average degree is often quite small (say at most 10 in a million vertex graph), but vertex neighborhoods are often dense. Finding dense subgraphs is a critical aspect of graph mining It has been used for finding communities and spam link farms in web graphs, graph visualization, real-time story identification, DNA motif detection in biological networks, finding correlated genes, epilepsy prediction, finding price value motifs in financial data, graph compression, distance query indexing, and increasing the throughput of social networking site servers. However, most standard formulations of this problem (like clique, quasi-clique, k-densest subgraph) are NP-hard. Furthermore, current dense subgraph finding algorithms usually optimize some objective, and only find a few such subgraphs without providing any structural relations, whereas the goal is rarely to find the "true optimum," but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine relationships among them. In this project, we first aim to devise algorithms and provide 3 implementations with nice visualizations to find the hierarchy between dense subgraphs, and then understand the structure of the hierarchy to gain more insight on the hidden patterns in real-world networks. Another important aspects in graph analysis is the temporal nature of networks. Networks evolve over time and in many applications data arrives at a high velocity, and thus it is important to design algorithms that can process data efficiently. We report three main results towards identifying dense structures in large evolving graphs. First, we will show how the hierarchical connectedness structure can be maintained efficiently, where connectedness is defined by increasing levels of connectivity strength. Next, we present dense structure can be identified in bipartite graphs without building projection graphs. And finally, we present a new method for peeling algorithms This new approach avoids sequential nature of peeling algorithms and is amenable to parallelization, which is crucial for processing high velocity data.

97 MATHEMATICS AND COMPUTING↗