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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32

UAS remote sensing (Osprey platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance, Seward Peninsula, Alaska, 2017

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group (https://www.bnl.gov/testgroup). This package includes raw (L0) data from 14 flights flown over the NGEE-Arctic Council Mile Marker 71 (MM71), Kougarok MM64, and Teller MM 27 sites in August, 2017. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. This package provides the Level 0 (raw, unprocessed) data collected by the Osprey platform. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), tabular (*.dat, *.csv, *.waypoint), and image (*.jpg) formats. This metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

A landing pad system for multicopy gene integration in Issatchenkia orientalis

The robust nature of the non-conventional yeast Issatchenkia orientalis allows it to grow under highly acidic conditions and therefore, has gained increasing interest in producing organic acids using a variety of carbon sources. Recently, the development of a genetic toolbox for I. orientalis, including an episomal plasmid, characterization of multiple promoters and terminators, and CRISPR-Cas9 tools, has eased the metabolic engineering efforts in I. orientalis. However, multiplex engineering is still hampered by the lack of efficient multicopy integration tools. To facilitate the construction of large, complex metabolic pathways by multiplex CRISPR-Cas9-mediated genome editing, we developed a bioinformatics pipeline to identify and prioritize genome-wide intergenic loci and characterized 47 gRNAs located in 21 intergenic regions. These loci are screened for guide RNA cutting efficiency, integration efficiency of a gene cassette, the resulting cellular fitness, and GFP expression level. We further developed a landing pad system using components from these well-characterized loci, which can aid in the integration of multiple genes using single guide RNA and multiple repair templates of the user’s choice. We have demonstrated the use of the landing pad for simultaneous integrations of 2, 3, 4, or 5 genes to the target loci with efficiencies greater than 80%. As a proof of concept, we showed how the production of 5-aminolevulinic acid can be improved by integrating five copies of genes at multiple sites in one step. We have further demonstrated the efficiency of this tool by constructing a metabolic pathway for succinic acid production by integrating five gene expression cassettes using a single guide RNA along with five different repair templates, leading to the production of 9 g/L of succinic acid in batch fermentations. Furthermore, this study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in a non-conventional yeast. This landing pad system will be a valuable tool for the metabolic engineering of I. orientalis.

59 BASIC BIOLOGICAL SCIENCES↗

Phonon-Mediated Quasiparticle Lifetime Renormalizations in Few-Layer Hexagonal Boron Nitride

Understanding the collective behavior of the quasiparticles in solid-state systems underpins the field of non-volatile electronics, including the opportunity to control many-body effects for well-desired physical phenomena and their applications. Hexagonal boron nitride (hBN) is a wide energy bandgap semiconductor, showing immense potential as a platform for lowdimensional device heterostructures. It is an inert dielectric used for gated devices, having a negligible orbital hybridization when placed in contact with other systems. Despite its inertness, we discover a large electron mass enhancement in few-layer hBN affecting the lifetime of the π-band states. We show that the renormalization is phonon-mediated and consistent with both single- and multiple-phonon scattering events. Our findings thus unveil a so-far unknown many-body state in a wide-bandgap insulator, having important implications for devices using hBN as one of their building blocks.

36 MATERIALS SCIENCE↗

ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mechanical tunneling based threshold-annealing process. The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing dynamics onto a network of integrate-and-fire neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer and the resulting spiking dynamics replicates the optimal escape mechanism and convergence of SA, particularly at low-temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved benchmark combinatorial optimization problems such as MAX-CUT and Max Independent Set. Across multiple runs, NeuroSA consistently generates distribution of solutions that are concentrated around the state-of-the-art results (within 99%) or surpass the current state-of-the-art solutions for Max Independent Set benchmarks. Furthermore, NeuroSA is able to achieve these superior distributions without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform.

