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At least 1,711 records · Page 95

Biogeochemical controls on iron speciation and cycling across upland to shoreline gradients in freshwater and estuarine coastal soils (Lake Erie and Chesapeake Bay, United States)

Coastal environments are dynamic interfaces that mediate carbon and nutrient exchanges between terrestrial landscapes and open waters, and understanding the biogeochemical factors controlling these exchanges, particularly iron (Fe) redox transformations, is crucial for predicting coastal ecosystem functions. Here, we investigated the mechanisms controlling Fe speciation changes across upland-to-shoreline gradients in freshwater and estuarine soils using Fe K-edge X-ray absorption spectroscopy, solid and porewater composition analysis, and 16S rRNA sequencing analysis. We show that Fe transformations depend primarily on inundation patterns. In unsaturated uplands, Fe occurs as Fe(III) oxyhydroxides, mainly goethite (9–35 %), Fe(II,III)-phyllosilicates (39–89 %), and Fe(III)-organic species (0–61 %). Soils influenced by estuarine waters exhibit porewater sulfide concentrations reaching up to 221 μM, Fe- and S-cycling bacteria, and up to 81 % pyrite (FeS 2 ), indicating that sulfur-driven redox dynamics control Fe transformations. In lacustrine wetlands, Fe(III) reduction is indicated by porewater Fe(II) concentrations increasing to 1.0–2.1 mM, and ~10–15 % of Fe as Fe(II,III)-(hydr)oxides (green rust), vivianite (Fe 3 (PO 4 ) 2 ·8H 2 O), and/or adsorbed Fe(II) species. EXAFS data also indicate reduction of structural Fe(III) to Fe(II) in phyllosilicates. The presence of Fe- and S-cycling bacteria, as well as sulfide (0–10 μM), suggests that Fe-cycling is microbially driven and potentially coupled with cryptic S-cycling. Fe(II) oxidation was indicated above/near the water table by the presence of Fe(III) oxyhydroxides (ferrihydrite, lepidocrocite). Furthermore, negligible Fe(III) or sulfate reduction was observed at some water-saturated sites located at the upland-wetland transition, likely due to oxic (sub-)surface water inputs. Overall, our results highlight the importance of considering both Fe-speciation and hydro-biogeochemical dynamics when predicting Fe-cycling at coastal interfaces.

54 ENVIRONMENTAL SCIENCES↗

Heterolytic Hydrogen Activation: Understanding Support Effects in Water–Gas Shift, Hydrodeoxygenation, and CO Oxidation Catalysis

Identifying the role of oxide supports in transition metal catalysis is critical toward our understanding of heterogeneous catalysis. The water-gas shift (WGS) reaction is a prototypical example where oxide support dictates catalytic activity, yet the cause for this remains uncertain. Herein, we show that a single descriptor—the equilibrium constant for hydroxyl formation—relates the WGS turnover frequency across disparate oxide supports. The dissimilar equilibrium constant, or oxophilicity, between early and late transition metals exemplify the utility of metal-support interfacial sites to circumvent adsorption-energy scaling restrictions, thereby providing bifunctional gains for the WGS reaction class. In relation, the equilibrium constant for hydroxyl formation is equivalent to the equilibrium constant for the formal heterolytic dissociation of hydrogen, and therefore, reflects the ability of the metal-support interface to participate in hydrogen heterolysis. The ubiquitous coexistence, yet divergent chemical behavior of homo- and heterolytically activated hydrogen renders oxide support identity central toward our understanding of hydrogenation catalysis. This work was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences and performed at the Environmental Molecular Sciences Laboratory in (EMSL), which is a DOE Office of Science User Facility located at the Pacific Northwest National Laboratory (PNNL). PNNL is a multiprogram national laboratory operated for DOE by Battelle. Computational resources were provided by a user proposal at the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility. N.N. would like to thank Oliver Y. Gutierrez for critical feedback during the final stage of manuscript preparation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sirepo : an open-source cloud-based software interface for X-ray source and optics simulations

