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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Connected Traffic Signal Coordination Optimization Framework through Network-Wide Adaptive Linear Quadratic Regulator–Based Control Strategy

Traffic congestion in metropolitan areas causes several significant challenges, such as longer travel times, decreased productivity, increased fuel consumption and vehicle emissions, and even severe injuries during crashes. Traffic signal control is a management approach to reduce traffic congestion and allocate the appropriate right of way for safety and mobility efficiency, both in temporal and spatial domains. Here, this study proposes a network-wide adaptive signal control coordination optimization framework based on the linear quadratic regulator algorithm. The traffic flow conditions driven by signal control inputs are formulated based on their network-wide state-space representation. After modeling traffic control regulation constraints, an adaptive linear quadratic regulator algorithm is designed to maximize the network-wide total throughput under the current conditions. Optimal signal control split time durations for multiple intersections in the network are derived by solving the algebraic Riccati equation. Furthermore, the recursive least square parameter estimation method is employed to quantify dynamic traffic condition changes. To verify the effectiveness of this proposed signal control framework, both simulation and real-world experimental tests are conducted for multiple intersections in downtown Chattanooga, Tennessee, United States. In preparation for real-world experimental tests, pipelines for real-time data processing implementation and historical traffic flow data analysis are conducted. The test results demonstrate that the proposed control framework achieves a decrease in travel time by up to 19.4%, total time spent (TTS) by up to 11.9%, and relative queue balance (RQB) by up to 15.6%. The research findings indicate that the proposed signal control framework can be generalized to handle large scale signal control optimization network-wide.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

From Powder to Power: Tailored Pre-Milling Strategy that Optimizes Microstructure for Efficient Hydrogen Evolution

The hydrogen evolution reaction (HER) plays a critical role in enabling large-scale electrolytic hydrogen production and advancing future technologies and fuel production. Among non-precious metals, NiMo-based catalysts are particularly attractive due to their capability to promote both water dissociation and hydrogen adsorption in alkaline media. However, conventional NiMo catalysts often suffer from incomplete alloying, particle aggregation, weak metal–support interactions, and surface oxidation, which significantly limit active site utilization, electronic conductivity, and long-term stability. Herein, we report a scalable, solid-state, two-step ball milling strategy for constructing an efficient NiMo/C catalyst for the HER. Pre-milling the metal precursors prior to carbon incorporation promotes efficient solid-state activation, leading to the formation of uniformly alloyed, ultrafine, and defect-rich Ni–Mo nanoparticles with robust metal–carbon interfacial anchoring. Benefiting from this integrated structural design, the optimized NiMo/C catalyst exhibits low overpotentials and Tafel slopes, reduced charge-transfer resistance, and excellent durability under alkaline conditions. Comprehensive structural and surface analysis reveal that the enhanced HER performance can be attributed to the synergistic interplay of homogeneous Ni–Mo alloying, uniform nanoparticle dispersion on a defect-rich carbon scaffold, enhanced accessibility of catalytically active sites, and optimized electronic coupling that stabilizes the catalyst surface. This work highlights the two-step solid-state ball milling strategy as a simple, robust, and scalable route for the preparation of effective and durable non-precious metal HER electrocatalysts, offering practical insights toward large-scale and inexpensive hydrogen production.

Yang, Xiaoxuan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2024

Status of the INFN LASA in-kind contribution to PIP-II project

The status of INFN LASA in-kind contribution to the PIP-II project at Fermilab is reported in this paper. The effort for the series production of the 38 INFN LASA designed, 5-cell cavities with beta 0.61 for the LB650 section of the linac commenced and the status of ongoing activities and major procurements is here conveyed. At the same time, preliminary tests on INFN LB650 cavity prototypes are progressing in order to optimize the complete preparation and qualification cycle. All cavities will be produced, and surface treated in industry to reach the unprecedented performances required, qualified through vertical cold test at state-of-the art infrastructures and delivered as installation ready at the string assembly site.

