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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tuning electrical and interfacial thermal properties of bilayer MoS2 via electrochemical intercalation

Layered two-dimensional (2D) materials such as MoS 2 have attracted much attention for nano- and opto-electronics. Recently, intercalation (e.g. of ions, atoms, or molecules) has emerged as an effective technique to modulate material properties of such layered 2D films reversibly. We probe both the electrical and thermal properties of Li-intercalated bilayer MoS 2 nanosheets by combining electrical measurements and Raman spectroscopy. Furthermore, we demonstrate reversible modulation of carrier density over more than two orders of magnitude (from 0.8 × 10 12 to 1.5 × 10 14 cm -2 ), and we simultaneously obtain the thermal boundary conductance between the bilayer and its supporting SiO 2 substrate for an intercalated system for the first time. This thermal coupling can be reversibly modulated by nearly a factor of eight, from 14 ± 4.0 MW m -2 K -1 before intercalation to 1.8 ± 0.9 MW m -2 K -1 when the MoS 2 is fully lithiated. These results reveal electrochemical intercalation as a reversible tool to modulate and control both electrical and thermal properties of 2D layers.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Kinetically Controlled Synthesis of Rhodium Nanocrystals with Different Shapes and a Comparison Study of Their Thermal and Catalytic Properties

Here, we report the synthesis of Rh nanocrystals with different shapes by controlling the kinetics involved in the growth of preformed Rh cubic seeds. Specifically, Rh nanocrystals with cubic, cuboctahedral, and octahedral shapes can all be obtained from the same cubic seeds under suitable reduction kinetics for the precursor. The success of such a synthesis also relies on the use of a halide-free precursor to avoid oxidative etching, as well as the involvement of a sufficiently high temperature to remove Br – ions from the seeds while ensuring adequate surface diffusion. The availability of Rh nanocrystals with cubic and octahedral shapes allows for an evaluation of the facet dependences of their thermal and catalytic properties. The data from in situ electron microscopy studies indicate that the cubic and octahedral Rh nanocrystals can keep their original shapes up to 700 and 500 °C, respectively. When tested as catalysts for hydrazine decomposition, the octahedral nanocrystals exhibit almost 4-fold enhancement in terms of H 2 selectivity relative to the cubic counterpart. As for ethanol oxidation, the order is reversed, with the cubic nanocrystals being about three times more active than the octahedral sample.

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

Novel method to control explosive shock sensitivity: A mesoscale study to understand the effect of thermally expandable microsphere (TEM) inclusions in high explosives (HE) microstructure

When the void content and/or void structure of a high explosive (HE) is altered by some means (i.e., bulk heating or mechanical damage), the shock initiation behavior of the material changes. The ability to precisely predict the change in shock sensitivity after an HE has undergone microstructural changes is a crucial capability in multi-scale reactive flow models. Here, we utilize thermally expandable microspheres (TEMs) as a dopant in a polymer bonded explosive (PBX) matrix to alter the shock initiation properties in a controlled fashion. Here, using a mesoscale modeling approach, we evaluated how a single TEM (before and after thermal expansion) behaves under shock compression, as well as how the matrix PBX in the direct vicinity of the TEM is affected. We first examined the effect of an unexpanded TEM in the explosive matrix and found that its presence does not significantly perturb the bulk flow and by extension will not affect bulk sensitivity. Next, we examined the effect of an expanded TEM and found that its presence significantly perturbs the flow via hydrodynamic jetting, which causes a secondary shock wave with a strength that exceeds that of the incident wave. Finally, we showed that this secondary shock interacts with the downstream porosity to ignite a larger fraction of the overall pore volume, commensurate with the secondary shock strength and the affected volume, increasing the global (bulk) shock sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Three-dimensional hierarchical nanoporous copper via direct ink writing and dealloying

Three-dimensional (3D) hierarchical nanoporous Cu (3DHNP-Cu) is synthesized using a combination of direct ink writing (DIW) based 3D printing, thermal sintering, and chemical dealloying of Mn–Cu alloys. Through tuning processing conditions such as ink composition and cooling rate (after sintering), with consideration of Mn loss during sintering, 3DHNP-Cu with fully bicontinuous nanostructures and negligible residual Mn can be produced after dealloying. The 3DHNP-Cu is comprised of structural features that span seven orders of magnitude, where DIW digitally controls macroscale porous features, thermal sintering and degradation of the binding polymer determines microscale porous features, and dealloying gives rise to nanoscale pores.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nondiffractive beam shaping for enhanced optothermal control in metal additive manufacturing

