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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Prototype Early Planetary Organic Processor Assembly (OPA) Based on Dual-Stage Anaerobic Membrane Bioreactor (AnMBR) for Fecal and Food Waste Treatment and Resource Recovery

Long-duration, deep-space exploration and habitation missions demand robust and reliable technologies to ensure crew health, safety, and mission success. Local food production will be essential for crew nutrition and morale. However, at $10,000/lb, the payload costs and mass/volume limitations to transport and provide the necessary resources, including fertilizer, for an anticipated 30-month mission become challenging over time. For mission success and sustainability, the Environmental Control and Life Support System (ECLSS) of the near future will need to recover resources from all “waste” sources and be near-closed loop. Organic wastes (e.g., fecal and food) offer a renewable source of C, N, P, water and other trace elements necessary to sustain crop production. However, these high solidwastes are often difficult to treatdue to factors includingheterogeneity, complexity, high organic strength, and the presence of pathogens. To date, there is no flight-ready technology capable of treating mixed organic wastes, creating a technology gap for future space missions. To address this need, a prototype Organic Processor Assembly (OPA) was developed through collaboration between the University of South Florida (USF) and NASA’s Kennedy Space Center (KSC). The OPA is based on the anaerobic membrane bioreactor (AnMBR), a hybrid technology coupling high-rate anaerobic digestion with membrane filtration. The system is designed for an early planetary base (EPB) scenario to aid in closing the resource recovery loop and decreaseresupply dependence. This presentation discusses initial research pertaining to: 1) design challenges in maximizing hydraulic/organic throughputandReliability, Availability, Maintainability, and Safety(RAMS)while minimizingmass and volume; 2) create capabilities for treating simulated high solids waste under steady and non-steady state conditions; and 3) measuresolids performance parameter(s). Future research and development pertaining to further optimization on system operation, performance, and expanded treatment capabilities arepresented.

Bioreactor↗
DOE OSTI2022

Scaling Superconducting Quantum Computers with Chiplet Architectures

Fixed-frequency transmon quantum computers (QCs) have advanced in coherence times, addressability, and gate fidelities. Unfortunately, these devices are restricted by the number of on-chip qubits, capping processing power and slowing progress toward fault-tolerance. Although emerging transmon devices feature over 100 qubits, building QCs large enough for meaningful demonstrations of quantum advantage requires overcoming many design challenges. For example, today’s transmon qubits suffer from significant variation due to limited precision in fabrication. As a result, barring significant improvements in current fabrication techniques, scaling QCs by building ever larger individual chips with more qubits is hampered by device variation. Severe device variation that degrades QC performance is referred to as a defect. Here, we focus on a specific defect known as a frequency collision. When transmon frequencies collide, their difference falls within a range that limits two-qubit gate fidelity. Frequency collisions occur with greater probability on larger QCs, causing collision-free yields to decline as the number of on-chip qubits increases. As a solution, we propose exploiting the higher yields associated with smaller QCs by integrating quantum chiplets within quantum multi-chip modules (MCMs). Yield, gate performance, and application-based analysis show the feasibility of QC scaling through modularity. Our results demonstrate that chiplet architectures, relative to monolithic designs, benefit from average yield improvements ranging from 9.6 – 92.6 × for ≲5 qubit machines. In addition, our simulations explore the design space of chiplet systems and discover configurations that demonstrate average two-qubit gate infidelity reductions that are at best 0.815 × their monolithic counterpart. Lastly, we observe that carefully-selected modular systems achieve fidelity improvements on a range of benchmark circuits.

quantum architecture↗
DOE OSTI2023

Phase stability and tensorial thermal expansion properties of single to high-entropy rare-earth disilicates