43 PARTICLE ACCELERATORS↗
NASA NTRS2002

Glennan Microsystems Initiative

During the 2001-2002 award period, we performed research on Pt/Ti/bare 6H-SiC and bare 4H-SiC interfaces in order to identify their electronic properties as a function of surface preparation. The overall aim of this work is to optimize the electronic properties of metal contacts to SiC as well as the active SiC material itself as a function of surface preparation and subsequent processing. Initially, this work has involved identifying bare surface, subsurface, and metal induced gap states at the metal-SiC contact and correlating energies and densities of deep levels with Schottky barrier heights. We used low energy electron-excited nanoluminescence (LEEN) spectroscopy, X-ray photoemission spectroscopy (XPS), and Secondary Ion Mass Spectrometry (SIMS) in order to correlate electronic states and energy bands with chemical composition, bonding, and crystal structure. A major development has been the discovery of polytype transformations that occur in 4H-SiC under standard microelectronic process conditions used to fabricate SiC devices. Our results are consistent with the stacking fault generation, defect formation, and consequent degradation of SiC recently reported for state-of-the-art ABB commercial diodes under localized electrical stress. Our results highlight the importance of -optimizing process conditions and material properties - anneal times, temperatures and doping to control such structural changes within epitaxial SiC layers. Thus far, we have established threshold times and temperatures beyond which 4H-SiC exhibits 3C-SiC transformation bands for a subset of dopant concentrations and process conditions. On the basis of this temperature time behavior, we have been able to establish an activation energy of approximately 2.5 eV for polytype transformation and dislocation motion. Work continues to establish the fundamental mechanisms underlying the polytype changes and its dependence on material parameters.

Brillson, Leonard J.↗
DOE OSTI2022

Universal control of a six-qubit quantum processor in silicon

Future quantum computers capable of solving relevant problems will require a large number of qubits that can be operated reliably. However, the requirements of having a large qubit count and operating with high fidelity are typically conflicting. Spins in semiconductor quantum dots show long-term promise but demonstrations so far use between one and four qubits and typically optimize the fidelity of either single- or two-qubit operations, or initialization and readout. Here, we increase the number of qubits and simultaneously achieve respectable fidelities for universal operation, state preparation and measurement. We design, fabricate and operate a six-qubit processor with a focus on careful Hamiltonian engineering, on a high level of abstraction to program the quantum circuits, and on efficient background calibration, all of which are essential to achieve high fidelities on this extended system. State preparation combines initialization by measurement and real-time feedback with quantum-non-demolition measurements. These advances will enable testing of increasingly meaningful quantum protocols and constitute a major stepping stone towards large-scale quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware

Quantum optimal control is a promising approach to improve the accuracy of quantum gates, but it relies on complex algorithms to determine the best control settings. CPU or GPU-based approaches often have delays that are too long to be applied in practice. It is paramount to have systems with extremely low delays to quickly and with high fidelity adjust quantum hardware settings, where fidelity is defined as overlap with a target quantum state. Here, we utilize machine learning (ML) models to determine control-pulse parameters for preparing Selective Number-dependent Arbitrary Phase (SNAP) gates in microwave cavity qudits, which are multi-level quantum systems that serve as elementary computation units for quantum computing. The methodology involves data generation using classical optimization techniques, ML model development, design space exploration, and quantization for hardware implementation. Our results demonstrate the efficacy of the proposed approach, with optimized models achieving low gate trace infidelity near $10^{-3}$ and efficient utilization of programmable logic resources.

