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NASA NTRSDate not supplied

High Temperature Pressure (HTP) Boron Nitride Nanotube (BNNT): Discovery and Commercialization

Future NASA missions for space exploration require key technological elements that must provide sustainability, survivability and operational envelope in extreme environments, such as the high and low extremes in pressures and temperatures, ionizing radiations, chemical and/or physical corrosion, and hypervelocity particles. Advanced multifunctional materials enable revolutionary design schemes for future aerospace vehicles and structures for the extreme environments of NASA missions. Recent studies of nanocomposite materials have shown the potential for both structural integrity and multifunctional capabilities, such as sensing, actuating, health monitoring, radiation shielding, energy harvesting, thermal management, and thermal protection in extreme environments. After the advent of carbon nanotube (CNT) in 1991, scientists predicted that boron and nitrogen, carbons immediate neighbors on the periodic chart, might also form perfect nanotubes, namely boron nitride nanotubes (BNNTs). The discovery and progress of a new catalyst-free method for synthesizing highly crystalline, very long, and small diameter BNNTs under a high temperature and pressure (HTP) environment have enabled new applications for multifunctional materials. The white color BNNTs offer extraordinary properties including neutron radiation shielding, piezoelectricity, electrostriction, high thermal oxidative stability (>800C in air), not present in CNTs, as well as excellent mechanical strength and toughness, equivalent to CNTs. The characteristics of the BNNTs and their composites along with CNT composites are discussed in this presentation along with their potential aerospace applications in extreme environments.

Cheol Park↗

NASA NTRS2018

Experimental Effervescence and Freezing Point Depression Measurements of Nitrogen in Liquid Methane-Ethane Mixtures

NASA is designing an unmanned submarine to explore the depths of the hydrocarbon-rich seas on Saturn’s moon Titan. Data from Cassini indicates that the Titan north polar environment sustains stable seas of variable concentrations of ethane, methane, and nitrogen, with a surface temperature near 93 K. The submarine must operate autonomously, study atmosphere/sea exchange, interact with the seabed, hover at the surface or any depth within the sea, and be capable of tolerating variable hydrocarbon compositions. Currently, the main thermal design concern is the effect of effervescence on submarine operation, which affects the ballast system, science instruments, and propellers. Twelve effervescence measurements on various liquid methane-ethane compositions with dissolved gaseous nitrogen are thus presented from 1.5 bar to 4.5 bar at temperatures from 92 K to 96 K to simulate the conditions of the seas. After conducting effervescence measurements, two freezing point depression measurements were conducted. The freezing liquid line was depressed more than 15 K below the triple point temperatures of pure ethane (90.4 K) and pure methane (90.7 K). Experimental effervescence measurements will be used to compare directly with effervescence modeling to determine if changes are required in the design of the thermal management system as well as the propellers.

Freezing Point Depression↗

DOE OSTI2026

Surrogate modeling of Monte Carlo radiation transport with convolutional neural networks for shielding optimization

Here, we present a machine learning (ML)-based surrogate model using convolutional neural networks (CNN) designed to emulate the attenuation of neutron fields as they pass through various shielding materials. This model can compute the outgoing neutron flux almost instantaneously and achieves reasonable accuracy compared to traditional Monte Carlo (MC)-based codes, which are computationally intensive. This emulator alleviates the complexity of neutron radiation transport through shielding materials by reducing the dimensionality and enables shielding optimization for a known radiation environment. This optimization process, which would have taken an unrealistic timeline due to several complex radiation transport simulations, can now be achieved in minutes, thus increasing computational capabilities in radiation shielding assessment. We demonstrate the applications of this emulator in computing effective dose rates and optimizing shielding solutions for a heavy-ion accelerator facility, such as the Facility for Rare Isotope Beams, where secondary neutrons produced via beam interactions dominate the radiation environment.

accelerator shielding↗

NASA NTRS2026

GVIPS Prediction of Cyclic Ratchetting Behavior and Cycles with Interrupted Relaxation Periods of TIMETAL 21S at 650 °C

