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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Flexible Multiferroic Bulk Heterojunction with Giant Magnetoelectric Coupling via van der Waals Epitaxy

Magnetoelectric nanocomposites have been a topic of intense research due to their profound potential in the applications of electronic devices based on spintronic technology. Nevertheless, in spite of significant progress made in the growth of high-quality nanocomposite thin films, the substrate clamping effect still remains a major hurdle in realizing the ultimate magnetoelectric coupling. To overcome this obstacle, an alternative strategy of fabricating a self-assembled ferroelectric–ferrimagnetic bulk heterojunction on a flexible muscovite via van der Waals epitaxy is adopted. In this paper, we investigated the magnetoelectric coupling in a self-assembled BiFeO 3 (BFO)–CoFe 2 O 4 (CFO) bulk heterojunction epitaxially grown on a flexible muscovite substrate. The obtained heterojunction is composed of vertically aligned multiferroic BFO nanopillars embedded in a ferrimagnetic CFO matrix. Moreover, due to the weak interaction between the flexible substrate and bulk heterojunction, the interface is incoherent and, hence, the substrate clamping effect is greatly reduced. The phase-field simulation model also complements our results. The magnetic and electrical characterizations highlight the improvement in magnetoelectric coupling of the BFO–CFO bulk heterojunction. A magnetoelectric coupling coefficient of 74 mV/cm·Oe of this bulk heterojunction is larger than the magnetoelectric coefficient reported earlier on flexible substrates. Finally and therefore, this study delivers a viable route of fabricating a remarkable magnetoelectric heterojunction and yet flexible electronic devices that are robust against extreme conditions with optimized performance.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Blueprint for DOE Quantum Supercomputing: Ensuring U.S. Leadership in the Quantum Decade

Quantum computing stands at the threshold of a transformative decade, where the field will evolve from small-scale demonstrations toward practical scientific computing at scale. This Blueprint identifies fault-tolerant quantum computers (FTQCs) as a viable, scalable, and broadly applicable path to achieving “quantum scientific utility,” defined as solving scientifically valuable problems beyond the reach of conventional, classical computers. This capability is expected to show scientific demonstrations in the late 2020s and to mature in the early-to-mid 2030s. This Blueprint outlines a strategy to prepare the U.S. Department of Energy (DOE) for FTQCs and their integration into the U.S. national scientific computing infrastructure. Its purpose is to identify the steps, milestones, and research directions necessary for DOE to enable initial deployment of FTQCs in 2028 as a scientific tool for the nation and mature this capability into the 2030s. DOE has a long history of supporting quantum information science and technology, contributing significantly to research advancements, training a quantum-ready workforce, and providing access to early small-scale quantum hardware. Given recent demonstrations of logical operations on error-corrected logical qubits and the advancement of commercial hardware roadmaps, DOE should begin preparations for large-scale, fault-tolerant quantum computing deployment for DOE science missions. This Blueprint proposes that DOE focus on (1) deploying first-generation scientifically relevant quantum computers with at least 100 logical qubits and performing at least 10,000 to 100,000 hard logical operations in scientifically relevant calculations; (2) developing essential FTQC programming competencies, system software, and facility readiness; and (3) investing in cutting edge focused R&D that fosters breakthroughs in scientific applications, algorithms, and logical architectures needed to accelerate the advent of scientific utility. This effort will position DOE to transition to larger systems: production-scale quantum computers that comprise 1,000 to 10,000 logical qubits, perform 1 to 10 billion hard logical operations, and execute scientifically useful computations at scale. Achieving these goals will require DOE facilities to evolve with urgency to support scientific campaigns that integrate quantum and classical computing resources into efficient workflows, novel software and firmware environments for compiling and routing quantum programs on FTQC machines, and suitable infrastructure for quantum hardware. It will also require further development and optimization of scientific applications from the fields of materials science, quantum chemistry, and high-energy and nuclear physics. The Blueprint calls for transformative R&D and collective action to accelerate the advent of scientific quantum utility and bring it within reach by 2028.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Design of an advanced flight planning system

The demand for both fuel conservation and four-dimensional traffic management require that the preflight planning process be designed to account for advances in airborne flight management and weather forecasting. The steps and issues in designing such an advanced flight planning system are presented. Focus is placed on the different optimization options for generating the three-dimensional reference path. For the cruise phase, one can use predefined jet routes, direct routes based on a network of evenly spaced grid points, or a network where the grid points are existing navaid locations. Each choice has its own problem in determining an optimum solution. Finding the reference path is further complicated by choice of cruise altitude levels, use of a time-varying weather field, and requiring a fixed time-of-arrival (four-dimensional problem).