Temperature limitations in nickel-base superalloys have resulted in the emergence of SiC-based ceramic matrix composites as a viable replacement for gas turbine components in aviation applications. Higher operating temperatures allow for reduced fuel consumption but present a materials design challenge related to environmental degradation. Rare-earth disilicates (RE 2 Si 2 O 7 ) have been identified as coatings that can function as environmental barriers and minimize hot component degradation. In this work, single- and multiple-component rare-earth disilicate powders were synthesized via a sol-gel method with compositions selected to exist in the monoclinic C 2/m phase (β phase). Phase stability in multiple cation compositions was shown to follow a rule of mixtures and the C 2/m phase could be realized for compositions that contained up to 25% dysprosium, which typically only exists in a triclinic, P $\bar1$, phase. All compositions exhibited phase stability from room temperature to 1200°C as assessed by X-ray diffraction. The thermal expansion tensors for each composition were determined from high-temperature synchrotron X-ray diffraction and accompanying Rietveld refinements. It was observed that ytterbium-containing compositions had larger changes in the α 31 shear component with increasing temperature that led to a rotation of the principal axes. Principal axes rotation of up to 47° were observed for ytterbium disilicate. The results suggest that microstructure design and crystallographic texture may be essential future avenues of investigation to ensure thermo-mechanical robustness of rare-earth disilicate environmental barrier coatings.

36 MATERIALS SCIENCE↗
NASA NTRS2007

Metabolic Heat Regenerated Temperature Swing Adsorption for CO(sub 2) and Heat Removal/Rejection in a Martian PLSS

Two of the fundamental problems facing the development of a Portable Life Support System (PLSS) for use on Mars, are (i) heat rejection (because traditional technologies use sublimation of water, which wastes a scarce resource and contaminates the premises), and (ii) rejection of CO2 in an environment with a ppCO2 of 0.4-0.9 kPa. Patent-pending Metabolic heat regenerated Temperature Swing Adsorption (MTSA) technology is being developed to address both these challenges. The technology utilizes an adsorbent that when cooled with liquid CO2 to near sublimation temperatures (~195K) removes metabolically-produced CO2 in the vent loop. Once fully loaded, the adsorbent is then warmed externally by the vent loop (approx. 300K), rejecting the captured CO2 to Mars ambient. Two beds are used to effect a continuous cycle of CO2 removal/rejection as well as facilitate heat exchange out of the vent loop. Any cryogenic fluid can be used in the application; however, since CO2 is readily available at Mars and can be easily produced and stored on the Martian surface, the solution is rather elegant and less complicated when employing liquid CO2. As some metabolic heat will need to be rejected anyway, finding a practical use for metabolic heat is also an overall benefit to the PLSS. To investigate the feasibility of the technology, a series of experiments was conducted which lead to the selection and partial characterization of an appropriate adsorbent. The adsorbent NaX successfully removed CO2 from a simulated vent loop at the prescribed temperature swing anticipated during PLSS operating conditions on Mars using a cryogenic fluid. Thermal conductivity of the adsorbent was also measured to eventually aid in a demonstrator design of the technology. These results provide no show stoppers to the development of MTSA technology and allow its development to focus on other design challenges as listed in the conclusions.

Iacomini, Christine↗
NASA NTRS2007

Metabolic Heat Regenerated Temperature Swing Adsorption for CO2 and Heat Removal/Rejection in a Martian PLSS

Two of the fundamental problems facing the development of a Portable Life Support System (PLSS) for use on Mars, are (i) heat rejection (because traditional technologies use sublimation of water, which wastes a scarce resource and contaminates the premises), and (ii) rejection of carbon dioxide (CO2) in an environment with a CO2 partial pressure (ppCO2) of 0.4-0.9 kPa. Patent-pending Metabolic heat regenerated Temperature Swing Adsorption (MTSA) technology is being developed to address both these challenges. The technology utilizes an adsorbent that when cooled with liquid CO2 to near sublimation temperatures (~195K) removes metabolically-produced CO2 in the ventilation loop. Once fully loaded, the adsorbent is then warmed externally by the ventilation loop (~300K), rejecting the captured CO2 to Mars ambient. Two beds are used to provide a continuous cycle of CO2 removal/rejection as well as facilitate heat exchange out of the ventilation loop. Any cryogenic fluid can be used in the application; however, since CO2 is readily available on Mars and can be easily produced and stored on the Martian surface, the solution is rather elegant and less complicated when employing liquid CO2. As some metabolic heat will need to be rejected anyway, finding a practical use for metabolic heat is also an overall benefit to the PLSS. To investigate the feasibility of the technology, a series of experiments were conducted which lead to the selection and partial characterization of an appropriate adsorbent. The Molsiv Adsorbents 13X 8x12 (also known as NaX zeolite) successfully removed CO2 from a simulated ventilation loop at the prescribed temperature swing anticipated during PLSS operating conditions on Mars using a cryogenic fluid. Thermal conductivity of the adsorbent was also measured to eventually aid in a demonstrator design of the technology. These results provide no show stoppers to the development of MTSA technology and allow its development to focus on other design challenges as listed in the conclusions section of this paper.

