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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Design Paradigm for Modular Multilevel Converter-Based Generator Rectifier Systems

Modular Multilevel Converters (MMC) are being widely considered for medium to high voltage DC applications. Designing such converters through multi-objective optimization is of interest because such an approach allows the trade-off between competing objectives (for example mass and loss) to be explicitly and quantitatively identified. In this work, an optimization based design paradigm for MMC based generator rectifier systems is proposed. Such development typically requires detailed component design and simulation models for the electric machine and converter which are computationally expensive. As an alternative, the proposed work utilizes an electric machine metamodel, inductor metamodel, and high-speed steady-state simulation model for the MMC to facilitate multi-objective optimization minimizing system metrics of interest while satisfying system constraints. A case study is undertaken to demonstrate the functionality of the proposed design paradigm.

42 ENGINEERING↗
DOE OSTI2022

Design Evaluation of a Next-Generation High-Temperature Particle Receiver for Concentrating Solar Thermal Applications

High-temperature particle receivers are being developed to achieve temperatures in excess of 700 °C for advanced power cycles and solar thermochemical processes. This paper describes designs and features of a falling particle receiver system that has been evaluated and tested at the National Solar Thermal Test Facility at Sandia National Laboratories. These advanced designs are intended to reduce heat losses and increase the thermal efficiency. Novel features include aperture covers, active air flow, particle flow obstructions, and optimized receiver shapes that minimize advective heat losses, increase particle curtain opacity and uniformity, and reduce cavity wall temperatures. Control systems are implemented in recent on-sun tests to maintain a desired particle outlet temperature using an automated closed-loop proportional–integral–derivative controller. These tests demonstrate the ability to achieve and maintain particle outlet temperatures approaching 800 °C with efficiencies between 60 and 90%, depending on incident power, mass flow, and environmental conditions. Lessons learned regarding the testing of design features and overall receiver operation are also presented.

Mills, Brantley H.↗
DOE OSTI2023

Flexible tape-drive target system for secondary high-intensity laser-driven sources

Here, we present the development of a flexible tape-drive target system to generate and control secondary high-intensity laser-plasma sources. Its adjustable design permits the generation of relativistic MeV particles and x rays at high-intensity (i.e., ≥1 × 10 18 W cm —2 ) laser facilities, at high repetition rates (>1 Hz). The compact and robust structure shows good mechanical stability and a high target placement accuracy (<4 μm RMS). Its compact and flexible design allows for mounting in both the horizontal and vertical planes, which makes it practical for use in cluttered laser-plasma experimental setups. The design permits ~170° of access on the laser-driver side and 120° of diagnostic access at the rear. A range of adapted apertures have been designed and tested to be easily implemented to the targetry system. The design and performance testing of the tape-drive system in the context of two experiments performed at the COMET laser facility at the Lawrence Livermore National Laboratory and at the Advanced Lasers and Extreme Photonics (ALEPH) facility at Colorado State University are discussed. Experimental data showing that the designed prototype is also able to both generate and focus high-intensity laser-driven protons at high repetition rates are also presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Polymer Deconstruction and Redesign Strategies for Plastics Recycling

Advancing plastics recycling requires both the selective deconstruction of existing polymers and the design of new materials that enable efficient reuse without loss of performance. This perspective highlights an integrated approach that is rooted in polymer chemistry, catalysis, and process engineering which can enable a circular plastics economy. Here, we outline recent advances in catalytic, solvolytic, and enzymatic pathways for plastic deconstruction, and examine the molecular design principles driving next-generation recyclable-by-design and bio-based polymers. Despite these advances, major knowledge gaps remain in understanding the evolution of polymer morphology and catalyst structure during deconstruction, assessing deconstruction processes with realistic polymers, and offering redesigned polymers with competitive cost and environmental advantage over conventional plastics. United States Department of Energy (U.S. DOE) national laboratories offer unique capabilities to address these challenges through in situ and operando characterization, high-throughput experimentation, environmental studies, technoeconomic and life cycle assessment, scale-up support, and collaboration networks. Advances made in understanding plastic deconstruction mechanisms and structure-property correlations of redesigned polymers inform emerging research directions including autonomous experimentation, real-time feedback-enabled process optimization, and protein engineering for enzymatic depolymerization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Design and strategy for next-generation silicon carbide composites for nuclear energy

