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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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1,197 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mechanically Accelerated Depolymerization of Entangled Linear Polymer Melts

Mechanical forces can enhance the chemical depolymerization of synthetic polymers when shear flow accelerates chain scission. To quantify the extent of mechanically-accelerated scission, the effect of simple shear flow (duration and strength) with low Weissenberg and Deborah numbers was investigated by considering the impact of applied work in both simple shear and shear dominated mixed flows. Hydrogenated polyisoprene was chosen as a model linear, entangled system. The conditions (strain amplitude, frequency, and shearing time) necessary to increase chain scission were assessed in the rubbery melt. Shear flow accelerated chain scission at higher temperatures, suggesting an activated process. Isothermal scission versus work curves were superposed by applying shift factors a T,S , whose Arrhenius-like temperature dependence gave an apparent activation energy for chain scission of ~ 110 kJ/mol, which is likely a combination of the activation energy of viscosity and bond energy. This work provides a base for quantifying the impact of shear on depolymerization of polymer melts and highlight the connection between viscous dissipation and scission chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

A Laboratory Breadboard System for Dual-Arm Teleoperation

The computing architecture of a novel dual-arm teleoperation system is described. The novelty of this system is that: (1) the master arm is not a replica of the slave arm; it is unspecific to any manipulator and can be used for the control of various robot arms with software modifications; and (2) the force feedback to the general purpose master arm is derived from force-torque sensor data originating from the slave hand. The computing architecture of this breadboard system is a fully synchronized pipeline with unique methods for data handling, communication and mathematical transformations. The computing system is modular, thus inherently extendable. The local control loops at both sites operate at 100 Hz rate, and the end-to-end bilateral (force-reflecting) control loop operates at 200 Hz rate, each loop without interpolation. This provides high-fidelity control. This end-to-end system elevates teleoperation to a new level of capabilities via the use of sensors, microprocessors, novel electronics, and real-time graphics displays. A description is given of a graphic simulation system connected to the dual-arm teleoperation breadboard system. High-fidelity graphic simulation of a telerobot (called Phantom Robot) is used for preview and predictive displays for planning and for real-time control under several seconds communication time delay conditions. High fidelity graphic simulation is obtained by using appropriate calibration techniques.

A K Bejczy↗
DOE OSTI2024

Why Perovskite Thermal Stress is Unaffected by Thin Contact Layers

Metal halide perovskite photovoltaics have emerged as a high efficiency, low-cost alternative that can potentially rival or enhance conventional silicon technology. Despite exceptional initial power conversion efficiencies, achieving compliance with international standards and widespread adoption requires further enhancements to their operational stability. Notably, addressing mechanical strain and stress in brittle perovskites has emerged as a pivotal approach to mitigate chemical degradation and improve reliability during thermal cycling. Here, in this study, a popularized strain engineering strategy is investigated in which a high coefficient of thermal expansion (CTE) hole transport layer (i.e., PDCBT) is cast onto inorganic perovskite (CsPbI 2 Br) at 100 °C. Contrary to previously published results, the X-ray diffraction (XRD):Sin 2 ψ and substrate curvature measurement techniques show that the hole transport layer has no discernible impact on perovskite strain. The accuracy of the XRD:Sin 2 ψ method for measuring strain is highlighted in contrast to an analysis based on shifts of single XRD peaks which can be influenced by multiple artifacts. The findings in this study are in accordance with mechanics theory: thin layers are unable to induce significant strain changes in perovskite thin films as the force they apply is negligible compared to that applied by a thick and stiff substrate.