Iacomini, Christine↗
DOE OSTI2025

The Artificial Scientist: in-Transit Machine Learning of Plasma Simulations

Large-scale simulations or scientific experiments produce petabytes of data per run. This poses massive challenges for I/O and storage when scientific analysis workflows are run manually offline. Unsupervised deep learning-based techniques to extract patterns and non-linear relations from these large amounts of data provide a way to build scientific understanding from raw data, reducing the need for manual pre-selection of analysis steps, but require exascale compute and memory to process the full dataset available. In this paper, we demonstrate a heterogeneous streaming workflow in which plasma simulation data is streamed directly to a Machine Learning (ML) application training a model on the simulation data in-transit, completely circumventing the capacity-constrained filesystem bottleneck. This workflow employs openPMD to provide a high level interface to describe scientific data and also uses ADIOS2, to transfer volumes of data that exceed the capabilities of the filesystem. We employ experience replay to avoid catastrophic forgetting in learning from this non-steady state process in a continual manner and adapt it to improve model convergence while learning in-transit. As a proof-of-concept, we approach the ill-posed inverse problem of predicting particle dynamics from radiation in a particle-incell (PIConGPU) simulation of the Kelvin-Helmholtz instability (KHI). We detail hardware-software co-design challenges as we scale PIConGPU to full Frontier, the Top-1 system as of June 2024 Top500 list.

Kelling, Jeffrey [Helmholtz-Zentrum Dresden Rossen↗
DOE OSTI2022

Structural and Optical Properties of High Entropy (La,Lu,Y,Gd,Ce)AlO 3 Perovskite Thin Films

Mixtures of Ce-doped rare-earth aluminum perovskites are drawing a significant amount of attention as potential scintillating devices. However, the synthesis of complex perovskite systems leads to many challenges. Designing the A-site cations with an equiatomic ratio allows for the stabilization of a single-crystal phase driven by an entropic regime. This work describes the synthesis of a highly epitaxial thin film of configurationally disordered rare-earth aluminum perovskite oxide (La 0.2 Lu 0.2 Y 0.2 Gd 0.2 Ce 0.2 )AlO 3 and characterizes the structural and optical properties. The thin films exhibit three equivalent epitaxial domains having an orthorhombic structure resulting from monoclinic distortion of the perovskite cubic cell. An excitation of 286.5 nm from Gd 3+ and energy transfer to Ce 3+ with 405 nm emission are observed, which represents the potential for high-energy conversion. These experimental results also offer the pathway to tunable optical properties of high-entropy rare-earth epitaxial perovskite films for a range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hierarchical Gaussian process-based Bayesian optimization for materials discovery in high entropy alloy spaces

