AmeriFlux US-INg INFLUX - Wayne Twp Comm (Site-7)
This is the AmeriFlux version of the carbon flux data for the site US-INg INFLUX - Wayne Twp Comm (Site-7). Site Description - Urban site, tower is a lattice communications tower
Forsythe, Brandon R↗
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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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ChatPORT: Fine-Tuned LLM for Easy Code {PORT}ing
Fine-tuning existing LLMs for specialized tasks has become a very attractive alternative due to its low cost and quick development cycle. With many pre-trained LLMs available, it is an increasingly complex task to choose the correct model as the starting point or base model. In this work we discuss ChatPORT - a specialized fine-tuned LLM geared towards providing correctly translated codes from one programming model to another. We evaluate a number of base models and compare and contrast their features and characteristics that make them a viable starting point. In this paper, we focus on the OpenMP offload porting capabilities of ChatPORT. We build our training data using kernels from the Heterogeneous Computing Benchmarks (HeCBench) [12] and the OpenMP Validation and Verification suite [5] to fine-tune the base models. We then test the model using unseen kernels extracted from the HeCBench benchmark suite. Our results show that: (1) not all open LLMs geared towards HPC are aware of programming models like OpenMP, (2) although all base models benefit from fine-tuning they learn differently and produce different correctness rates, (3) depending on the memory size and compute resource available, different base models can be used for fine-tuning without significantly affecting the quality of transpiled code they generate, (4) fine-tuning improved the correctness rate of the LLM by an average of 43.2%, and (5) feedback-based training data further increased the correctness rate by an average of 6% over the LLMs tested.
Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗
Get ROL-ing: An Introduction to Sandia's Rapid Optimization Library.
Abstract not provided.
Kouri, Drew↗
Harnessing Carbon: A Review of Current Technologies for Transform-ing Methane into Value-added Products
The concern over greenhouse gases, methane (CH 4 ) and carbon dioxide (CO 2 ), is increasing rapidly. There have been strides to find solutions to this global issue but there is not a clear path to a successful end goal. The concentration of CH 4 and CO 2 in the atmosphere has increased significantly over the last 60 years, methane is a great source of concern due to its ability to trap a high amount of heat in the atmosphere. These greenhouse gases contribute to global warming which has caused changes in the environment, including the melting of ice caps, and altered weather patterns. This review investigates biotechnology that has promising potential to aid in the mitigation of the negative effects methane has on the environment by exploring microorganisms, specifically methanotrophs, for their ability to convert methane into secondary value-added products that can be used for a wide range of applications. Methane as a feedstock could provide financial benefits due to the vast amount of methane available from sources like landfills, wastewater treatment plants, and agricultural sites. Furthermore, this review will look at the prospects of bioreactor technology and the potential for more environmentally friendly plastics, such as polyhydroxyalkanoate (PHA), to shy away from traditional petroleum-based plastics. The continuous advancement of bioreactor technology is crucial to mitigating greenhouse gas emissions.
36 MATERIALS SCIENCE↗
DELVE-ing into the Jet: A Thin Stellar Stream on a Retrograde Orbit at 30 kpc
We perform a detailed photometric and astrometric analysis of stars in the Jet stream using data from the first data release of the DECam Local Volume Exploration Survey DR1 and Gaia EDR3. We discover that the stream extends over ∼ 29° on the sky (increasing the known length by 18°), which is comparable to the kinematically cold Phoenix, ATLAS, and GD-1 streams. Using blue horizontal branch stars, we resolve a distance gradient along the Jet stream of 0.2 kpc deg$^{−1}$, with distances ranging from D $_{⊙}$ ∼ 27–34 kpc. We use natural splines to simultaneously fit the stream track, width, and intensity to quantitatively characterize density variations in the Jet stream, including a large gap, and identify substructure off the main track of the stream. Furthermore, we report the first measurement of the proper motion of the Jet stream and find that it is well aligned with the stream track, suggesting the stream has likely not been significantly perturbed perpendicular to the line of sight. Finally, we fit the stream with a dynamical model and find that it is on a retrograde orbit, and is well fit by a gravitational potential including the Milky Way and Large Magellanic Cloud. These results indicate the Jet stream is an excellent candidate for future studies with deeper photometry, astrometry, and spectroscopy to study the potential of the Milky Way and probe perturbations from baryonic and dark matter substructure.
