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At least 451 records · Page 25

Moore Machine Motion Controls Refurbishment Statement of Work and Specification

Diamond Turning Machines known as “Moore” machines are used in the production of Potassium diHydrogen Phosphate (KDP) optics required for the National Ignition Facility (NIF). These machines are owned by the Department of Energy, as provided by Lawrence Livermore National Security LLC (LLNS). Moore Machines 1 and 2 are located at the Gooch & Housego (G&H) facility in Highland Heights, OH. The existing Aerotech motion controllers, motor drivers/amplifiers, input/output (I/O) hardware, control computer, software user interface, human machine interface (HMI), cabling, and encoders are beyond service life and require replacement. This Statement of Work (SoW) defines the motion control system refurbishment requirements for the Moore diamond turning machines designated Moore 1 and Moore 2. The motion controls system design shall include a motion control computer, control software, motor drive amplifiers and controllers, linear scale encoders, rotary encoders, HMI, power distribution, emergency stop (E-Stop) and interlocks, cabling, switches, solenoids, transducers, sensors, actuators, ancillary system interfaces, and related components necessary for a complete machine tool control system. The Subcontractor shall include effort to standardize systems between the two machines if reasonably possible.

42 ENGINEERING↗

Genome-scale Design and Engineering of Non-model Yeast Organisms for Production of Biofuels and Bioproducts

The overall goal of this project was to develop genome-scale design and engineering tools for two non-model yeast organisms including Rhodotorula toruloides and Issatchenkia orientalis to produce high-levels of fatty acids-derived products and organic acids, respectively. The project was performed between 9/15/2017 and 9/14/2024 (the last two-years were no-cost extensions). The team consisted of Huimin Zhao (Lead PI) and Christopher Rao (Co-PI) from the University of Illinois at Urbana-Champaign (UIUC), Costas Maranas (Co-PI) from the Pennsylvania State University, Joshua Rabinowitz (Co-PI) and Martin Wuhr (Co-PI) from Princeton University, and Yasuo Yoshikuni (Co-PI) from the DOE Joint Genome Institute. The team has made great progress in both tool development and fundamental understanding of these two non-model yeasts. In total, there were 40 research publications (one of them is still under review) and one patent application as well as numerous oral presentations.

60 APPLIED LIFE SCIENCES↗

A geometric framework for momentum-based optimizers for low-rank training

Low-rank pre-training and fine-tuning have recently emerged as promising techniques for reducing the computational and storage costs of large neural networks. Training low-rank parameterizations typically relies on conventional optimizers such as heavy ball momentum methods or Adam. In this work, we identify and analyze potential difficulties that these training methods encounter when used to train low-rank parameterizations of weights. In particular, we show that classical momentum methods can struggle to converge to a local optimum due to the geometry of the underlying optimization landscape. To address this, we introduce novel training strategies derived from dynamical low-rank approximation, which explicitly account for the underlying geometric structure. Our approach leverages and combines tools from dynamical low-rank approximation and momentum-based optimization to design optimizers that respect the intrinsic geometry of the parameter space. We validate our methods through numerical experiments, demonstrating faster convergence, and stronger validation metrics at given parameter budgets.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

Science Breakthroughs 2030. Final report

Agriculture is a fundamental societal activity, characterized by many different landscapes, crops, markets, and participants. Food, agricultural, and biofuels products are central to the daily life of all citizens, though most do not recognize the fragility of the environment that brings forth this abundance. As is noted in the 2012 report from the President's Council of Advisors on Science and Technology, Agricultural Preparedness and the United States Agricultural Research Enterprise (PCAST, 2012) the food and agricultural system faces constant challenges in: Managing new pests, pathogens, and invasive plants. Increasing the efficiency of water use. Growing food in a changing climate. Reducing the environmental footprint of agriculture. Managing the production of bioenergy. Producing safe and nutritious food. Assisting with global food security and maintaining abundant yields. Science Breakthroughs 2030 was organized to identify the most compelling research directions in food and agriculture, in particular those empowered by the application of insights and tools from disciplines of science and engineering not typically associated with food and agricultural research. A committee appointed by the Chairman of the National Research Council explored ideas for research directions with input from the scientific community, with the objective of producing a report describing ambitious and achievable scientific pathways to address major problems and create new opportunities in food and agriculture. Following numerous meetings, a jamboree, and town hall, the appointed committee prepared a report that has subsequently become a reference for federal agencies supporting research in the food and agricultural space. It highlights five key areas for research investment with broad application across food and agriculture: integrated systems research; sensor development; data mining and information sciences, genomics; and the microbiome.