Sirepo , a browser-based GUI for X-ray source and optics simulations, is presented. Such calculations can be performed using SRW ( Synchrotron Radiation Workshop ), which is a physical optics computer code, allowing simulation of entire experimental beamlines using the concept of a `virtual beamline' with accurate treatment of synchrotron radiation generation and propagation through the X-ray optical system. SRW is interfaced with Sirepo by means of a Python application programming interface. Sirepo supports most of the optical elements currently used at beamlines, including recent developments in SRW . In particular, support is provided for the simulation of state-of-the-art X-ray beamlines, exploiting the high coherence and brightness of modern light source facilities. New scientific visualization and reporting capabilities have been recently implemented within Sirepo , as well as automatic determination of electron beam and undulator parameters. Publicly available community databases can be dynamically queried for error-free access to material characteristics. These computational tools can be used for the development and commissioning of new X-ray beamlines and for testing feasibility and optimization of experiments. The same interface can guide simulation on a local computer, a remote server or a high-performance cluster. Sirepo is available online and also within the NSLS-II firewall, with a growing number of users at other light source facilities. Our open source code is available on GitHub.

99 GENERAL AND MISCELLANEOUS↗

Singularity-EOS: Performance Portable Equations of State and Mixed Cell Closures

We present Singularity-EOS, a new performance-portable library for equations of state and related capabilities. Singularity-EOS provides a large set of analytic equations of state, such as the Gruneisen equation of state, and tabulated equation of state data under a unified interface. It also provides support capabilities around these equations of state, such as Python wrappers, solvers for finding pressure-temperature equilibrium between multiple equations of state, and a unique modifier framework, allowing the user to transform a base equation of state, for example by shifting or scaling the specific internal energy. All capabilities are performance portable, meaning they compile and run on both CPU and GPU for a wide variety of architectures.

97 MATHEMATICS AND COMPUTING↗

Data Evaluation of Actinide Cross Sections: 238 Pu, 237 Pu, and 236 Pu

This report documents the recent evaluation of the 236 Pu, 237 Pu, and 238 Pu cross section sets. Nuclear data evaluation is the fundamental interface that takes measured nuclear cross section data and turns them into a continuous curve that 1) is consistent with other measurements and nuclear reaction theory/models, and 2) is required by down-stream users. All experiments that generate nuclear data need to include an evaluation step for their data to be broadly useful to the end users.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE BSSD Performance Management Metrics Report Q1

Microbes play key roles in our biosphere, from driving global nutrient cycling to impacting plant, animal and human health and disease. Complex data from microbial genomes, proteins, and metabolites provide a window into these tiny engines that drive life on our planet. Yet these data are dispersed among researchers’ laboratories and various repositories, making it difficult to access. This calls for new ways of managing data, improving data interoperability, advancing community standards, and creating an infrastructure where data are shared efficiently. We have built the National Microbiome Data Collaborative (NMDC) to advance how scientists create, use, and reuse data to redefine the way we understand and harness the power of microbes. The vision of the National Microbiome Data Collaborative (NMDC) is to drive a microbiome data sharing network connecting data, people, and ideas to advance microbiome innovation and discovery. The NMDC was launched in 2019 and brought together DOE National Laboratories to collaborate across resources, capabilities, and expertise. The NMDC team was strategically assembled to include software developers, microbial researchers, metadata experts, and multi-omics specialists. The diversity of the NMDC team reflects the inherently interdisciplinary nature of microbiome science, and we leverage the strengths of the DOE National Laboratory system. Towards BER’s goal of advancing an iterative systems biology approach to the understanding of microbial genomes, the NMDC serves as a foundation for infrastructure, data standards, and community building. Together with the flagship DOE User Facilities, the Joint Genome Institute (JGI) and the Environmental Molecular Sciences Laboratory (EMSL), we are developing core capabilities in metadata standards for environmental descriptors and sample handling and processing; standardized bioinformatic workflows; an interface for data search and access; and robust community engagement activities. The NMDC production platform supports long-term data infrastructure and community building for BER’s bioenergy and environmental research goals. Our approach leverages lessons learned and an ambitious framework for collaborative, interdisciplinary data infrastructure to support microbiome research. The NMDC supports data, information, and knowledge access through three defined software tools – the Submission Portal, NMDC EDGE, and the Data Portal – driven by community needs. Herein, we describe the value proposition for the microbiome research community, our overarching strategy, and challenges and opportunities for developing the NMDC as both an infrastructure and community engagement program.