79 ASTRONOMY AND ASTROPHYSICS↗
DELVE-ing into the Milky Way’s Globular Clusters: Assessing Extratidal Features in NGC 5897, NGC 7492, and Testing Detectability with Deeper Photometry
Extratidal features around globular clusters (GCs) are tracers of their disruption, stellar stream formation, and their host’s gravitational potential. However, these features remain challenging to detect due to their low surface brightness. We conduct a systematic search for such features around 19 GCs in the DECam Local Volume Exploration (DELVE) survey Data Release 2, discovering a new extra-tidal envelope around NGC 5897 and find tentative evidence for an extended envelope surrounding NGC 7492. Through a combination of dynamical modeling and analyzing synthetic stellar populations, we demonstrate these envelopes may have formed through tidal disruption. We use these models to explore the detectability of these features in the upcoming Legacy Survey of Space and Time (LSST), finding that while LSST’s deeper photometry will enhance detection significance, additional methods for foreground removal like proper motions or metallicities may be important for robust stream detection. Our results both add to the sample of globular clusters with extratidal features and provide insights on interpreting similar features in current and upcoming data.
Chiti, A. [Univ. of Chicago, IL (United States); S↗
Auto-HPCnet: An Automatic Framework to Build Neural Network-based Surrogate for High-Performance Computing Applications
High-performance computing communities are increasingly adopt- ing Neural Networks (NN) as surrogate models in their applications to generate scientific insights. Replacing an execution phase in the application with NN models can bring significant performance im- provement. However, there is a lack of tools that can help domain scientists automatically apply NN-based surrogate models to HPC applications. We introduce a framework, named Auto-HPCnet, to democratize the usage of NN-based surrogates. Auto-HPCnet is the first end-to-end framework that makes past proposals for the NN-based surrogate model practical and disciplined. Auto-HPCnet introduces a workflow to address unique challenges when apply- ing the approximation, such as feature acquisition and meeting the application-specific constraint on the quality of final computation outcome. We show that Auto-HPCnet can leverage NN for a set of HPC applications and achieve 5.50× speedup on average (up to 16.8× speedup and with data preparation cost included) while meeting the application-specific constraint on the final computation quality.
Dong, Wenqian↗
Improved Beam Loss Accounting with Fast Data Acquisition (DAQ) Chassis
Identifying the source of beam loss events in the CE-BAF accelerator can be a challenging task. However, with our new prototype system, this task becomes more effi-cient. The system, developed in the fall of 2022, utilizes a dispersive beam position monitor (BPM) and the exist-ing switched electrode electronics BPM hardware. Previ-ously a commercial off-the-shelf data acquisition (DAQ) system was employed to capture BPM wire signals at a sample rate of 20 kS/s. The fast shutdown signal triggered the system, which disables the beam at the injector. Analysis of beam position and energy variation before a beam loss event was used to determine if the beam loss event was associated with an energy transient. The proto-type system, implemented using National Instruments hardware and LabVIEW® software, relied on a software trigger. Manual post-processing was required to ascertain whether the fault was due to an un-tripped cavity with a gradient or phase transient. This work focuses on deploying a Fast DAQ Chassis to monitor BPM hardware in real time and during beam loss events. This system was originally developed and in-stalled in CEBAF to monitor the time-domain RF control signals in the legacy analog RF systems. This technology was leveraged to also monitor BPM signals. As the new system employs a hardware trigger, developing tools to automatically identify faults linked to energy transients unrelated to cavity faults will be straightforward. This paper will discuss the project's initial updates, underlin-ing the crucial role of each member of our team in this achievement
Tiskumara, J.↗
Development and Evaluation of a General Drag Model for Gas-Solid Flows via Deep Learning
This project presents the development and evaluation of a general drag model for gas–solid multiphase flows using deep learning techniques. A comprehensive database of more than 4,000 experimental and numerical data points for spherical and non spherical particles was compiled, incorporating geometric features such as sphericity, aspect ratio, and orientation. Several predictive approaches—including traditional em pirical correlations, machine learning, and deep neural networks—were benchmarked, with the proposed Drag Coefficient Correlation-aided Deep Neural Network (DCC DNN) demonstrating superior accuracy. To account for particle–particle interactions, additional drag data were generated using CFD-based simulations of packed and flu idized beds, leading to the development of a retrained model capable of incorporat ing volume fraction effects. Integration of the trained model with the MFiX CFD solver was achieved using FTorch, enabling drag predictions during discrete element method (DEM) simulations. Validation against experimental data for single particles and fluidized beds confirmed the model’s improved predictive ability, particularly for non-spherical geometries. While the model performed strongly under fluidized con ditions, limitations remained in unfluidized regimes, suggesting a need for expanded datasets. Overall, this study demonstrates the feasibility of combining deep learning with physics-informed CFD to improve drag modeling for gas–solid flows, with promis ing implications for scaling multiphase simulations in industrial applications.
