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At least 703 records · Page 39

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DOE OSTI2018

Identification of Selective Dual ROCK1 and ROCK2 Inhibitors Using Structure-Based Drug Design

A HTS campaign identified compound 1, an excellent hit-like molecule to initiate medicinal chemistry efforts to optimize a dual ROCK1 and ROCK2 inhibitor. Substitution (2-Cl, 2-NH 2 , 2-F, 3-F) of the pyridine hinge binding motif or replacement with pyrimidine afforded compounds with a clean CYP inhibition profile. Cocrystal structures of an early lead compound were obtained in PKA, ROCK1, and ROCK2. This provided critical structural information for medicinal chemistry to drive compound design. The structural data indicated the preferred configuration at the central benzylic carbon would be $(R)$, and application of this information to compound design resulted in compound 16. This compound was shown to be a potent and selective dual ROCK inhibitor in both enzyme and cell assays and efficacious in the retinal nerve fiber layer model after oral dosing. This tool compound has been made available through the AbbVie Compound Toolbox. Finally, the cocrystal structures also identified that aspartic acid residues 176 and 218 in ROCK2, which are glutamic acids in PKA, could be targeted as residues to drive both potency and kinome selectivity. Introduction of a piperidin-3-ylmethanamine group to the compound series resulted in compound 58, a potent and selective dual ROCK inhibitor with excellent predicted drug-like properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Effects of transmission line geometry on traveling-wave metal-insulator-metal rectenna infrared detectors

The transmission line impedance of traveling-wave diodes can circumvent resistance-capacitance time constant limitations of metal-insulator-metal diodes in rectennas operating at optical frequencies. We performed three-dimensional simulations of a traveling-wave diode rectenna using a linear finite-element electromagnetic solver. We develop a method to analyze metal-insulator-metal traveling-wave rectennas by using the field profiles from the linear finite-element solver and accounting for the nonlinear current-voltage characteristics during postprocessing. The traveling-wave diode length produces resonance at half surface plasmon wavelength intervals. With optimized cross section and length parameters, we observe a peak system responsivity of 239μA/W and a detectivity of 5.7×10 4 Jones.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Improving ideal MHD equilibrium accuracy with physics-informed neural networks

We present a novel approach to compute three-dimensional magnetohydrodynamic equilibria with isotropic pressure profiles and nested surfaces by parametrizing Fourier modes with artificial neural networks (NNs). The full nonlinear global force residual of single equilibria across the volume in real space is then minimized with first order optimizers and compared to equilibria computed by conventional solvers. Already, we observe competitive computational cost to arrive at the same minimum residuals computable with existing codes. With increased computational cost, lower minima of the residual are computable with the NNs than with any other tested solver, establishing a new lower bound for the force residual. We use minimally complex NNs, and we expect significant improvements for solving not only single equilibria with NNs, but also for creating NN models valid over continuous distributions of equilibria.

ideal magnetohydrodynamics↗

DOE OSTI2021

Key Learnings from Hydraulic Fracturing Test Site - 2 (HFTS-2), Delaware Basin

Hydraulic fractures (HF) play a dominant role in oil and gas production from unconventional reservoirs, fracture characteristics, geometry, and extent are generally not well known and are typically inferred from various monitoring methods or subsurface models. The Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp formation of the Permian (Delaware) Basin. HFTS-2, a unique joint industry program (JIP) that brings together government, academia, and industry, focused on field data acquisition and interpretation. The project has built a comprehensive HF research dataset that includes microseismic (MS), 1,500 ft of core, diagnostic formation injection tests (DFIT), fluid characterization, advanced logs, geochemistry, downhole gauges, varying completions, and permanent fiber optic (FO) cable in vertical and horizontal wells. These data were integrated and used to characterize HF geometry/dimensions and resulting depletion profiles, gain insights for completion design, and achieve a better understanding of parent well depletion effects on child well performance. The analysis and integration of the comprehensive HFTS-2 diagnostics dataset provide insights for optimal well placement and completions and improves understanding about the effects of parent well depletion. Furthermore, this dataset can be used to blind test and develop subsurface workflows for unconventional resources. Key learnings from HFTS-2 and the new technologies tested can easily be transferred to other unconventional plays.