Silicon carbide (SiC) ceramic-based composites continue to be attractive material options for fusion in-vessel components and fission reactor core structures because of their exceptional high-temperature capability and favorable neutronic properties. As performance data accumulates, the limitations of the current generation of nuclear-grade SiC composites are becoming more apparent. These limitations mainly involve strength degradation during high-dose neutron irradiation. In this paper, we discuss several options for improving the performance of the next generation of SiC composites to enhance the radiation resistance, along with new experimental results on neutron irradiation resistance. The main emphasis is on the selection of the fibers and the design and development of alternative interphase layers for advanced composites.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

MULTI-LEADER: MULTI-source LEarning-Accelerated Design of high-Efficiency multi-stage compRessor (Final Technical Report)

The objective of MULTI-LEADER is to cut design costs by 80% while generating more energy-efficient designs of multi-stage compressors by developing and implementing novel machine learning (ML) techniques, which enable faster and fewer design iterations, improved solver performance, and concurrent multi-disciplinary design. Current industrial practices for the design of multi-stage compressors involve simulation-based design optimization with successive levels of model fidelity, iteratively evaluated between distinct disciplines, one stage at a time to tackle the high dimensional design variations. This project addresses these key design challenges: (1) concurrent optimization of multiple stages under many non-linear constraints; (2) multitude of evaluation of high-fidelity and expensive solvers and their gradients during optimization convergence in high-dimensional design; (3) multi-disciplinary design to maximize aerodynamic performance while guaranteeing structural integrity and additive manufacturability; (4) utilization of multiple fidelity of solvers with disparate parameterization and modeling assumptions. MULTI-LEADER achieved more than 5x speed up in detailed design of more energy-efficient compressors via these machine learning (ML) innovations: (i) rapid design surrogates by multi-source learning from diverse fidelities across multiple disciplines, (ii) physics-constrained data-augmented modeling for improved empiricism, (iii) generative manifold embedding for high dimensional concurrent design without gradient information; (iv) budget-constrained fidelity-adaptive sampling towards fewer design iterations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Exploring solvation structure and transport behavior for rational design of advanced electrolytes for next generation of lithium batteries

The efficacy of electrolytes significantly affects battery performance, leading to the development of several strategies to enhance them. Despite this, the understanding of solvation structure remains inadequate. It is imperative to understand the structure–property–performance relationship of electrolytes using diverse techniques. Here, this review explores the recent advancements in electrolyte design strategies for high capacity, high-voltage, wide-temperature, fast-charging, and safe applications. To begin, the current state-of-the-art electrolyte design directions are comprehensively reviewed. Subsequently, advanced techniques and computational methods used to understand the solvation structure are discussed. Additionally, the importance of high-throughput screening and advanced computation of electrolytes with the help of machine learning is emphasized. Finally, future horizons for studying electrolytes are proposed, aimed at improving battery performance and promoting their application in various fields by enhancing the microscopic understanding of electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2020

Application and assessment of deep learning for the generation of potential NMDA receptor antagonists

Uncompetitive antagonists of the N-methyl D-aspartate receptor (NMDAR) have demonstrated therapeutic benefit in the treatment of neurological diseases such as Parkinson's and Alzheimer's, but some also cause dissociative effects that have led to the synthesis of illicit drugs. The ability to generate NMDAR antagonists in silico is therefore desirable for both new medication development and preempting and identifying new designer drugs. Recently, generative deep learning models have been applied to de novo drug design as a means to expand the amount of chemical space that can be explored for potential drug-like compounds. In this study, we assess the application of a generative model to the NMDAR to achieve two primary objectives: (i) the creation and release of a comprehensive library of experimentally validated NMDAR phencyclidine (PCP) site antagonists to assist the drug discovery community and (ii) an analysis of both the advantages conferred by applying such generative artificial intelligence models to drug design and the current limitations of the approach. We apply, and provide source code for, a variety of ligand- and structure-based assessment techniques used in standard drug discovery analyses to the deep learning-generated compounds. Overall, we present twelve candidate antagonists that are not available in existing chemical databases to provide an example of what this type of workflow can achieve, though synthesis and experimental validation of these compounds are still required.

