Aqua Ions–Graphene Interfacial and Confinement Behavior: Insights from Isobaric–Isothermal Molecular Dynamics
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catalysis (heterogeneous)↗
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Aqueous CO 2 Solutions at Silica Surfaces and within Nanopore Environments. Insights from Isobaric–Isothermal Molecular Dynamics
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bio-inspired, mechanical behavior, carbon sequestr↗
Simulating Ru L 3 -Edge X-ray Absorption Spectroscopy with Time-Dependent Density Functional Theory: Model Complexes and Electron Localization in Mixed-Valence Metal Dimers
Ruthenium L3-edge X-ray absorption (XA) spectroscopy probes unoccupied 4d orbitals of the metal atom and is increasingly being used to investigate the local electronic structure in ground and excited electronic states of Ru complexes. The simultaneous development of computational tools for simulating Ru L3-edge spectra is crucial for interpreting the spectral features at a molecular level. This study demonstrates that time-dependent density functional theory (TDDFT) is a viable and predictive tool for simulating ruthenium L3-edge XA spectroscopy. We systematically investigate the effects of exchange correlation functional and implicit and explicit solvent interactions on a series of RuII and RuIII complexes in their ground and electronic excited states. The TDDFT simulations reproduce all of the experimentally observed features in Ru L3-edge XA spectra within the experimental resolution (0.4 eV). Our simulations identify ligand-specific charge transfer features in complicated Ru L3-edge spectra of [Ru(CN)6]4- and RuII polypyridyl complexes illustrating the advantage of using TDDFT in complex systems. We conclude that the B3LYP functional most accurately predicts the transition energies of charge transfer features in these systems. We use our TDDFT approach to simulate experimental Ru L3-edge XA spectra of transition metal mixed-valence dimers of the form [(NC)5MII-CN-RuIII(NH3)5] (where M = Fe or Ru) dissolved in water. Our study determines the spectral signatures of electron delocalization in Ru L3-edge XA spectra. We find that the inclusion of explicit solvent molecules is necessary for reproducing the spectral features and the experimentally determined valencies in these mixed-valence complexes. This study validates the use of TDDFT for simulating Ru 2p excitations using popular quantum chemistry codes and providing a powerful interpretive tool for equilibrium and ultrafast Ru L3-edge XA spectroscopy.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Chemical influence of ammonia on suppressing soot formation pathways
There is interest in mixing ammonia (NH3) with hydrocarbons, as this decreases overall CO2 emissions from the fuel mixture when burned. Co-firing NH3 with hydrocarbons like methane (CH4) also enables stable combustion over a larger set of operating conditions in engines and gas turbines than firing only NH3 permits. When NH3 is co-fired with hydrocarbons, the influence of NH3 on soot formation chemistry becomes relevant. In this work, soot concentrations in laminar nonpremixed co-flow flames of NH3/CH4 and N2/CH4 were analyzed using color-ratio pyrometry. The concentrations of combustion species (CH4, CO2, H2O, O2, C2H2, C6H6, HCN) across the different flames were also determined using on-line electron-impact mass spectrometry. The flames were also interrogated with 2D CFD simulations, which employ a detailed chemical mechanism tailored to capturing fuel-nitrogen chemistry. Addition of NH3 to CH4 flames was found to decrease soot concentrations more significantly than N2-addition (Fig. 1). The NH3/CH4 flames were found to have higher flame temperatures than the N2/CH4 flames, implying the suppression of soot afforded by NH3 is due to a chemical influence of NH3, as opposed to thermal or dilution effects. Based on experimental and simulated soot volume fractions and species concentrations, soot formation pathways affected by NH3 are postulated.
10 SYNTHETIC FUELS↗
Advancing graph-based algorithms for predicting flow and transport in fractured rock
Discrete fracture network (DFN) models are a powerful alternative to continuum models for subsurface flow and transport simulations because they explicitly include fracture geometry and network topology, thereby allowing for better characterization of the latter's influence on flow and transport through fractured media. Recent advances in high performance computing have opened the door for flow and transport simulations in large explicit three-dimensional DFN, but this increase in model fidelity and system size comes at a huge computational cost because of the large number of mesh elements required to represent thousands of fractures (with sizes that can range several orders of magnitude, from mm to km). In most subsurface applications, fracture characteristics are only known statistically and numerous realizations are needed to bound uncertainty in flow and transport in the system, thereby exacerbating the computational burden. blackGraphs provide a simple and elegant way to characterize, query, and interrogate fracture network connectivity. We propose a DFN model reduction framework where various graph-representations are used in conjunction with high-fidelity DFN simulations to increase computational efficiency while retaining accuracy of key quantities of interest. The appropriate choice of a graph-representation, namely, which attributes of the DFN are to be represented as nodes and which ones as edges connecting those nodes, depends on the relevant scientific questions. We demonstrate that the proposed DFN model reduction framework provides an efficient means for DFN modeling through both system reduction of the DFN using graph-based properties and combining DFN and graph-based flow and transport simulations.