42 ENGINEERING↗

Designer membraneless organelles sequester native factors for control of cell behavior

Subcellular compartmentalization of macromolecules increases flux and prevents inhibitory interactions to control biochemical reactions. Inspired by this functionality, we sought to build designer compartments that function as hubs to regulate the flow of information through cellular control systems. Here we report a synthetic membraneless organelle platform to control endogenous cellular activities through sequestration and insulation of native proteins. We engineer and express a disordered protein scaffold to assemble micron size condensates and recruit endogenous clients via genomic tagging with high-affinity dimerization motifs. By relocalizing up to ninety percent of a targeted enzymes to synthetic condensates, we efficiently control cellular behaviors, including proliferation, division, and cytoskeletal organization. Further, we demonstrate multiple strategies for controlled cargo release from condensates to switch cells between functional states. These synthetic organelles offer a powerful and generalizable approach to modularly control cell decision-making in a variety of model systems with broad applications for cellular engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prioritizing ICS Beachhead Systems for Cyber Vulnerability Testing

Cyber Testing for Resilient Industrial Control Systems™ (CyTRICS™) is the Department of Energy’s (DOE’s) program for cybersecurity vulnerability testing, digital subcomponent enumeration, and forensic assessment. CyTRICS leverages best-in-class test facilities and analytic capabilities at six DOE National Laboratories and strategic partnerships with key stakeholders including technology developers, manufacturers, asset owners and operators, and interagency partners. During the program’s development, CyTRICS established a unique methodology for prioritizing digital components within operational technology (OT) and industrial control systems (ICS) in the Energy Sector Industrial Base (ESIB) for cyber vulnerability testing. The CyTRICS Prioritization Process leverages multiple characteristics of systems, components, and their contextual deployment to calculate a quantification of individual digital components for CyTRICS testing. The initial version of the CyTRICS Prioritization Process was premised largely upon the impact which could result to an industrial control system if the digital component under testing was compromised, either through malicious means, faulty engineering, or other modes. The worldwide compromise of the SolarWinds Orion platform, first reported in December 2020, through malicious interference with the digital patching cycle was a watershed event in cyber supply chain security. The SolarWinds compromised demonstrated the strategic importance of certain types of ubiquitous software, and the ability to generate widespread cybersecurity effects. To address this challenge and as a part of the Department of Energy’s response to the SolarWinds compromise, DOE’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER) directed the National Laboratories to evolve the CyTRICS Prioritization Process methodology to encompass additional factors related to the strategic importance of digital components. CESER directed CyTRICS researchers to identify, characterize, and append strategic factors to the CyTRICS Prioritization Process to provide additional weight to these characteristics. National Laboratory expert researchers identified functionality, distribution, and platform characteristics for digital components in ICS and OT that they assessed would be likely targeted in strategic initial-access cyber attack. CyTRICS has termed these factors “ICS Beachhead Systems,” leveraging a definition first advanced by Schneider Electric, which is intended as a blanket term to encompass digital components, products, and systems in OT. This paper describes the ICS Beachhead Systems identified and the rationale for inclusion. As a next step in the research and refinement process, the National Laboratories will validate this initial set of characteristics against digital components evaluated by the CyTRICS program and current implementation of the CyTRICS Prioritization Process. After validation, CyTRICS researchers will then develop a scoring methodology to generate a quantitative score to assess the degree to which a digital component is characterized as an ICS Beachhead System. Finally, the National Laboratories will append this scoring to the existing CyTRICS Prioritization Process algorithm.

97 MATHEMATICS AND COMPUTING↗

Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method, we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology is benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We apply this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detect 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of phosphorylation events relevant to mitochondrial and brain biology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inverse design of nanoporous crystalline reticular materials with deep generative models

Reticular frameworks are crystalline porous materials that form via the self-assembly of molecular building blocks in different topologies, with many having desirable properties for gas storage, separation, catalysis, biomedical applications and so on. The notable variety of building blocks makes reticular chemistry both promising and challenging for prospective materials design. Here we propose an automated nanoporous materials discovery platform powered by a supramolecular variational autoencoder for the generative design of reticular materials. We demonstrate the automated design process with a class of metal–organic framework (MOF) structures and the goal of separating carbon dioxide from natural gas or flue gas. Our model shows high fidelity in capturing MOF structural features. Here, we show that the autoencoder has a promising optimization capability when jointly trained with multiple top adsorbent candidates identified for superior gas separation. MOFs discovered here are strongly competitive against some of the best-performing MOFs/zeolites ever reported.

