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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Multi‐Stage Optimization of Pore Size and Shape in Pore‐Space‐Partitioned Metal–Organic Frameworks for Highly Selective and Sensitive Benzene Capture

Abstract Compared to exploratory development of new structure types, pushing the limits of isoreticular synthesis on a high‐performance MOF platform may have higher probability of achieving targeted properties. Multi‐modular MOF platforms could offer even more opportunities by expanding the scope of isoreticular chemistry. However, navigating isoreticular chemistry towards best properties on a multi‐modular platform is challenging due to multiple interconnected pathways. Here on the multi‐modular pacs (partitioned acs) platform, we demonstrate accessibility to a new regime of pore geometry using two independently adjustable modules (framework‐forming module 1 and pore‐partitioning module 2). A series of new pacs materials have been made. Benzene/cyclohexane selectivity is tuned, progressively, from 4.5 to 15.6 to 195.4 and to 482.5 by pushing the boundary of the pacs platform towards the smallest modules known so far. The exceptional stability of these materials in retaining both porosity and single crystallinity enables single‐crystal diffraction studies of different crystal forms (as‐synthesized, activated, guest‐loaded) that help reveal the mechanistic aspects of adsorption in pacs materials.

Chen, Yichong↗
DOE OSTI2024

Multi–Stage Optimization of Pore Size and Shape in Pore–Space–Partitioned Metal–Organic Frameworks for Highly Selective and Sensitive Benzene Capture

Compared to exploratory development of new structure types, pushing the limits of isoreticular synthesis on a high-performance MOF platform may have higher probability of achieving targeted properties. Multi-modular MOF platforms could offer even more opportunities by expanding the scope of isoreticular chemistry. However, navigating isoreticular chemistry towards best properties on a multi-modular platform is challenging due to multiple interconnected pathways. Here on the multi-modular pacs (partitioned acs) platform, we demonstrate accessibility to a new regime of pore geometry using two independently adjustable modules (framework-forming module 1 and pore-partitioning module 2). A series of new pacs materials have been made. Benzene/cyclohexane selectivity is tuned, progressively, from 4.5 to 15.6 to 195.4 and to 482.5 by pushing the boundary of the pacs platform towards the smallest modules known so far. The exceptional stability of these materials in retaining both porosity and single crystallinity enables single-crystal diffraction studies of different crystal forms (as-synthesized, activated, guest-loaded) that help reveal the mechanistic aspects of adsorption in pacs materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Chapter 6: An Improved Leaf Protoplast System for Highly Efficient Transient Expression in Switchgrass (Panicum virgatum L.)

As a robust perennial C4-type monocot plant and a native species to North America, switchgrass (Panicum virgatum) has been evaluated and designated as a strong candidate bioenergy crop by the U.S. DOE. Although genetic modifications of switchgrass have been used to successfully reduce the recalcitrance of switchgrass biomass for biofuel production, the generation of transgenic switchgrass is still a slow and laborious process. A transient protoplast system can provide an excellent platform to accelerate the selection of genes-of-interest for tailoring switchgrass biomass. However, partially due to the lack of the complete genomic information, the attempts to optimize the transient protoplast system for switchgrass remain scarce. In this chapter, we provide an improved protocol for switchgrass protoplast isolation, increased transformation efficiency using CsCl gradient ultracentrifugation-derived plasmid DNA and extended application of the transient switchgrass protoplast system to analyze protein expression using western blot.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2014

Non destructive technique for cracks detection by an eddy current in differential mode for steel frames