58 GEOSCIENCES↗
Permafrost Extent on the Alaskan Beaufort Shelf From Surface-Towed Controlled-Source Electromagnetic Surveys
We have developed a surface-towed electric dipole-dipole system capable of operating in shallow water and deployable from small vessels. Our system uses electromagnetic energy from a modulated manmade source to interrogate the underlying resistivity structure of the seafloor. We used this system in the summers of 2014 and 2015 to map subsea ice-bearing permafrost on the Beaufort shelf along 200 km of coastline, from Tigvariak Island to Harrison Bay. Permafrost is resistive and was found to be anisotropic, likely due to interbedded layers of frozen and unfrozen sediment. Maps of depth to permafrost and its thickness were produced from electrical resistivity inversions and results compared to borehole logs in the area. We observed elevated resistivity values offshore the Sagavanirktok River outflow, supporting the idea that fresh groundwater flow has a preserving effect on submerged permafrost. This system provides a cost effective method that could be used to further quantify permafrost extent, provide a baseline for measurements of future degradation, and provide observational constraints to aid in permafrost modeling studies.
54 ENVIRONMENTAL SCIENCES↗
InterCarb: A Community Effort to Improve Interlaboratory Standardization of the Carbonate Clumped Isotope Thermometer Using Carbonate Standards
Abstract Increased use and improved methodology of carbonate clumped isotope thermometry has greatly enhanced our ability to interrogate a suite of Earth‐system processes. However, interlaboratory discrepancies in quantifying carbonate clumped isotope (Δ 47 ) measurements persist, and their specific sources remain unclear. To address interlaboratory differences, we first provide consensus values from the clumped isotope community for four carbonate standards relative to heated and equilibrated gases with 1,819 individual analyses from 10 laboratories. Then we analyzed the four carbonate standards along with three additional standards, spanning a broad range of δ 47 and Δ 47 values, for a total of 5,329 analyses on 25 individual mass spectrometers from 22 different laboratories. Treating three of the materials as known standards and the other four as unknowns, we find that the use of carbonate reference materials is a robust method for standardization that yields interlaboratory discrepancies entirely consistent with intralaboratory analytical uncertainties. Carbonate reference materials, along with measurement and data processing practices described herein, provide the carbonate clumped isotope community with a robust approach to achieve interlaboratory agreement as we continue to use and improve this powerful geochemical tool. We propose that carbonate clumped isotope data normalized to the carbonate reference materials described in this publication should be reported as Δ 47 (I‐CDES) values for Intercarb‐Carbon Dioxide Equilibrium Scale.
58 GEOSCIENCES↗
Distributed Acoustic Sensing as a Distributed Hydraulic Sensor in Fractured Bedrock
Distributed acoustic sensing (DAS) was originally intended to measure oscillatory strain at frequencies of 1 Hz or more on a fiber optic cable. Recently, measurements at much lower frequencies have opened the possibility of using DAS as a dynamic strain sensor in boreholes. A fiber optic cable mechanically coupled to a geologic formation will strain in response to hydraulic stresses in pores and fractures. A DAS interrogator can measure dynamic strain in the borehole, which can be related to fluid pressure through the mechanical compliance properties of the formation. Because DAS makes distributed measurements, it is capable of both locating hydraulically active features and quantifying the fluid pressure in the formation. We present field experiments in which a fiber optic cable was mechanically coupled to two crystalline rock boreholes. The formation was stressed hydraulically at another well using alternating injection and pumping. The DAS instrument measured oscillating strain at the location of a fracture zone known to be hydraulically active. Rock displacements of less than 1 nm were measured. Laboratory experiments confirm that displacement is measured correctly. These results suggest that fiber optic cable embedded in geologic formations may be used to map hydraulic connections in three-dimensional fracture networks. A great advantage of this approach is that strain, an indirect measure of hydraulic stress, can be measured without beforehand knowledge of flowing fractures that intersect boreholes. The technology has obvious applications in water resources, geothermal energy, CO 2 sequestration, and remediation of groundwater in fractured bedrock.
