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Blade: A package for block-triangular form improved Feynman integrals decomposition
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Recommendations for improving rigor and reproducibility in site specific characterization
Heterogeneous catalysis is driven by the interaction of reactant molecules and the catalyst surface. The locus of this interaction as well as the surrounding ensemble of atoms is referred to as the catalyst active site. Active site characterization attempts to distinguish active catalytic sites from inactive surface sites, to elucidate the structural and chemical nature of active sites, and to quantify active site concentration. Numerous techniques have been demonstrated to provide compositional and structural information about the active sites within a catalyst. However, each technique has its own limitations and experimental pitfalls that can lead to data misinterpretation or irreproducible results. Further, this work aims to provide an overview of the types of data that can be collected, to outline common experimental challenges and how to avoid them, and to assemble relevant references for the most used active site characterization techniques. More broadly, we aim to outline best practices for researchers to collect, interpret, and report active site characterization data in a way that provides the most benefit to the broader catalysis community. Increasing the rigor and reproducibility of active site characterization offers a strategy to better link properties with catalytic performance and to enable the community to develop consensus concerning these relationships.
High-Level Reverse Intersystem Crossing and Molecular Rigidity Improve Spin Statistics for Triplet–Triplet Annihilation Upconversion
The structural factors affecting triplet−triplet annihilation (TTA) at the molecular level are not well-understood. Here, our steady-state photoluminescence and transient absorption results demonstrate that the spin statistical factor, η, decreases from 0.60 to 0.46 and 0.14 going from 9,10-diphenylanthracene (DPA) to the 1,5-DPA and 2,6-DPA isomers, respectively, during photon upconversion with a platinum octaethylporphyrin sensitizer. Density functional theory (DFT) shows that η depends on the energetics of hot triplet states and molecular rigidity. The significantly high conical intersection energy between the S 0 and T 1 states for 9,10-DPA gives its longer triplet lifetime. Time-dependent DFT calculations show that 9,10-DPA and 1,5-DPA can undergo high-level reverse intersystem crossing from their T 2 and T 3 states, respectively, to the bright S 1 state, increasing the limit of the spin statistical factor. Both factors ultimately serve to enhance the TTA efficiency. Furthermore, this work provides insight into designing molecules for efficient light-emitting and photon upconversion applications.
Improving nuclear data evaluations with predictive reaction theory and indirect measurements
Nuclear reaction data required for astrophysics and applications is incomplete, as not all nuclear reactions can be measured or reliably predicted. Neutron-induced reactions involving unstable targets are particularly challenging, but often critical for simulations. In response to this need, indirect approaches, such as the surrogate reaction method, have been developed. Nuclear theory is key to extract reliable cross sections from such indirect measurements. We describe ongoing efforts to expand the theoretical capabilities that enable surrogate reaction measurements. We focus on microscopic predictions for charged-particle inelastic scattering, uncertainty-quantified optical nucleon-nucleus models, and neural-network enhanced parameter inference.
Improving streamflow predictions across CONUS by integrating advanced machine learning models and diverse data
Accurate streamflow prediction is crucial to understand climate impacts on water resources and develop effective adaption strategies. A global long short-term memory (LSTM) model, using data from multiple basins, can enhance streamflow prediction, yet acquiring detailed basin attributes remains a challenge. To overcome this, we introduce the Geo-vision transformer (ViT)-LSTM model, a novel approach that enriches LSTM predictions by integrating basin attributes derived from remote sensing with a ViT architecture. Applied to 531 basins across the Contiguous United States, our method demonstrated superior prediction accuracy in both temporal and spatiotemporal extrapolation scenarios. Geo-ViT-LSTM marks a significant advancement in land surface modeling, providing a more comprehensive and effective tool for better understanding the environment responses to climate change.
Deletion of biofilm synthesis in Eubacterium limosum ATCC 8486 improves handling and transformation efficiency
Abstract Eubacterium limosum is an acetogenic bacterium of potential industrial relevance for its ability to efficiently metabolize a range of single carbon compounds. However, extracellular polymeric substance (EPS) produced by the type strain ATCC 8486 is a serious impediment to bioprocessing and genetic engineering. To remove these barriers, here we bioinformatically identified genes involved in EPS biosynthesis, and targeted several of the most promising candidates for inactivation, using a homologous recombination-based approach. Deletion of a single genomic region encoding homologues for epsABC, ptkA, and tmkA resulted in a strain incapable of producing EPS. This strain is significantly easier to handle by pipetting and centrifugation, and retains important wild-type phenotypes including the ability to grow on methanol and carbon dioxide and limited oxygen tolerance. Additionally, this strain is also more genetically tractable with a 2-fold increase in transformation efficiency compared to the highest previous reports. This work advances a simple, rapid protocol for gene knockouts in E. limosum using only the native homologous recombination machinery. These results will hasten the development of this organism as a workhorse for valorization of single carbon substrates, as well as facilitate exploration of its role in the human gut microbiota.
