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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 145 records · Page 8

Investigation of heat pump technologies for high-temperature applications above 250 °C

This paper examines heat pump (HP) technologies to achieve heat supply temperatures above 250 °C, referred to as ultra-high-temperature heat pump (UHTHP). UHTHP, as a low-carbon heat delivery and heat augmentation technology, can offer an alternative to traditional combustion heating for decarbonizing high-temperature industrial processes. However, the heat supply temperature of over 250 °C surpasses the temperature range typically covered in the high-temperature HP literature and existing capabilities of commercial HP systems. This paper reviews HP technologies with the potential to evolve into UHTHP. Additionally, UHTHP studies in the literature are analyzed to compare the pros, cons, and technical potentials of various HPs using different thermodynamic cycles and fluids. Furthermore, we then pinpoint the technical gaps and challenges that have hindered widespread adoption of UHTHP in industry, explore potential improvements and solutions, and discuss the feasibility. Current efforts aim to lay the ground for future research, development, and commercial deployment for UHTHP.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

A transfer learning approach to energy-efficient control of small and medium-sized commercial buildings

Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.

ASHRAE guideline 36↗

Extreme hardness at high temperature with a lightweight additively manufactured multi-principal element superalloy

Materials are needed that can tolerate increasingly harsh environments, especially ones that retain high strength at extreme temperatures. Higher melting temperature alloys, like those consisting primarily of refractory elements, can greatly increase the efficiency of turbomachinery used in grid electricity production worldwide. Existing alloys, including Ni- and Co-based superalloys, used in components like turbine blades, bearings, and seals, remain a performance limiting factor due to their propensity, despite extensive optimization efforts, for softening and diffusion-driven elongation at temperatures often well above half their melting point. To address this critical materials challenge, we present results from integrating additive manufacturing and alloy design to guide significant improvements in performance via traditionally difficult-to-manufacture refractory alloys. We present an example of a multi-principal element alloy (MPEA), consisting of five refractory elements and aluminum, that exhibited high hardness and specific strength surpassing other known alloys, including superalloys. The alloy shows negligible softening up to 800°C and consists of four compositionally distinct phases, in distinction to previous work on MPEAs. Density functional theory calculations reveal a thermodynamic explanation for the observed temperature-independent hardness and favorability for the formation of this multiplicity of phases.

36 MATERIALS SCIENCE↗

Liquid-free covalent reinforcement of carbon nanotube dry-spun yarns and free-standing sheets

Carbon nanotubes (CNTs) possess exceptional mechanical properties, surpassing stiffness and strength metrics of common materials such as steel alloys by 100× at the nanoscale. However, when myriads of individual CNTs are bundled together into macroscopic ensembles like fibers or sheets, the result is a 100-fold drop in strength compared to its individual components. Here we present a general strategy aimed to close this gap in property scaling. By using vapor-phase polymerization of a crosslinkable polymer, we reinforced the weak interlinkages among individual CNTs within both yarns and sheets to promote a better transference of mechanical load across the structure. Furthermore, after the treatment, dry-spun, low-density 2.3 μm thin yarns increased their elastic moduli by at least 300%, and free-standing CNT sheets exhibited a 10× boost. In-situ synchrotron small-angle X-ray scattering revealed that polymer-reinforced yarns undergo limited CNT bundle rearrangement when subjected to tensile loads compared to pristine yarns. This evidence supports the hypothesis that the polymer hinders CNTs slippage, the root cause of the poor scaling of mechanical properties in these materials. While we demonstrated this reinforcement method for CNT structures, it is not specific to CNTs and could be used in a wide variety of other hierarchical nanostructured ensembles.