High thermal gradients and complex melt pool instabilities involved in powder bed fusion–based metal additive manufacturing using focused Gaussian-shaped beams often lead to high porosity, poor morphological quality, and degraded mechanical performance. We show here that Bessel beams offer unprecedented control over the spatiotemporal evolution of the melt pool in stainless steel (SS 316L) in comparison to Gaussian beams. Notably, the nondiffractive nature of Bessel beams enables greater tolerance for focal plane positioning during 3D printing. We also demonstrate that Bessel beams significantly reduce the propensity for keyhole formation across a broad scan parameter space. High-speed imaging of the melt pool evolution and solidification dynamics reveals a unique mechanism where Bessel beams stabilize the melt pool turbulence and increase the time for melt pool solidification, owing to reduced thermal gradients. Consequently, we observe a distinctively improved combination of high density, reduced surface roughness, and robust tensile properties in 3D-printed test structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Giant isotope effect on phonon dispersion and thermal conductivity in methylammonium lead iodide

Lead halide perovskites are strong candidates for high-performance low-cost photovoltaics, light emission, and detection applications. A hot-phonon bottleneck effect significantly extends the cooling time of hot charge carriers, which thermalize through carrier–optic phonon scattering, followed by optic phonon decay to acoustic phonons and finally thermal conduction. To understand these processes, we adjust the lattice dynamics independently of electronics by changing isotopes. We show that doubling the mass of hydrogen in methylammonium lead iodide by replacing protons with deuterons causes a large 20 to 50% softening of the longitudinal acoustic phonons near zone boundaries, reduces thermal conductivity by ~50%, and slows carrier relaxation kinetics. Phonon softening is attributed to anticrossing with the slowed libration modes of the deuterated molecules and the reduced thermal conductivity to lowered phonon velocities. Our results reveal how tuning the organic molecule dynamics enables control of phonons important to thermal conductivity and the hot-phonon bottleneck.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A dynamic thermal algal growth model for pilot-scale open-channel raceways

Here this study describes the makeup of and results from a simulation consisting of a lumped thermal model integrated with a dynamic algae growth model to simulate the microalgae productivity of an open-channel raceway cultivation system. The thermal model considers the dynamic effects of weather, light absorption, convective heat transfer, radiation heat transfer, conductive heat transfer, thermal capacitance, and water control strategies. The dynamic algae growth model solves a set of ordinary differential equations consisting of growth functions dependent on incident radiation, temperature, nutrient availability, basal metabolism, and losses due to dark- and photo-respiration. Relative errors in the predicted ash-free dry weight of Nannochloropsis oceanica are 12.5%, -6.1%, and 4.4% for three separate replicates of cultivation cycles (~4.2 m 2 ) performed at AzCATI during the ATP 3 Unified Field Studies in Fall, Spring, and Summer. This research demonstrates that thermal modeling is an essential contributor to the validation of microalgae growth models.

09 BIOMASS FUELS↗
DOE OSTI2025

Additive manufacturing of mullite ceramic by digital light processing

Mullite material was successfully additively manufactured using digital light processing (DLP). The printed geometry involves a one-step process of pyrolysis, de-binding, and sintering under a plain atmosphere to achieve an average of 76 % ceramic yield and linear shrinkage of 12 %. Furthermore, the thermal profile was carefully controlled to obtain consistent phases in which the XRD shows a mullite phase. Here, in addition, the Weibull analysis was conducted on the sintered flexural specimens, showing a Weibull modulus (m) of 13.05 with a characteristic strength (σ 0 ) of 94.96 MPa. Synchrotron microtomography was performed on the sintered specimens, which showed two distinct porosity distributions (small and large). Large porosity (non-spherical elongated) is the primary cause of decreased material strength, while small porosity (spherical) is the sintering product. The measured thermal conductivity of the specimens was in the range of 2.7–3.1 W/m∙k and decreased with an increase in temperature. Lastly, large-scale prototypes were printed concurrently with a fine resolution of 25 μm without any compromise on the predetermined design and structure.