Improved Decarbonization Planning through Climate Resiliency Modeling
California has set ambitious decarbonization goals concerning both emissions and the portion of energy generated by renewable resources. However, climate change poses considerable uncertainties. Variation in load is driven both by the level of electrification as well as the impact of climate change on weather. Further, climate change stands to make weather more variable, impacting not just load but generation from renewable resources. In this paper, we approach the issue of the impacts of climate change on decarbonization planning from two perspectives. First, we look at the range of decarbonization pathways through 8 pathways that account for differences in socioeconomic development, global emissions, and warming. Second, we develop a more robust way of ensuring the reliability of energy resources planning than the commonly used planning reserve margin. We show that the proposed method can save between 6 and 14 billion dollars in investment and maintenance costs and outline critical policy implications concerning the reliance of power plants for satisfying planning reliability requirements, including the potential retirement of dozens of peaker power plants.
Improving Frequency Stability and Minimizing Load Shedding Events by Adopting Grid-Scale Energy Storage with Grid Forming Inverters
The upward adoption trend of renewable generation not only means cleaner energy integrated into modern power grids, but also that most new generation sources are based on front-end inverter bridges, used as interfaces to most wind generation and all the solar PV. It is well known that due to their power electronics-based construction rather than rotational shafts, these sources do not provide inertia inherently, nor substantial amounts of short-circuit currents. However, stable energy such as what can be stored in energy storage systems, although interfaced via inverters, can be controlled to respond to system disturbances in a manner that emulates inertial behavior. This paper focuses on the application of such energy storage systems to augment inertia in the island of Puerto Rico. To do so, a user defined inverter model that contains grid forming capabilities and fast frequency response is modeled and integrated into the real transmission system in power flow and dynamics software. Energy storage is then connected to two selected areas so that it not only provides frequency regulation to avoid widespread load shedding events, but also other tangible benefits. The simulated cases suggest that even relatively small energy storage systems can avert load shedding events if adequately placed in the transmission network.
Demonstration of Improved CHP Systems utilizing Improved Gas Turbine and sCO2 Cycles Using Additive Manufacturing (AM) Components
This project seeks to integrate a sCO2 bottoming cycle with a 5.3 MW gas turbine to develop a CHP system that is able to transition rapidly between 50% and 100% load by engaging or bypassing the bottoming cycle while maintaining electrical system efficiency above 30% at all times. The project team will engineer an optimized design of the power systems. The needed new key components, such as advanced heat exchangers and a steam injection system for the gas turbine, will be developed and their performance demonstrated in rig tests. The feasibility of the whole integrated CHP system will be validated through a cyber-physical approach.
CF6 jet engine performance improvement program. Short core exhaust nozzle performance improvement concept
The short core exhaust nozzle was evaluated in CF6-50 engine ground tests including performance, acoustic, and endurance tests. The test results verified the performance predictions from scale model tests. The short core exhaust nozzle provides an internal cruise sfc reduction of 0.9 percent without an increase in engine noise. The nozzle hardware successfully completed 1000 flight cycles of endurance testing without any signs of distress.
Improved canopy reflectance modeling and scene inference through improved understanding of scene pattern
The Li-Strahler reflectance model, driven by LANDSAT Thematic Mapper (TM) data, provided regional estimates of tree size and density within 20 percent of sampled values in two bioclimatic zones in West Africa. This model exploits tree geometry in an inversion technique to predict average tree size and density from reflectance data using a few simple parameters measured in the field (spatial pattern, shape, and size distribution of trees) and in the imagery (spectral signatures of scene components). Trees are treated as simply shaped objects, and multispectral reflectance of a pixel is assumed to be related only to the proportions of tree crown, shadow, and understory in the pixel. These, in turn, are a direct function of the number and size of trees, the solar illumination angle, and the spectral signatures of crown, shadow and understory. Given the variance in reflectance from pixel to pixel within a homogeneous area of woodland, caused by the variation in the number and size of trees, the model can be inverted to give estimates of average tree size and density. Because the inversion is sensitive to correct determination of component signatures, predictions are not accurate for small areas.
NextGen Operational Improvements: Will they Improve Human Performance
Modernization of the National Airspace System depends critically on the development of advanced technology, including cutting-edge automation, controller decision-support tools and integrated on-demand information. The Next Generation Air Transportation System national plan envisions air traffic control tower automation that proposes solutions for seven problems: 1) departure metering, 2) taxi routing, 3) taxi and runway scheduling, 4) departure runway assignments, 5) departure flow management, 6) integrated arrival and departure scheduling and 7) runway configuration management. Government, academia and industry are simultaneously pursuing the development of these tools. For each tool, the development process typically begins by assessing its potential benefits, and then progresses to designing preliminary versions of the tool, followed by testing the tool's strengths and weaknesses using computational modeling, human-in-the-loop simulation and/or field tests. We compiled the literature, evaluated the methodological rigor of the studies and served as referee for partisan conclusions that were sometimes overly optimistic. Here we provide the results of this review.
Adding a Pinch of Salt Improves El Niño Models Salinity Data from Satellites Improves our Understanding of the Ocean's Upper Layers... and the Large-scale Waves that Travel Through Them
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Improving Bondline Time of Flight Predictions Utilizing Machine Learning and Hardware Improvements
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Implementation of Improved Parameterization of Terrestrial Flux in WRF‐VPRM Improves the Simulation of Nighttime CO 2 Peaks and a Daytime CO 2 Band Ahead of a Cold Front
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