36 MATERIALS SCIENCE↗

Competing conduction mechanisms in high performance carbon nanotube fibers

The performance of carbon nanotube (CNT) cables, a contender for copper-wire replacement, is tied to its metallic and semi-conducting-like conductivity responses with temperature; the origin of the semi-conducting-like response however is an underappreciated incongruity in literature. With controlled aspect-ratio and doping-degree, over 61 unique cryogenic experiments including anisotropy and Hall measurements, CNT cable performance is explored at extreme temperatures (65 mK) and magnetic-fields (60 T). A semi-conducting-like conductivity response with temperature becomes temperature-independent approaching absolute-zero, uniquely demonstrating for the first time the necessity of heterogeneous fluctuation induced tunneling; complete de-doping leads to localized hopping, contrasting graphite's pure metallic-like response. High-field magneto-resistance (including novel +22 % longitudinal magneto-resistance near room-temperature) is analyzed with hopping and classical two-band models, both yielding a similar parameter useful for conductor development. Varying field-orientation angle uncovers significant two- and four-fold symmetries that are shown to be from Aharonov-Bohm-like corrections to the curvature-induced bandgap, a first for macroscale CNT fibers. Tight-binding calculations using Green's Function formalism model the largest, coherent transport to-date in commensurate CNT bundles in magnetic-field, revealing non-uniform transmission across bundle cross-sections with doping restoring uniformity; independent of doping, transport in bundle-junction-bundle systems are predominantly from CNTs adjacent to the other bundle—demonstrating that smaller bundles are more efficient for electronic transport. The final impact is predicting the ultimate conductivity of heterogeneous CNT cables using temperature and field-dependent transport, surpassing conductivity of traditional metals.

36 MATERIALS SCIENCE↗

Microwave-assisted synthesis of mixed-linker covalent organic frameworks enabling tunable and ultrahigh iodine capture

The use of covalent organic frameworks (COFs) for hazardous radioiodine capture has been highly sought after recently. However, the synthesis of high-performance COF adsorbents while circumventing the limitations of traditional solvothermal methods remains largely unexplored. Herein, we for the first time combine microwave-assisted synthesis and mixed-linker strategy to fabricate multivariate COF adsorbents (X% OMe-TFB-BD COFs, X% = 0, 33, 50, 67, and 100 mol%) with varying ratios of benzidine (BD) and 3,3'-dimethoxylbenzidine (BD-OMe) linkers in a rapid and facile manner. Adjusting the BD-OMe/BD mole ratios has led to distinct variations in density, crystallinity, porosity, morphology, and thermal/chemical stability of the resultant COFs, which empowered fine-tuning of the adsorption performance towards static iodine vapor. Remarkably, the 50% OMe-TFB-BD COF exhibited an ultrahigh iodine adsorption capability of 8.2 g g –1 , surpassing those of single-component COFs, mixed-linker COFs with other methoxy content, physically blended mixtures, and most existing COF adsorbents. Moreover, 50% OMe-TFB-BD COF was recyclable seven times without obvious loss in its adsorption capacity. Finally, this work underscores the substantial potential of microwave-assisted mixed-linker strategy as a viable approach for developing multivariate COFs with shortened reaction times, precisely tailored pore environment, and tunable sorption properties, which are of considerable promise for environmental remediation and other niche applications.

36 MATERIALS SCIENCE↗

Unlocking naphtha from polyolefins using Ni-based hydrocracking catalysts

Naphtha (C 5 -C 12 alkanes) is a platform feedstock in the petroleum industry and an ideal target for reutilizing plastic waste at scale. Hydrocracking has emerged as a promising technology for deconstructing polyolefins to naphtha. However, contemporary catalysts rely on Pt to achieve high rates, while earth-abundant metals (EAM) perform poorly. Herein, we develop high-performance Ni/BEA catalysts for polyolefin hydrocracking, achieving complete low-density polyethylene (LDPE) deconstruction with 80 % maximum naphtha yield within 12 h at 250 °C, 60 bar H 2 , and a catalyst-to-polymer ratio of 1:100. These catalysts are versatile, accommodating virgin resins and commercial polymer products, and are directly reusable and regenerable. Comparative analysis highlights that 5Ni/BEA(25) exhibits the highest naphtha productivity of 11.4 $\huge{(}$$\frac{g_{Naphtha}}{g_{cat}{•h}}$$\huge{)}$, surpassing previously reported Pt- and EAM-based catalysts by 2.5–6.2x. Technoeconomic and life-cycle analyses reveal naphtha from LDPE hydrocracking is economically and environmentally competitive to fossil-fuel-derived naphtha. In conclusion, these advancements pave the way for the industrial implementation of earth-abundant Ni-based catalysts in polyolefin hydrocracking, followed by retrofitting steam crackers to address plastics waste at scale.