14 SOLAR ENERGY↗
NASA NTRS1966

Non-Metallic Materials

Nonmetallic materials development - cryogenic insulation, adhesives research, and membrane diffusion theory

Materials Science↗
DOE OSTI2024

The Electron‐Density Distribution of UCl 4 and Its Topology from X‐ray Diffraction

Abstract The chemistry of electrons in actinide complexes and materials is still poorly understood and represents a serious challenge and opportunity for experiment and theory. The study of the electron density distribution of the ground state of such systems through X‐ray diffraction represents a unique opportunity to quantitatively investigate different chemical bonding interactions at once, but was considered “almost impossible” on heavy‐atom systems, until very recently. Here, we present a combined experimental and theoretical investigation of the electron density distribution in UCl_ 4 crystals and comparison with the previously reported spin density distribution from polarized neutron diffraction. All approaches provide a consistent picture in terms of electron and spin density distribution, and chemical bond characterization. More importantly, the synergy between experiments and quantum‐mechanical calculations allows to highlight the remarkable sensitivity of X‐ray diffraction to electrons in materials.

Chemistry↗
NASA NTRS2026

NASA Weather Balloon Demonstration of an Additively Manufactured Antenna

Additive manufacturing (AM) enables low-cost, lightweight, and geometrically flexible antennas for rapid deployment missions. This work reports a left-hand circularly polarized magneto-electric dipole printed on a Radix dielectric with inkjet silver metallization and demonstrated as a process replacement for NASA weather-balloon RF hardware. By combining substrate fabrication and metallization, AM provides value for unrecoverable or field-replaceable systems. A physics based verification workflow links AM-specific material behavior to electromagnetic performance and yields bounded total, radiation, and mismatch efficiencies. Standard surface-impedance and roughness models failed to reproduce the frequency-dependent radiation loss observed in printed inks, underscoring the need for AM-specific conductor parameterization. Mission testing confirmed TDRSS link closure from NASA’s Columbia Scientific Balloon Facility and validated a repeatable print–measure–fly workflow for bounding RF performance and qualifying AM antennas for field use.

Peter Moschetti↗
NASA NTRSDate not supplied

NASA Weather Balloon Demonstration of an Additively Manufactured Antenna

Additive manufacturing (AM) enables low-cost, lightweight, and geometrically flexible antennas for rapid deployment missions. This work reports a left-hand circularly polarized magneto-electric dipole printed on a Radix dielectric with inkjet silver metallization and demonstrated as a process replacement for NASA weather-balloon RF hardware. By combining substrate fabrication and metallization, AM provides value for unrecoverable or field-replaceable systems. A physics based verification workflow links AM-specific material behavior to electromagnetic performance and yields bounded total, radiation, and mismatch efficiencies. Standard surface-impedance and roughness models failed to reproduce the frequency-dependent radiation loss observed in printed inks, underscoring the need for AM-specific conductor parameterization. Mission testing confirmed TDRSS link closure from NASA’s Columbia Scientific Balloon Facility and validated a repeatable print–measure–fly workflow for bounding RF performance and qualifying AM antennas for field use.

Peter Moschetti↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
DOE OSTI2025

A Phenazine‐Based Two‐Dimensional Covalent Organic Framework for Photochemical CO 2 Reduction with Increased Selectivity for Two‐Carbon Products

Abstract The reduction of carbon dioxide (CO₂) into valuable products will contribute to sustainable carbon use. Here we report the photocatalytic reduction of CO₂ to carbon monoxide, formate, and oxalate ions using a redox‐active phenazine‐based 2D covalent organic framework (Phen‐COF) and its phenazine monomer. Under similar irradiation conditions,Phen‐COFproduced 2.9 times more CO, 11 times more formate, and 13 times more oxalate compared to equimolar amounts of the monomeric phenazine, demonstrating that the COF architecture enhances catalytic performance (TOF COF : 10 −7 s −1 CO, 10 −8 s −1 formate, and 10 −11 s −1 oxalate). Structural analysis, including X‐ray diffraction and N₂ porosimetry, confirmed the COF's long‐range order and porosity. Mechanistic studies suggest a sequential formate‐to‐oxalate pathway, with CO and formate acting as intermediates. These results demonstrate the potential of the COF architecture to improve the performance of metal‐free, redox‐active aromatic systems such as phenazines to facilitate efficient and selective CO₂ conversion under mild conditions.

Chemistry↗