In this paper, a nondestructive technique is used as a tool to control cracks and microcracks in materials. A simulation by a numerical approach such as the finite element method is employed to detect cracks and eventually; to study their propagation using a crucial parameter such as the stress intensity factor. This approach has been used in the aircraft industry to control cracks. Besides, it makes it possible to highlight the defects of parts while preserving the integrity of the controlled products. On the other side, it is proven that the reliability of the control of defects gives convincing results for the improvement of the quality and the safety of the material. Eddy current testing (ECT) is a standard technique in industry for the detection of surface breaking flaws in magnetic materials such as steels. In this context, simulation tools can be used to improve the understanding of experimental signals, optimize the design of sensors or evaluate the performance of ECT procedures. CEA-LIST has developed for many years semi-analytical models embedded into the simulation platform CIVA dedicated to non-destructive testing. The developments presented herein address the case of flaws located inside a planar and magnetic medium. Simulation results are obtained through the application of the Volume Integral Method (VIM). When considering the ECT of a single flaw, a system of two differential equations is derived from Maxwell equations. The numerical resolution of the system is carried out using the classical Galerkin variant of the Method of Moments. Besides, a probe response is calculated by application of the Lorentz reciprocity theorem. Finally, the approach itself as well as comparisons between simulation results and measured data are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Quantum utility in simulating the real-time dynamics of the Fermi–Hubbard model using superconducting quantum computers

The Fermi–Hubbard model is a fundamental model in condensed matter physics that describes strongly correlated electrons. On the other hand, quantum computers are emerging as powerful tools for exploring the complex dynamics of these quantum many-body systems. In this work, we demonstrate the quantum simulation of the one-dimensional Fermi–Hubbard model using IBM's superconducting quantum computers, employing over 100 qubits. We introduce a first-order Trotterization scheme and extend it to an optimized second-order Trotterization for the time evolution in the Fermi–Hubbard model, specifically tailored for the limited qubit connectivity of quantum architectures, such as IBM's platforms. Notably, both Trotterization approaches are scalable and maintain a constant circuit depth at each Trotter step, regardless of the qubit count, enabling us to precisely investigate the relaxation dynamics in the Fermi–Hubbard model by measuring the expectation value of the Néel observable (staggered magnetization) for time-evolved quantum states. Lastly, our successful measurement of expectation values in such large-scale quantum many-body systems, especially at longer time scales with larger entanglement, highlights the quantum utility of superconducting quantum platforms over conventional classical approximation methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Low power implementation of high frequency SiPM readout for Cherenkov and scintillation detectors in TOF-PET

State-of-the-art (SoA) electronic readout for silicon photomultiplier (SiPM)-based scintillation detectors that demonstrate experimental limits in achievable coincidence time resolution (CTR) leverage low noise, high frequency signal processing to facilitate a single photon time response that is near the limit of the SiPMs architecture. This readout strategy can optimally exploit fast luminescence and prompt photon populations, and promising measurements show detector concepts employing this readout can greatly advance PET detector CTR, relative to SoA in clinical systems. However, the technique employs power hungry components which make the electronics chain impractical for channel-dense time-of-flight (TOF)-PET detectors. We have developed and tested a low noise and high frequency readout circuit which is performant at low power and consists of discrete elements with small footprints, making it feasible for integration into TOF-PET detector prototypes. A 3 × 3 mm 2 Broadcom SiPM with this readout chain exhibited sub-100 ps single photon time resolution at 10 mW of power consumption, with a relatively minor performance degradation to 120 ± 2 ps FWHM at 5 mW. CTR measurements with 3 × 3 × 20 mm 3 LYSO and fast LGSO scintillators demonstrated 127 ± 3 ps and 113 ± 2 ps FWHM at optimal power operation and 133 ± 2 ps and 121 ± 3 ps CTR at 5 mW. BGO crystals 3 × 3 × 20 mm 3 in size show 271 ± 5 ps FWHM CTR (1174 ± 14 ps full-width-at-tenth-maximum (FWTM)) at optimal power dissipation and 289 ± 8 ps (1296 ± 33 ps FWTM) at 5 mW. The compact and low power readout topology that achieves this performance thereby offers a platform to greatly advance PET system CTR and also opportunities to provide high performance TOF-PET at reduced material cost.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Federated Deep Reinforcement Learning for Decentralized VVO of BTM DERs