59 BASIC BIOLOGICAL SCIENCES↗

Turbo-Turtle v0.12.1

A collection of solid body modeling tools for 2D sketched, 2D axisymmetric, and 3D revolved models. It also contains general purpose meshing and image generation utilities appropriate for any model, not just those created with this package. Implemented for Abaqus and Cubit as backend modeling and meshing software. Orginal implementation targeted Abaqus so most options and descriptions use Abaqus modeling concepts and language. Turbo-Turtle makes a best effort to maintain common behaviors and features across each third-party software’s modeling concepts. As much as possible, the work for each subcommand is performed in Python 3 to minimize solution approach duplication in third-party tools. The third-party scripting interface is only accessed when creating the final tool specific objects and output. The tools contained in this project can be expanded to drive other meshing utilities in the future, as needed by the user community. This project derives its name from the origins as a sphere partitioning utility following the turtle shell (or soccer ball) pattern.s.

Brindley, Kyle↗

Binary-level Software Compatibility Tool Agreement

Application Binary Interface (ABI) compatibility is essential for system or software updates to ensure that libraries continue to function. Tools that can assess a binary or library ABI can thus be used to make predictions about compatibility, and predict downstream bugs by informing developers and users about issues. In this work, we are interested in describing a set of well-known tools for assessing ABI, and testing them in a controlled set experiments to assess tool agreement. We run 7660 smaller experiments across tools (N=30,640 total results) to evaluate not only predictions, but also each tool’s ability to provide detail about underlying issues. In this paper, along with highlighting the problem of assessing ABI compatibility and critiquing the pros and cons of currently available tools, we provide guidance to developers interested to test ABI based on our empirical results and suggestions for future work.

ABI↗

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗

Obtaining the solid-liquid interfacial free energy via multi-scheme thermodynamic integration: Ag-ethylene glycol interfaces

The solid-liquid interfacial free energy γ sl is an important quantity in wetting, nucleation, and crystal growth. Although various methods have been developed to calculate γ sl with atomic-scale simulations, such calculations still remain challenging for multi-component interfaces between molecular fluids and solids. In this paper, we present a multi-scheme thermodynamic integration method that is inspired by the “cleaving-wall” method and aimed at obtaining γ sl for such systems using open-source simulation packages. This method advances two aspects of its predecessor methods. First, we incorporate separate schemes to resolve difficulties when manipulating periodic boundary conditions of the supercell using open-source simulation packages. Second, we introduce a numerical approximation to obtain thermodynamic integrands for complex force fields when an analytical differentiation is not readily available. To demonstrate this method, we obtain γ sl for interfaces between Ag(100) and Ag(111) and ethylene glycol (EG). These interfacial free energies mirror interfacial potential energies for each facet. We also estimate entropies of interface formation and these are consistent with theoretical predictions in signs and trends. For the Ag-EG systems, we find that the largest contribution to γ sl is the free energy to create the bare metal surfaces. The second-largest contribution to γ sl is from the liquid-solid interaction. Finally, this user-friendly method will accelerate investigation in a broad range of research topics, such as the thermodynamic effect of structure-directing agents in solution-phase shape-controlled nanocrystal syntheses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

RICH (Robotic Interface Control & Handling) System for VULCAN

High flux neutron beam and high efficiency detectors warrant quick turn arounds of neutron diffraction measurements at the engineering materials diffractometer VULCAN. Efficient change and alignment of samples and automatic measurements at VULCAN are desired for better use of neutron beam time by users. In this work, we aim to develop a proof-of-concept Robotic Interactive Control & Handling System (RICH) for sample handling at VULCAN that could assist high throughput experiments and reduce the overhead time significantly. This was realized by a six-axis desktop robot with trained AI models. The trained AI models can recognize and locate samples in various types of positions in a live video stream. In addition, we developed smart algorithms which used our models on multiple cameras to recognize where samples are with respect to multiple point of views, and then using user-inputted parameters, align them to perform complex measurements.