The predictive performance of a multimechanism GVIPS model with saturating hardening function is assessed against a set of high temperature cyclic experiments under both strain-control and stress-control at varying rates of loading as well as several complex interrupted cyclic responses. The material specimens were composed of the titanium alloy, TIMETAL 21S, and tested at 650 °C, see Lissenden et al., 2007. The model did a very good job of predicting the variety of tests, particularly given the fact that only monotonic loading tests (tensile, creep, relaxation) and a single fully reversed cycle was used for characterization. It was particularly interesting that the model was capable of reasonably capturing the rate of accumulated strain during ratchetting under tensile mean stress. Given complex interrupted cyclic response, the model was able to both qualitatively and even quantitatively predict reasonably well both the cyclic and associated relaxation periods (in all quadrants of the stress-strain space) thus confirming the validity of the chosen functional forms for both hardening and thermal recovery. The quantitative inaccuracy is associated with the fact that the material specimens tested by Lissenden et al., 2007 was significantly “softer” than those tested by Castelli in Saleeb et al., 1994 which were used for characterization of the GVIPS model parameters.

Viscoplaticity↗

NASA NTRS2026

Development of the Orion Life-Support Integration Facility (OLIF)

Testing the life support hardware of a vehicle that is going to take humans beyond low-Earth orbit (LEO) in conditions similar to space is crucial. The Orion Life-Support Integration Facility (OLIF) at NASA Johnson Space Center (JSC) was designed and built to test the Orion vehicle’s hardware and software as integrated systems to provide a complete Environmental Control and Life Support System (ECLSS) system-level qualification. The existing 11 Foot human rated vacuum chamber has been adapted to accommodate and integrate various qualification and flight like components of the Orion vehicle’s Air Revitalization System (ARS), Pressure Control System (PCS), Active Thermal Control System (ATCS) and the Orion Crew Survival System Suits (OCSS). The ultimate goal was to create an analog testbed that could safely support up to four test subjects in open “shirt-sleeve” or closed suit loop configurations and simulate Orion Cabin conditions. This integrated hardware/software ARS and PCS will help identify any technical issues that should be addressed prior to the Artemis-2 mission. This paper will discuss the history of Orion ECLSS hardware development testing in the 11 Foot Chamber, the challenge of integrating flight hardware and software control systems, and the capabilities that make it a unique, world class facility for NASA. It will provide an overview of past and future testing, and the lessons learned along the way.

Peter A Masi↗

DOE OSTI2024

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry↗

NASA NTRS2026

Glenn Research Center Propulsion Systems Laboratory 2026 Customer Guide

This guide describes the Propulsion Systems Laboratory (PSL) at the NASA Glenn Research Center. It was written to help customers understand the various components involved in conducting a test program within the PSL. The PSL complex supports two large-engine test cells that simulate altitude flight conditions for a wide range of research and experimental tests. These test cells operate at altitudes up to 90,000 ft and speeds from subsonic to above supersonic. Test points such as pressure, temperature, and Mach number can be set at the engine or test article inlet based on customer requirements. The facility’s support systems include the heated and cooled combustion air systems; altitude exhaust system; hydraulic system; nitrogen, oxygen, and hydrogen systems; thrust measurement system, which includes the facility’s single- and multi-axis thrust stands; inlet system; and electrical systems. In addition to providing a detailed description of PSL systems and capabilities, this guide discusses the facility’s history and past tests and addresses facility safety procedures, pretest requirements, and test operation standards.