09 BIOMASS FUELS↗

Depletion Benchmark Analysis on a Lead Fast Reactor Using PyARC/OpenMC

PyARC is a user-friendly fast reactor analysis tool that automates multiphysics workflows using the “extended suite” of Argonne Reactor Computation (ARC) codes by providing a single common input for model definition, code execution, and output post-processing. A lead fast reactor (LFR) benchmark model is used to perform depletion calculations using the newly integrated OpenMC depletion capability in PyARC, building on previous analysis using the ARC codes through PyARC and Serpent. Results for core lifetime k-effective, shutdown decay heat, and end-of-life heavy-metal inventory are compared to verify the PyARC/OpenMC integration against the PyARC/ARC workflow and Serpent for depletion analysis of LFR designs. The results show satisfactory agreement among all three methods, with remaining discrepancies largely attributable to differences in nuclear data libraries and decay-chain modeling detail rather than to fundamental modeling limitations.

Kiesling, Kalin R.↗

Optimize the Autonomous Sensor Fish Device for Understanding Interactions of Aquatic Animals with Marine and Hydrokinetic and Hydro Systems (CRADA 476) Final Report

This project at the Pacific Northwest National Laboratory (PNNL) enhances our understanding of how aquatic life interacts with marine renewable energy (MRE) and hydropower systems through the development and testing of advanced sensor technology. The Marine Sensor Fish (MSF) and its smaller variants, the Sensor Fish Mini (SF Mini) and Flexible Sensor Fish (FSF), measure critical environmental stressors, such as shear forces, pressure changes, and strike impacts, that are essential for assessing the risks posed by energy devices, including tidal turbines, hydropower installations, and other MRE infrastructure. Rigorous field testing has shown that these tools are effective in capturing detailed data on turbulence, pressure variations, strike impacts, and other stressors near these devices, providing valuable insights into the conditions faced by aquatic species. Economically, these tools offer renewable energy developers a practical solution for streamlining environmental assessments and ensuring regulatory compliance, ultimately reducing costs associated with evaluating and mitigating ecological impacts. This research also benefits the public by promoting the growth of renewable energy sources that protect aquatic ecosystems, advancing both sustainable energy production and environmental stewardship.

13 HYDRO ENERGY↗

Atmospheric Modeling to Enable Prediction of Golden Eagle Interactions with Wind Power Plants

This panel will explore the use of technologies and methods that enhance our understanding of eagle behavior in and near wind energy facilities. The decreasing costs of tracking technologies and substantial computational capabilities are allowing for finer resolution and confidence of eagle observations and the modeling of such datasets increase our understanding of their movements and use of airspace and underlying landscapes. Behavior ecologists' intrinsic knowledge of eagle behavior can augment and further enhance inferences from technology-derived information alone, e.g., GPS, camera, radar, etc. The panel will discuss the state of science and, given the cost-effective tools available, what research objectives are emerging to better assess and reduce wind-eagle risk. The discussion will focus on the following areas: Integrating Behavioral and Quantitative Ecologist perspectives of bald eagle and golden eagle behavior and wind energy risk; Regional-scale vs. facility-scale investigations of bald eagle and golden eagle use of airspace. For example, avoidance behavior to assess risk at facility-scale, and eagle use of landscapes, e.g., territories, nesting, and life-cycle behavior; Bald eagle and golden eagle use of airspace and nexus with atmospheric flow dynamics of wind energy generation; GPS, biomonitoring, tracking camera, radar, and other tools/techniques for deepening the knowledge of eagle behavior in and around wind farms.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