Circular Economy↗

Programmable bionanocomposite coated fertilizers for prolonged controlled release of nitrogen

Controlled-release fertilizers (CRFs) present a promising solution for alleviating food and nutrient scarcity. However, their development has been mainly hindered by both rapid and unsynchronized nutrient release and unsustainable coating materials. In this study, we address this issue by developing a new coating layer for CRFs using a programmable biopolyurethane nanocomposite. This nanocomposite is prepared from diphenylmethane diisocyanate (MDI)-functionalized bentonite nanoclay (BNT-MDI) and a biopolyol from biomass waste. The results show that the BNT-MDI-doped CRFs (BCRFs) exhibit an impressive nitrogen (N)-release longevity of approximately 120 days at a 4 wt% coating ratio, surpassing previous CRF formulations. In a 30-day snap bean cultivation study, BCRF significantly improved root length (1000%), leaf length (257%), leaf width (400%), and plant height (1400%) compared to the control. The superior performance of BCRF is attributed to the PU-nanoclay biocomposite film, with full nano-exfoliation, controllable porosity, and high crosslinking density. Furthermore, we introduce a new dynamic release mechanism and establish a quantitative relationship between the nanostructure, property, and release performance of BCRF by combining the multiplicative and diffusion models for porous materials. Finally, this study provides a theoretical framework and a straightforward methodology for designing programmable nanocomposite structures for future biobased CRFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intensified biogas to liquid (IBGTL) Process: Experimental validation and modeling analysis

The Intensified Biogas to Liquid (IBGTL) process aims to overcome traditional economy-of-scale barriers in biogas-to-liquid fuel production by integrating bi-reforming and Fischer-Tropsch synthesis (FTS) in a single IBGTL reactor. This reactor operates at uniform pressure with different optimized temperatures across two zones for efficient conversion, utilizing multifunctional bi-reforming catalysts and high-temperature FTS catalysts. Bench scale experiments were carried out using landfill gas (LFG) in a single pass process, and the yield data from these experiments were fed into process scale-up design and techno-economic analysis (TEA) across four scenarios: (1) a single pass process, (2) a process with material recycling, (3) a process with liquefied petroleum gas (LPG) co-product recovery, and (4) a process with electricity generation from the fuel gas produced. TEA identified Scenario 2 as the most cost-effective, achieving a Minimum Fuel Selling Price (MFSP) of $\$4.59$ per gallon, competitive with the current national diesel price of $\$4.7$ per gallon. However, comparison with the conventional two-reactor system highlights the need for catalyst performance improvements. Sensitivity analysis emphasized the importance of manufacturing cost, liquid fuel yield, and biogas flow rate. Further analysis determined that the IBGTL process must achieve a diesel mass yield beyond 11.7% to surpass the economic viability of the conventional TriFTS (Tri-reforming followed by Fischer-Tropsch Synthesis) process. If the IBGTL process attains the TriFTS yield of up to 17%, the resulting MFSP could be approximately 31% lower than the current TriFTS MFSP. Furthermore, renewable energy credits and carbon credits can further enhance the economic viability of BGTL processes.

09 BIOMASS FUELS↗

Unraveling the relationship between physicochemical properties of NiFeReOx catalysts and the correlated performance toward electrochemical oxygen evolution reaction

NiFeO x catalysts with single site Re dopants exhibit much higher active and stability toward electrochemical oxygen evolution reaction (OER) compared to traditional NiFeO x catalysts. Nevertheless, the relationship between physicochemical properties of NiFeReO x catalysts and the correlated performance toward OER is unclear, which hampers to enhance the OER performance further. Herein, we prepared a series of NiFeReO x catalysts with different physicochemical properties by treating them at different temperatures (up to 350 °C) and then evaluated their performance toward OER. Here, the results show that heat treatment can convert all metal oxidation states to higher values as well as specific surface areas, which are believed to favor real active site generation and OER activity enhancement. A decrease in activity is observed with the temperature increase at the low current range, and the smallest overpotential of 248 mV at 10 mA cm −2 is achieved with the pristine NiFeReO x catalyst. In contrast, the heat-treated samples possess smaller Tafel slopes and lower charge transfer resistance likely due to enhanced intrinsic activity (from higher oxidation states) and conductivity, which facilitate the reaction kinetics and surpass the pristine sample at a large current density. Additionally, the sample treated at 350 °C exhibits a higher activity at 1000 mA cm −2 (1.68 V vs. RHE compared to pristine sample of 1.92 V vs. RHE); however, it manifests a poorer stability compared to the pristine one due to the imbalance of reconstruction/transformations that occurred on the catalyst surface during OER operation. Our work unravels the relationship between physicochemical properties of NiFeReO x catalysts and the correlated OER performance and provides valuable insights for designing NiFeReO x catalysts with high activity and durability.