The future of grid control requires a hybrid approach combining centralized and decentralized methods to fully utilize the potential of smart edge devices with artificial intelligence (AI) capabilities. This paper aims to develop and evaluate a federated deep reinforcement learning (FDRL) framework for decentralized adaptive volt-var optimization (VVO) of behind-the-meter (BTM) distributed energy resources (DERs). First, this paper models a single deep reinforcement learning (DRL) agent using the Markov Decision Process (MDP) framework for decentralized adaptive VVO of BTM DERs. Two DRL algorithms, soft actor-critic (SAC) and twin-delayed deep deterministic policy gradient (TD3), are compared for their effectiveness in optimizing VVO. Results show that TD3 outperforms SAC, achieving a 71.3% improvement in mean reward. Finally, the DRL agent is deployed within the FDRL framework, using the Flower platform, to enhance learning, provide adaptive control, and ensure data privacy for BTM DERs.

Ravi, Abhijith↗
DOE OSTI2020

Next-generation geospatial-temporal information technologies for disaster management

Traditional geographic information systems (GIS) have been disrupted by the emergence of Big Data in the form of geo-coded raster, vector, and time-series Internet-of-Things data. This article discusses the application of new scalable technologies that go far beyond relational databases and file-based storage on spinning disk or tape to incorporate both storage and processing data in the same platform. The roles of the Apache Hadoop Distributed File Systems and NoSQL key-value stores such as the Apache Hbase are discussed, along with indexing schemes that optimally support geospatial-temporal use. Here, we highlight how this new approach can rapidly search multiple GIS data layers to obtain insights in the context of early warning, impact evaluation, response, and recovery to earthquake and wildfire disasters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Independent Metadata Update VOL Connector for HDF5 (IMM VOL) v0.1

We have built a new framework that enables independent metadata updates within HDF5 files. Our framework includes the following components: an overlay network that's optimized for 1-to-All and All-to-All communication; root-less/server-less Bcast and AllReduce operations for reduced synchronization; a distributed consensus-making platform; an execution order keeping system, and a progress engine for generic threadless concurrence handling.

Li, Tonglin↗
DOE OSTI2018

STTR Phase I: Low-Cost, High-Accuracy, Whole-Building Carbon Dioxide Monitoring for Demand Control Ventilation

This STTR Phase I project assessed the feasibility of a new CO 2 sensing system optimized for low-cost, high-accuracy, whole-building monitoring for use in demand control ventilation. The focus was on the development of a wireless networking platform and associated firmware to provide signal conditioning and conversion, fault- and disruptiontolerant networking, and multi-hop routing at building scales to avoid wiring costs. Early exploration of a bridge (or “gateway”) to direct digital control services was also explored. Results of the project contributed to an improved understanding of a new electrochemical sensor for monitoring indoor CO 2 concentrations, as well as the electronics and networking infrastructure required to deploy those sensors at building scales. New knowledge was acquired concerning the sensor’s accuracy, environmental response, and failure modes, and the acquisition electronics required to achieve accuracy over a wide range of CO 2 concentrations. The project demonstrated that the new sensor offers repeatable correspondence with commercial optical sensors, with supporting electronics that offer gain accuracy within 0.5%, and acquisition accuracy within 1.5% across three orders of magnitude variation in generated current. Considering production, installation, and maintenance costs, the technology presents a foundation for achieving whole-building CO 2 sensing at a price point below $0.066 / sq-ft – meeting economic feasibility criteria established by the Department of Energy. The technology developed under this award addresses obstacles on the critical path to enabling whole-building CO 2 sensing and demand control ventilation in commercial retrofits, small commercial buildings, residential complexes, and other highpotential structures that have been slow to adopt these technologies. It presents an opportunity to significantly reduce energy use throughout the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