54 ENVIRONMENTAL SCIENCES↗
Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture
Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process–guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.
54 ENVIRONMENTAL SCIENCES↗
Distributed Acoustic Sensing to Estimate the Permeability
Optical fiber in a borehole can be interrogated with distributed acoustic sensors (DAS) to capture fracture displacements with the potential to map surrounding fracture networks. We designed a laboratory experiment to test the capability of DAS to determine borehole flow characteristics, and we show that for the first time DAS can be used to remotely estimate permeability. Optical fiber was wrapped around a bead filled pipe and the pressure drop and flow velocity were measured to directly calculate permeability. A machine learning model using statistical features from continuous DAS estimated the bulk permeability. Fluid interactions with the permeable material demonstrate insufficient resolution using DAS amplitude-based measurements for estimating pressure drop to infer permeability. Variations in the spectral domain relate DAS measurements to the pressure drop and provide consistent permeability estimates. Resolution with DAS is sufficient to estimate permeability and provides a reliable method to monitor at depth in borehole conditions.
58 GEOSCIENCES↗
iVirus: facilitating new insights in viral ecology with software and community data sets imbedded in a cyberinfrastructure
Microbes affect nutrient and energy transformations throughout the world’s ecosystems, yet they do so under viral constraints. In complex communities, viral metagenome (virome) sequencing is transforming our ability to quantify viral diversity and impacts. Although some bottlenecks, for example, few reference genomes and nonquantitative viromics, have been overcome, the void of centralized data sets and specialized tools now prevents viromics from being broadly applied to answer fundamental ecological questions. Here we present iVirus, a community resource that leverages the CyVerse cyberinfrastructure to provide access to viromic tools and data sets. The iVirus Data Commons contains both raw and processed data from 1866 samples and 73 projects derived from global ocean expeditions, as well as existing and legacy public repositories. Through the CyVerse Discovery Environment, users can interrogate these data sets using existing analytical tools (software applications known as ‘Apps’) for assembly, open reading frame prediction and annotation, as well as several new Apps specifically developed for analyzing viromes. Because Apps are web based and powered by CyVerse supercomputing resources, they enable scalable analyses for a broad user base. Finally, a use-case scenario documents how to apply these advances toward new data. This growing iVirus resource should help researchers utilize viromics as yet another tool to elucidate viral roles in nature.
59 BASIC BIOLOGICAL SCIENCES↗
Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis
The heterotrimeric G-protein complex is minimally composed of Ga, Gb, and Gc subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.
54 ENVIRONMENTAL SCIENCES↗
A zero-knowledge protocol for nuclear warhead verification
The verification of nuclear warheads for arms control involves a paradox: international inspectors will have to gain high confidence in the authenticity of submitted items while learning nothing about them. Proposed inspection systems featuring ‘information barriers’, designed to hide measurements stored in electronic systems, are at risk of tampering and snooping. Here we show the viability of a fundamentally new approach to nuclear warhead verification that incor-porates a zero-knowledge protocol, which is designed in such a way that sensitive information is never measured and so does not need to be hidden. We interrogate submitted items with energetic neutrons, making, in effect, differential measurements of both neutron transmission and emission. Calculations for scenarios in which material is diverted from a test object show that a high degree of discrimination can be achieved while revealing zero information. Our ideas for a physical zero-knowledge system could have applications beyond the context of nuclear disarmament. The proposed technique suggests a way to perform comparisons or computations on personal or confidential data without measuring the data in the first place.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
New CRISPR–Cas systems from uncultivated microbes
We present that CRISPR-Cas systems provide microbes with adaptive immunity by employing short DNA sequences, termed spacers, that guide Cas proteins to cleave foreign DNA. Class 2 CRISPR-Cas systems are streamlined versions, in which a single RNA-bound Cas protein recognizes and cleaves target sequences. The programmable nature of these minimal systems has enabled researchers to repurpose them into a versatile technology that is broadly revolutionizing biological and clinical research. However, current CRISPR-Cas technologies are based solely on systems from isolated bacteria, leaving the vast majority of enzymes from organisms that have not been cultured untapped. Metagenomics, the sequencing of DNA extracted directly from natural microbial communities, provides access to the genetic material of a huge array of uncultivated organisms. Here, using genome-resolved metagenomics, we identify a number of CRISPR-Cas systems, including the first reported Cas9 in the archaeal domain of life, to our knowledge. This divergent Cas9 protein was found in little-studied nanoarchaea as part of an active CRISPR-Cas system. In bacteria, we discovered two previously unknown systems, CRISPR-CasX and CRISPR-CasY, which are among the most compact systems yet discovered. Notably, all required functional components were identified by metagenomics, enabling validation of robust in vivo RNA-guided DNA interference activity in Escherichia coli. Lastly, interrogation of environmental microbial communities combined with in vivo experiments allows us to access an unprecedented diversity of genomes, the content of which will expand the repertoire of microbe-based biotechnologies.