36 MATERIALS SCIENCE↗

Integration of SARS-CoV-2 testing and genomic sequencing into influenza sentinel surveillance in Uganda, January to December 2022

The Uganda Virus Research Institute, National Influenza Center laboratory integrated SARS-CoV-2 polymerase chain reaction testing and genomic sequencing into the influenza surveillance program that was established in 2007. A total of 7,698 nasopharyngeal/oropharyngeal (NP/OP) swab samples were collected and analyzed from ILI/SARI sentinel sites across the country from January to December 2022. All samples were tested for influenza and SARS-CoV-2. Of these, 252 (3.3%), 162 (2.1%), and 589 (7.7%) were positive for influenza A, influenza B, and SARS-CoV-2, respectively. Out of 414 influenza-positive samples, 122 (29.5%) were AH1pdm09, 130 (31.4%) were AH3, and 162 (39.1%) were B-Victoria. All SARS-CoV-2 sequenced samples were of the Omicron variant, with subvariants of concern known to evade the immune system being detected, such as BQ.1 and XBB.2. Other SARS-CoV-2 positive samples collected from other health centers in the community outside the surveillance sites were included into SARS-CoV-2 genomic sequencing with similar patterns with respect to variants. In all, the ILI/SARI surveillance system has shown to be an efficient, cost-effective, and sustainable program, providing a ready platform to monitor the circulation of SARS-CoV-2 in communities at the national level while remaining vigilant for the persistent threat of influenza. The integration of SARS-CoV-2 detection and genomic surveillance into the influenza surveillance program will strengthen the laboratory response capacity, as well as facilitate the timely release of SARS-CoV-2 genomic information to be used to complement the multiple response strategies for COVID-19 pandemic mitigation.

59 BASIC BIOLOGICAL SCIENCES↗

Advanced grid-forming (GFM) inverter controls, modeling and system impact study for inverter dominated grids

Our main goals in this project are to understand: 1) the stability of the power system with very high penetration of PV or other inverter-based resources (IBR), 2) the interactions among IBRs and traditional generators, and 3) the impact of the GFM inverters on bulk power system. To achieve these goals, we took a holistic research and development approach. First, an impedance-based large system modeling and stability analysis tool was developed to aid the large IBR system small-signal stability analysis. Second, consensus-based control and transient overload ride through were developed to control and coordinate multiple GFM inverters in a large system to maintain transient stability during big grid events. Third, high fidelity electromagnetic transient (EMT) IBR models were developed and integrated into a large reduced WECC model to study the system impact from IBRs. Lastly, extensive validation tests of the GFM control which was developed in this project and implemented in two 1MW commercial solar inverters were performed using different validation platforms, e.g., control hardware-in-the-loop (CHIL) platform, power hardware- in-the-loop (PHIL) platform, and a real PV plant.

14 SOLAR ENERGY↗

Open-Loop Control Co-Design of Semisubmersible Floating Offshore Wind Turbines Using Linear Parameter-Varying Models

Here, this paper discusses a framework to design elements of the plant and control systems for floating offshore wind turbines in an integrated manner using linear parameter-varying models. Multiple linearized models derived from aero-elastic simulation software in different operating regions characterized by the incoming wind speed are combined to construct an approximate low-fidelity model of the system. The combined model is then used to generate open-loop, optimal control trajectories as part of a nested control co-design strategy that explores the system’s power production and stability using the platform pitch tilt as a proxy in the context of crucial plant and control design decisions. The radial distance between the central and outer columns and the diameter of the outer columns of the semisubmersible platform are the plant design variables. The platform stability and power production are studied for different plant design decisions. The effect of plant decisions on subsequent power production and stability response of the floating wind turbine is quantified in terms of the levelized cost of energy. The results show that the inner-loop constraints and the plant design decisions affect the turbine’s power and, subsequently, the cost of the system.