EPIsembleVis: A geo-visual analysis and comparison of the prediction ensembles of multiple COVID-19 models

In this work, we present EPIsembleVis, a web-based comparative visual analysis tool for evaluating the consistency of multiple COVID-19 prediction models. Our approach analyzes a collection of COVID-19 predictions from different epidemiological models as an ensemble and utilizes two metrics to quantify model performance. These metrics include (a) prediction uncertainty (represented as the dispersion of predictions in each ensemble) and (b) prediction error (calculated by comparing individual model predictions with the recorded data). Through an interactive visual interface, our approach provides a data-driven workflow for (a) selecting and constructing the COVID-19 model prediction ensemble based on the spatiotemporal overlap of available predictions of multiple epidemiological models, (b) quantifying the model performance using both the uncertainty of each model prediction ensemble, and the error of each ensemble member that represents individual model predictions, and (c) visualizing the spatiotemporal variability in the projection performance of individual models using a suite of novel ensemble visualization techniques, such as the data availability map, a spatiotemporal textured-tile calendar, multivariate rose chart, and time-series leaflet glyph. We demonstrate the capability of our ensemble visual interface through a case study that investigates the performance of weekly COVID-19 predictions, which are provided through the COVID-19 Forecast Hub UMass-Amherst Influenza Forecasting Center of Excellence [47] for the United States and United States Territories. The EPIsembleVis tool is implemented using open-source web technologies and adaptive system design, rendering it interoperable with Elasticsearch and Kibana for automatically ingesting COVID-19 predictions from online repositories, and it is generalizable for analyzing worldwide projections from more epidemiological models.

60 APPLIED LIFE SCIENCES↗

Investigation of Cold Spray as a Dry Storage Canister Repair and Mitigation Tool

The lack of a permanent spent nuclear fuel repository means utilities are faced with extending licenses for dry cask storage systems (DCSS) canisters far beyond their original 20-year license period. DCSS canisters are made from austenitic stainless steels (SSs) and fabricated using fusion welds. High heat input and melting associated with fabrication welds causes material around the weld to be susceptible to chloride-induced stress corrosion cracking (CISCC). The purpose of the work reported here is to investigate the use of cold spray for repair and mitigation of CISCC in DCSS canisters to ensure integrity far beyond their original license period. This report presents an analysis of cold spray for canister life extension, a summary of related efforts, relevant technology down selections, work accomplished, and future efforts relative to use of cold spray for repair and mitigation of CISCC in DCSS canisters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Integrating Chemical Catalysis and Biological Conversion of Carbon Intermediates for Deriving Value-Added Products from Carbon Dioxide

Carbon dioxide valorization represents an appealing approach to reducing greenhouse gases in the atmosphere. While electrocatalysis is an effective tool to reduce CO 2 into small carbon compounds, it becomes increasingly challenging to efficiently produce compounds with more carbon atoms. In contrast, while biological systems struggle to utilize CO 2 , they can readily upcycle other small carbon compounds. This project explores the use of a two-stage process that electrocatalytically converts CO 2 into methanol, formate, or acetate which is subsequently utilized by Methylotuvimicrobium alcaliphilum 20Z to produce medium chain length polyhydroxyalkanoate. A techno-economic analysis and life cycle assessment evaluates the commercial viability of the process as well as its carbon emissions. We show here an enhanced CO 2 -to-methanol electroconversion step coupled with the use of a microbial culture adapted to the process conditions to be the optimal configuration for economic potential.

09 BIOMASS FUELS↗

Design Methods, Tools, and Data for Ceramic Solar Receivers Year 1 Continuation Report

This report describes the first year of work on a project to develop the methods, tools, and data required to analyze high temperature ceramic Concentrating Solar Power (CSP) components. This first year focused on developing the methods and data required for a time-independent assessment of potential components, focusing in particular on ceramic solar receivers. The report describes both model development and testing work focused on accomplishing this goal. Our overall conclusion is that high temperature ceramic CSP components are viable and could provide a means to overcome the expected low reliability and short service life for equivalent components constructed from Ni-based superalloys. Based on the results reported here, we recommend the project continue to Phase II which will develop more sophisticated, realistic models for time-dependent failure of ceramics operating in expected CSP component conditions and develop the time-dependent ceramic test data needed to parameterize these models, using commercial SiC as a reference material.