Bayesian optimization (BO) is a powerful and data-efficient method for iterative materials discovery and design, particularly valuable when prior knowledge is limited, underlying functional relationships are complex or unknown, and the cost of querying the materials space is significant. Traditional BO methodologies typically utilize conventional Gaussian Processes (cGPs) to model the relationships between material inputs and properties, as well as correlations within the input space. However, cGP-BO approaches often fall short in multi-objective optimization scenarios, where they are unable to fully exploit correlations between distinct material properties. Leveraging these correlations can significantly enhance the discovery process, as information about one property can inform and improve predictions about others. Here, this study addresses this limitation by employing advanced kernel structures to capture and model multi-dimensional property correlations through multi-task (MTGPs) or deep Gaussian Processes (DGPs), thus accelerating the discovery process. We demonstrate the effectiveness of MTGP-BO and DGP-BO in rapidly and robustly solving complex materials design challenges that occur within the context of complex multi-objective optimization over FCC FeCrNiCoCu high entropy alloy (HEA) spaces, where traditional cGP-BO approaches fail. Furthermore, we highlight how the differential costs associated with querying various material properties can be strategically leveraged to make the materials discovery process more cost-efficient.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Coal-derived graphene foam and micron-sized silicon composite anodes for lithium-ion batteries

Silicon-based materials demonstrate significant potential as lithium-ion batteries (LIBs) anode, but their expansion and degradation present engineering design challenges for commercial application. In this study, a porous three-dimensional (3D) graphene and micron-sized silicon composite anode (Si@G foam) was synthesized using humic acid (HA) derived from coal as a graphene precursor. In-situ formation of graphene structure through reducing HA was confirmed by Raman spectra. The reduced HA (rHA) shows similar electrical conductivity compared to the commercial conductive carbon. SEM images depict a 3D skeleton of coal-derived graphene, with silicon particles distributed on the 3D graphene foam's internal surface. The Si@G composite-anode displays a good reversible capacity of ~656 mAh/g at a current density of 50 mA/g, as well as a high-rate capability of ~433 mAh/g at a current density of 800 mA/g, and outstanding cycling stability –89.8% capacity retention after 300 cycles, which is significantly higher than that of other foam structures. During lithiation and de-lithiation, the graphene foam serves as a matrix of electrical conductors and a volume expansion support for silicon. This 3D graphene network will be beneficial for developing advanced silicon-based anodes for high-performance LIBs.

25 ENERGY STORAGE↗
DOE OSTI2023

Integral and Separate Effects Test Facilities To Support Water Cooled Small Modular Reactors: A Review

This study reviews previous experimental facilities and test programs relevant to water-cooled reactor system design and analysis to meet regulatory compliances. This study aims to find the best solution for designing the required experiments, obtaining necessary test data, and verifying the developed computer code/models to support the new reactor design and development while minimizing cost and time while leveraging experiences from previous facilities to minimize. Nuclear reactor licensing requires supportive design, analysis, and experimental results to ensure the safety of the full-scale prototype reactor in regular operation, as well as during postulated accident scenarios. These reactor design analyses are generally performed using system codes and other associated simulation tools that require assessment, verification and validation using an appropriate experimental dataset. Experimental facilities used for reactor system safety analysis and system code assessments are categorized into integral effects test (IET) and separate effects test (SET) facilities. Further, these IET and SET experiments and studies use geometrically scaled systems to reproduce the prototype system behavior at a reasonable cost, albeit with some scaling-related distortions. The design challenge of these model facilities is to identify and minimize scaling distortions while reproducing the most important operational phenomena in steady-state operation and in postulated accident scenarios. Lessons learned from previous experimental facilities, models, and correlations can support the development of new multipurpose, scaled, hybrid, integrated, and modular experimental facilities for advanced light water-cooled small modular reactors (SMRs). Successful operation of these facilities can significantly reduce upfront reactor development and demonstration costs and time to deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Structure Sensitive Reaction Kinetics of Chiral Molecules on Intrinsically Chiral Surfaces