17 WIND ENERGY↗

Tunable topological Dirac surface states and van Hove singularities in kagome metal GdV 6 Sn 6

Transition-metal-based kagome materials at van Hove filling are a rich frontier for the investigation of novel topological electronic states and correlated phenomena. To date, in the idealized two-dimensional kagome lattice, topologically Dirac surface states (TDSSs) have not been unambiguously observed, and the manipulation of TDSSs and van Hove singularities (VHSs) remains largely unexplored. Here, we reveal TDSSs originating from a $\mathbb{Z}_2$ bulk topology and identify multiple VHSs near the Fermi level (E F ) in magnetic kagome material GdV 6 Sn 6 . Using in situ surface potassium deposition, we successfully realize manipulation of the TDSSs and VHSs. The Dirac point of the TDSSs can be tuned from above to below E F , which reverses the chirality of the spin texture at the Fermi surface. These results establish GdV 6 Sn 6 as a fascinating platform for studying the nontrivial topology, magnetism, and correlation effects native to kagome lattices. They also suggest potential application of spintronic devices based on kagome materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Imaging of multiple fluorescent proteins in canopies enables synthetic biology in plants

Reverse genetics approaches have revolutionized plant biology and agriculture. Phenomics has the prospect of bridging plant phenotypes with genes, including transgenes, to transform agricultural fields. Genetically encoded fluorescent proteins (FPs) have revolutionized plant biology paradigms in gene expression, protein trafficking and plant physiology. While the first instance of plant canopy imaging of green fluorescent protein (GFP) was performed over 25 years ago, modern phenomics has largely ignored fluorescence as a transgene expression device despite the burgeoning FP colour palette available to plant biologists. Here, we show a new platform for stand-off imaging of plant canopies expressing a wide variety of FP genes. The platform-the fluorescence-inducing laser projector (FILP)-uses an ultra-low-noise camera to image a scene illuminated by compact diode lasers of various colours, coupled with emission filters to resolve individual FPs, to phenotype transgenic plants expressing FP genes. Each of the 20 FPs screened in plants were imaged at >3 m using FILP in a laboratory-based laser range. We also show that pairs of co-expressed fluorescence proteins can be imaged in canopies. The FILP system enabled a rapid synthetic promoter screen: starting from 2000 synthetic promoters transfected into protoplasts to FILP-imaged agroinfiltrated Nicotiana benthamiana plants in a matter of weeks, which was useful to characterize a water stress-inducible synthetic promoter. FILP canopy imaging was also accomplished for stably transformed GFP potato and in a split-GFP assay, which illustrates the flexibility of the instrument for analysing fluorescence signals in plant canopies.

abiotic stress↗

High-Performance Computing Based EMT Simulation: Power Grid with IBRs

Electromagnetic transient (EMT) simulation of power grids with high-fidelity models of inverter-based resources (IBRs) is time-consuming and difficult to scale. The necessity for high-fidelity models of IBRs that incorporate the dynamics of individual inverters within IBRs has been showcased in recent studies. These studies focused on events with partial power reduction in each IBR during a transmission line fault in the power grid. These types of events have been documented in multiple North American Electric Reliability Council (NERC) reports in the past decade. It is imperative then to find solutions to speed-up EMT simulations and scale the size of the region with IBRs studied in EMT simulations. In this paper, a combination of numerical simulation algorithms with high-performance computing techniques are employed in discretization and linear solvers employed in the proposed RE-INTEGRATE EMT simulation platform for power grid with IBRs. For ease of scalability, modular and object-oriented programming is used as these techniques are implemented. Additionally, automation software is developed to convert legacy software codes to the proposed RE-INTEGRATE EMT simulation platform. Thereafter, this platform is evaluated on multi-core central processing units (CPUs). Finally, scale-up tests are performed to showcase the scalability that is possible.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗