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

Modular repeat protein sculpting using rigid helical junctions

The ability to precisely design large proteins with diverse shapes would enable applications ranging from the design of protein binders that wrap around their target to the positioning of multiple functional sites in specified orientations. We describe a protein backbone design method for generating a wide range of rigid fusions between helix-containing proteins and use it to design 75,000 structurally unique junctions between monomeric and homo-oligomeric de novo designed and ankyrin repeat proteins (RPs). Of the junction designs that were experimentally characterized, 82% have circular dichroism and solution small-angle X-ray scattering profiles consistent with the design models and are stable at 95 °C. Crystal structures of four designed junctions were in close agreement with the design models with rmsds ranging from 0.9 to 1.6 Å. Electron microscopic images of extended tetrameric structures and ~10-nm-diameter “L” and “V” shapes generated using the junctions are close to the design models, demonstrating the control the rigid junctions provide for protein shape sculpting over multiple nanometer length scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A robust alloy design (RAD) strategy for next-generation (IV) nuclear fission reactors

Next-generation nuclear reactors demand structural materials capable of withstanding extreme conditions, including high temperatures, intense neutron flux, and corrosive environments. Multi-Principal Element Alloys (MPEAs) have emerged as promising candidates due to their exceptional radiation tolerance, thermal stability, and compositional flexibility. This study introduces a versatile and customizable Robust Alloy Design (RAD) strategy for systematically designing MPEAs for GEN-IV reactor fuel cladding. The RAD framework integrates nuclear-relevant selection criteria, empirical parameter assessments, and high-throughput CALPHAD simulations to efficiently narrow compositional space and identify stable alloys. A unified RAD score developed for the first time, combines key performance metrics, including fuel-clad chemical interaction (FCCI), neutron absorption cross-section (NAC), valence electron configuration (VEC), and melting point factor (MPF), into a flexible ranking system adaptable to reactor-specific priorities. Among 724 candidates, V555(5Al–5Cr–5Fe–85V) emerged as the top alloy, validated experimentally with a homogeneous single-phase BCC microstructure and superior mechanical properties (nano-indentation: 3.389 ± 0.258 GPa; Vickers hardness: 240 ± 6.7 HV), significantly outperforming Zircaloy-4 and V-4Cr-4Ti. Importantly, the RAD strategy is not limited to nuclear applications; its customizable weighting system enables scalability to other extreme environments. This adaptability positions RAD strategy as a versatile tool for advanced materials design across multiple industries.

Alloy design↗
DOE OSTI2021

Computational design of microarchitected porous electrodes for redox flow batteries

Porous electrodes are used as the core reactive component across electrochemical technologies. In flowing systems, controlling the fluid distribution, species transport, and reactive environment is critical to attaining high performance. However, conventional electrode materials like felts and papers provide few opportunities for precise engineering of the electrode and its microstructure. To address these limitations, architected electrodes composed of unit cells with spatially varying geometry determined via computational optimization are proposed. Resolved simulation is employed to develop a homogenized description of the constituent unit cells. These effective properties serve as inputs to a continuum model for the electrode when used in the negative half-cell of a vanadium redox flow battery. Porosity distributions minimizing power loss are then determined via computational design optimization to generate architected porosity electrodes. The architected electrodes are compared to bulk, uniform porosity electrodes and found to lead to increased power efficiency across operating flow rates and currents. The design methodology is further used to generate a scaled-up electrode with comparable power efficiency to the bench-scale systems. Finally, the variable porosity architecture and computational design methodology presented here thus offers a novel pathway for automatically generating spatially engineered electrode structures with improved power performance.