Sanders, Flor [Columbia U.]↗
DOE OSTI2022

An optimized approach and inflation media for obtaining complimentary mass spectrometry-based omics data from human lung tissue

Human disease states are biomolecularly multifaceted and can span across phenotypic states, therefore it is important to understand diseases on all levels, across cell types, and within and across microanatomical tissue compartments. To obtain an accurate and representative view of the molecular landscape within human lungs, this fragile tissue must be inflated and embedded to maintain spatial fidelity of the location of molecules and minimize molecular degradation for molecular imaging experiments. Here, we evaluated agarose inflation and carboxymethyl cellulose embedding media and determined effective tissue preparation protocols for performing bulk and spatial mass spectrometry-based omics measurements. Mass spectrometry imaging methods were optimized to boost the number of annotatable molecules in agarose inflated lung samples. This optimized protocol permitted the observation of unique lipid distributions within several airway regions in the lung tissue block. Laser capture microdissection of these airway regions followed by high-resolution proteomic analysis allowed us to begin linking the lipidome with the proteome in a spatially resolved manner, where we observed proteins with high abundance specifically localized to the airway regions. We also compared our mass spectrometry results to lung tissue samples preserved using two other inflation/embedding media, but we identified several pitfalls with the sample preparation steps using this preservation method. Overall, we demonstrated the versatility of the inflation method, and we can start to reveal how the metabolome, lipidome, and proteome are connected spatially in human lungs and across disease states through a variety of different experiments.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^8 determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

J Wayne Mullinax↗
NASA NTRSDate not supplied

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗
NASA NTRSDate not supplied

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗
DOE OSTI2022

Functionalizing aromatic compounds with optical cycling centres

Molecular design principles provide guidelines for augmenting a molecule with a smaller group of atoms to realize a desired property or function. Here, we demonstrate that these concepts can be used to create an optical cycling centre, the Ca(I)–O unit, that can be attached to a number of aromatic ligands, enabling the scattering of many photons from the resulting molecules without changing the molecular vibrational state. Such capability plays a central role in quantum state preparation and measurement, as well as laser cooling and trapping, and is therefore a prerequisite for many quantum science and technology applications. We provide further molecular design principles that indicate the ability to optimize and expand this work to an even broader class of molecules. This represents a great step towards a quantum functional group, which may serve as a generic qubit moiety that can be attached to a wide range of molecular structures and surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Interplay Between Time and Energy in Bosonic Noisy Quantum Metrology

Quantum entanglement and coherence often allow for protocols that outperform classical ones in estimating a system’s parameter. When using infinite-dimensional probes (such as a bosonic mode), one could, in principle, obtain infinite precision in a finite time for both classical and quantum protocols, which makes it hard to quantify potential quantum advantage. However, such a situation is unphysical, as it would require infinite resources, so one needs to impose some additional constraint: typically the average energy employed by the probe is finite. Here we treat both energy and time as a resource, showing that, in the presence of noise, there is a nontrivial interplay between the average energy and the time devoted to the estimation. Our results are valid for the most general metrological schemes (e.g., adaptive schemes, which may involve entanglement with external ancillae or any kind of continuous measurement). We apply recently derived precision bounds for all parameters characterizing the paradigmatic case of a bosonic mode, subject to Lindbladian noise. We show how the time employed in the estimation should be partitioned in order to achieve the best possible precision. In most cases, the optimal performance may be obtained without the necessity of adaptivity or entanglement with ancilla. We compare results with classical strategies. Interestingly, for temperature estimation, applying a fast-prepare-and-measure protocol with Fock states provides better scaling with the number of photons than any classical strategy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Mitigating Cascading Outages in Severe Weather Using Simulation-Based Optimization

Severe weather events can trigger cascading power outages and lead to significant losses. In this work, we investigate cascading outage mitigation under severe weather conditions. Given day-ahead weather forecasts and component failure models, we aim to identify a set of power lines that can be hardened to minimize the expected impact of potential cascading outages. Since the expected load shedding cannot be expressed as an explicit function of line hardening decisions and system states, we developed a cascading outage simulator to estimate the expected value of load shedding under various initial weather-related disruption scenarios generated using a weather forecast. To avoid massive enumeration of all possible combinations of line hardening decisions and reduce the simulation efforts, we employed an efficient simulation-based optimization approach that quickly identifies the (near) optimal line hardening decisions in the presence of both large simulation noises due to the highly variable initial disturbances and system states, and significant randomness in the subsequent cascades. Furthermore, the algorithm is also able to utilize parallel computing to dramatically reduce computation time to support decision making in preparation for severe weather conditions. We performed a case study on the Northeast Power Coordinating Council (NPCC) 140-bus system model to demonstrate that our approach can significantly improve power grid resilience to adverse weather events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Sparse Phase Ansatzes for Resource-Efficient Qudit State Preparation via the SNAP-Displacement Protocol