Enantiospecific heterogeneous catalysis utilizes chiral surfaces to resolve enantiomers via structure sensitive surface chemistry. The catalyst design challenge is the identification of chiral surface structures that maximize enantiospecificity. Herein, we develop data driven models for the enantiospecificity of tartaric acid reactions on chiral Cu(hkl) R&S surfaces. Measurements of enantiospecific rate constants were obtained by using curved Cu(hkl) R&S surfaces that enable kinetic measurements on hundreds of chiral surface orientations. One model uses feature vectors derived from generalized coordination numbers to capture the local structure around Cu atoms exposed by the Cu(hkl) R&S surfaces. The second model introduces the use of chiral cubic harmonic functions to capture the symmetry constraints of the face-centered cubic Cu structure. The model using 58 generalized coordination numbers has a fitting error similar to that of the model using only 5 cubic harmonic functions. The two models predict maxima in the enantiospecificity on surfaces with very similar surface orientations. The models developed in this work are applicable for any enantiospecific reaction happening on any chiral material with a cubic lattice structure, opening the way to understanding the surface structure sensitivity of the enantiospecific reaction kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Continuous Liquid–Liquid Extraction and in-Situ Membrane Separation of Miscible Liquid Mixtures

Separation operations are critical across a wide variety of manufacturing industries and account for about one quarter of all in-plant energy consumption in the United States. Conventional liquid-liquid separation operations require either thermal or chemical treatment, both of which have a large environmental impact and carbon footprint. Consequently, there is a great need to develop sustainable, clean methodologies for separation of miscible liquid mixtures. The greatest opportunities to achieve this lie in replacing high-energy separation operations (e.g., distillation) with low-energy alternatives such as liquid-liquid extraction. One of the primary design challenges in liquid-liquid extraction is to maximize the interfacial area between two immiscible (e.g., polar and non-polar) liquids for efficient mass transfer. However, this often involves energy-intensive methods including ultrasonication, pumping the feed and the extractant through packed columns with high tortuosity, or using a supercritical fluid as an extractant. Emulsifying the feed and the extractant, especially with a surfactant, offers a large interfacial area, but subsequent separation of emulsions can be energy-intensive and expensive. Thus, emulsions are typically avoided in conventional extraction operations. Herein, we discuss a novel, easily scalable, platform separation methodology termed CLEANS (Continuous Liquid-liquid Extraction And iN-situ membrane Separation). CLEANS integrates emulsion-enhanced extraction with continuous, gravity-driven, membrane-based separation of emulsions into a single unit operation. Furthermore, our results demonstrate that the addition of a surfactant and emulsification significantly enhance extraction (by > 250% in certain cases), even for systems where the best extractants for miscible liquid mixtures are known. Utilizing the CLEANS methodology, we demonstrate continuous separation of a wide range of miscible liquid mixtures, including soluble organic molecules from oils, alcohols from esters, and even azeotropes.

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

Stress-tolerant non-conventional microbes enable next-generation chemical biosynthesis

Microbial chemical production is a rapidly growing industry, with much of the growth fueled by advances in synthetic biology. New approaches have enabled rapid strain engineering for the production of various compounds; however, translation to industry is often problematic because native phenotypes of model hosts prevent the design of new low-cost bioprocesses. Here, in this work, we argue for a new approach that leverages the native stress-tolerant phenotypes of non-conventional microbes that directly address design challenges from the outset. Growth at high temperature, high salt and solvent concentrations, and low pH can enable cost savings by reducing the energy required for product separation, bioreactor cooling, and maintaining sterile conditions. These phenotypes have the added benefit of allowing for the use of low-cost sugar and water resources. Non-conventional hosts are needed because these phenotypes are polygenic and thus far have proven difficult to recapitulate in the common hosts Escherichia coli and Saccharomyces cerevisiae.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multivalent optical cycling centers: towards control of polyatomics with multi-electron degrees of freedom

Optical control of polyatomic molecules promises new opportunities in precision metrology and fundamental chemistry, as well as quantum information and many-body science. Contemporary experimental and theoretical efforts have mostly focused on cycling photons via excitation of a single electron localized to an alkaline earth (group 2)-like metal center. In this paper, we consider pathways towards optical cycling in polyatomic molecules with multi-electron degrees of freedom, which arise from two or more cycling electrons localized to p-block post-transition metal and metalloid (group 13, 14, and 15) centers. Here, we characterize the electronic structure and rovibrational branching of several prototypical candidates using ab initio quantum chemical methods. Despite increased internal complexity and challenging design parameters, we find several molecules possessing quasi-closed photon cycling schemes with highly diagonal, visible and near-infrared transitions. Furthermore, we identify new heuristics for engineering optically controllable and laser-coolable polyatomic molecules with multi-electron cycling centers. Our results help elucidate the interplay between hybridization, repulsion, and ionicity in optically active species and provide new directions for using polyatomic molecules with complex electronic structure as a resource for quantum science and measurement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Weakly solvating electrolytes: a solvation-centric paradigm for rechargeable metal batteries

