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At least 181 records · Page 10

Implementation of Ion Exchange Processes on Industrial Waste Streams for CO 2 Mineralization

Economic development and population growth will lead to an increase in global energy consumption. Large coal-fired power plants (>500 MW) account for almost half of the total CO 2 emissions from fossil fuel combustion, and nearly 26% of the global fossil fuel and industry CO 2 emissions. Long-term management of the more than 36 Gt of CO 2 that is emitted globally per year is urgently needed. CO 2 mineralization is an attractive method of sequestering CO 2 because it captures CO 2 as an insoluble carbonate mineral, mimicking the natural process of rock weathering. Here, we present a pathway for accelerated CO 2 mineralization enabled by divalent cations sourced from liquid streams. In this work, we investigate a mineralization route that converts flue gas CO 2 to precipitated calcium carbonate (PCC) using waste aqueous streams as the calcium source. The proposed mineralization route integrates CO 2 utilization and waste liquid management at coal power plants. Maintaining alkalinity during carbonation is the primary challenge in this process. Instead of relying on the consumption of costly and unsustainable sources of alkalinity (e.g., sodium hydroxide), we used regenerable solids to increase the pH of water by ion exchange. The increase in alkalinity creates a more thermodynamically favorable environment for calcite precipitation. The capacities for ion exchange of various commercially available zeolites and ion exchange resins in CO 2 -saturated water were studied through batch equilibrium and column ion-exchange experiments. During ion exchange, H + in the water exchanges with Na + , Ca 2+ or K + in the zeolite or resin. Batch equilibrium isotherms for H + –Na + exchange were collected by first adding varying amounts of the ion exchange solid (0 – 1.0 kg per kg of water) to CO 2 -saturated water (pCO 2 = 1 atm, pH 4) to determine the maximum H + –Na + exchange achievable. Ion-exchange column studies were performed to determine breakthrough capacity of the system. In both systems, an increase in pH coupled with an increase in Na concentration was observed, demonstrating the feasibility of forward ion exchange. Zeolitic materials increased the alkalinity of the solution from pH 4 to around 10, whereas ion exchange resins containing weakly acidic functional groups (e.g., carboxylic acid) exhibited higher affinity for H + , increasing pH to 11.3 and surpassing the pH shift induced by the zeolitic materials. The extent of calcite precipitation was evaluated by mixing the alkaline CO 3 2- -rich water obtained after passing through the ion-exchange column and a CaCl 2 solution. Calcite yields are as expected from chemical thermodynamics. Calcium carbonate yields found experimentally were about 26 and 8 mmol per kg water for the weakly acidic ion exchange resin and zeolitic materials, respectively. The results from these studies indicate that ion exchange processes can be used as an alternative to the addition of stoichiometric inorganic bases (e.g., sodium hydroxide) to induce alkalinity for the consequent precipitation of CaCO 3 . Instead, weakly acidic ion exchange resins commonly used for water hardness removal were alternatively used to induce pH swings in the aqueous solutions. The high calcium carbonate yields obtained for the materials examined demonstrate the potential application of this process. In addition, the successful operation of the calcium carbonate production process at standard temperature and pressure conditions support its potential for industrial implementation.

Simonetti, Dante↗

History of Ultrasonic Inspection of High-Level Waste Tanks at SRS - 20220

The Liquid Waste Disposition Projects (LWDP) Structural Authority and Inspection Engineering Support Group has teamed with the Materials Science and Technology Non-destructive Evaluation Group of Savannah River National Laboratory (SRNL) to implement a comprehensive In-Service Inspection (ISI) program for the High-Level Waste (HLW) tanks in the sites tank farms. The purpose of this program is to demonstrate the structural and leak integrity of the tanks to maintain the function of waste containment throughout the desired service life. Four types of waste tanks were constructed at Savannah River Site (SRS) from 1951 thru 1981 to store radioactive nuclear waste from the separations process. The Type I, II and III are carbon steel cylindrical tanks with varying degrees of access to the side walls and very limited access to the tank bottom. The tanks contain 750,000 to 1.3 million gallons of waste and are buried or backfilled with soil. The tanks are 75'-85' in diameter and 24'-33' from tank bottom to the tank roof. Inspection of the HLW tanks is made difficult by radiation, contamination, and small access openings. Through the years these challenges have been overcome by progressive improvements to programs and equipment resulting in the sophisticated wall crawler Ultrasonic Testing (UT) technology of today. A formal inspection program was developed and put in service in 1972. UT thickness measurements were first made in 1967 and 1969 of selected waste tanks using an analog-type instrument to measure the thickness of the carbon steel walls. Routine inspections for thinning were performed from 1972-1985 and then discontinued because no thinning had been observed and this technique could not detect pitting or cracking. UT inspections resumed in 1994 using a sophisticated robotic wall crawler with UT technology capable of detecting thinning, cracking and pitting. The current program focuses on the newer Type III tanks that are used primarily for storage. The program was upgraded in 2003 to include selected regions of the tank wall, secondary wall and annulus floor on a 7 to 10-year frequency. The facility is currently in its third cycle of tank inspections. Thus far, there have been no reportable indications of service induced degradation. This result provides assurance that the chemistry control program has been effective at mitigating corrosion and that the tanks remain structurally sound even after more than 40 years of service. This paper will present the UT technology first used at SRS and the evolution to the current systems and their capabilities. Additionally, plans for equipment upgrades that will improve the extent of inspection will be discussed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