Sorensen, J. A.↗
NASA NTRS1993

Cycler orbit between Earth and Mars

A periodic orbit between Earth and Mars has been discovered that, after launch, permits a space vehicle to cycle back and forth between the planets with moderate maneuvers at irregular intervals. A Space Station placed in this cycler orbit could provide a safe haven from radiation and comfortable living quarters for astronauts en route to Earth or Mars. The orbit is largely maintained by gravity assist from Earth. Numerical results from multiconic optimization software are presented for a 15-year period from 1995 through 2010.

Byrnes, Dennis V.↗
NASA NTRSDate not supplied

Optical Modem Enabling Broadband Datacom Links for Crewed Cis-Lunar Missions

We report on the design, development, and testing of our high-power broadband optical modem supporting NASA’s crewed Artemis-2 mission. The O2O modem will be mounted in the crewed Orion module and provide a broadband 505,000 km bi-directional optical link back to earth while en route to the moon. The full-duplex modem consists of a high-power optical transmitter and receiver optimized for serially-concatenated pulse-position modulation (SCPPM). The transmitter is a master-oscillator power-amplifier optical architecture using efficient cladding-pumped amplification in erbium-ytterbium co-doped fiber. The transmitter outputs up to 1 W at ≈1550 nm (limited for eye safety) and supports 6 different user-rates ranging from 20.39 Mb/s to 260.95 Mb/s using PPM16 and PPM32 modulation formats. The optical receiver supports two user-rates: 10.19 Mb/s and 20.39 Mb/s with both rates employing PPM32. The narrowband receiver filtering is optimized to simultaneously accept four separate wavelength channels to mitigate atmospherics through spatial diversity. A configurable interleaver provides additional protection against atmospherics-based signal fading and a powerful soft-decision error correction scheme enables highly sensitive detection. The measured sensitivities at the two bit-rates are -73.8 and -71.8dBm, respectively. The architecture was designed for reliable operation in space, featuring automatic hardware interlocks, pump sparing for the amplifiers, and autonomous operation of all internal hardware and software control loops. The protoflight unit (PFU) was put through rigorous environmental testing which included pyroshock, vibration, electromagnetic interference/compatibility, and thermal-vacuum testing. The modem successfully passed all the environmental screening and has been declared at Technology Readiness Level (TRL) 6.

space communications↗
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 OSTI2024

Effect of realistic routing on the social burden metric

The distance people travel to reach critical services is a key input to the Social Burden metric used by Sandia’s Resilient Node Cluster Analysis Tool (ReNCAT) in the optimization’s objective function. By default, ReNCAT utilizes Euclidian distances between population blocks and critical facilities when calculating Social Burden. However, these straight-line distances do not reflect how most residents or goods would travel throughout the area. As distance is a vital input to the burden calculation, a more realistic distance calculation will yield more realistic burden values. This work uses real road networks and calculates the shortest distance path between population centers and critical facilities using a standard graph theory approach. These realistic route distances are then used to compute Social Burden for four areas of study. It was found that distances using real road routes are generally, but not always, longer than the Euclidean distance. The increased length increases the final Social Burden metric, however, the overall burden percent change ranged between 17% and 52%, which means the impact of realistic routes relies heavily upon the area’s road topology. It was found that rural locations within an area may have larger burden increases than urban areas as more dense road networks allow routes to more closely follow a straight-line path. Additionally, using the most straight forward routing algorithms requires high computational effort for areas with large road networks. While it is believed this process can be made more performant, that task is beyond this scope of work.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

A simulation‐based integrated virtual testbed for dynamic optimization in smart manufacturing systems