25 ENERGY STORAGE↗
DOE OSTI2023

Towards a new generation long trace profiler LTP-2020: optical design of pencil beam interferometry sensor

Improvements in the quality of synchrotron beamline x-ray optics required for next-generation light sources (e.g. the ALS Upgrade project) drive the need to improve the performance of the metrology instrumentation used to measure these components. The Long Trace Profiler (LTP) that is in use at many synchrotron metrology laboratories around the world has some known issues that affect the accuracy of its measurements. The main error source is optical path difference (OPD) phase error introduced into the probe beam by inhomogeneities in the glass components used in the optical head. We have developed a new optical head design, LTP-2020, that replaces the cube polarizing beamsplitter (PBS) with a thin wedge plate polarizing beamsplitter (WPBS) and replaces the cemented doublet lens with an aspheric singlet. Both of these components significantly reduce the glass volume traversed by the laser probe beam. Careful attention to ghost ray interference produced by back reflection from optical surfaces is necessary to minimize distortion in the primary image that translates into systematic error in the slope angle measurement. We make extensive use of a commercial raytracing program to model the back reflections and adjust component parameters as necessary to minimize distortion. Deliberate misalignment of components is necessary to make the system perform correctly. Stringent requirements are placed on the 45◦ incidence coatings on the WPBS and on the normal incidence coatings on the lens and camera window elements. We encourage our colleagues who wish to upgrade their current LTP systems to join us in the procurement of these custom optical components.

Takacs, Peter Z.↗
DOE OSTI2022

C6 Hydroxymethyl-Substituted Carbapenem MA-1-206 Inhibits the Major Acinetobacter baumannii Carbapenemase OXA-23 by Impeding Deacylation

Acinetobacter baumannii has become a major nosocomial pathogen, as it is often multidrug-resistant, which results in infections characterized by high mortality rates. The bacterium achieves high levels of resistance to β-lactam antibiotics by producing β-lactamases, enzymes which destroy these valuable agents. Historically, the carbapenem family of b-lactam antibiotics have been the drugs of choice for treating A. baumannii infections. However, their effectiveness has been significantly diminished due to the pathogen’s production of carbapenem-hydrolyzing class D β-lactamases (CHDLs); thus, new antibiotics and inhibitors of these enzymes are urgently needed. Here, we describe a new carbapenem antibiotic, MA-1-206, in which the canonical C6 hydroxyethyl group has been replaced with hydroxymethyl. The antimicrobial susceptibility studies presented here demonstrated that this compound is more potent than meropenem and imipenem against A. baumannii producing OXA-23, the most prevalent CHDL of this pathogen, and also against strains producing the CHDL OXA-24/40 and the class B metallo-β-lactamase VIM-2. Our kinetic and mass spectrometry studies revealed that this drug is a reversible inhibitor of OXA-23, where inhibition takes place through a branched pathway. X-ray crystallographic studies, molecular docking, and molecular dynamics simulations of the OXA-23-MA-1-206 complex show that the C6 hydroxymethyl group forms a hydrogen bond with the carboxylated catalytic lysine of OXA-23, effectively preventing deacylation. These results provide a promising strategy for designing a new generation of CHDL-resistant carbapenems to restore their efficacy against deadly A. baumannii infections. Carbapenem antibiotics are the drugs of choice for treatment of deadly infections caused by Gram-negative bacteria. However, their efficacy is severely compromised by the wide spread of carbapenem-hydrolyzing class D β-lactamases (CHDLs). The importance of this research is the discovery that substitution of the canonical hydroxyethyl group of carbapenems by a hydroxymethyl significantly enhances stability against inactivation by the major CHDL of Acinetobacter baumannii, OXA-23. These results provide a novel strategy for designing next-generation, carbapenemase-stable carbapenems to fight multidrug-resistant infections caused by Gram-negative pathogens

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Approach and Model Used to Represent a Timeline Analysis for Security Design Enhancements