funcX: Federated Function as a Service for Science

Here, funcX is a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. Unlike centralized FaaS systems, funcX decouples the cloud-hosted management functionality from the edge-hosted execution functionality. funcX's endpoint software can be deployed, by users or administrators, on arbitrary laptops, clouds, clusters, and supercomputers, in effect turning them into function serving systems. funcX's cloud-hosted service provides a single location for registering, sharing, and managing both functions and endpoints. It allows for transparent, secure, and reliable function execution across the federated ecosystem of endpoints-enabling users to route functions to endpoints based on specific needs. funcX uses containers (e.g., Docker, Singularity, and Shifter) to provide common execution environments across endpoints. funcX implements various container management strategies to execute functions with high performance and efficiency on diverse funcX endpoints. funcX also integrates with an in-memory data store and Globus for managing data that may span endpoints. We motivate the need for funcX, present our prototype design and implementation, and demonstrate, via experiments on two supercomputers, that funcX can scale to more than 130000 concurrent workers. We show that funcX's container warming-aware routing algorithm can reduce the completion time for 3,000 functions by up to 61% compared to a randomized algorithm and the in-memory data store can speed up data transfers by up to 3x compared to a shared file system.

97 MATHEMATICS AND COMPUTING↗

Videos and front speeds of frontal ring-opening metathesis polymerization (FROMP) of DCPD/ENB with norbornene-functionalized PDMS comonomers

This dataset contains videos and front speed measurements for 16 frontal ring-opening metastasis polymerization experiments of dicyclopentadiene (DCPD)/5-ethylidene-2-norbornene (ENB) resins and norbornene-functionalized polydimethylsiloxane (nor-PDMS) comonomers. Each run was carried out in a 10 mm diameter glass test tube and recorded to quantify front propagation behavior. Reported front speeds were extracted by video tracking and reported maximum front temperatures were measured with a thermocouple.

Clarke, Brandon R.↗

pvOps v.0.1

This python package contains a series of functions to facilitate fusion of text-based and time series production data collected at photovoltaic sites. The package also contains example datasets and tutorials to help demonstrate how the functions can be used. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1554 O

Gunda, Thushara↗

Rotational memory function of SPC/E water

Memory effects are essential for the dynamics of condensed materials and are responsible for non-exponential relaxation of correlation functions of dynamic variables through the memory function. Memory functions of dipole rotations for water have never been calculated directly from molecular dynamics simulations. We present here calculations of memory functions for single-dipole rotations and for the overall dipole moment of the sample for SPC/E water. The normalized memory functions for single-particle and collective dipole dynamics turn out to be nearly identical. This result validates theories of dielectric spectroscopy in terms of single-particle time correlation functions and the connection between the collective and single-particle relaxation times through the Kirkwood factor. The dielectric function in this formalism contains no new dynamic information that does not exist in the single-dipole correlation function. A short memory time, ≲1 fs, justifies the use of the mathematics of rotational diffusion to describe the dynamics of a single molecular dipole moment in bulk water. Here, an analytical equation for the rotational memory time is derived.

Asthagiri, Dilipkumar N. [Oak Ridge National Labor↗

Putting error bars on density functional theory dataset

This dataset contains submission files and raw output files from high-throughput DFT simulations to analyze the systemic errors in lattice constant, bulk moduli and formation energy predictions for a range of binary and ternary oxides using four exchange correlation functionals (LDA, PBE, PBEsol and vdW-DF-C09). This data was then used as the basis for employing materials informatics methods to predict the expected errors in the lattice constants of the studied compounds. Predicted errors were also used to better the DFT-predicted lattice parameters. Our results emphasize the link between the computed errors and the electron density and hybridization errors of a functional. In essence, these results provide “error bars” for choosing a functional for the creation of high-accuracy, high-throughput datasets as well as avenues for the development of XC functionals with enhanced performance, thereby enabling the accelerated discovery and design of new materials.