Abstract In a manufacturing system, production control‐related decision‐making activities occur at different levels. At the process level, one of the main control activities is to tune the parameters of individual manufacturing equipment. At the system level, the main activity is to coordinate production resources and to route parts to appropriate workstations based on their processing requirement, priority indices, and control policy. At the factory level, the goal is to plan and schedule the processing of parts at different operations for the entire system in order to optimize certain objectives. Note that the results of such activities at different levels are closely coupled and affect the overall performance of the manufacturing system as a whole. Therefore, it is important to systematically integrate these control and optimization activities into one unified platform to ensure the goal of each individual activity is aligned with the overall performance of the system. In this paper, we develop a simulation‐based virtual testbed that implements dynamic optimization, automatic information exchange, and decision‐making from the process‐level, system‐level, and factory‐level of a manufacturing system into an integrated computation environment. This is demonstrated by connecting a Python‐based numerical computation program, discrete‐event simulation software (Simul8), and an optimization solver (CPLEX) via a third‐party master program. The application of this simulation‐based virtual testbed is illustrated by a case study in a machining shop.

Sun, Yuting↗
DOE OSTI2026

Carbon dioxide pipeline network transportation cost model: evaluating economic and geographic factors for efficient carbon capture, storage, and utilization

This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.

CCS↗
DOE OSTI2022

Joint routing of conventional and range-extended electric vehicles in a large metropolitan network

Range-extended electric vehicles combine the higher efficiency and environmental benefits of battery-powered electric motors with the longer mileage and autonomy of conventional internal combustion engines. This combination is particularly advantageous for time-constrained delivery routing in dense urban areas, where battery recharging along routes can be too time-consuming to economically justify the use of all-electric vehicles. However, switching from electric to conventional fossil fuel modes also results in higher costs and emissions and lower efficiency. This paper analyzes this heterogeneous vehicle routing problem and describes two solution methods: an exact branch-price-and-cut algorithm and an iterated tabu search metaheuristic. From a methodological perspective, we find that the exact algorithm consistently obtains tight lower bounds that also serve to certify the metaheuristic solutions as near-optimal. From a policy standpoint, we examine a large-scale real-world case study concerning parcel deliveries in the Chicago metropolitan area and quantify various operational metrics including energy costs and vehicle miles traveled. We find that by deploying roughly 20% of range -extended vehicles with a modest all-electric range of 33 miles, parcel distributors can save energy costs by up to 17% while incurring less than 0.5% increase in vehicle miles traveled. Increasing the range to 60 miles further reduces costs by only 4%, which can alternatively be achieved by decreasing the average service time by 1 minute or increasing driver working time by 1 hour. In conclusion, our study reveals several key areas of improvement on which vehicle manufacturers, distributors, and policy makers can focus their attention.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

SimH 2 : an integrated techno-economic modeling framework for hydrogen pipeline infrastructure and network optimization

Large-scale hydrogen (H 2 ) pipeline transport design and network optimization have seldom been reported due to the lack of a cost model accounting for the relationship between transport cost and hydrogen mass flow rate. Here, this work introduced a system-level cost model for hydrogen pipeline transport at supercritical state and integrated it with an existing CO 2 pipeline network tool, SimCCS, for hydrogen-specific pipeline design and optimization. The Intermountain West (I-West) region of the U.S., historically dependent on fossil fuel-based economies, is chosen to demonstrate the capabilities of our H 2 pipeline cost model and transport network optimization platform called SimH 2 . Two scenarios are examined: one where the pipeline is not allowed to pass through disadvantaged communities and the other where it is permitted. The results highlight that incorporating disadvantaged-community constraints lead to longer pipeline routes and increased transport costs, reflecting the trade-offs involved in equitable infrastructure development. It is demonstrated that the newly developed SimH 2 tool not only enables the efficient design of H 2 transportation pipelines but also optimizes the network by accounting for local terrain and the presence of disadvantaged areas.