58 GEOSCIENCES↗

DOE OSTI2025

Robot-based Additive Manufacturing of Lego-type Modular Molds for Wind Blades

The objective of this project is to reduce the cost and lead time of horizontal wind turbine blade mold tooling and blade transportation, while maintaining the highest standards of blade quality. The solution involves a smart-design family of modular molds that are easily transportable to fabrication sites near the place of service. Key innovations include the use of additive manufacturing (AM) to integrate conformal thermal management channels, offering enhanced control over the thermal profiles tailored to specific blade materials. This approach enables in-situ quality assurance during mold fabrication, significantly improves mold life, and allows for reuse across multiple production cycles. Ultimately, the solution aims to optimize both tooling and transportation costs, contributing to the scalability of wind turbine blade production. A significant barrier to scaling up the production of large wind turbine blades lies in the high costs associated with tooling and the transportation of blades. Traditional molds are expensive, bulky, and difficult to transport, adding considerable lead time and cost to the overall manufacturing process. Additionally, transporting blades to distant locations for final assembly further exacerbates these challenges. The project aims to address these inefficiencies by demonstrating a modularized, additive-manufactured mold that meets all necessary blade specification requirements, specifically for blade lengths between 120m and 150m.

17 WIND ENERGY↗

DOE OSTI2020

The Link Between the Ecology of the Prokaryotic Rare Biosphere and Its Biotechnological Potential

Current research on the prokaryotic low abundance taxa, the prokaryotic rare biosphere, is growing, leading to a greater understanding of the mechanisms underlying organismal rarity and its relevance in ecology. From this emerging knowledge it is possible to envision innovative approaches in biotechnology applicable to several sectors. Bioremediation and bioprospecting are two of the most promising areas where such approaches could find feasible implementation, involving possible new solutions to the decontamination of polluted sites and to the discovery of novel gene variants and pathways based on the attributes of rare microbial communities. Bioremediation can be improved through the realization that diverse rare species can grow abundant and degrade different pollutants or possibly transfer useful genes. Further, most of the prokaryotic diversity found in virtually all environments belongs in the rare biosphere and remains uncultivatable, suggesting great bioprospecting potential within this vast and understudied genetic pool. This Mini Review argues that knowledge of the ecophysiology of rare prokaryotes can aid the development of future, efficient biotechnology-based processes, products and services. However, this promise may only be fulfilled through improvements in (and optimal blending of) advanced microbial culturing and physiology, metagenomics, genome annotation and editing, and synthetic biology, to name a few areas of relevance. In the future, it will be important to understand how activity profiles relate with abundance, as some rare taxa can remain rare and increase activity, whereas other taxa can grow abundant. The metabolic mechanisms behind those patterns can be useful in designing biotechnological processes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Radar-based Snow Property Profile Retrievals for NSA

The product contains estimated snow microphysical properties retrieved primarily from vertically-profiling radar observations using a priori constraints that are dependent on atmospheric state. The product provides data at 1-minute time resolution, including snowfall rate at the surface and vertical profiles at 300-meter resolution of snow particle size distribution parameters and snow water contents. Estimated uncertainties for the snowfall rates and snow water contents are also provided. The product is obtained using an optimal estimation retrieval in which radar forward model and a priori state characteristics are based on expected snow particle microphysical and radar scattering properties evaluated from field experiment data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Probing the optical properties and toxicological profile of zinc tungstate nanorods

Zinc tungstate is a semiconductor known for its favorable photocatalytic, photoluminescence, and scintillation properties, coupled with its relatively low cost, reduced toxicity, and high stability in biological and catalytic environments. In particular, zinc tungstate evinces scintillation properties, namely the ability to emit visible light upon absorption of energetic radiation such as x rays, which has led to applications not only as radiation detectors but also for biomedical applications involving the delivery of optical light to deep tissue, such as photodynamic therapy and optogenetics. Here, we report on the synthesis of zinc tungstate nanorods generated via an optimized but facile method, which allows for synthetic control over the aspect ratio of the as-synthesized anisotropic motifs via rational variation of the solution pH. Additionally, we investigate the effect of aspect ratio on their resulting photoluminescent and radioluminescent properties. We further demonstrate the potential of these zinc tungstate nanorods for biomedical applications, such as photodynamic therapy for cancer treatment, by analyzing their toxicological profile within cell lines and neurons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Near-optimal combination of high performance and insensitivity in a shock compressed high explosive single crystal

