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At least 595 records · Page 33

Emergent multiferroism with magnetodielectric coupling in EuTiO 3 created by a negative pressure control of strong spin-phonon coupling

Negative pressure has emerged as a powerful tool to tailor the physical properties of functional materials. However, a negative pressure control of spin-phonon coupling for engineering magnetism and multiferroicity has not been explored to date. Here, using uniform three-dimensional strain-induced negative pressure in nanocomposite films of (EuTiO 3 ) 0.5 :(MgO) 0.5 , we demonstrate an emergent multiferroicity with magnetodielectric coupling in EuTiO 3 , matching exactly with density functional theory calculations. Density functional theory calculations are further used to explore the underlying physics of antiferromagnetic-paraelectric to ferromagnetic-ferroelectric phase transitions, the spin-phonon coupling, and its correlation with negative pressures. The observation of magnetodielectric coupling in the EuTiO 3 reveals that an enhanced spin-phonon coupling originates from a negative pressure induced by uniform three-dimensional strain. Our work provides a route to creating multiferroicity and magnetoelectric coupling in single-phase oxides using a negative pressure approach.

36 MATERIALS SCIENCE↗

A Python Instrument Control and Data Acquisition Suite for Reproducible Research

Tools that standardize and automate experimental data collection are needed for greater confidence in research results. The National Synchrotron Light Source-II (NSLS-II) has generated an open-source Python data acquisition, management, and analysis software suite that automates X-ray experiments and collects an experimental record that facilitates complete reproducibility. Here, we show that the NSLS-II tools are not only useful for X-ray science at large-scale facilities by presenting an add-on package that adapts these tools for use in a small laboratory with common physics and electrical engineering instruments. The composite software suite eases and automates the execution of experiments, records extensive metadata, stores data in portable containers, and speeds up the analysis through tools for comprehensive searches. In total, this software suite increases the reproducibility of laboratory experiments. We demonstrate the software via the evaluation of two lock-in amplifiers-the miniature ADA2200 and the ubiquitous Stanford Research Systems (SRS) SR810. The frequency resolution, signal-to-noise ratio, and dynamic reserve of the lock-in amplifiers are measured and presented. The usage of the software suite is described throughout these measurements so that the reader can implement the tools in their lab.

97 MATHEMATICS AND COMPUTING↗

Accounting for hydrological and microbial processes on greenhouse gas budgets from river systems (Final Report)

River systems have a disproportionately large impact on carbon and nitrogen cycling on this planet. For instance, despite their much smaller size in area, it is estimated that global carbon dioxide emission from river systems exceed the emission from lakes and reservoirs, and are on par with the estimated oceanic and land carbon sinks. Closing carbon and nitrogen budgets in river systems requires knowledge of end member greenhouse gas (GHG) products (e.g. carbon dioxide, nitrous oxide, methane), which typically have not been measured in river systems. Moreover, while the production of these gasses is thought to be microbially derived, little is known about microbial activities in sediments of large rivers, despite their potentially high influence on biogeochemical budgets. Typically, when we think of rivers we visualize the channels that carve through the earth, but this only represents a small part of the hydrologic exchange that a river participates in. Rivers are more than conduits; they are dynamically exchanging water and materials with surrounding terrestrial and subsurface environments. In fact, 96% of the carbon dioxide produced within river systems occurs in hyporheic zones, or sediment regions beneath and alongside a river where groundwater and river water mix. In fact, it is widely recognized that microbial processes in hyporheic zones, also known as the river’s liver, strongly influence the fate of carbon, nutrients, and contaminants transported through watersheds. Despite this general knowledge, observational studies linking nitrogen and carbon gas production to microbial activity, and studies of overall gas emissions, are limited across river systems, but especially absent from larger rivers. To identify microbial processes responsible for GHG emissions from large rivers, and to quantify their environmental drivers and dependencies, we selected the Columbia River as a representative field site. This is the largest river west of the North American Continental Divide, and produces a drainage and discharge roughly double of the Nile in Egypt. This river is also an important source for agricultural irrigation and generates more hydroelectric power than any other North American river. Dams manage the release of water in the river, with these changes in river discharge patterns strongly impacting microbial activities in hyporheic zones. Specifically, we target a region down-river from the Priest Rapids Dam (WA) associated with the PNNL SFA, where water discharge from the dam is highly controlled, resulting in 1.5 m fluctuations in river stage daily. This dynamic river stage creates an ideal research opportunity for investigating hydrological perturbations in GHG production, uptake, and emission from large river systems. In this exploratory 1-year project, we conducted data-driven field research to provide observations needed to support predictions about GHG flux from river ecosystems. Using porewater dialysis and surface flux measurements, we observed where and when GHGs were produced and is the emission impacted by river stage. Using meta-omics tools, we determined what microbial processes control production and consumption of GHG in these systems. Finally, we provided key observations to parameterize models that could predict the effect of environmental conditions on GHG emission in the Columbia River near shore environment, at the scale that the modeled processes operate. Closing knowledge gaps in the linkages between river stage, microbial processes, and GHG production and emission, as well as the spatial distribution and ecosystem dependencies of these processes, is necessary to better parameterize land surface models. We provide some of the first, detailed GHG measurements paired microbial activity from large river systems. Our findings have direct relevance to many other large rivers with flows altered by hydroelectric energy, reservoirs, snowmelt, tides, or agriculture.