36 MATERIALS SCIENCE↗

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *

Abstract Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The experimental data sets contain signatures of long-range phenomena such as physical order parameter fields, polarization, and strain gradients in STEM, or standing electronic waves and carrier-mediated exchange interactions in STM, all superimposed onto scanning system distortions and gradual changes of contrast due to drift and/or mis-tilt effects. Correspondingly, while the human eye can readily identify certain patterns in the images such as lattice periodicities, repeating structural elements, or microstructures, their automatic extraction and classification are highly non-trivial and universal pathways to accomplish such analyses are absent. We pose that the most distinctive elements of the patterns observed in STM and (S)TEM images are similarity and (almost-) periodicity, behaviors stemming directly from the parsimony of elementary atomic structures, superimposed on the gradual changes reflective of order parameter distributions. However, the discovery of these elements via global Fourier methods is non-trivial due to variability and lack of ideal discrete translation symmetry. To address this problem, we explore the shift-invariant variational autoencoders (shift-VAEs) that allow disentangling characteristic repeating features in the images, their variations, and shifts that inevitably occur when randomly sampling the image space. Shift-VAEs balance the uncertainty in the position of the object of interest with the uncertainty in shape reconstruction. This approach is illustrated for model 1D data, and further extended to synthetic and experimental STM and STEM 2D data. We further introduce an approach for training shift-VAEs that allows finding the latent variables that comport to known physical behavior. In this specific case, the condition is that the latent variable maps should be smooth on the length scale of the atomic lattice (as expected for physical order parameters), but other conditions can be imposed. The opportunities and limitations of the shift VAE analysis for pattern discovery are elucidated.

97 MATHEMATICS AND COMPUTING↗

Amplitudes, supersymmetric black hole scattering at $\mathcal{O}\left({G}^5\right)$, and loop integration

We compute the potential-graviton contribution to the scattering amplitude, the radial action, and the scattering angle of two extremal black holes in $\mathcal{N}$ = 8 supergravity at the fifth post-Minkowskian order and to next-to-leading order in a large mass expansion (first self-force order). Properties of classical unitarity cuts allow us to focus on the integration-by-parts reduction of planar integrals, while nonplanar integrals at this order are obtained from the planar ones by straightforward manipulations. We present the solution to the differential equations for all master integrals necessary to evaluate the classical scattering amplitudes of massive scalar particles at this order in all gravitational theories, in particular in $\mathcal{N}$ = 8 supergravity, and in general relativity. Despite the appearance of higher-weight generalized polylogarithms and elliptic functions in the solution to the differential equation for master integrals, the final supergravity answer is remarkably simple and contains only (harmonic) polylogarithmic functions up to weight 2. The systematic analysis of elliptic integrals discussed here, as well as the particular organization of boundary integrals in $\mathcal{N}$ = 8 observables are independent of supersymmetry and may have wider applications, including to aspects of collider physics.

Black Holes↗

Composites of functional polymers: Toward physical intelligence using flexible and soft materials

Abstract Materials that can assist with perception and responsivity of an engineered machine are said to promote physical intelligence. Physical intelligence may be important for flexible and soft materials that will be used in applications like soft robotics, wearable computers, and healthcare. These applications require stimuli responsivity, sensing, and actuation that allow a machine to perceive and react to its environment. The development of materials that exhibit some form of physical intelligence has relied on functional polymers and composites that contain these polymers. This review will focus on composites of functional polymers that display physical intelligence by assisting with perception, responsivity, or by off-loading computation. Composites of liquid crystal elastomers, shape-memory polymers, hydrogels, self-healing materials, and transient materials and their functionalities are examined with a viewpoint that considers physical intelligence. Graphic Abstract

36 MATERIALS SCIENCE↗

Designer molecules of the synaptic organizer MDGA1 reveal 3D conformational control of biological function