Achieving the desired combination of superior detonation performance and insensitivity to shock initiation has been a long-standing goal in high explosive (HE) science and technology. Having previously established the shock insensitivity of 1,1-diamino-2,2-dinitroethene (also known as DADNE or FOX-7) single crystals to 20 GPa (extended to 25 GPa in this work), the FOX-7 detonation response was determined through wave profile measurements in ~250 μm thick single crystals shock compressed to 64 GPa. Quite unexpectedly, FOX-7 demonstrated the classic Chapman–Jouguet (C–J) detonation response—reaction completion in the detonation front (<0.7 ns) at pressures of 44 GPa and higher—not observed in other insensitive high explosives. Here, the experimentally determined C–J pressure (35 GPa), detonation wave velocities and the detonation products equation of state—together with shock insensitivity to 25 GPa—demonstrate that FOX-7 single crystals display a near-optimal combination of high performance and shock insensitivity, not observed in another HE crystal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Physics‐based iterative reconstruction for dual‐source and flying focal spot computed tomography

Purpose For single‐source helical Computed Tomography (CT), both Filtered‐Back Projection (FBP) and statistical iterative reconstruction have been investigated. However, for dual‐source CT with flying focal spot (DS‐FFS CT), a statistical iterative reconstruction that accurately models the scanner geometry and acquisition physics remains unknown to researchers. Therefore, our purpose is to present a novel physics‐based iterative reconstruction method for DS‐FFS CT and assess its image quality. Methods Our algorithm uses precise physics models to reconstruct from the native cone‐beam geometry and interleaved dual‐source helical trajectory of a DS‐FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture. In addition, we design forward system models to compute the locations of deflected focal spots, the dimension, and sensitivity of voxels and detector units, as well as the length of intersection between x‐rays and voxels. The forward system models further represent the coordinated movement between the dual sources by computing their x‐ray coverage gaps and overlaps at an arbitrary helical pitch. With the above models, we reconstruct images by an advanced Consensus Equilibrium (CE) numerical method to compute the maximum a posteriori estimate to a joint optimization problem that simultaneously fits all models. Results We compared our reconstruction with Siemens ADMIRE, which is the clinical standard hybrid iterative reconstruction (IR) method for DS‐FFS CT, in terms of spatial resolution, noise profile, and image artifacts through both phantoms and clinical scan datasets. Experiments show that our reconstruction has a higher spatial resolution, with a Task‐Based Modulation Transfer Function (MTF task ) consistently higher than the clinical standard hybrid IR. In addition, our reconstruction shows a reduced magnitude of image undersampling artifacts than the clinical standard. Conclusions By modeling a precise geometry and avoiding data rebinning or interpolation, our physics‐based reconstruction achieves a higher spatial resolution and fewer image artifacts with smaller magnitude than the clinical standard hybrid IR.

Wang, Xiao↗

DOE OSTI2024

Hydrogen sensing in different hydrogen-carrying gases using composites of PdSnO 2 and halloysite nanotubes

Here, in this work, we developed composites of palladium-decorated tin dioxide (PdSnO 2 ) and halloysite nanotubes (HNTs) by adding different amounts of HNTs as additives into PdSnO 2 , and investigated how the different amounts of HNTs in the composites and the different hydrogen (H 2 ) carrying gases (air and helium (He)) could affect the H 2 sensing performance of such composites (PdSnO 2 -HNT). Through the sensing-performance characterization using H 2 carried by air, it was found that PdSnO 2 with an appropriate small amount of HNTs (i.e., 2 % of PdSnO 2 mass) can improve the sensing performance with respect to limit of detection (LOD) and response/recovery time. Further, the optimal PdSnO2-HNT composite as a sensor was tested to detect H 2 in He. The testing results indicated that the composite can detect H 2 in He, but its performance parameters (i.e., the profile of calibration curve, LOD, and response time) are different from those of such a sensor in detecting H 2 in air. Moreover, the composite still presented better sensing performance than PdSnO 2 without HNTs in detecting H 2 in He. Possible reasons for the effects of HNT and H 2 -carrying gas on the sensing performance of PdSnO 2 -HNT-based sensors were discussed. We believe that this study provides valuable insights into the functionality and the adaptability of PdSnO 2 -HNT-based H 2 sensors in diverse operational conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Evaluation of the response to electrons and pions in the scintillating fiber and lead calorimeter for the future electron-ion collider