Next-generation reactors will be able to use risk to inform and performance base the licensing of many aspects of the reactor, facility, and site design, including attributes of physical security. There are several factors related to security, including site topography, reactor design, and physical protection system components, to consider when designing the physical protection system into the overall facility design and plan of operation. With the versatility of advanced reactors, especially micro reactors, methods are needed to simplify and quickly evaluate potential timelines for designing a site configuration. This report describes an approach to generate qualitative and quantitative insights using a risk-informed simulation. The modeling process is described in detail, focusing on three aspects: (1) the facility mission time (the time required to control the plant until safe), (2) the attacker timeline (the time to potential sabotage), and (3) the response timeline (the time to counter the facility attack). The modeling capabilities also are extended to include facility physical phenomena such as thermal-hydraulics and heat transfer to capture realistic representation of dynamic changes to a facility. While the plant models and examples are hypothetical and do not represent a real facility, these modeling approaches could be used for future security-by-design engineering in advanced reactors. The outputs and insights from the modeling approach may be used to modify and optimize the security posture of a facility by efficiently making modifications to the model and seeing the overall impact from the modification. Lastly, use of the approach described in this report can also provide the technical basis for a physical protection program, describing how the facility and security strategy will cope with off-normal events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Excited Rydberg states in MoSe 2 /WSe 2 heterostructures

The functional form of Coulomb interactions in the transition metal dichalcogenides (TDMs) and other van der Waals solids is critical to many of their unique properties, e.g. strongly-correlated electron states, superconductivity and emergent ferromagnetism. This paper presents measurements of key excitonic energy levels in MoSe 2 /WSe 2 heterostructures. These measurements are obtained from resonance Raman experiments on specific Raman peaks only observed at excited states of the excitons. This data is used to validate a model of the Coulomb potential in these structures which predicts the exciton energies to within ~5 meV. This model is used to determine the effect of heterostructure formation on the single-particle band gaps of the layers and will have a wide applicability in designing the next generation of more complex TDM structures.

Materials Science↗
DOE OSTI2020

Assessment of Existing Transportation Packages for Use with HALEU

Commercial light water reactor operators and fuel vendors in the United States are pursuing changes to fuel that include increased 235 U enrichment. Economic studies generally anticipate maximum near-term fuel assembly designs with up to 8 wt.% 235 U. Many next-generation nuclear reactor designs require high-assay low-enriched uranium (HALEU) (19.75 wt.% > 235 U > 5 wt.%) fuel. One necessary element for the commercial-scale use of HALEU is the ability to safely transport large quantities of enriched fuel material in multiple forms. However, there is uncertainty as to whether subcriticality requirements can be satisfied with existing package designs and whether existing critical benchmark experiment data are sufficient to support criticality safety code validation for HALEU transportation applications. This study assesses the potential to use currently licensed transportation packages for the transportation of increased enrichment unirradiated U fuel forms. The assessment uses selected package designs that represent the five categories of fuel form-boiling water reactor pins and assemblies, pressurized water reactor pins and assemblies, UF 6 , U-metal and tristructural isotropic (TRISO) particles, and UO 2 pellets or powder-and focuses on demonstrating subcriticality and identifying benchmark critical experiments appropriate for use in criticality computer code validation. Key quantities of interest that relate to subcriticality are limiting conditions (e.g., optimum moderation), package or package array k eff , package capacity, and package transportation array size. The SCALE TSUNAMI-3D and TSUNAMI Indices and Parameters codes are used for sensitivity and uncertainty calculations and for identification of candidate critical benchmark experiments for code validation. The primary metric for identifying candidate benchmarks is the similarity coefficient, c k . For each fuel form category, a representative package is evaluated. Results provided for each package evaluation include enrichment and packaging limits (e.g., maximum transportation array size as a function of enrichment) and benchmark critical experiment similarity coefficients. Results indicate that there are viable means for increasing enrichments into the HALEU range across the spectrum of fuel forms with differing increase amounts available for different packages. Sources of subcriticality margin to offset increased enrichment reactivity include reduced transportation array size, reduced fissile mass, burnable absorber credit, and safety analysis margin harvesting. For all packages except the DN-30, numerous critical benchmark experiment candidates for validation were identified.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Architector

Architector is a 3D chemical structure generation software package designed to take minimal 2D information about ligands and metal centers and generates chemically sensible 3D conformers and stereochemistry of the organometallic compounds. Architector is capable of high-throughput in-silico construction of s-, p-, d-, and f-block organometallic complexes. Architector represents a transformative step towards cross-periodic table computational design of metal complex chemistry.

Yang, Ping↗