Additive manufacturing↗
DOE OSTI2021

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Ultra-High Temperature Thermal Barrier Coating Development and Validation

The most effective method to improve industrial gas turbine power is to increase firing temperature. To maintain component durability at these higher temperatures, thermal barrier coatings (TBC’s) are playing an increasing role in protecting turbine hardware. TBC’s have been successfully used on Solar Turbines’ combustor liners and turbine airfoils, but there is a need for TBC’s that can operate at higher temperatures. Based on recent, favorable rig testing experience, Solar recognized that yttrium aluminum garnet (YAG) TBC’s made by the Solution Precursor Plasma Spray Process (SPPS) has great potential for higher turbine temperatures. This testing verified the thermal cycle durability of the SPPS YAG TBC’s, as well as demonstrated that the temperature drop through the SPPS YAG TBC was twice that measured across a companion APS YSZ TBC. The SPPS YAG TBC with the potential for a 200°C improvement in temperature capability represents a materials breakthrough. The SPPS process also produces a number of unique microstructural features that confer superior properties. SPPC TBC’s have ultra-fine splats that increase toughness and erosion resistance, and the process can be tailored to produce through-thickness cracks for strain-tolerance and control porosity for lower thermal conductivity and increase coating abradability. This proposal would include further development of SPPS YAG density-graded coatings, optimization of the application process, and validation of higher temperature capability and durability through rig and engine testing of coated combustion liners and turbine outer air seals. The technology would be advanced from a TRL 3 to a proposed TRL 6 by overcoming processing concerns on efficiency, application distance and optimization of a graded coating without impacting coating durability by demonstrating the coating performance on components in rig and development gas turbine engine testing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magnetoanisotropic thermal transport in a topological Josephson junction

Highlights: • Thermal conductance is sensitive to orientation and magnitude of the exchange field. • The NDTC is exhibited and tuned by the magnitude of the exchange field. • The interplay of zero-energy ABSs and thermal transport has been well inferred. • Our findings can apply to the energy control in hybridized mesoscopic systems. The thermal transport in Joesphson junctions, particularly, based on topological insulators (TIs), has not been extensively studied so far. Herein, we theoretically investigate the magnetoanisotropic thermal transport in a TI-based Josephson hybrid structure with a ferromagnetic insulator sandwiched between two superconductors (SCs). It is shown that the thermal conductance and current both are considerably sensitive to the orientation and magnitude of the exchange field. In particular, the negative differential thermal conductance is exhibited, which is modulated by the exchange field. More interestingly, zero-energy Andreev bound states are confirmed with the help of the thermal conductance, which in turn demonstrates itself to be of significance in the thermal transport. It is expected that these findings could have potential applications for the energy control in various hybridized mesoscopic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Directed Self-Assembly of the Organic Semiconductor C8-BTBT-C8 in Anodic Aluminum Oxide Nanopores

Controlling the self-assembly of organic semiconductors at the nanoscale is critical for advancing high-performance electronic and photonic devices, yet it remains challenging due to their intrinsic anisotropic crystallization and sensitivity to processing conditions. Here, in this study, we demonstrate that cylindrical nanoconfinement within anodic aluminum oxide membranes provides a versatile platform to precisely tune the molecular orientation and phase behavior of the prototypical organic semiconductor 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT-C8). Combining temperature-dependent high-resolution synchrotron X-ray scattering with optical birefringence measurements, we uncover that confinement geometries (pore diameters 25–180 nm) and surface chemistry govern the emergence of distinct smectic A textures, featuring molecular layers either parallel or perpendicular to the pore axis. The competition between axial and radial smectic layering is modulated by pore size, surface hydrophilicity, and thermal history, enabling reversible control over domain orientations and transitions between liquid crystalline and crystalline states. Notably, nanoconfinement stabilizes the smectic phase over an expanded temperature range compared to bulk, while inducing complex multidomain configurations owing to geometric constraints and anchoring conditions. Our results elucidate fundamental mechanisms by which anisotropic nanoscale confinement directs the self-organization of highly conjugated organic molecules, with implications for optimizing directional charge transport and anisotropic optical responses in organic–inorganic hybrid nanoarchitectures. This study establishes nanoconfinement as a powerful strategy to engineer morphology and functional properties in organic semiconducting materials with nanoscale precision.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Physics vs structure: A systematic benchmark of learning strategies for multi-zone building thermal dynamics

Recent advances in physics-informed and data-driven machine learning promise improved thermal models for advanced building control, yet there is limited quantitative evidence on when added physics structure and architectural complexity are beneficial. Here, this work presents a systematic benchmark of five representative system identification methods for modeling multi-zone building thermal dynamics: linear state-space models, multi-layer perceptrons, neural state-space models, neural ordinary differential equations, and physically-consistent neural networks. The methods are evaluated across multiple data regimes and zone coupling strategies. Using a high-fidelity multi-zone commercial building emulator, we examine short-term and long-term prediction accuracy, computational efficiency, and ease of development. Our results reveal critical trade-offs between prediction performance, model complexity, and physical consistency. We demonstrate that decoupled, nonlinear black-box models consistently outperform coupled physics-constrained architectures in both predictive accuracy and out-of-distribution robustness in majority of the test cases for the building type considered in the study. Our findings quantify the cost of complexity in building thermal modeling and provide concrete, actionable, scenario-based guidelines for selecting model classes for control-oriented applications.