42 ENGINEERING↗

Verification of RESRAD-OFFSITE Code (V.4)

This report documents the verification of RESRAD-OFFSITE Version 4.0 and describes, where necessary, the verification of the following: • The data comprising the standard dose and risk coefficient libraries in the RESRAD database files Master_dcf_ICRP07.mdb and Master_dcf_2k.mdb. • The extraction and transfer of the data from the selected database file to the computational code by the RESRAD-OFFSITE 4.0 interface, ResOWin.exe. • The different processes that are modeled by the main computational code in RESRAD OFFSITE 4.0, ResOMain.exe. • The data displayed in the graphical and text reports. Many verifications were performed as part of the quality assurance quality control program associated with the development and release of RESRAD-OFFSITE 4.0, namely: • developer testing, • internal independent testing, and • release testing. Some were also performed in response to questions from users regarding the performance of the code. The main text of the report focuses on summarizing a subset of those tests, both independent and developer tests that verified the computations performed by the code. The verifications included in this report served as the basis for the development of the release tests of the computational executables and provided the quantitative results to be compared with the code output. The input and output interfaces and the data transfers between the various executables of the code were tested while performing the verification testing. They were tested intentionally during release testing. This report also provides some basic information to help in understanding the activities that were verified. The report: • outlines the components of RESRAD-OFFSITE 4.0 and the interconnections between these components, • outlines the processes modeled by the computational code, • provides summary figures and tables to offer confirmation of the verification of the computational components of the code, • reproduces the verifiers’ reports, if available, in individual appendices, • refers to the previous verification report (Yu et al. 2011) for more details about some of the verifications, and • reproduces the test cases and the testers’ reports from the release testing in individual appendices, when possible.

54 ENVIRONMENTAL SCIENCES↗

A publicly available PyTorch-$\mathrm{ABAQUS}$ $\mathrm{UMAT}$ deep-learning framework for level-set plasticity

Here this paper introduces a publicly available PyTorch-ABAQUS deep-learning framework of a family of plasticity models where the yield surface is implicitly represented by a scalar-valued function. In particular, our focus is to introduce a practical framework that can be deployed for engineering analysis that employs a user-defined material subroutine (UMAT/VUMAT) for ABAQUS, which is written in FORTRAN. To accomplish this task while leveraging the back-propagation learning algorithm to speed up the neural-network training, we introduce an interface code where the weights and biases of the trained neural networks obtained via the PyTorch library can be automatically converted into a generic FORTRAN code that can be a part of the UMAT/VUMAT algorithm. To enable third-party validation, we purposely make all the data sets, source code used to train the neural-network-based constitutive models, and the trained models available in a public repository. Furthermore, the practicality of the workflow is then further tested on a dataset for anisotropic yield function to showcase the extensibility of the proposed framework. A number of representative numerical experiments are used to examine the accuracy, robustness and reproducibility of the results generated by the neural network models.

36 MATERIALS SCIENCE↗

AnalyzeThat: A Programmable Shared-Memory System for an Array of Processing-In-Memory Devices

Processing In Memory (PIM), the concept of integrating processing directly with memory, has been attracting a lot of attention since PIM can assist in overcoming the throughput limitation caused by data movement between CPU and memory. The challenge, however, is that it requires the programmers to have a deep understanding of the PIM architecture to maximize the benefits such as data locality and parallel thread execution on multiple PIM devices. In this study, we present AnalyzeThat, a programmable shared-memory system for parallel data processing with PIM devices. Thematic to AnalyzeThat is a rich PIM-Aware Data Structure (PADS), which is an encapsulation that integrally ties together the data, the analysis tasks and the runtime needed to interface with the PIM device array. The PADS abstraction provides (i) a key-value data container that allows programmers to easily store data on multiple PIMs, (ii) a suite of parallel operations with which users can easily implement data analysis applications, and (iii) a runtime, hidden to programmers, which provides the mechanisms needed to overlay both the data and the tasks on the PIM device array in an intelligent fashion, based on PIM-specific information collected from the hardware. We have developed a PIM emulation framework called AnalyzeThat. Our experimental evaluation with representative data analytics applications suggests that the proposed system can significantly reduce the PIM programming effort without losing its technology benefits.