MDGAs (MAM domain-containing glycosylphosphatidylinositol anchors) are synaptic cell surface molecules that regulate the formation of trans-synaptic bridges between neurexins (NRXNs) and neuroligins (NLGNs), which promote synaptic development. Mutations in MDGAs are implicated in various neuropsychiatric diseases. MDGAs bind NLGNs in cis on the postsynaptic membrane and physically block NLGNs from binding to NRXNs. In crystal structures, the six immunoglobulin (Ig) and single fibronectin III domains of MDGA1 reveal a striking compact, triangular shape, both alone and in complex with NLGNs. Whether this unusual domain arrangement is required for biological function or other arrangements occur with different functional outcomes is unknown. Here, we show that WT MDGA1 can adopt both compact and extended 3D conformations that bind NLGN2. Designer mutants targeting strategic molecular elbows in MDGA1 alter the distribution of 3D conformations while leaving the binding affinity between soluble ectodomains of MDGA1 and NLGN2 intact. In contrast, in a cellular context, these mutants result in unique combinations of functional consequences, including altered binding to NLGN2, decreased capacity to conceal NLGN2 from NRXN1β, and/or suppressed NLGN2-mediated inhibitory presynaptic differentiation, despite the mutations being located far from the MDGA1-NLGN2 interaction site. Thus, the 3D conformation of the entire MDGA1 ectodomain appears critical for its function, and its NLGN-binding site on Ig1-Ig2 is not independent of the rest of the molecule. As a result, global 3D conformational changes to the MDGA1 ectodomain via strategic elbows may form a molecular mechanism to regulate MDGA1 action within the synaptic cleft.

MDGAs↗

Copper-dependent halogenase catalyses unactivated C−H bond functionalization

Carbon–hydrogen (C–H) bonds are the foundation of essentially every organic molecule, making them an ideal place to do chemical synthesis. The key challenge is achieving selectivity for one particular C(sp 3 )−H bond. In recent years, metalloenzymes have been found to perform C(sp 3 )−H bond functionalization. Despite substantial progresses in the past two decades, enzymatic halogenation and pseudohalogenation of unactivated C(sp 3 )−H—providing a functional handle for further modification—have been achieved with only non-haem iron/α-ketoglutarate-dependent halogenases, and are therefore limited by the chemistry possible with these enzymes. Here, in this work, we report the discovery and characterization of a previously unknown halogenase ApnU, part of a protein family containing domain of unknown function 3328 (DUF3328). ApnU uses copper in its active site to catalyse iterative chlorinations on multiple unactivated C(sp 3 )−H bonds. By taking advantage of the softer copper centre, we demonstrate that ApnU can catalyse unprecedented enzymatic C(sp 3 )−H bond functionalization such as iodination and thiocyanation. Using biochemical characterization and proteomics analysis, we identified the functional oligomeric state of ApnU as a covalently linked homodimer, which contains three essential pairs—one interchain and two intrachain—of disulfide bonds. The metal-coordination active site in ApnU consists of binuclear type II copper centres, as revealed by electron paramagnetic resonance spectroscopy. This discovery expands the enzymatic capability of C(sp 3 )−H halogenases and provides a foundational understanding of this family of binuclear copper-dependent oxidative enzymes.

biocatalysis↗

sparse_bias

This is a python package used to fit an unknown function from data that potential contains systematic biases related to metadata. The model fits the unknown function and uses a Bayesian horseshoe prior model to impose sparsity on the bias terms. This code has been generalized from research code developed for AIACHNE into a package that should have more general application in a wider class of statistical models.

Walton, Noah↗

Evaluating the Physisorption and Chemisorption of Iodine on Bismuth-Functionalized Carbon Foams

Bismuth-containing carbon materials have been shown to be highly promising sorbents for the capture of radioiodine. However, there is still a need to understand the effects of carbon and bismuth on the iodine sorption mechanism. In this study, we show the relationship between the physical and chemical sorption of iodine under different bismuth loading conditions. Here, highly porous and non-friable conductive carbon foams were prepared and bismuth was electrodeposited to provide strong iodine binding sites. For pure carbon foams, equal ratios of physisorbed and chemisorbed iodine-carbon phases were detected before desorption. As the concentration of bismuth increased, the chemisorption between bismuth and iodine dominated the total capture mechanism and physisorption was almost completely eliminated. Additionally, chemisorption of iodine depended upon the size and specific surface area of the bismuth particles present within the framework of the foam.

36 MATERIALS SCIENCE↗

De novo design of protein homodimers containing tunable symmetric protein pockets

Function follows form in biology, and the binding of small molecules requires proteins with pockets that match the shape of the ligand. For design of binding to symmetric ligands, protein homo-oligomers with matching symmetry are advantageous as each protein subunit can make identical interactions with the ligand. Here, we describe a general approach to designing hyperstable C2 symmetric proteins with pockets of diverse size and shape. We first designed repeat proteins that sample a continuum of curvatures but have low helical rise, then docked these into C2 symmetric homodimers to generate an extensive range of C2 symmetric cavities. We used this approach to design thousands of C2 symmetric homodimers, and characterized 101 of them experimentally. Of these, the geometry of 31 were confirmed by small angle X-ray scattering and 2 were shown by crystallographic analyses to be in close agreement with the computational design models. These scaffolds provide a rich set of starting points for binding a wide range of C2 symmetric compounds.