54 ENVIRONMENTAL SCIENCES↗

Evolution of the ATLAS TDAQ online software framework towards Phase-II upgrade: Use of Kubernetes as an orchestrator of the ATLAS Event Filter computing farm

The ATLAS experiment at the LHC at CERN continuously evolves its TDAQ system to meet the challenges of new physics goals and technological advancements. As ATLAS prepares for the Phase-II Run 4 of the LHC, significant enhancements in the TDAQ Controls and Configuration (TDAQ-CC) tools have been designed to ensure efficient data collection, processing, and management. This abstract presents the evolution of ATLAS TDAQ-CC system leading up to Phase-II Run 4. As part of the evolution towards Phase-II, Kubernetes has been chosen to orchestrate the Event Filter (EF) farm. By leveraging Kubernetes, ATLAS can dynamically allocate computing resources, scale processing capacity in response to changing data taking conditions and ensure high availability of data processing services. The integration of the Kubernetes with the TDAQ Run Control framework enables perfect synchronisation between the experiment’s data acquisition components and the computing infrastructure. We will discuss the architectural considerations and implementation challenges involved in Kubernetes integration with the ATLAS TDAQ-CC system. We will highlight the benefits of using Kubernetes as an EF farm orchestrator, including improved resource utilization, enhanced fault tolerance, and simplified deployment and management of data processing workflows. In addition, we will report on the extensive testing of Kubernetes that was conducted using a farm of 2500 servers within the experiment data taking environment, demonstrating its scalability and robustness in handling the demands of the ATLAS TDAQ system for Phase-II. The adoption of Kubernetes represents a significant step forward in the evolution of ATLAS TDAQ-CC system, aligning with industry best practices in container orchestration.

Corso Radu, Alina [Univ. of California, Irvine, CA↗

Robotic Crane System for the Deconstruction of Chernobyl Unit 4 - 18583

The Chernobyl Nuclear Power Plant (ChNPP) Unit 4 accident occurred on April 26, 1986 leaving a severely damaged reactor building and a highly radioactive area. To minimize the long-term radiological impact to personnel and the environment, Unit 4 was immediately enclosed by a structure named the Object Shelter (OS). To transform the OS into an ecologically safe system, the Shelter Implementation Plan (SIP) was developed in 1997. The most significant SIP tasks was the design and construction of the New Safe Confinement (NSC). The NSC is a 36,000 tonne arch enclosure that includes a suite of process equipment to address the ruins of Unit 4 while assuring the safety of workers, public, and the environment. The NSC has a span of 257 meters, length of 164 meters, and height of 110 meters and is designed for a 100 years life. The New Safe Confinement was slid from its erection area to directly over Unit 4 (a distance of 327 meters) in November 2016. One of the major mechanical handling systems installed in the NSC is the Main Cranes System (MCS), designed and fabricated by PaR Systems (USA). The planned deconstruction activities require the handling of shielded waste disposal casks containing fuel as well as transporting extremely large structural elements -remotely controlled using video surveillance equipment. The lifting activities required the cranes to be tele-robotically controlled to prevent inadvertent collisions, expedite repetitive and high accuracy functions, protect the equipment and structures within the NSC as well as increase the overall effectiveness of the MCS. In addition, due to the elevated radiation levels, remote deconstruction activities will need to be performed. The MCS has design provisions included for a tele-robotically controlled manipulator and a suite of tooling to be used for multiple activities including concrete coring, cutting, debris collection and other heavy demolition activities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Quantification of cerivastatin toxicity supports organismal performance assays as an effective tool during pharmaceutical safety assessment