Efficient preparation of nonclassical bosonic states is a central requirement for quantum computing, simulation, and precision metrology. We study resource-efficient quantum state preparation in bosonic qudit systems using the SNAP-displacement (SD) protocol. Existing SD-based approaches typically require a large number of gates and SNAP phases, resulting in complex control pulses with longer ansatz durations and amplified impact of photon-loss and control errors. In this work, we focus on the near- to medium-term regime, in which noisy quantum devices impose trade-offs on the fidelity that can be achieved, which must be taken into account. Specifically, we propose to optimize only a subset of the SNAP phases and introduce three progressively more general sparse ansatzes. To provide fine-grained control and identify the most suitable ansatz for a given target fidelity, we further employ a scalarized multi-objective optimization that trades off fidelity against either the number of phases or the duration of the ansatz. Numerical results for several target states and qudit dimensions up to $d=64$, evaluated through the hypervolume of the Pareto frontiers, show that these sparse ansatzes achieve favorable trade-offs over the fully parameterized SD protocol in both ideal and noisy settings. The advantage is strongest and most consistent when minimizing the number of phases, while improvements in ansatz duration are smaller and more dependent on the target-state family and noise level, suggesting a practical route to more efficient near- and medium-term bosonic state preparation.

Ferrari Dacrema, Maurizio [Milan Polytechnic] (ORC↗
DOE OSTI2024

Fully quantum algorithm for mesoscale fluid simulations with application to partial differential equations

Fluid flow simulations marshal our most powerful computational resources. In many cases, even this is not enough. Quantum computers provide an opportunity to speed up traditional algorithms for flow simulations. We show that lattice-based mesoscale numerical methods can be executed as efficient quantum algorithms due to their statistical features. This approach revises a quantum algorithm for lattice gas automata to reduce classical computations and state preparation at every time step. For this, the algorithm approximates the qubit relative phases and subtracts them at the end of each time step. Phases are evaluated using the iterative phase estimation algorithm and subtracted using single-qubit rotation phase gates. Further, this method optimizes the quantum resource required and makes it more appropriate for near-term quantum hardware. We also demonstrate how the checkerboard deficiency that the D1Q2 scheme presents can be resolved using the D1Q3 scheme. The algorithm is validated by simulating two canonical partial differential equations: the diffusion and Burgers' equations on different quantum simulators. We find good agreement between quantum simulations and classical solutions for the presented algorithm.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2015

CapiBRIC- Capillary-Based Brine Residual In-Containment for Secondary Water Recovery

One of the goals of the AES Life Support Systems Project is to achieve 98% water loop closure for long-duration human exploration missions. Brine water recovery is the primary technology gap that must be bridged to realize this goal. In response to an Agency call for technologies to compete in an October down-select, Capi-BRIC was chosen through a JSC down-select as the strongest candidate to go forward. This resulted in a period of intense development to increase its TRL in preparation for the Agency down-select. This was achieved through rapid prototype design, fabrication, and test at JSC and in a zero-g drop tower at Portland State University. INNOVATION CapiBRIC takes a novel approach of optimizing the containment geometry to support capillary flow and static phase separation to enable evaporation in a microgravity environment. OUTCOME TRL was advanced from 3 to 4, and was selected for continued funding through the AES program. CapiBRIC is poised for development into an ISS technology demonstration, proving its viability as an enabling technology for exploration.