The performance of the Baby Barrel Electromagnetic Calorimeter (Baby BCAL) — a small-scale lead-scintillating-fiber (Pb/ScFi) prototype of the GlueX Barrel Electromagnetic Calorimeter (BCAL) — was tested in a dedicated beam campaign at the Fermilab Test Beam Facility (FTBF). This study provides a benchmark for the Pb/ScFi component of the future Barrel Imaging Calorimeter (BIC) in the ePIC detector at the Electron-Ion Collider (EIC). The detector response to electrons and pions was studied at beam energies between 4 and 10 GeV, extending previous GlueX tests to a higher energy regime. The calibrated detector exhibits good linearity within uncertainties, and its electron energy resolution meets EIC requirements. The data further constrain the constant term in the energy resolution to below 1.9%, improving upon previous constraints at lower energies. Simulations reproduce key features of the electron and pion data within the limitations of the collected dataset and the FTBF test environment. Electron-pion separation in the test beam setup was analyzed using multiple methods, incorporating varying degrees of beam-related effects. The inclusion of longitudinal shower profile information enhanced the separation performance, underscoring its relevance for the full-scale BIC in ePIC. These results provide essential benchmarks for the Pb/ScFi section of the future BIC, validating detector simulations and guiding optimization strategies for electron-pion discrimination.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Optimized Highly Efficient SSCB Using Organic Substrate Packaging for Electric Vehicle Applications

Solid State Circuit Breakers (SSCBs) are an attractive protection solution for their arcless current interruption and fast actuation speeds over mechanical breakers. This paper proposes a Bidirectional SSCB (BSSCB) with a thermally defined and digitally controlled current time profile for fault protection in EV and other low-voltage DC systems. The paper proposes an organic packaging approach utilizing flex circuitry to develop a reliable, cost-effective power module for BSSCBs. The paper studies transient heat transfer in the power modules using finite element analysis (FEA). An RC themal ladder network is extracted to define a fusing curve. To demonstrate and verify the design, a 1kV/50 A SiC MOSFET BSSCB prototype is fabricated and tested, having a power density of 60 W/cm3 and 4x reduction in form factor over presently researched breakers. Also, given are results for 750 V/150 A operation showing interruption in 2.4 μs.

organic power packaging↗

DOE OSTI2025

Preliminary Study on Fine-Grained Power and Energy Measurements on Grace Hopper GH200 with Open-Source Performance Tools

The increasing adoption of tightly integrated, heterogeneous architectures, combined with the slowdown of Moore’s law, has made application power and energy-driven optimizations critical to efficiently use high-performance computing systems. This paper introduces a newly developed open-source toolkit that seamlessly integrates the Linux real-time hardware monitoring program hwmon with the Performance Application Programming Interface and the Score-P performance measurement system, thereby enabling fine-grained power and energy measurements for high-performance computing applications. Our primary target platform is the Wombat test bed, which is a system based on the NVIDIA GH200 superchip. The toolkit can capture transient power peaks with high temporal resolution (50 ms) and, thanks to Score-P integration, can map power metrics to specific code regions, thereby providing actionable information on power-intensive operations and inefficiencies. The toolkit also provides a holistic view of both the power and the energy consumption of the entire GH200 superchip by covering all major components: the Grace CPU, the Hopper GPU, and the I/O subsystem. Experiments that use Locally Self-consistent Multiple Scattering, which is an application for first-principles calculations of materials developed at Oak Ridge National Laboratory, have demonstrated the tool’s ability to identify transient power spikes and uncover opportunities for energy-aware optimizations. Additionally, we introduce a Python-based utility for converting Open Trace Format 2 traces to Parquet format, thus enabling advanced data analysis for numerical integration methods applied to power data for accurate energy profiling.