BISON: A Flexible Code for Advanced Simulation of the Performance of Multiple Nuclear Fuel Forms

BISON is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library. One of its major goals is to have a great amount of flexibility in how it is used, including in the types of fuel it can analyze, the geometry of the fuel being modeled, the modeling approach employed, and the dimensionality and size of the models. Fuel forms that can be modeled include standard light water reactor fuel, emerging light water reactor fuels, tri-structural isotropic fuel particles, and metallic fuels. BISON is a platform for research in nuclear fuel performance modeling while simultaneously serving as a tool for the analysis of nuclear fuel designs. Recent research in BISON includes techniques such as the extended finite element method for fuel cracking, exploration of high-burnup light water reactor fuel behavior, swelling behavior of metallic fuels, and central void formation in mixed-oxide fuel. BISON includes integrated documentation for each of its capabilities, follows rigorous software quality assurance procedures, and has a growing set of rigorous verification and validation tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantum Sensing for Energy Applications: Review and Perspective

On its revolutionary threshold, quantum sensing is creating potentially transformative opportunities to exploit intricate quantum mechanical phenomena in new ways to make ultrasensitive measurements of multiple parameters. Concurrently, growing interest in quantum sensing has created opportunities for its deployment to improve processes pertaining to energy production, distribution, and consumption. Safe and secure utilization of energy is dependent upon addressing challenges related to material stability and function, secure monitoring of infrastructure, and accuracy in detection and measurement. A summary of well-established and emerging quantum sensing materials and techniques, as well as the corresponding sensing platforms that have been developed for their deployment is provided here. Specifically, the enhancement of existing advanced sensing technologies with quantum methods and materials is focused on, enabling the realization of an unprecedented level of sensitivity, placing an emphasis on relevance to the energy industry. The review concludes with a discussion on high-value applications of quantum sensing to the energy sector, as well as remaining barriers to sensor deployment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A multi-agent approach to distribution system fault section estimation in smart grid environment

We report that Multi-Agent Systems (MAS) are seen from different areas as one of the paramount trends for the next generation of power systems. Numerous published studies about MAS discuss its utilization in power distribution networks but none focuses on the prior step to restoration and self-healing that is fault section estimation. This paper aims to show how MAS can improve the utilities’ reliability indexes and consumer satisfaction by overcoming the multiple fault section estimation problem. In order to do this, the authors considered using MAS as a means of communication between smart meters. The purpose of smart meters usage is to employ devices that are already present in smart grids, mainly because of their reading and saving data capacity. The proposed method was tested on a radial feeder generated by the authors. The network was built on HYPERSIM, a software platform of OPAL-RT Technologies. The simulation results show that this MAS provides speed, efficiency, and automation for the process of fault section estimation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cellular fluidics

The natural world provides many examples of multiphase transport and reaction processes that have been optimized by evolution. These phenomena take place at multiple length and time scales and typically include gas–liquid–solid interfaces and capillary phenomena in porous media. Many biological and living systems have evolved to optimize fluidic transport. However, living things are exceptionally complex and very difficult to replicate, and human-made microfluidic devices (which are typically planar and enclosed) are highly limited for multiphase process engineering. In this paper, we introduce the concept of cellular fluidics: a platform of unit-cell-based, three-dimensional structures—enabled by emerging 3D printing methods—for the deterministic control of multiphase flow, transport and reaction processes. We show that flow in these structures can be ‘programmed’ through architected design of cell type, size and relative density. We demonstrate gas–liquid transport processes such as transpiration and absorption, using evaporative cooling and CO 2 capture as examples. We design and demonstrate preferential liquid and gas transport pathways in three-dimensional cellular fluidic devices with capillary-driven and actively pumped liquid flow, and present examples of selective metallization of pre-programmed patterns. Our results show that the design and fabrication of architected cellular materials, coupled with analytical and numerical predictions of steady-state and dynamic behaviour of multiphase interfaces, provide deterministic control of fluidic transport in three dimensions. Cellular fluidics may transform the design space for spatial and temporal control of multiphase transport and reaction processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