59 BASIC BIOLOGICAL SCIENCES↗
Metabolomic data streaming for biology-dependent data acquisition
During the last 10 years, metabolomics has emerged as a powerful technology to interrogate cellular biochemistry at the global level. Although much of the success has been driven by advances in mass spectrometry, developments in bioinformatic resources for data processing have been equally important. Additionally, the widely used metabolomic software XCMS, in particular, has undergone substantial improvements since its first introduction in 2005 (ref. 1). In addition to improved algorithms for peak picking, retention time alignment and data visualization, XCMS has transitioned from a command-line interface requiring expertise with the R programming language, to a web-based platform with a graphical user interface2. This web-based platform, which we call XCMS Online, enables thousands of users to upload their metabolomic data and perform cloud-based processing.
59 BASIC BIOLOGICAL SCIENCES↗
Near-threshold H/D exchange in CD{sub 3}CHO photodissociation.
Measuring the isotopic abundance of hydrogen versus deuterium atoms is a key method for interrogating reaction pathways in chemistry. H/D 'scrambling' is the intramolecular rearrangement of labile isotopes of hydrogen atoms and when it occurs through unanticipated pathways can complicate the interpretation of such experiments. Here, we investigate H/D scrambling in acetaldehyde at the energetic threshold for breaking the formyl C-H bond and reveal an unexpected unimolecular mechanism. Laser photolysis experiments of CD{sub 3}CHO show that up to 17% of the products have undergone H/D exchange to give CD{sub 2}H + DCO. Transition-state theory calculations reveal that the dominant mechanism involves four sequential H- or D-shifts to form CD{sub 2}HCDO, which then undergoes conventional C-C bond cleavage. At the lowest energy the molecule undergoes an average of 20 H- or D-shifts before products are formed, evincing significant scrambling of H and D atoms. Analogous photochemically induced isomerizations and isotope scrambling are probably important in both atmospheric chemistry and combustion reactions.
08 HYDROGEN↗
Tuning charge and correlation effects for a single molecule on a graphene device
The ability to understand and control the electronic properties of individual molecules in a device environment is crucial for developing future technologies at the nanometre scale and below. Achieving this, however, requires the creation of three-terminal devices that allow single molecules to be both gated and imaged at the atomic scale. We have accomplished this by integrating a graphene field effect transistor with a scanning tunnelling microscope, thus allowing gate-controlled charging and spectroscopic interrogation of individual tetrafluoro-tetracyanoquinodimethane molecules. We observe a non-rigid shift in the molecule’s lowest unoccupied molecular orbital energy (relative to the Dirac point) as a function of gate voltage due to graphene polarization effects. Our results show that electron–electron interactions play an important role in how molecular energy levels align to the graphene Dirac point, and may significantly influence charge transport through individual molecules incorporated in graphene-based nanodevices.
36 MATERIALS SCIENCE↗
Kinetic gating mechanism of DNA damage recognition by Rad4/XPC
The xeroderma pigmentosum C (XPC) complex initiates nucleotide excision repair by recognizing DNA lesions before recruiting downstream factors. How XPC detects structurally diverse lesions embedded within normal DNA is unknown. Here we present a crystal structure that captures the yeast XPC orthologue (Rad4) on a single register of undamaged DNA. The structure shows that a disulphide-tethered Rad4 flips out normal nucleotides and adopts a conformations similar to that seen with damaged DNA. Contrary to many DNA repair enzymes that can directly reject non-target sites as structural misfits, our results suggest that Rad4/XPC uses a kinetic gating mechanism whereby lesion selectivity arises from the kinetic competition between DNA opening and the residence time of Rad4/XPC per site. This mechanism is further supported by measurements of Rad4-induced lesion-opening times using temperature-jump pertubation spectroscopy. Kinetic gating may be a general mechanism used by site-specific DNA-binding proteins to minimize time-consuming interrogations of non-target sites.
59 BASIC BIOLOGICAL SCIENCES↗