97 MATHEMATICS AND COMPUTING↗

Algorithm and Architecture Independent Benchmarking with SEAK

Many applications of high performance embedded computing are limited by performance or power bottlenecks. We have designed the Suite for Embedded Applications & Kernels (SEAK), a new benchmark suite, (a) to capture these bottlenecks in a way that encourages creative solutions; and (b) to facilitate rigorous, objective, end-user evaluation for their solutions. To avoid biasing solutions toward existing algorithms, SEAK benchmarks use a mission-centric (abstracted from a particular algorithm) and goal-oriented (functional) specification. To encourage solutions that are any combination of software or hardware, we use an end-user black-box evaluation that can capture tradeoffs between performance, power, accuracy, size, and weight. The tradeoffs are especially informative for procurement decisions. We call our benchmarks future proof because each mission-centric interface and evaluation remains useful despite shifting algorithmic preferences. It is challenging to create both concise and precise goal-oriented specifications for mission-centric problems. This paper describes the SEAK benchmark suite and presents an evaluation of sample solutions that highlights power and performance tradeoffs.

algorithms and kernels↗

MO-F-CAMPUS-T-02: An Electronic Whiteboard Platform to Manage Treatment Planning Process

Purpose: In an effort to improve patient safety and streamline the radiotherapy treatment planning (TP) process, a software based whiteboard had been developed and put in use in our facility Methods: The electronic whiteboard developed using SQL database (DB) and PHP/JavaScript based web interface, is published via department intranet and login credentials. The DB stores data for each TP process such as patient information, plan type, simulation/start dates, physician, dosimetrist, QA and the current status in planning process. Users interact with the DB per plan and perform status updates in real time as the planning process progresses. All user interactions with the DB are recorded with timestamps so as to calculate statistical information for TP process management such as contouring times, planning and review times, dosimetry, physics and therapist QA times. External beam and brachytherapy plans are categorized according to complexity (ex: IMRT, 3D, HDR, LDR etc) and treatment types and applicators. Each plan category is assigned specific timelines for each planning process. When a plan approaches or passes the predetermined timeline, users are alerted via color coded graphical cues. When certain process items are not completed in time, pre-determined actions are triggered such as a delay in treatment start date. Results: Our institution has been using the electronic whiteboard for two years. Implementation of pre-determined actions based on the statistical information collected by the whiteboard improved our TP process. For example, the average time for normal tissue contouring decreased from 0.73±1.37 to 0.24±0.33 days. The average time for target volume contouring decreased from 3.2±2.84 to 2.37±2.54 days. This increase in efficiency allows more time for quality assurance processes, improving patient safety. Conclusion: The electronic whiteboard has been an invaluable tool for streamlining our TP processes. It facilitates timely and accurate communication between all parties involved in the TP process increasing patient safety.

60 APPLIED LIFE SCIENCES↗

Security Catch and Release Automation Manager (SCRAM) v1.0

This is a security automation tool heavily influenced by the tool written at NCSA https://github.com/ncsa/bhr-site. The tool is a web interface that aims to centralize information on blocking malicious traffic. There is a list of currently blocked traffic, a place for other tools to automatically add traffic they deem malicious, as well as for human users to input blocks. * Logging and auditing, to determine who made what change and when * Automated expiration of changes (e.g. an exception is added for 2 weeks, after which time it will be removed) * Validation of changes and verification that the change has been applied * Fine-grained role-based access

Oehlert, Samuel↗

BioC2G Tool v1

The BioC2G tool provides an interface for running technoeconomic analyses and life-cycle assessments of biofuel and bioproduct production pathways. Models for the pathways are currently built into the tool: limonene, limonane, bisabolene, bisabolane, ethanol, isoprenol, DMCO, and HEFA. Additionally, a "Custom" option is available for analyzing a bioproduction pathway not included among the built-in examples. Users must supply key product properties and process parameters. Three types of model runs are available in the tool: minimum selling price (MSP), water consumption, and greenhouse gas (GHG) emissions. Running the MSP model yields a breakdown of MSP by major process stage of production, along with a a table of estimated capital expenditures (CAPEX) and annual operating expenditures (OPEX). Running the water consumption and GHG models yields a breakdown of water consumed and carbon emissions respectively, per unit of end product. A breakdown of these metrics by major process stage is also provided. Model run results can be viewed in the web interface numerically and graphically, as well as downloaded in CSV format. Detailed documentation on model methodology and assumptions is also available for download.

Huntington, Tyler↗