Engine Icing Test Facility↗

DOE OSTI2026

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗

DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗

NASA NTRSDate not supplied

Accelerating SNP Development with Radiation Source Approximations for Far-Field Environment Modeling

The successful development and deployment of space nuclear power and propulsion technology requires a high-fidelity, efficient means of modeling ex-core radiation fields. Monte Carlo particle transport codes provide enable the highest level of fidelity in radiation field modeling but are inefficient for modeling ex-core radiation without modification. This paper details the development of an approach to ex-core radiation field modeling that maintains the fidelity of a Monte Carlo transport approach without sacrificing computational efficiency. This approach is based on recent improvements to an existing Monte Carlo transport acceleration technique known as surface source banking. As the transport of many particles is required to ensure adequate uncertainty in far field transport, analytical reconstruction techniques are employed to represent surface source banks as sampleable series of distributions in particle phase from which an arbitrarily large number of particles can be generated and simulated. All steps of this approach are incorporated into an AMA model to test both the underlying mathematics of the analytical source reconstruction process, as well as the relevance of the technique as a whole towards SNP applications. These tests demonstrated that this approach is capable of accelerating far-field radiation modeling in SNP-relevant scenarios by factors of at least nine over purely eigenvalue-based scenarios without significantly sacrificing simulation accuracy.

Surface Source Banking↗

DOE OSTI2024

Simulating hindered grain boundary diffusion using the smoothed boundary method

Abstract Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the smoothed boundary method to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.

Materials Science↗

DOE OSTI2026

Advanced LiFSI-LiPF6 Electrolyte for Wide-Temperature and Thermally Stable Lithium-Ion Batteries

A new optimized LiFSI–LiPF6 dual-salt controlled-solvation electrolyte (E-DS) is demonstrated to enable practical graphite||LiNi0.8Mn0.1Co0.1O2 cells (˜4.0 mAh cm?²) to achieve exceptional performance and safety under extreme conditions. By optimizing anion coordination with the smaller, more dissociating FSI? anion, the E-DS forms ultrathin, dense, and inorganic-rich electrode/electrolyte interphases that dramatically suppress solvent decomposition, transition-metal dissolution, and surface reconstruction compared to the conventional LiPF6/carbonate electrolyte. Consequently, E-DS cells deliver >78% capacity retention after 300 cycles at 60 °C, retain fast discharging capacity at 30 °C, and operate effectively at -20 °C. Most strikingly, fully charged full cells with E-DS, even under overcharging to 4.8 V, show a lower heat evolution in stable formulations — transforming a traditionally unstable high-voltage/high-temperature configuration into an intrinsically safe state. This work establishes a new benchmark for carbonate-containing electrolytes, simultaneously achieving high energy density, fast-discharging capability, wide-temperature operation (-20 to 60 °C), and outstanding thermal safety in nickel-rich lithium-ion batteries.

electrode/electrolyte interphase↗

NASA NTRS2004

New Lithium-ion Polymer Battery for the Extravehicular Mobility Unit Suit

The Extravehicular Mobility Unit (EMU) suit currently has a silver-zinc battery that is 20.5 V and 45 Ah capacity. The EMU's portable life support system (PLSS) will draw power from the battery during the entire period of an EVA. Due to the disadvantages of using the silver-zinc battery in terms of cost and performance, a new high energy density battery is being developed for future use, The new battery (Lithium-ion battery or LIB) will consist of Li-ion polymer cells that will provide power to the EMU suit. The battery design consists of five 8 Ah cells in parallel to form a single module of 40 Ah and five such modules will be placed in series to give a 20.5 V, 40 Ah battery. Charging will be accomplished on the Shuttle or Station using the new LIB charger or the existing ALPS (Air Lock Power Supply) charger. The LIB delivers a maximum of 3.8 A on the average, for seven continuous hours, at voltages ranging from 20.5 V to 16.0 V and it should be capable of supporting transient pulses during start up and once every hour to support PLSS fan and pump operation. Figure 1 shows the placement of the battery in the backpack area of the EMU suit. The battery and cells will undergo testing under different conditions to understand its performance and safety characteristics.