Catalyst reconstruction↗

Stable yet hydrophilic graphene oxide nanomembranes by zwitterionic reduction for dye desalination

Holey graphene oxide (HGO) nanosheets have emerged as a promising membrane platform for dye desalination, and they must be reduced to enhance hydrophobicity and stability for long-term underwater operation, which usually decreases water and salt permeance. Herein, we develop a facile method to stabilize HGO nanosheets while retaining their hydrophilicity by reducing them with sulfobetaine amine (SBAm, a superhydrophilic zwitterion), achieving high water and salt permeance and a high salt/dye separation factor. Specifically, HGO nanosheets react with SBAm via an amine-epoxide reaction, rendering reduced HGO nanosheets containing superhydrophilic zwitterions. The effects of in-plane pores, zwitterion content, and layer thickness on the membrane chemistry, structure, and salt/dye separation properties of the SBAm-reduced HGOs (SHGOs) are thoroughly examined. The membrane achieves a Na 2 SO 4 /Direct red separation factor of up to 850, surpassing the state-of-the-art GO membranes. Moreover, hollow fiber membrane modules based on SHGOs are fabricated and exhibit stable performance in multi-cycle tests over 100 h of operation with mixed dye-salt solutions, demonstrating the scalability of our approach and its potential for practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rheological characterization of 3D printable geopolymers

This study demonstrates a two-step approach that enables quantification of concrete printability through dynamics mode rheological measurements; I) modeling shearing history during extrusion; II) monitoring the hardening evolution of deposited material by applying a strain smaller than the critical strain. It is shown that the shearing history of the material is removed by imposing a pre-shearing above the critical strain, and zero value yield stress is measured for all specimens. At step II, a linear extrapolation of the green strength development can quantify the static yield stress at the origin, which we used to quantify the material printability. As far as this yield stress surpasses the stress level that exists in the printed structure, the material retains its shape stability. We show the performance of the model on a series of geopolymer mortars with a wide range of rheological properties as a function of material composition, aging, and pre-shearing consequences.

36 MATERIALS SCIENCE↗

Comparative study of three yttrium organometallic compounds for the stabilization of the cubic phase in YSZ deposited by PE-CVD

In this work, the efficiencies of three organometallic yttrium precursors used to produce YSZ coatings by plasma-enhanced chemical vapor deposition were studied. Yttrium (III) acetylacetonate, Y (acac) 3 , yttrium (III) hexafluoroacetylacetonate, Y (acacF 6 ) 3 , and yttrium (III) tris(2,2,6,6-tetramethyl-3,5-heptanedionate), Y (tmhd) 3 , were used to stabilize the cubic phase in zirconia deposited at temperatures from 500 to 800 °C. Our results showed that at temperatures between 500 and 600 °C, Y (tmhd) 3 appeared to be the most efficient dopant as it introduced the highest concentration of yttria (1–2.7 mol%) with only 6.4–5.6 at.% carbon. However, at 700 and 800 °C, Y (acac) 3 introduced twice as much yttria (8–15 mol%) as Y (tmhd) 3 with almost the same amount of carbon (5.4–3 at.%). Conversely, Y (acacF6)3 was the least efficient as it maintained a low concentration of yttria of around 0.7–1.8 mol% with 3.6–8.2 at.% carbon for all the deposition temperatures. Among these precursors, only Y (acac) 3 surpassed 8 mol% yttria and achieved a fully stabilized cubic phase at 800 °C, with the remaining samples stabilizing only the tetragonal phase. The tetragonal phase was stabilized due to the formation of crystallites of around 10 nm. The observed difference in the efficiency of the three precursors was correlated to important differences in their decomposition behavior as observed by mass spectrometry and thermogravimetry/differential scanning calorimetry.