Building thermal modeling↗
DOE OSTI2022

Understanding curing dynamics of arylacetylene and phthalonitrile thermoset blends

Tetrakis(phenylethynyl)benzene (TPEB), a high char yield arylacetylene resin, was blended with a resorcinol-based PEEK™-like oligomeric phthalonitrile resin (Res). Here, we observed the influence of each polymer precursor on the structural changes and material dynamics of different mixtures of these resins during thermal curing to produce thermosets with high char retention. We provide insight to help understand fundamental processes that control and tune this complex thermally driven curing mechanism, which, to date, has not been well understood. We show that an equivalent blend of Res and TPEB mitigates the exothermic curing process and exhibits a low viscosity, which may facilitate processing of these thermosetting blends for composite manufacturing. To obtain a more comprehensive overview of the different dynamics of these polymers during curing, we correlated thermodynamic changes with rheology, materials characterization, and molecular dynamics derived from neutron scattering. Our efforts shed more light on the thermally driven chemical changes, physical transformation, and gelation dynamics that drive or accompany softening and curing of these two distinct crosslinking resin groups.

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

Impact Response of Control Atmosphere Plasma Spray Deposited Materials

Thermal spray processing of metals and respective blends is becoming increasingly attractive due to the unique properties such as increased yield strength, low ductility, and differences in tensile and compressive strengths that result from microstructural features due to the spray process compared to other additive manufacturing methods. Here we report the results of plate impact experiments applied to Controlled Atmosphere Plasma Spray deposits of tantalum (Ta), niobium (Nb), and a tantalum-niobium blend (TaNb). These methods allowed for definition of the Hugoniot for each material type and the assessment of the Hugoniot Elastic Limit (HEL). Spallation experiments were conducted, and soft recovery of each material type allowed for scanning electron microscopy to characterize the fracture mechanism during tensile loading.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Commercialization of Reflected Target Non-Intrusive Assessment (ReTNA) Tool, for Indoor Optical Analysis of Heliostats

Under HelioCon, NLR began developing a new optical measurement system, called Reflected Target Non-Intrusive Assessment (ReTNA). ReTNA has shown promise towards addressing metrology gaps for heliostat used in concentrated solar thermal (CST) plant. This project is focused on advancing this measurement system from the laboratory into industry, where it can provide valuable information for heliostat developers during research, development, and qualification of a heliostat design, and be used for quality assurance during heliostat manufacture. Over the course of this project, ReTNA was deployed at several commercial heliostat facilities. The system developed and deployed with the primary project partner, Solar Dynamics LLC, is described in detail. The report discusses each project Milestone, the ending status, the achieved value, and how these Milestones improve and qualify the ReTNA measurement tool. Finally, the final report covers the market advancements, path forward, commercial successes, and lessons learned. Final Technical report for TCF Base Technology-Specific project TCF-23-20118, Commercialization of Reflected Target Non-Intrusive Assessment (ReTNA) tool, for indoor optical analysis of Heliostats.

14 SOLAR ENERGY↗
DOE OSTI2025

Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

By virtually representing a physical object and process, a digital twin (DT) enables optimal autonomous operations by combining classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems. A DT’s values depend on how well models estimate quantities of interest and on how uncertainty is handled. Moreover, DTs often combine physics-based and data-driven models with mixed fidelities, where classical uncertainty quantification (UQ) struggles with many sources of uncertainty and real-time constraints. Here, this work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system. The tool is developed using metadata from an automated DT development process to learn correlations between sources of uncertainties and outcomes. During operation, it compares predictions with measurements, attributes discrepancies to dominant sources, and recommends parameter and configuration updates. We verify the workflow on a synthetic temperature-control problem and deploy it on a virtual Thermal Energy Delivery System, reducing mismatch and improving control robustness.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Continuous soil temperature measurements from 2019-10-4 to 2020-10-4, Teller road Mile 27, Seward Peninsula, Alaska

The dataset contains depth-resolved soil temperature measured at 45 discrete locations in a watershed located along the Nome-Teller road at Mile 27 in Seward Peninsula, Alaska. The dataset was generated to understand the local heterogeneity of soil thermal dynamics and their controls in a discontinuous permafrost region. At each location, temperatures were measured by a distributed temperature profiling probe designed based on Dafflon et al (2022). The dataset includes a description of the probe locations in the "Probe_locations.csv" file and the 45 data files (Soil_temperatures_*.csv). Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in NGA513_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