IDAES-PSE Software Tools for Optimizing Energy Systems and Market Interactions

Modern power grids coordinate electricity production and consumption via multi-scale wholesale energy markets. Historically, levelized cost metrics were the de facto standard for techno-eco-nomic analyses of energy systems and comparison of technology options. However, these metrics neglect the complexity of energy infrastructure including the time-varying value of electricity. An emerging alternative is multi-period optimization, which considers the locational marginal price of electricity as input data (parameters). In this work, we present a general interface for multi-period optimization with time-varying energy prices to facilitate rapid analysis and comparison of potential energy systems models. The PriceTakerModel class is written in the IDAES-PSE platform and allows users to generate a multi-period, price-taker model instance, as well as automatically generate common operational constraints for their model, such as start-up and shutdown. We show this interface successfully generates multi-period price-taker models, facilitates model discrimination, and aids in analyzing various technologies for deployment in unique energy markets.

Laky, Daniel↗
DOE OSTI2023

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Implementation of McMurchie–Davidson Algorithm for Gaussian AO Integrals Suited for SIMD Processors

We report an implementation of the McMurchie− Davidson evaluation scheme for 1- and 2-particle Gaussian AO integrals designed for processors with Single Instruction Multiple Data (SIMD) instruction sets. Like in our recent MD implementation for graphical processing units (GPUs) [Asadchev, A.; Valeev, E. F.. J. Chem. Phys. 2024, 160, 244109.], variable-sized batches of shellsets of integrals are evaluated at a time. By optimizing for the floating point instruction throughput rather than minimizing the number of operations, this approach achieves up to 50% of the theoretical hardware peak FP64 performance for many common SIMD-equipped platforms (AVX2, AVX512, NEON), which translates to speedups of up to 30 over the state-of-the-art one-shellset-at-a-time implementation of Obara−Saika-type schemes in Libint for a variety of primitive and contracted integrals. As with our previous work, we rely on the standard C++ programming language such as the std::simd standard library feature to be included in the 2026 ISO C++ standard without any explicit code generation to keep the code base small and portable. The implementation is part of the open source LibintX library freely available at https://github.com/ValeevGroup/libintx.

Basis sets↗
DOE OSTI2017

Cell Sage Re Mix HD

Cell Sage is a computational tool that allows science-based evaluation and exploration of battery life cycles over near limitless combination of aging conditions which helps battery end-users to optimize their investments.

25 ENERGY STORAGE↗
DOE OSTI2013

Microchannel gel electrophoretic separation systems and methods for preparing and using

A micro-analytical platform for performing electrophoresis-based immunoassays was developed by integrating photopolymerized cross-linked polyacrylamide gels within a microfluidic device. The microfluidic immunoassays are performed by gel electrophoretic separation and quantifying analyte concentration based upon conventional polyacrylamide gel electrophoresis (PAGE). To retain biological activity of proteins and maintain intact immune complexes, native PAGE conditions were employed. Both direct (non-competitive) and competitive immunoassay formats are demonstrated in microchips for detecting toxins and biomarkers (cytokines, c-reactive protein) in bodily fluids (serum, saliva, oral fluids). Further, a description of gradient gels fabrication is included, in an effort to describe methods we have developed for further optimization of on-chip PAGE immunoassays. The described chip-based PAGE immunoassay method enables immunoassays that are fast (minutes) and require very small amounts of sample (less than a few microliters). Use of microfabricated chips as a platform enables integration, parallel assays, automation and development of portable devices.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Microchannel gel electrophoretic separation systems and methods for preparing and using