42 ENGINEERING↗
Mercury’s Chaotic Secular Evolution as a Subdiffusive Process
Abstract Mercury’s orbit can destabilize, generally resulting in a collision with either Venus or the Sun. Chaotic evolution can causeg 1 to decrease to the approximately constant value ofg 5 and create a resonance. Previous work has approximated the variation ing 1 as stochastic diffusion, which leads to a phenomological model that can reproduce the Mercury instability statistics of secular andN-body models on timescales longer than 10 Gyr. Here we show that the diffusive model significantly underpredicts the Mercury instability probability on timescales less than 5 Gyr, the remaining lifespan of the solar system. This is becauseg 1 exhibits larger variations on short timescales than the diffusive model would suggest. To better model the variations on short timescales, we build a new subdiffusive phenomological model forg 1 . Subdiffusion is similar to diffusion but exhibits larger displacements on short timescales and smaller displacements on long timescales. We choose model parameters based on the behavior of theg 1 trajectories in theN-body simulations, leading to a tuned model that can reproduce Mercury instability statistics from 1–40 Gyr. This work motivates fundamental questions in solar system dynamics: why does subdiffusion better approximate the variation ing 1 than standard diffusion? Why is there an upper bound ong 1 , but not a lower bound that would prevent it from reachingg 5 ?
Astronomy & Astrophysics↗
Scaling Equitable Finance
Driven by dramatic declines in up-front cost, the U.S. solar photovoltaics (PV) industry has taken off over the past decade, growing from 1 gigawatt of installed capacity in 2009 to 89 gigawatts in 2020—or enough capacity to power roughly 19 million homes. The industry is expected to double in size over just the next 5 years.1 Much of the growth has been driven by large, utility-scale projects that can produce 5 mega- watts or more of power—enough to power at least 1,000 homes. The cost of electricity produced by these projects has decreased by more than 70 percent since 2010. As of Q3 2020, development costs of large, util- ity-scale solar PV power plants were under $1 per watt, down by more than 70 percent from 2010.2 A robust array of investors has come forward to efficiently deliver capital to these kinds of utility-scale projects including large banks, insurance companies, pension funds, and others. But low- and moderate-income communities, including communities of color, are at risk of being left behind in the transition to clean energy. Mission- driven solar project developers and financial institu- tions have been working alongside energy justice advocates to open up solar access for these communi- ties, using strategies ranging from community solar, to solar installations on affordable multifamily housing, to distributed solar and storage programs, and more. Their goals go beyond simply generating more green energy to advancing social equity by: • empowering communities to control their energy future • stabilizing energy prices, saving money, and build- ing wealth for low-income families • creating quality jobs • improving health by reducing pollution • providing energy resilience for vulnerable communities Mission-driven actors are successfully deploying a wide variety of strategies to meet these goals, from helping low-income homeowners get solar—and some- times battery storage, to developing solar projects serv- ing affordable rental housing and community facilities, to building larger “shared solar” projects to which households from across the community can subscribe. However, the financing ecosystem does not work nearly as well for these “mission driven” solar proj- ects as it does for utility-scale projects. For home rooftop solar, even if low-income consumers have a home and suitable roof, they may fail to qualify for federal tax incentives, lack adequate credit to qualify for a loan—or the mission-driven lenders seeking to serve them may not be adequately capitalized to make long-term loans. For mission-driven commercial or community-scale projects, assembling nearly every component of the project capital stack—whether bridging early-stage costs, attracting tax credit equity investors, securing long-term debt, or coming up with sponsor equity and filling gaps—can present challenges. A variety of obstacles contribute to the scarcity of financing for low-income solar, including small project sizes, lack of developer balance sheet capacity, both real and perceived issues with credit risk, elevated technical assistance needs, and greater subsidy requirements to pursue goals such as deep energy affordability, climate resilience, or job creation. Still other obstacles are regulatory: for example, not all states allow community solar projects or Power Purchase Agreements, common strategies used for providing low-income solar—and the potential for regulations to