A major problem in pharmaceutical development is that adverse effects remain undetected during preclinical and clinical trials, but are later revealed after market release when prescribed to many patients. We have developed a fitness assay known as the organismal performance assay (OPA), which evaluates individual performance by utilizing outbred wild mice ( Mus musculus ) that are assigned to an exposed or control group, which compete against each other for resources within semi-natural enclosures. Performance measurements included reproductive success, survival, and male competitive ability. Our aim was to utilize cerivastatin (Baycol ® , Bayer), a pharmaceutical with known adverse effects, as a positive control to assess OPAs as a potential tool for evaluating the safety of compounds during preclinical trials. Mice were exposed to cerivastatin (~4.5 mg/kg/day) into early adulthood. Exposure ceased and animals were released into semi-natural enclosures. Within enclosures, cerivastatin-exposed females had 25% fewer offspring and cerivastatin-exposed males had 10% less body mass, occupied 63% fewer territories, sired 41% fewer offspring, and experienced a threefold increase in mortality when compared to controls. OPAs detected several cerivastatin-nduced adverse effects indicating that fitness assays, commonly used in ecology and evolutionary biology, could be useful as an additional tool in safety testing during pharmaceutical development.

59 BASIC BIOLOGICAL SCIENCES↗

Operability and control in process intensification and modular design: Challenges and opportunities

Abstract In this article, the importance of considering operability and control criteria in the analysis and design of intensified and modular processes is discussed. We first analyze the impact on operability of key factors including: (i) degrees of freedom, (ii) process constraints, (iii) numbering up vs. scaling up, and (iv) dynamic/periodic operation. Comparative examples are presented to showcase the pros and cons in intensified/modular systems vs. their conventional counterparts from operability and control aspects. Then we look into metrics and tools to address these challenges such as: (i) flexibility analysis, (ii) operability‐based design, and (iii) advanced model‐based control. Considering different conceptual design stages as synthesis intensification, steady‐state design, and dynamic operational optimization, we highlight the need to incorporate different levels of operability considerations. Future research opportunities and perspectives are also identified, particularly emphasizing the importance of a holistic strategy for integrated design, operability, and control of intensified and modular process systems.

Pistikopoulos, Efstratios N.↗

Software Requirements for a Consequence Management Sample Data Simulator for Training and Drills

This document describes the requirements for a software tool that will enable FRMAC to simulate large sets of sample result data that is based realistically on simulated radionuclide deposition grids from NARAC. The user of this tool would be scientists involved in exercise and drill planning or part of the simulation cell of an exercise controller team. A key requirement is that this tool must be able to be run with a reasonable amount of training and job aids by any person within the Assessment, Laboratory Analysis, or Monitoring and Sampling divisions of the FRMAC to support any level of exercise from the small IPX to the national level full scale exercise. This tool should be relatively lean and stand-alone so that the user can run it in the field with limited IT resources. This document will describe the desired architecture, design characteristics, order of operations, and algorithms that can be given to a software development team to assist them in project scoping, costing, and eventually, development.

61 RADIATION PROTECTION AND DOSIMETRY↗

Resultant Cutting Trajectories on Machine Tools with Raster Tool Motion

The formation of the resultant raster trajectories in machine tools are established on the basis of Lissajous figures, taking account of additional workpiece motion for finishing purposes. Kinematic and geometric formulas are obtained for the relative tool and workpiece trajectory with strict kinematic coupling. These formulas are required in practice for abrasive lapping. They permit control of the resultant abrasive-cutting trajectory in finishing the precision planes of the workpiece.

42 ENGINEERING↗

Development of Computational Approaches for Simulation and Advanced Controls for Hybrid Combustion-Gasification Chemical Looping

This document provides the results of the project through September 2009. The Phase I project has recently been extended from September 2009 to March 2011. The project extension will begin work on Chemical Looping (CL) Prototype modeling and advanced control design exploration in preparation for a scale-up phase. The results to date include: successful development of dual loop chemical looping process models and dynamic simulation software tools, development and test of several advanced control concepts and applications for Chemical Looping transport control and investigation of several sensor concepts and establishment of two feasible sensor candidates recommended for further prototype development and controls integration. There are three sections in this summary and conclusions. Section 1 presents the project scope and objectives. Section 2 highlights the detailed accomplishments by project task area. Section 3 provides conclusions to date and recommendations for future work.