Jeevarajan, J. A.↗

DOE OSTI2025

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion↗

NASA NTRS2025

ISS Radiator Face Sheet Anomaly Investigation and Return to Function

Maintaining sufficient heat rejection on the International Space Station (ISS) is critical to the function of the Low-Earth Orbit station. The External Active Thermal Control System (EATCS) rejects the excess heat generated by the US On-Orbit Segment (USOS) modules. The system uses single-phase liquid ammonia to collect the heat and reject it to six radiators (three on the Starboard side, three on the Port side). Each radiator is made up of eight panels. In September 2008, imagery of the Starboard radiators was conducted and showed one of the panels’ face sheets had peeled up from the internal honeycomb core structure. Out of an abundance of caution, the radiator was isolated from the rest of the EATCS and the ammonia was vented to space. Since the radiator was vented, periodic imagery of all radiator panels was taken to monitor any changes in the face sheet and inspect for other radiator anomalies. In January 2025, after years of trending and inspections, the radiator was reintegrated into the system to increase heat rejection capabilities. This paper will document the multi-year investigation that took place to determine root cause and mitigations implemented to reduce risk to the system. A summary of the data since the investigation will show rationale for reintegrating the radiator even with the damaged panel. The goal of the paper is to document the investigation for historical purposes and provide future programs with findings discovered during the investigation.

Aaron Rodriguez↗

NASA NTRS2026

ISS Radiator Face Sheet Anomaly Investigation and Return to Function

Aaron Rodriguez↗

DOE OSTI2025

Bioinspired Dry‐Steam Superinsulation Straw Foam

Abstract Cellulosic materials offer sustainable advantages for building energy conservation. However, their development has been hindered by reduced thermal performance, often caused by structural collapse during the transition from solution to solid. Inspired by natural goose down, a bio‐based, lightweight insulation foam derived from agricultural waste straw is presented. Through in situ synthesis, bio‐silica fibers with branched structures capable of supporting hollow silica microspheres are fabricated. After steam‐mediated processing, the resulting foam exhibit low density (95 mg cm − 3 ), high porosity (95.5%), low thermal conductivity (0.03 ± 0.003 W mK −1 ), and a cyclic compressive strength of 90 kPa at 50% strain. Owing to the synergistic microstructure formed by branched bio‐fibers and hollow silica spheres, the bio‐silica foam exhibit outstanding thermal insulation performance relative to other bio‐based foams prepared by ambient drying. A passivated insulation panel is further developed by incorporating this material as the core component, achieving a thermal conductivity of 0.0275 W mk −1 and flexural strength of 6.85 MPa. The panel demonstrated durability with stable thermal performance throughout a 60‐day outdoor test. Moreover, the bio‐silica foam shows a carbon footprint of 7.50 kgCO₂ kg −1 at 70.2 wt.% silica, highlighting its promise as a sustainable insulation solution for green buildings.

Chemistry↗

NASA NTRS2025

High-density Boron Nitride Nanotube Composites via Surfactant-stabilized Lyotropic Liquid Crystals for Enhanced Space Radiation Shielding

Despite significant technological advancements in space exploration, human space travel and colonization remain limited by the health risks associated with space radiation. Boron nitride nanotubes (BNNTs) have been proposed as an advanced material for space applications due to their high specific strength and efficient radiation shielding capabilities. However, the practical implementation of BNNTs has been slow, primarily due to technological challenges in fabricating structural materials incorporating BNNTs. In this study, a method is presented for fabricating high-density BNNT films that are mechanically robust, exhibit high thermal conductivity, and effectively attenuate space radiation. The key advancement enabling high-density BNNT films is the successful preparation of BNNT liquid crystals (LCs), achieved through the strategic use of a commercial dodecylbenzenesulfonic acid surfactant. This surfactant ensures exceptional BNNT stability in aqueous dispersion, even at concentrations exceeding the LC phase transition threshold. Simulations, estimating the equivalent radiation dose to the human body in space, indicate that a high-density BNNT film with a surface density of 50 g cm−2 reduces the total dose equivalent rate by 56% compared to zero shielding. This enhancement would allow astronauts to extend their mission duration on the lunar surface by a factor of two.

Young-Kyeong Kim↗