shift over time creates risks that mission-driven projects can ill afford. This report synthesizes information garnered from 47 key informant interviews, four focus group discus- sions involving 60 stakeholders, and a review of the substantial existing literature on low-income solar finance to assess the current landscape of mission- driven solar development in the United States, examine the roles that community-based financial institutions could play, and recommend public invest- ments and policy changes that could help to scale the provision of equitable solar finance. Key recommen- dations for policymakers and funders in the renew- able energy and community development fields that emerge from this process include the following: • Help to capitalize and support community-based lenders to provide flexible, low-cost, and long- term financing to mission-driven solar projects— including providing guarantees or other forms of credit enhancement. • Provide federal support for equitable solar, including a grant-in-lieu-of-credits option for the Investment Tax Credit to improve access to this critical government subsidy. • Develop pools of government and philanthropic support that can complement financing from community-based lenders to complete the capi- tal stack for mission-driven projects, as well as to support education and technical assistance to both consumers and potential project sponsors. • Create a national Renewable Energy Credits pro- gram that includes social equity targets to provide a baseline of support for clean energy generation. • Change utility regulations to remove barriers to low-income solar projects; lower permitting costs; provide greater certainty for developers, consumers and owners; and measure progress toward equity in renewable energy policy implementation.
14 SOLAR ENERGY↗
GrayQb: A Radiological Contamination Locating and Mapping Tool
Benefits Technology Overview Easy to operate • Self-contained unit for imaging – no special power, cooling or handling requirements • Standard color camera, easy to use gamma camera and reader • Software automatically processes images, sliders to adjust intensity display • Lightweight – less than 5 lbs. without additional background shielding
Timmons, Daren↗
Evaluating the Hybrid Modelling Competition: A Step Towards Developing Good Modelling Practice
Hybrid modelling, a combination of mechanistic and data-driven modelling, is a promis¬ing approach to advance current mathematical models towards improved deci¬sion support tools for today's water-related challenges. Researchers have been develop¬ing guidelines or references for good modelling practices in the water field for mecha¬nistic (Rieger et al., 2012) and data-driven (Zhu et al., 2023) modelling, respectively. However, good modelling practices for hybrid modelling are currently missing (Schneider et al., 2022). Therefore, the International Water Association’s (IWA) hybrid modelling working group initiated the first competition on a data science competition platform (i.e. Kaggle) for water resource recovery modelling at the Watermatex con¬ference in September 2023 in Quebec. The main objective of this competition was to gain insights and experience to create good modelling practices. Further goals were to motivate students, researchers, and practitioners model, foster a vibrant and engaged community, and evaluate the efficacy of com¬petitions in solving modelling challenges within the water domain. Our next goal is that facilities will measure and gather relevant data for future competitions to solve their challenges from a modeller’s perspective.
Schneider, Mariane↗
Reflections on the role of MOOSE in Unleashing a Golden Era of American Energy Innovation
As the use of artificial intelligence spreads across most professions, projections for the expected energy consumption of these virtual assistants/workers dictate a large increase in energy production. Recent published estimates refer to up to a necessary tripling of nuclear energy production~\cite{iaea}. % TODO add citations This is supported by the new administration, calling on February 5th to "unleash Commercial Nuclear Power in the United States" and to launch the "long-awaited American nuclear renaissance"~\cite{doe-order}. The Department of Energy (DOE) is tasked with "enabl[ing] the rapid deployment and export of next generation nuclear technology". In terms of research of development, we must seek to "unleash American Energy Innovation", by "focus[ing] our time and resources on technologies that will advance basic science, grow America’s scientific leadership, reduce costs for American families [...]". To that end, the Department will "prioritize affordable, reliable, and secure energy technologies, including fossil fuels, advanced nuclear, geothermal, and hydropower." Following this call to action, we elect to examine the role of the open-source Multiphysics Object Oriented Simulation Environment (MOOSE)~\cite{moose3} in meeting the stated goals.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