Electrolyte design has long followed a solvation-first paradigm that prioritizes solvents capable of maximizing salt dissociation and ionic conductivity, while treating interfacial degradation and rheological limitations as secondary constraints. Although this approach has enabled significant progress in lithium-ion and sodium-ion batteries, it inherently favors solvent-dominated solvation structures that destabilize reactive metal interfaces. Weakly solvating electrolytes (WSEs) offer a fundamentally different strategy. By using solvents with intrinsically low donor strength and minimal electrostatic affinity for cations, WSEs suppress cation–solvent coordination and promote anion-rich solvation shells without relying on salt superconcentration. This shift lowers desolvation barriers, redirects interfacial decomposition pathways, and supports the formation of inorganic-rich, stable interphases. In this review, we discuss the molecular and solvation criteria that distinguish WSEs from conventional and concentrated or locally concentrated electrolyte systems, examine their implementation across different chemistries, and identify unresolved design challenges. WSEs are presented not as a niche formulation, but as a solvation-centric framework for rethinking electrolyte function in metal battery technologies.

Karbak, Mehdi [Pacific Northwest National Laborato↗
DOE OSTI2024

Design considerations of series type hybrid circuit breaker (S‐HCB)

Abstract The series‐type direct current (DC) hybrid circuit breaker (S‐HCB) concept was previously reported to offer better performance than solid‐state circuit breakers (SSCB) and hybrid circuit breakers (HCB). S‐HCB offers low conduction power loss like an HCB and ‐scale interruption time, which is even faster than an SSCB. It uses a pulse transformer to isolate the lower‐voltage high‐inductance power electronic circuit from the high‐voltage, low‐inductance main power loop. This paper provides analysis of the impact of the S‐HCB circuit components on the overall system performance and a scalable S‐HCB design guide for different DC system voltage and current ratings. In addition, system energy flow analysis is performed in the time domain to provide an understanding of how energy is delivered, dissipated, and released throughout the entire fault interruption process. The S‐HCB prototype was experimentally tested at 3 kV/30 A and 6 kV/150A with the results showing the interruption of the low fault current of 30 A and the high fault current of 150 A within 8 and maintaining the fault current at a near zero value for 300 to enable an arcless opening of a series mechanical switch. The key design challenges of S‐HCB at high voltage and high current ratings were discussed and possible solutions to mitigate those challenges were introduced.

Alashi, Mahmoud↗
DOE OSTI2024

Boosting RDataFrame performance with transparent bulk event processing

RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. Thanks to its design inspired by declarative programming principles, RDataFrame enables the development of highperformance, highly parallel analyses without requiring expert knowledge of multi-threading and I/O: user logic is expressed in terms of self-contained, small computation kernels tied together by a high-level API. This design completely decouples analysis logic from its actual execution, and opens several interesting avenues for workflow optimization. In particular, in this work we explore the benefits of moving internal data processing from an event-by-event to a bulkby-bulk loop. This refactoring dramatically reduces the framework’s runtime overheads; in collaboration with the I/O layer it improves data access patterns; it exposes information that optimizing compilers might use to auto-vectorize the invocation of user-defined computations; finally, while existing user-facing interfaces remain unaffected, it becomes possible to additionally offer interfaces that explicitly expose bulks of events, useful e.g. for the injection of GPU kernels into the analysis workflow. In order to inform similar future R&D, design challenges will be presented, as well as an investigation of the relevant timememory trade-off backed by novel performance benchmarks.

Guiraud, Enrico↗