08 HYDROGEN↗
DOE OSTI2023

Rapid and Energy‐Efficient Synthesis of Disordered Rocksalt Cathodes

Abstract Lithium‐rich transition metal oxides with a cation‐disordered rocksalt structure (disordered rocksalt oxides or DRX) are promising candidates for sustainable, next‐generation Li‐ion cathodes due to their high energy densities and compositional flexibility, enabling Co‐ and Ni‐free battery chemistries. However, current methods to synthesize DRX compounds require either high temperature (≈1000 °C) sintering for several hours, or high energy ball milling for several days in an inert atmosphere. Both methods are time‐ and energy‐intensive, limiting the scale up of DRX production. The present study reports the rapid synthesis of various DRX compositions in ambient air via a microwave‐assisted solid‐state technique resulting in reaction times as short as 5 min, which are more than two orders of magnitude faster than current synthesis methods. The DRX compounds synthesized via microwave are phase‐pure and have a similar short‐ and long‐range structure as compared to DRX materials synthesized via a standard solid‐state route, resulting in nearly identical electrochemical performance. In some cases, microwave heating allows for better particle size and morphology control. Overall, the rapid and energy‐efficient microwave technique provides a more sustainable route to produce DRX materials, further incentivizes the development of next‐generation DRX cathodes, and is key to accelerating their optimization via high‐throughput studies.

25 ENERGY STORAGE↗
DOE OSTI2018

Microstructure and mechanical behavior of hot-work tool steels processed by Selective Laser Melting

Highlights: • H11 and a modified H11 hot work tool steels have been produced by SLM. • As-built alloys are characterized by α-Fe cells surrounded by C-rich γ-Fe regions. • Rapidly solidified structures revealed able to respond to precipitation hardening. • Mechanical behavior of AM H11 is similar to that obtained by conventional processes. - Abstract: The present study is aimed at identifying and testing high-strength alloys for tooling applications featuring suitable processability for laser-based additive manufacturing technologies. The microstructure and mechanical properties of the H11 hot-work tool steel and a leaner version of the same alloy (L-H11) processed by Selective Laser Melting were assessed as a function of specific microstructural conditions obtained by performing different heat treatments. Tempering was performed on quenched alloys or simply from as built material. The rapidly solidified microstructures revealed able to respond directly to precipitation hardening treatment without performing any prior solution annealing. The microstructure of the as-built alloys revealed characterized by α-Fe dendritic cells decorated at boundaries by C-rich γ-Fe regions. Air quenching was responsible for the transformation of the solidification cells into lath martensitic structures and for the formation of the M{sub 3}C phase, which transformed into more complex carbide species on tempering. The hardness of quenched and tempered H11 steel is similar to that obtained by processing the alloy with conventional routes, and the final hardness gap between the two SLM processed H11 and L-H11 alloys treated according to optimal tempered condition was limited to 62 HV.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A reversible phase transition for sodium insertion in anatase TiO 2

Anatase TiO 2 is a potential negative electrode for sodium-ion batteries. The sodium storage mechanism is, however, still under debate, yet its comprehension is required to optimize the electrochemical properties. To clarify the sodium storage mechanism occurring in anatase, we have used both electrochemical and chemical routes from which we obtained similar trends. During the first discharge, an irreversible plateau region is observed which corresponds to the insertion of Na+ within the interstitial sites of anatase and is accompanied by a drastic loss of the long-range order as revealed by X-ray diffraction, high resolution of high angle annular dark-field scanning transmission electron microscope (HAADF-STEM), and pair distribution function (PDF) analysis. Further structural analysis of the total scattering data indicates that the sodiated phase displays a layered-like rhombohedral R3m structure built from the stacking of Ti and Na slabs. Because of the initial 3D network of anatase, the reduced phase shows strong disorder due to cationic intermixing between the Ti and Na slabs and the refined chemical formula is (Na 0.43 Ti 0.57 ) 3a 0.22 Na 0.39 Ti 0.39 ) 3b O 2 , where refers to vacancy. The presence of high valence Ti ions in the Na layers induces a contraction of the c-parameter as compared to the ordered phase. Upon desodiation, the structure further amorphized and the local structure probed by PDF is shown to be similar to the anatase TiO 2 , suggesting that the 3D network is recovered. The reversible sodium insertion/deinsertion is thus attributed to the rhombohedral active phase formed during the first discharge, and an oxidized phase featuring the local structure of anatase. Due to the amorphous nature of the two phases, the potential-composition curves are characterized by a sloping curve. Lastly, a comparison between the intercalation of lithium and sodium into anatase TiO 2 performed by DFT calculations confirmed that, for the sodiated phase, the rhombohedral structure is more stable than the tetragonal phase observed during the lithiation of nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure–Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. Here, we present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Peptide-Directed PdAu Nanoscale Surface Segregation: Toward Controlled Bimetallic Architecture for Catalytic Materials