20 FOSSIL-FUELED POWER PLANTS↗

Additively Manufactured Photovoltaic Inverter (AMPVI)

Successful integration of hundreds of gigawatts of solar photovoltaics (PV) into the electric power system requires transformative power conversion system design that optimizes various trade-offs among conflicting objectives, such as performance, reliability, functionality, and cost. To address this need, National Renewable Energy Laboratory, Oak Ridge National Laboratory, and Purdue University teamed up to develop a unique PV inverter design. The Additively Manufactured Photovoltaic Inverter (AMPVI) combines newer wide bandgap high-voltage silicon carbide (SiC) semiconductor devices with revolutionary concepts such as additive manufacturing and multi-objective magnetic design optimization. The AMPVI will not only provide superior technical capabilities in terms of energy conversion but also mitigate market barriers for SiC-based PV inverters. The benefits for this design will include better utilization of PV power due to higher DC voltage, lower operations and maintenance costs, better system efficiency, longer system lifetime, and advanced grid support functionalities for easier grid integration. All these advantages will lead to a significant reduction of the levelized cost of energy for PV systems. Activities in Budget Period 1 (BP1) of this 3-year integrated project were focused on development and component-level validation of the foundational building blocks needed for the AMPVI. Multiple interrelated tasks were completed in parallel during work towards the initial development of the high-voltage SiC-based power block, gate driver, controller board, and control algorithms. Initial development of magnetic design tools and initial inverter thermal and mechanical design was also completed in this period. All these activities ensured that the initial prototype (called “alpha-prototype”) power block and controller would be ready after BP1 for integration into the first inverter prototype (i.e., the alpha-prototype inverter) in BP2.

14 SOLAR ENERGY↗

A Suite of Mechanistic Epidemiological Decision Support Tools

Objective: We will demonstrate tools that allow mechanistic contraints on disease progression and epidemic spread to play off against interventions, mitigation, and control measures. The fundamental mechanisms of disease progression and epidemic spread provide important constraints on interpreting changing epidemic cases counts with time and geography in the context of on-going interventions, mitigations, and controls. Models such as these that account for the effects of human actions can also allow evaluation of the importance of categories of epidemic and disease controls. Introduction: We present the EpiEarly, EpiGrid, and EpiCast tools for mechanistically-based biological decision support. The range of tools covers coarse-, medium-, and fine-grained models. The coarse-grained, aggregated time-series only data tool (EpiEarly) provides a statistic quantifying epidemic growth potential and associated uncertainties. The medium grained, geographically-resolved model (EpiGrid) is based on differential equation type simulations of disease and epidemic progression in the presence of various human interventions geared toward understanding the role of infection control, early vs. late diagnosis, vaccination, etc. in outbreak control. A fine-grained hybrid-agent epidemic model (EpiCast) with diurnal agent travel and contagion allows the analysis of the importance of contact-networks, travel, and detailed intervention strategies for the control of outbreaks and epidemics. Methods: We use three types of methods for simulation and analysis. They are: (1) Bayesian and regression methods allowing estimation of the basic reproductive number from case-count data; (2) ordinary-differential equation integration with modifications to account for discreteness of disease spread when case counts are small (we include space- and time-dependent effects); and (3) methods that hybridize agent-based travel, mixing, and disease progression with nested-mass action contagion (i.e. not fully agent-based). From the perspective of decision support, the crucial feature of mechanistic infectious epidemiological models is a way to capture the human interventions that determine epidemic outcome. Categorizing types of mitigation into those that change the force of infection, and those that branch disease progression allows a common framework that can be extended from medium-grained models through fine-grained. Our canonical example is our EpiGrid tool which allows for the modulation of the force of infection (i.e. contagion) with time (and potentially space), the vaccination of a susceptible population in a geographically-targeted manner, movement controls, and branching our disease progression model to account for early- vs. late-intervention during host disease progression.ResultsWe will present analysis of diseases that exemplify the various aspects of analysis in support of outbreak and epidemic control. Human and animal diseases relevant to this demonstration include rinderpest, avian influenza, and measles. We will begin with EpiEarly’s estimate of epidemic potential using aggregated time-dependent case-count data. The key observation for EpiEarly is that under a wide range of situations a disease's reproductive number should be generalized to a distribution of possibilities to account for inherent randomness and other factors (including the variability of a disease contact network). We will then continue with a demonstration of EpiGrid’s capabilities for understanding and modelling the role of interventions including contagion control (the force of infection), treatment (changing disease progression and infectiousness depending on treatment), vaccination, culling, and movement controls. We will briefly touch on the capabilities of EpiCast for more detailed analysis of specific intervention strategies. Conclusions: We will demonstrate examples where modeling either contributed or plausibly would contribute to informing epidemic and outbreak control constrained by the possibilities of the underlying epidemic and disease dynamics.