Hernandez Mendoza, Oscar [ORNL] (ORCID:00000002538↗

DOE OSTI2022

Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers

The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Latency Analysis of the Nexus Digital Twin Framework

Real-time digital catalogs are increasingly relied upon to track metadata and connect disparate data sources for cloud-based data integration efforts. One such tool, Deeplynx Nexus is supporting real-time digital twin efforts through event-driven data integration and time-series queries. Nexus’s usefulness for these applications depends critically on how quickly individual records can be uploaded and downloaded, since delays directly affect the responsiveness of any system built on top of it. However, the actual latency a user should expect from Nexus has not been systematically measured before, particularly for the small, frequent transactions typical of live sensor feeds. Here we show that single-record round-trip latency is 61.1 ms on a local Nexus instance and 391.7 ms on the hosted production infrastructure, a roughly 6.4x difference driven primarily by fixed per-request overhead rather than data volume. This overhead dominates at small scale: comparing single-record and ten-record trials suggests approximately 56 ms of each single-record request is fixed connection and authentication cost rather than data-transfer time, meaning batching even a handful of records is substantially more efficient than transmitting them individually. At large batch sizes, this pattern reverses for uploads, which converge to near parity between local and hosted environments by 25,000-50,000 records, while download latency remains persistently 5.7-6.4x slower on hosted infrastructure even at scale. These results suggest that Nexus deployments intended for real-time digital twin applications should prioritize record batching over single-record transactions, and that download-path optimization on hosted infrastructure offers the largest remaining opportunity to reduce latency at scale. We anticipate these baseline measurements will serve as a reference point for future digital twin projects evaluating whether Nexus’s latency profile meets their real-time requirements, and as a benchmark for tracking the effect of future infrastructure or API changes.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Energy and mobility impacts of connected autonomous vehicles with co-optimization of speed and powertrain on mixed vehicle platoons

Intersections are known to be traffic bottlenecks where a significant amount of energy consumption could be caused due to deceleration/acceleration in the presence of red signals. With an increased level of connectivity and automation of intelligent transportation systems, connected autonomous vehicles (CAVs) are expected to be able to proactively adjust their driving strategies subject to constraints imposed by the predicted future traffic. As a result, many potential benefits can be achieved, such as improved energy efficiency, enhanced traffic safety, among many others. Notably, the way CAVs are controlled affects the following legacy vehicles (LVs) due to complex traffic dynamics. Here, we are particularly interested in studying the energy and mobility impact of CAVs with an improved traffic prediction method on mixed vehicle platoons at various market penetration rates. Leveraging traffic prediction, CAVs are controlled with co-optimization of their speed and gear position. Specifically, a traffic prediction framework in a rolling horizon fashion is employed based upon a modified Payne–Whitham (PW) model capable of handling mixed traffic consisting of CAVs and LVs. The prediction error of the modified PW model is reduced by 53.62% compared to that of the standard PW model under test scenarios. According to the predicted traffic conditions, speed and gear position of CAVs are co-optimized with the primary goal of minimizing energy consumption when driving on a signalized arterial. The energy benefits achieved by CAVs and the impact of CAVs on LVs behind are studied comprehensively for mixed vehicle platoons. The lead LV follows a real-world speed profile collected on TH-55 in Minnesota. Numerical results show that energy benefits achieved by the vehicle platoon range from 2% to 16%, and a 1% to 5% reduction in travel time for LVs behind CAVs is also observed, at different penetration rates of CAVs in various traffic scenarios. Furthermore, it is observed that CAVs using the proposed eco-driving approach appear to have a positive impact on the LVs behind in terms of energy consumption, regardless of the driving styles of the LVs ahead.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Generation of entangled-photons by a quantum dot cascade source in polarized cavities: Using cavity resonances to boost signals and preserve the entanglements

Motivated by recent advances in the development of single photon emitters for quantum information sciences, here we design and formulate a quantum cascade model that describes cascade emission by a quantum dot (QD) in a cavity structure while preserving entanglement that stores information needed for single photon emission. The theoretical approach is based on a photonic structure that consists of two orthogonal cavities in which resonance with either the first or second of the two emitted photons is possible, leading to amplification and rerouting of the entangled light. The cavity–QD scheme uses a four-level cascade emitter that involves three levels for each polarization, leading to two spatially entangled photons for each polarization. By solving the Schrodinger equation, we identify the characteristic properties of the system, which can be used in conjunction with optimization techniques to achieve the “best” design relative to a set of prioritized criteria or constraints in our optical system. The theoretical investigations include an analysis of emission spectra in addition to the joint spectral density profile, and the results demonstrate the ability of the cavities to act as frequency filters for the photons that make up the entanglements and to modify entanglement properties. The results provide new opportunities for the experimental design and engineering of on-demand single photon sources.

Chemistry↗