A micro-analytical platform for performing electrophoresis-based immunoassays was developed by integrating photopolymerized cross-linked polyacrylamide gels within a microfluidic device. The microfluidic immunoassays are performed by gel electrophoretic separation and quantifying analyte concentration based upon conventional polyacrylamide gel electrophoresis (PAGE). To retain biological activity of proteins and maintain intact immune complexes, native PAGE conditions were employed. Both direct (non-competitive) and competitive immunoassay formats are demonstrated in microchips for detecting toxins and biomarkers (cytokines, c-reactive protein) in bodily fluids (serum, saliva, oral fluids). Further, a description of gradient gels fabrication is included, in an effort to describe methods we have developed for further optimization of on-chip PAGE immunoassays. The described chip-based PAGE immunoassay method enables immunoassays that are fast (minutes) and require very small amounts of sample (less than a few microliters). Use of microfabricated chips as a platform enables integration, parallel assays, automation and development of portable devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Cooperative Routing for an Air–Ground Vehicle Team—Exact Algorithm, Transformation Method, and Heuristics

This paper considers a cooperative vehicle routing problem for an intelligence, surveillance, and reconnaissance mission in the presence of communication constraints between the vehicles. The proposed framework uses a ground vehicle and an unmanned aerial vehicle (UAV) that travel cooperatively and visit a set of targets while satisfying the communication constraints. The problem is formulated as a mixed-integer linear program, and a branch-and-cut algorithm is developed to solve the problem to optimality. Furthermore, a transformation method and a heuristic are also developed for the problem. The effectiveness of all the algorithms is corroborated through extensive computational experiments on several randomly generated instances. Furthermore, this paper is motivated by an intelligence, surveillance, and reconnaissance mission involving a single unmanned aerial vehicle (UAV) and a ground vehicle, where the vehicles must coordinate their activity in the presence of communication constraints. The combination of a small UAV and a ground vehicle is an ideal platform for such missions, since small UAVs can fly at low altitudes and can avoid obstacles or threats that would be problematic for the ground vehicle alone. This paper addresses the coordinated routing problem involving these two vehicles and presents an algorithm to obtain an optimal solution for this problem, fast heuristics to obtain good feasible solutions, and also a transformation method to transform any instance of this cooperative vehicle routing problem to an instance of the one-in-a-set traveling salesman problem.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

SU-E-T-157: CARMEN: A MatLab-Based Research Platform for Monte Carlo Treatment Planning (MCTP) and Customized System for Planning Evaluation

Purpose: Although there exist several radiotherapy research platforms, such as: CERR, the most widely used and referenced; SlicerRT, which allows treatment plan comparison from various sources; and MMCTP, a full MCTP system; it is still needed a full MCTP toolset that provides users complete control of calculation grids, interpolation methods and filters in order to “fairly” compare results from different TPSs, supporting verification with experimental measurements. Methods: This work presents CARMEN, a MatLab-based platform including multicore and GPGPU accelerated functions for loading RT data; designing treatment plans; and evaluating dose matrices and experimental data.CARMEN supports anatomic and functional imaging in DICOM format, as well as RTSTRUCT, RTPLAN and RTDOSE. Besides, it contains numerous tools to accomplish the MCTP process, managing egs4phant and phase space files.CARMEN planning mode assist in designing IMRT, VMAT and MERT treatments via both inverse and direct optimization. The evaluation mode contains a comprehensive toolset (e.g. 2D/3D gamma evaluation, difference matrices, profiles, DVH, etc.) to compare datasets from commercial TPS, MC simulations (i.e. 3ddose) and radiochromic film in a user-controlled manner. Results: CARMEN has been validated against commercial RTPs and well-established evaluation tools, showing coherent behavior of its multiple algorithms. Furthermore, CARMEN platform has been used to generate competitive complex treatment that has been published in comparative studies. Conclusion: A new research oriented MCTP platform with a customized validation toolset has been presented. Despite of being coded with a high-level programming language, CARMEN is agile due to the use of parallel algorithms. The wide-spread use of MatLab provides straightforward access to CARMEN’s algorithms to most researchers. Similarly, our platform can benefit from the MatLab community scientific developments as filters, registration algorithms etc. Finally, CARMEN arises the importance of grid and filtering control in treatment plan comparison.

60 APPLIED LIFE SCIENCES↗