59 BASIC BIOLOGICAL SCIENCES↗

HT Model Dataset

This website contains the dataset that was used for writing the manuscript "HT Model: Using the Molecular Transformer for predicting hydrotreating reactions" (PNNL-SA-186589) The dataset includes a collection of hydrotreating reactions compiled from 41 peer-reviewed literature sources. These sources contain experimental data related to hydrotreating reactions. These reactions involve the reaction of chemical compounds with hydrogen gas in the presence of a catalyst to remove heteroatoms or to convert specific functional groups. The dataset contains reactions both with and without reaction conditions. Reaction conditions refer to the specific parameters under which the reaction takes place, such as temperature and pressure. For each reaction, the dataset includes both SMILES and SELFIES representations. SMILES (Simplified Molecular Input Line Entry System) and SELFIES (SELF-referencIng Embedded Strings) are two popular notations used to represent chemical structures in a compact and standardized format. The dataset was created with the aim of training a predictive model, specifically using the Molecular Transformer architecture.

bioprocessing, hydrotreating, deep learning algori↗

Phosphonium-Based Polyzwitterions: Influence of Ionic Structure and Association on Mechanical Properties

This manuscript describes a synthetic strategy and structure–property investigation of unprecedented phosphonium-based zwitterionic homopolymers (polyzwitterions) and random copolymers (zwitterionomers). Free radical polymerization of 4-(diphenylphosphino)styrene (DPPS) provided neutral polymers containing reactive triarylphosphines. Quantitative postpolymerization alkylation of these pendant functionalities generated a library of polymers containing various concentrations of neutral phosphines, phosphonium ions, and phosphonium sulfobetaine zwitterions. The zwitterionic homo- and copolymers exhibited significantly higher glass transition temperatures (T g ) and enhanced mechanical reinforcement in comparison to neutral and phosphonium analogues. These changes in T g and mechanical properties were attributed to nanoscale morphological domains, which formed due to electrostatic interactions between zwitterionic groups, as revealed by X-ray scattering and broadband dielectric spectroscopy (BDS). BDS revealed increased static dielectric constants (>25) for the phosphonium zwitterionomers compared to ionomeric or neutral analogues. These high static dielectric constants for the solvent-free polyzwitterions supported their stronger polarization response in comparison with polymers containing neutral phosphines and phosphonium ions, and these interactions accounted for morphological differences and enhanced mechanical behavior. This work describes a versatile strategy for modulating electrostatic interactions with tunable mechanical properties for an unprecedented family of zwitterionic polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules

The soil microbiome is an invaluable component of the biosphere and critical for ecosystem functions, including biogeochemical cycling, soil-atmosphere gas exchange, degradation of toxic compounds, and promotion of plant growth and stress resistance/resilience. An improved understanding of the soil microbiome will help with predicting how these processes respond to external perturbations, and with harnessing beneficial aspects of the soil microbiome for agronomic applications such as crop amendments. However, the extensive taxonomic and functional diversity inherent within the soil microbiome hinders efficient analysis of this system. Microbial biodiversity in soils is orders of magnitude greater than other commonly studied systems such as the human gut microbiome (Blum, Zechmeister-Boltenstern, and Keiblinger 2019; Berendsen, Pieterse, and Bakker 2012). Thousands of microbial taxa may be found in a single gram of soil (Roesch et al. 2007), and high rates of gene flow and mutation further promote microbial diversification (Sergaki et al. 2018). Concomitantly, functional diversity in soil is similarly extensive. Soil is a heterogeneous mixture of microenvironments with defined physical and chemical attributes (Bach et al. 2018), within which numerous microbial guilds of distinct life-strategies and metabolic capacities can be found (Perez-Garcia, Lear, and Singhal 2016; H.-S. Song et al. 2014). Furthermore, the soil microbiome harbors a significant fraction of rare and/or quiescent members (Blagodatskaya and Kuzyakov 2013) that exist below the threshold of detection of current technologies. Such rare taxa may make significant contributions to process rates (Shade and Gilbert 2015; Dawson et al. 2017), but their scarcity complicates their identification and analysis. Finally, the vast amounts of information generated through holistic analyses of soil communities represent an intense computational burden (Scholz, Lo, and Chain 2012; Prosser 2015) that precludes assessment of the complete functional and taxonomic diversity contained in this ecosystem.

Naylor, Dan T.↗