Vapor–Fed Electrolyzers for Carbon Dioxide Reduction Using Tandem Electrocatalysts: Cuprous Oxide Coupled with Nickel–Coordinated Nitrogen–Doped Carbon
We report ethylene is particularly attractive due to its major importance as a feedstock for various applications including the polymer industry. As such, catalyst and electrolyzer developments are crucial to achieve industrially relevant ethylene production and efficiency levels. In this work, a tandem electrocatalyst composed of copper nanocubes and nickel-coordinated nitrogen-doped carbon (NiNC) is presented, which is integrated into gas diffusion electrodes (GDEs) for direct conversion of vapor-fed CO 2 into ethylene. Evaluation of tandem GDEs in the vapor-fed flow electrolyzer shows significantly increased ethylene selectivity in terms of faradaic efficiency and C 2 H 4 /CO ratio compared to a non-tandem copper GDE. The enhancements are attributed to the increased local CO availability near the copper surface via effective CO 2 to CO conversion on neighboring NiNC. The experimental results are validated by 3D resolved continuum simulations, which show increased flux of higher-order prod-ucts with the added CO flux from NiNC. The practical viability of Cu/NiNC catalyst is further evaluated in a membrane electrode assembly electrolyzer, achieving 40% FE toward ethylene at 150 mA cm -2 and 3.2 V. These find-ings highlight the high selectivity and formation rate of ethylene achieved by successful device integration of the Cu/NiNC catalyst, demonstrating the potential for implementation in large-scale sustainable CO 2 electrolyzers.
36 MATERIALS SCIENCE↗
Enhancing and Extinguishing the Different Emission Features of 2D (EA(1-)(x)FA(x))(4)Pb3Br10 Perovskite Films
2D hybrid perovskites are attractive for optoelectronic devices. In thin films, the color of optical emission and the texture of crystalline domains are often difficult to control. Here, a method for extinguishing or enhancing different emission features is demonstrated for the family of 2D Ruddlesden-Popper perovskites (EA(1-)(x)FA(x))(4)Pb3Br10 (EA = ethylammonium, FA = formamidinium). When grown from aqueous hydrobromic acid, crystals of (EA(1-)(x)FA(x))(4)Pb3Br10 retain all the emission features of their parent compound, (EA)(4)Pb3Br10. Surprisingly, when grown from dimethylformamide (DMF), an emission feature, likely self-trapped exciton (STE), near 2.7 eV is missing. Extinction of this feature is correlated with DMF being incorporated between the 2D Pb-Br sheets, forming (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y). Without FA, films grown from DMF form (EA)(4)Pb3Br10, retain little solvent, and have strong emission near 2.7 eV. Slowing the kinetics of film growth strengthens a different emission feature, likely a different type of STE, which is much broader and present in all compositions. Films of (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y) have large, micron-sized domains and homogeneous orientation of the semiconducting sheets, resulting in low electronic disorder near the absorption edge. The ability to selectively strengthen or extinguish different emission features in films of (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y) reveals a pathway to tune the emission color in these compounds.
2D halide perovskites↗
Glucose assimilation rate determines the partition of flux at pyruvate between lactic acid and ethanol in Saccharomyces cerevisiae
Engineered Saccharomyces cerevisiae expressing a lactic acid dehydrogenase can metab- olize pyruvate into lactic acid. However, three pyruvate decarboxylase (PDC) isozymes drive most carbon flux toward ethanol rather than lactic acid. Deletion of endoge- nous PDCs will eliminate ethanol production, but the resulting strain suffers from C 2 auxotrophy and struggles to complete a fermentation. Engineered yeast assimilating xylose or cellobiose produce lactic acid rather than ethanol as a major product with- out the deletion of any PDC genes. We report here that sugar flux, but not sensing, contributes to the partition of flux at the pyruvate branch point in S. cerevisiae express- ing the Rhizopus oryzae lactic acid dehydrogenase (LdhA). While the membrane glucose sensors Snf3 and Rgt2 did not play any direct role in the option of predominant product, the sugar assimilation rate was strongly correlated to the partition of flux at pyruvate: fast sugar assimilation favors ethanol production while slow sugar assimilation favors lactic acid. Applying this knowledge, we created an engineered yeast capable of simultaneously converting glucose and xylose into lactic acid, increasing lactic acid production to approximately 17 g L –1 from the 12 g L –1 observed during sequential consumption of sugars. This work elucidates the carbon source-dependent effects on product selection in engineered yeast.
59 BASIC BIOLOGICAL SCIENCES↗