14 SOLAR ENERGY↗

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↗

Environmental life cycle assessment of treatment and management strategies for food waste and sewage sludge

A consequential life cycle assessment (LCA) was utilized to compare the environmental impacts of food waste and sewage sludge management strategies. The strategies included a novel two-phase anaerobic digestion (AD) system and alternatives including landfill, waste-to-energy, composting, anaerobic membrane bioreactor, and conventional AD (wet continuous stirred-tank reactor [CSTR]). The co-management of food waste with sewage sludge was also considered for the two-phase AD system and for a conventional AD reactor. Further, a multidimensional LCA approach was taken, considering the five-midpoint impact categories of global warming, smog, human health particulate, acidification, and eutrophication estimated using the U.S. EPA Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts. Co-management of food waste and sewage sludge using the novel two-phase AD system was shown to maximize energy recovery and had a net global warming benefit while reducing other environmental impacts compared with the alternative management strategies. It had similar relative environmental advantages across all categories as conventional AD, with the advantage of a smaller physical footprint. However, both approaches featured net environmental burdens when the background electric grid intensity fell below 0.25 kg CO 2 -eq kWh -1 , as could be expected in a decarbonized electric future. Upgrading the biogas produced from AD to renewable natural gas can displace the use of fossil natural gas for other non-electricity energy requirements that are difficult to decarbonize and may extend the time period of significant environmental benefits of utilizing AD for organic waste management. Treatment of the nutrient-rich supernatant generated by the novel two-phase AD system could be an obstacle for utilities with stringent nutrient discharge limits. Future research and full-scale implementation are needed to demonstrate the benefits of the two-phase AD system predicted through this analysis.

54 ENVIRONMENTAL SCIENCES↗

ClusterCAD 2.0: an updated computational platform for chimeric type I polyketide synthase and nonribosomal peptide synthetase design

Abstract Megasynthase enzymes such as type I modular polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs) play a central role in microbial chemical warfare because they can evolve rapidly by shuffling parts (catalytic domains) to produce novel chemicals. If we can understand the design rules to reshuffle these parts, PKSs and NRPSs will provide a systematic and modular way to synthesize millions of molecules including pharmaceuticals, biomaterials, and biofuels. However, PKS and NRPS engineering remains difficult due to a limited understanding of the determinants of PKS and NRPS fold and function. We developed ClusterCAD to streamline and simplify the process of designing and testing engineered PKS variants. Here, we present the highly improved ClusterCAD 2.0 release, available at https://clustercad.jbei.org. ClusterCAD 2.0 boasts support for PKS-NRPS hybrid and NRPS clusters in addition to PKS clusters; a vastly enlarged database of curated PKS, PKS-NRPS hybrid, and NRPS clusters; a diverse set of chemical ‘starters’ and loading modules; the new Domain Architecture Cluster Search Tool; and an offline Jupyter Notebook workspace, among other improvements. Together these features massively expand the chemical space that can be accessed by enzymes engineered with ClusterCAD.

59 BASIC BIOLOGICAL SCIENCES↗

Identifying Performance Advantaged Biobased Chemicals Utilizing Bioprivileged Molecules

Two technology areas were advanced; a) novel molecules with improved performance in the end use application of organic corrosion inhibitors and flame retardant nylon polymers and b) development of a systematic process for identifying biomass-derived molecules with improved performance in end use applications. In total 17 novel organic corrosion inhibitors were identified that had significantly better performance than the commercial reference organic corrosion inhibitor and 7 novel nylons were synthesized with improved flame retardant properties relative to standard nylon-6,6. While an end-to-end systematic process for identifying biomass-derived molecules with improved end use performance was not completed, important progress was made computational tools for mining chemical structures from the literature and databases as well as establishing reaction network generation algorithms to aid in the discovery of novel molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modernizing Fermilab's Accelerator Control Hardware