Geospatial↗

An optogenetic toolkit for light-inducible antibiotic resistance

Abstract Antibiotics are a key control mechanism for synthetic biology and microbiology. Resistance genes are used to select desired cells and regulate bacterial populations, however their use to-date has been largely static. Precise spatiotemporal control of antibiotic resistance could enable a wide variety of applications that require dynamic control of susceptibility and survival. Here, we use light-inducible Cre recombinase to activate expression of drug resistance genes in Escherichia coli . We demonstrate light-activated resistance to four antibiotics: carbenicillin, kanamycin, chloramphenicol, and tetracycline. Cells exposed to blue light survive in the presence of lethal antibiotic concentrations, while those kept in the dark do not. To optimize resistance induction, we vary promoter, ribosome binding site, and enzyme variant strength using chromosome and plasmid-based constructs. We then link inducible resistance to expression of a heterologous fatty acid enzyme to increase production of octanoic acid. These optogenetic resistance tools pave the way for spatiotemporal control of cell survival.

59 BASIC BIOLOGICAL SCIENCES↗

Overview of FLORIS updates

In this paper, we review updates made to the FLORIS (FLOw Redirection and Induction in Steady State) open-source framework for wind farm control modeling, design and analysis. The updates are focused on improvements for large arrays of turbines - including heterogenous inflows and incorporating second-order wake steering effects - design, and analysis tools for practical application of wind farm control, and improvements to the software architecture for best practices in modularization and cooperative development.

17 WIND ENERGY↗

A New Light for Berkeley Lab—the Advanced Light Source Upgrade

The Advanced Light Source Upgrade Project (ALS-U) will leverage multibend achromat technology to endow the ALS with revolutionary soft X-ray capabilities, and has recently received formal approval to proceed to the preliminary design phase. Soft X-rays are a critical diagnostic tool for enabling the understanding and control of heterogeneous, hierarchical functional materials and chemical synthesis platforms since they can reveal chemical, electronic, and magnetic properties with very high sensitivity. Although the ALS has a strong track record in soft X-ray science over the last 25 years, it, like most other existing storage-ring-based X-ray light sources, lacks the simultaneous combination of nanometer spatial resolution, diverse spectroscopic contrast, and broad temporal sensitivity required to image the location of molecules, ions, and electrons, and to measure how their components migrate and interact to support efficient function. The high coherent flux of the upgraded ALS willenable a suite of tools that encompass 3D nanoscale imaging with high spectral sensitivity over broad space and time scales, dramatically amplifying the already high impact of ALS soft X-ray spectroscopies. Relative to many other synchrotron light source upgrade projects or new facilities being built today, the upgraded ALS will operate at a low electron-beam energy of 2 GeV and a high current of 500 mA, and is optimized for soft X-rays. Its soft X-ray coherent flux will be orders of magnitude higher than that of the existing ALS and beyond the coherent flux of any storage-ring-based light source operating, under construction, or currently planned. In total, the upgraded facility will provide an unprecedented combination of high stability, quasi-continuous radiation, and the highest possible coherent soft X-ray flux.

47 OTHER INSTRUMENTATION↗

Development of Data-Driven Models for Performance Prediction and Chemical Dosing of a Full-Scale Controlled Phosphorus Precipitation Reactor

This study evaluated the use of data-driven models to improve control of a struvite precipitation reactor that removes phosphorus from wastewater while producing a fertilizer product. The researchers developed predictive models for influent orthophosphate concentration, effluent orthophosphate concentration, and phosphorus removal using operational data from a full-scale MagPrex™ reactor at a water resource recovery facility in Denver, Colorado. Model predictions were used to recommend magnesium chloride dosing adjustments needed to achieve a target effluent phosphorus concentration. Several machine learning approaches were tested, with ridge regression providing the best predictions for influent orthophosphate concentration and phosphorus removal, and XGBoost providing the best predictions for effluent orthophosphate concentration. Simulation results indicated that the decision-support approach could correctly identify dosing adjustments in most cases and reduce chemical use. Full-scale implementation achieved lower accuracy due to changing operating conditions and limited historical data in some operating ranges. Here, the results demonstrate the potential of data-driven tools to support phosphorus recovery process control while also identifying practical limitations that affect deployment in full-scale systems.

42 ENGINEERING↗