Bimetallic nanoparticles are of immense scientific and technological interest given the synergistic properties observed when mixing two different metallic species at the nanoscale. This is particularly prevalent in catalysis, where bimetallic nanoparticles often exhibit improved catalytic activity and durability over their monometallic counterparts. Yet despite intense research efforts, little is understood regarding how to optimize bimetallic surface composition and structure synthetically using rational design principles. Recently, it has been demonstrated that peptide-enabled routes for nanoparticle synthesis result in materials with sequence-dependent catalytic properties, providing an opportunity for rational design through sequence manipulation. In this study, bimetallic PdAu nanoparticles are synthesized with a small set of peptides containing known Pd and Au binding motifs. The resulting nanoparticles were extensively characterized using high-resolution scanning transmission electron microscopy, X-ray absorption spectroscopy and high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Structural information obtained from synchrotron radiation methods were then used to generate model nanoparticle configurations using reverse Monte Carlo simulations, which illustrate sequence-dependence in both surface structure and surface composition. Replica exchange solute tempering molecular dynamic simulations were also used to predict the modes of peptide binding on monometallic surfaces, indicating that different sequences bind to the metal interfaces via different mechanisms. As a testbed reaction, electrocatalytic methanol oxidation experiments were performed, wherein differences in catalytic activity are clearly observed in materials with identical bimetallic composition. Finally, taken together, this study indicates that peptides could be used to arrive at bimetallic surfaces with enhanced catalytic properties, which could be leveraged for rational bimetallic nanoparticle design using peptide-enabled approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Decomposition of methane diluted with inert gas in an RF discharge cell

Decomposition of methane using non-thermal plasmas is an attractive route for producing hydrogen-rich gases and valuable carbon nanomaterials. Understanding how plasma discharge modes influence methane decomposition in optimizing plasma-assisted chemical conversion remains unexplored. This study explores the coupling between the discharge structure and product selectivity in RF capacitively coupled discharges operating in methane/inert gas mixtures in the pressure range of 2–3 torr. Under our experimental conditions the discharge exhibits mode transitions from uniform to striated in Ar and Kr and from diffuse to contracted in Ar and Kr with <5% CH 4 . The discharges in He and Ne remained uniform under our operating conditions, and their mixtures with CH 4 remained diffuse. A 0-d model for Ar/CH 4 discharge established a threshold for contraction while also asserting the importance of Ar$^{*}_{\textrm{m}}$ in the dissociation and ionization processes. The highest degree of methane decomposition, >99.7% with the main products of acetylene and graphitized solid carbon was achieved in the contracted discharge mode for both Kr or Ar with ⩽5% CH 4 . We demonstrate that contraction can play a crucial role in the effective decomposition of methane with value-added products and that both the electronic and thermal properties of plasma gas are responsible for this effect.

RF plasma↗
DOE OSTI2020

HPC-enabled computation of demand models at scale

The purpose of this project is to examine the energy impact of urban-scale traffic for the Los Angeles Basin by developing and implementing a scalable traffic assignment model. An energy optimization function will be posed and when integrated into the optimization code for travel assignment it can be mathematically proven to converge. The energy optimization function can then be compared to the typical travel time optimization that is traditionally used in traffic assignment models. The analysis will begin with static traffic assignment models with the routing for all origin and destinations computed in parallel on high performance computing facilities. Convergence of the numerical methods rely on the solution of convex programs (or extensions of these). This step will mostly consist of demonstrating the ability to parallelize the Frank Wolfe algorithm on various platforms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