Sargusingh, Miriam↗
DOE OSTI2024

Bench-scale Development of a Transformational Graphene Oxide-based Membrane Process for Post-combustion CO 2 Capture

Graphene-based materials, such as graphene and graphene oxide (GO), have been considered as next-generation membrane materials. GTI Energy and The State University of New York at Buffalo (UB) have been developing a transformational GO-based membrane process (designated as GO2) that integrates a high CO 2 /N 2 selectivity membrane (GO-1) and a high CO 2 flux membrane (GO-2) for post-combustion CO 2 capture. An innovative membrane structure, consisting of GO nanochannels intercalated by single-walled carbon nanotube (SWCNT), was developed. The membrane prepared on hollow fiber substrate showed CO 2 permeance as high as 1,300 GPU with CO 2 /N 2 selectivity >200. The membranes were successfully scaled up to effective area of 50-100 cm 2 . The 50-100 cm 2 membranes showed CO 2 /N 2 selectivity ≥200 and CO 2 permeance ≥1,000 GPU for the GO-1 type, and CO 2 /N 2 selectivity ≥20 and CO 2 permeance ≥2,500 GPU for the GO-2 type. The CO 2 capture performance of the GO-based membranes was tested using a simulated flue gas. The testing results indicate that the GO-based membranes are stable in the presence of flue gas contaminants. The GO-based membranes were then further scaled up to a surface area of 1,000 cm 2 . Good stability was achieved during an integrated testing with GO-1 and GO-2 membranes using simulated flue gas. A bench-scale system was designed, constructed, and tested at the National Carbon Capture Center (NCCC). Good stability was achieved during testing of a single-stage process with >10 shutdowns/startups at NCCC. During the integrated testing, the membranes showed good stability at 50°C and 57°C. 70-90% CO 2 removal efficiencies and ≥95% CO 2 purity were validated during the steady state operation at NCCC. Techno-economic analysis indicates the GO2 membrane-based process technology provides a reduction in both the levelized cost of electricity (LCOE) and cost of capture when compared to the reference B12B case presented in the Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity study prepared by the National Energy Technology Laboratory (NETL), before considering any system optimization or improvement opportunities. The benefits are primarily driven by a reduction in the equipment costs of the CO 2 capture process vs. the solvent-based reference process in NETL Case B12B as well as a decrease in the base plant size.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Integrated operation scenarios: Chapter 6 of the special issue: on the path to tokamak burning plasma operation

Here we report the progress of the development and optimization of operational scenarios for ITER and beyond, focusing upon baseline, hybrid, and steady-state scenarios since 2007. This includes advancements made by the integrated operation scenarios (IOS) topical group of the international tokamak physical activity as well as contributions from the broader tokamak community. The key area of research involves developing IOSs that encompass tokamak physics, operation, and technology by utilizing integrated modeling and control strategies. This requires leveraging available actuators to simultaneously control plasma position and shape, MHD activities that could lead to disruptions, transport, plasma-wall interaction and power exhaust, fuel cycle, fusion burn, and tritium breeding. The control extends from the plasma initiation phase, through the current ramp-up, flattop, start and end of the fusion burn, and current ramp-down, to the plasma termination phase. A review of the currently developed scenarios and modeling is provided in terms of (i) optimizing plasma initiation in ITER, (ii) preparing for the low activation phase to fully commission all tokamak systems and establish and validate physics and scenario conditions in preparation for deuterim-tritium (DT) operation, (iii) developing and preparing baseline and hybrid scenarios to demonstrate the feasibility of achieving these regimes within device constraints, (iv) exploring steady-state scenarios to meet ITER’s steady-state goals, (v) evaluating and preparing actuators for ITER, (vi) developing integrated control solutions using shared actuators. The most notable achievements include; (i) the development of ITER demonstration discharges by matching various dimensionless parameters, (ii) the development of scenarios in an ITER-like tungsten environment and DT operation, and (iii) the development of scenarios in superconducting tokamaks, enabling long-pulse operations with similar coil constraints to ITER. Along with these significant achievements, outstanding issues and recommendations for further research and development are provided. Importantly, this study goes beyond simply updating the ITER Physics Basis; it carries profound implications for the broader field of burning plasma research, offering valuable insights and guidance for the next generation of fusion experiments and devices.

ITER↗