Modernizing the Fermilab accelerator control system is essential to future operations of the laboratory's accelerator complex. The existing control system has evolved over four decades and uses hardware that is no longer available.The Accelerator Controls Operations Research Network (ACORN) Project will modernize the control system and replace end-of-life power supplies to enable future accelerator complex operations with megawatt particle beams. The ACORN project is planning to replace Fermilab s obsolete CAMAC crate-and-card controls hardware with modern MicroTCA hardware. There are over 2,000 CAMAC cards and over 250 CAMAC crates serving various functions in Fermilab s control system. We will review the existing CAMAC hardware and provide updates on the status of the ACORN project, which includes the conceptual design of the MicroTCA replacement hardware and software tools for supporting the installation of hundreds of MicroTCA crates.

43 PARTICLE ACCELERATORS↗

Current Status and Future Directions of All-Solid-State Batteries with Lithium Metal Anodes, Sulfide Electrolytes, and Layered Ternary Oxide Cathodes

All-solid-state batteries (ASSBs) offer great promise as a next-generation energy storage technology with higher energy density, wider operating temperature range, and improved safety for electric vehicles. ASSBs employing lithium metal anodes (Li), sulfide-based solid-state electrolytes (SSE), and Ni-rich layered transition metal oxide cathodes (LiMO 2 , M = Ni, Mn, Co, Al) are particularly promising due to its superior electrochemical performance compared to other solid-electrolyte systems. However, the battery cycle life at high cathode mass loading and high current is still limited because the failure mechanism is not fully understood. Lithium dendrite growth at the anode or inside a solid electrolyte still represents as a serious risk of cell failure. Interfacial resistance increases attributed to electrolyte decomposition and interfacial void formation at both cathode–electrolyte and anode–electrolyte interfaces lead to gradual capacity fading. In this Review, we present the fundamental challenges and recent scientific understandings of each component in ASSBs. The novel diagnostic tools for these components, especially the interfaces buried under the surface that are often hard for characterization are mainly examined. Lastly, we offer a perspective for future research directions. We hope this Review will provide a timely snapshot of state-of-the-art research progress in ASSBs to accelerate the development of ASSBs.

25 ENERGY STORAGE↗

Screening and Brief Interventions for Alcohol Use During Pregnancy: Practices Among US Primary Care Clinicians, DocStyles 2019

Alcohol use during pregnancy can cause birth defects and developmental disabilities. From 2018 through 2020, 13.5% of pregnant women reported current drinking. The US Preventive Services Task Force recommends evidence-based tools (eg, AUDIT-C and SASQ) for implementing screening and brief interventions to reduce excessive alcohol use among adults, including pregnant people, for whom any alcohol use is considered excessive. We used DocStyles 2019 data to conduct a cross-sectional analysis to examine current screening and brief intervention practices that primary care clinicians conduct among pregnant patients; clinicians’ confidence levels in conducting screening, brief interventions, and referral to treatment; and the documentation of brief interventions in the medical record. A total of 1,500 US adult medicine clinicians completed the entire survey. Among the respondents who conduct screening (N = 1,373) and brief interventions (N = 1,357) in their practice, nearly all reported implementing screening (94.6%) and brief interventions (94.9%) with their pregnant patients for alcohol use, but fewer than half felt confident about conducting their screening practices (46.5%). Two-thirds (64%) reported using a tool that met the criteria recommended by the US Preventive Services Task Force (USPSTF). Over half documented brief interventions in electronic health record notes (51.7%) or designated space (50.7%). Pregnancy presents a unique opportunity for clinicians to incorporate screening into routine obstetric care and encourage behavior change among patients. Most providers reported always screening their pregnant patients for alcohol use, but fewer used evidence-based USPSTF-recommended screening tools. Increased clinician confidence in screening and brief intervention, the use of standardized screening tools tailored to pregnant people, and maximal use of electronic health record technology may enhance the benefits of their application to alcohol use, which ultimately can reduce adverse outcomes associated with alcohol use during pregnancy.

60 APPLIED LIFE SCIENCES↗