36 MATERIALS SCIENCE↗

Effect of various post-extrusion tempering on performance of AA2024 tubes fabricated by shear assisted processing and extrusion

In this report aluminum alloy 2024 (AA2024) tubes were extruded using the shear assisted processing and extrusion (ShAPE) method. As a ubiquitous aerospace alloy, AA2024 has reached a high degree of maturity with respect to manufacturing processes, alloy chemistry and heat treatment to maximize material strength. Therefore, over the eight decades since the introduction of this alloy, the mechanical properties have plateaued, and the extrusion speed has reached a 3.5 m/min ceiling using conventional extrusion. The ShAPE technique enabled an extrusion speed of AA2024 up to 7.4 m/min at 480 °C which is surpassing the extrudability chart of this alloy. Variation of the standard T3510 and T8510 post extrusion heat treatments were applied to improve the mechanical performance of the ShAPE extruded AA2024 tube. The ultimate tensile strength and yield strength of AA2024-T8510 ShAPE extruded tube are 522.0 ± 3.3 MPa and 510.7 ± 3.3 MPa, which are respectively 18% and 32% higher than ASM-typical and ASTM minimum values. The elongation at break of ShAPE extruded AA2024-T8510 tubes is two times higher than the ASM-typical and ASTM-minimum values. This improved ductility is attributed to the refinement of grain size and secondary phases as well as due to the uniform dispersion of sub-micron strengthening precipitates formed during the ShAPE process.

42 ENGINEERING↗

Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials

Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.

2D materials↗

Effect of the numerical discretization scheme in Shock-Driven turbulent mixing simulations

In this work, we evaluate the effects of distinct numerical strategies in simulations of shock-driven turbulent mixing. An air-SF 6 -air gas curtain subjected to Mach 1.2 shock-waves is computed with Implicit Large-Eddy Simulation based on three numerical schemes: directional-split with Harten-Lax-van Leer (HLL) solver; directional-unsplit using HLL-Contact (HLLC) solver; and directional-unsplit with HLLC solver and a Low Mach number Correction (LMC). The results illustrate the importance of the numerical strategy to the accuracy of the predictions. Whereas both split and unsplit schemes result in a similar spatial development of the initial shock-driven instability, only the unsplit schemes can predict the turbulent mixing transition after reshock observed by the laboratory experiments. Such feature increases the mixing rate of the two fluids, this being particularly pronounced when the LMC is active due to i) the reduced flow Mach number, and ii) the larger effective Reynolds number. Since the selected mixing problem is driven by the deposition of vorticity at the fluids’ interface, the resultant flow physics is analyzed by investigating the contribution of distinct inviscid mechanisms to the production of vorticity: baroclinicity, stretching, and dilatation. As expected, it is observed that the production of vorticity is initially dominated by the baroclinicity mechanism. Yet, the relevance of the remainder mechanisms is enhanced after the reshock and may even surpass the baroclinicity term.

42 ENGINEERING↗

Long term oxidation of NiCoCrAlY coated Ni-based superalloys: A comparison of observed and simulated interdiffusion

Lifetimes of MCrAlY-type coatings can easily surpass 25 kh when the criteria of ß-depletion is used. To reduce experimental effort, it’s necessary to develop models capable of simulating interdiffusion and oxidation. In the present study, NiCoCrAlY coatings were high velocity oxyfuel deposited on PWA 1483, MARM247, and CMSX-4 substrates, and samples were exposed at 900 °C for 5–20 kh in air+10 vol%H 2 O to study interdiffusion rates. Here, Thermo-Calc/DICTRA was used to reproduce the observed differences, and microstructures were compared. Based on the agreement between calculated and observed rates, simulations were projected past the experimental exposures, utilizing ß-depletion as lifetime criteria.

36 MATERIALS SCIENCE↗

High-performance data format for scientific data storage and analysis

Here, in this article, we present the High-Performance Output (HiPO) data format developed at Jefferson Laboratory for storing and analyzing data from Nuclear Physics experiments. The format was designed to efficiently store large amounts of experimental data, utilizing modern fast compression algorithms. The purpose of this development was to provide organized data in the output, facilitating access to relevant information within the large data files. The HiPO data format has features that are suited for storing raw detector data, reconstruction data, and the final physics analysis data efficiently, eliminating the need to do data conversions through the lifecycle of experimental data. The HiPO data format is implemented in C++ and JAVA, and provides bindings to FORTRAN, Python, and Julia, providing users with the choice of data analysis frameworks to use. In this paper, we will present the general design and functionalities of the HiPO library and compare the performance of the library with more established data formats used in data analysis in High Energy and Nuclear Physics (such as ROOT and Parquete). In columnar data analysis, HiPO surpasses established data formats in performance and can be effectively applied to data analysis in other scientific fields.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