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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

Solid-State Syntheses, Crystallographic Spatial Disorders, Thermal Behaviors, and Bandgaps of Hybrid Organic-Inorganic Manganese Halides: A2Mn(Cl/Br)4 (A = NH4+, C(NH2)3+, & C3H4N2+)

By systematically optimizing solid-state synthesis via the concerted use of differential scanning calorimetry and in-situ variable-temperature X-ray diffraction, we report the discovery of four new hybrid organic-inorganic manganese halides A2Mn(Cl/Br)4 (A = NH4+, C(NH2)3+, C3H4N2+), with emphasis on how the organic fragment geometry, polarity, and electron-donating properties influence crystallographic spatial disorders, thermal behaviors, and optical band gaps. With a nonpolar tetrahedral cation, as in (NH4)2MnCl4 (P21/c, mP30) or (NH4)2MnBr4 (C2/c, mC180), the direct optical bandgaps (4.36–4.28 eV) are wider than those with an organic nonpolar planar geometry, as in (C(NH2)3)2MnBr4 (P21/c, mP300, 4.07 eV), or an organic polar planar geometry, as in (C3H4N2+)2MnBr4 (I41/a, tI384, 4.05 eV). Furthermore, the organic components affect the spatial arrangement and dimensionality of the resulting inorganic frameworks comprised of Mn(Cl/Br)6 octahedra, with varying distortions, or spatially disordered MnBr4 tetrahedra. These resulting trends, coupled with the systematic investigation into synthesis, and the motivation behind elucidating the nuanced role of the organic cation, altogether expand upon the phase-space of hybrid materials beyond perovskites and demonstrate the potential for a rational design of hybrid materials with tailored optoelectronic functionalities for advanced energy applications.

Lee, Shannon J.↗

Microporous water with high gas solubilities

Liquids with permanent microporosity can absorb larger quantities of gas molecules than conventional solvents , providing new opportunities for liquid-phase gas storage, transport, and reactivity. Current approaches to designing porous liquids rely on sterically bulky solvent molecules or surface ligands and thus are not amenable to many important solvents, including water. Here, we report a generalizable thermodynamic strategy to preserve permanent microporosity and impart high gas solubilities to liquid water. Specifically, we show how the external and internal surface chemistry of microporous zeolite and metal–organic framework nanocrystals can be tailored to promote the formation of stable dispersions in water while maintaining dry networks of micropores that are accessible to gas molecules. As a result of their permanent microporosity, these aqueous fluids can concentrate gases, including oxygen (O 2 ) and carbon dioxide (CO 2 ), to much higher densities than are found in typical aqueous environments. Furthermore, when these fluids are oxygenated, record-high capacities of O 2 can be delivered to hypoxic red blood cells, highlighting one potential application of this new class of microporous liquids for physiological gas transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resource Prospector (RP): A Cost-Effective Lunar Resource Pathfinder

Resource Prospector (RP) is an in-situ resource utilization (ISRU) technology demonstration mission under study by the NASA Human Exploration and Operations Mission Directorates (HEOMD). This clever mission is currently planned to launch in 2020 and will demonstrate extraction of oxygen, water and other volatiles, as well measure mineralogical content such as silicon and light metals, like aluminum and titanium, from lunar regolith. Expanding human presence beyond low-Earth orbit to asteroids and Mars will require the maximum possible use of local materials, so-called in-situ resources, and the moon presents a unique destination to conduct robotic investigations that advance ISRU capabilities, as well as providing significant exploration and science value. This mission is equally important; however, for how it executes as a risk-tolerant, cost-effective mission. RP follows on the path-finding approaches of the Lunar Crater Observation and Sensing Satellite (LCROSS) mission. The LCROSS mission confirmed the presence of water-ice on the moon, but also established a new lightweight-approach to project and mission execution which was considerably cheaper and faster than traditional NASA missions. RP has been designated as a Class D mission, just as LCROSS. This mission classification is the most risk-tolerant class of mission within the NASA risk framework and as such, is given more latitude to accept higher-levels of residual risk. The intention is that by saving monies normally spent attempting to assure a single missions success, more missions can be funded. A well-designed portfolio can accept occasional mission failure, as it still gets more done for the same investment of resources. This classification enables tailoring the NASA Policy Requirements (NPRs) to lighter-weight approaches to mission management and execution. RP is also studying both international and commercial partnerships as a means to maximize return on the investment. International partnerships provide both capabilities synergies and cost-sharing opportunities, while the evolving new space commercial options are revealing new approaches to acquiring cost-effective services, including the benefits of bundling services. Even the world of launch vehicles is changing, offering much less expensive access to space, especially if NASA is able to be flexible in how it approaches mission assurance. Finally, leveraging investments being made elsewhere within a program portfolio, can enable cost-savings by enabling two applications with one investment. RP will be the next pathfinder mission to both enable exploration capabilities for future missions, and continue to evolve cost-effective approaches for NASA.

Lunar↗

Tuning Interface Electronic Properties via Chiral Two‐Dimensional Metal‐Organic Frameworks

Control over structural symmetries in nanomaterials offers a powerful approach to engineer electronic properties. For instance, breaking of mirror symmetries in two-dimensional (2D) materials with a hexagonal lattice can lead to nontrivial electronic topologies and correlated-electron phenomena. Yet, the impact of structural chirality on the electronic properties of 2D materials and interfaces remains underexplored. Here, how chiral phases of a 2D metal-organic framework (MOF) with a hexagonal lattice—consisting of hexaazatriphenylene molecules coordinated to Cu atoms—scatter, confine, and perturb the Shockley surface state (SS) electrons of an underlying Ag(111) substrate is investigated. Via low-temperature scanning tunneling microscopy and spectroscopy, noncontact atomic force microscopy, and numerical calculations based on an electronic plane-wave expansion method, modifications of the Ag(111) SS band structure are shown and quantified, including gap openings and lifts of band degeneracies, driven exclusively by the structural chirality of the 2D MOF phases. These findings highlight how structural symmetries, in particular chirality, affect electronic states at material interfaces, expanding on the toolkit for designing 2D materials with tailored electronic properties.

band structure engineering↗

Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis

Molecular design is a critical aspect of various scientific and industrial fields, where the properties of molecules hold significant importance. In this study, a 3-fold methodology design is presented that leverages the power of generative artificial intelligence (AI), predictive modeling, and reinforcement learning to create tailored molecules with desired properties. This model synergistically combines deep learning techniques with Self-Referencing Embedded Strings (SELFIES) molecular representation to build a generative model that generates valid molecules and a graphical neural network model that accurately forecasts molecular properties. The Variational Autoencoder (VAE) coupled with reinforcement learning helps refine molecule generation based on targeted attributes. Data from an experimental study involving surfactants were used to test the framework. A validation of the structural integrity of the molecules generated was conducted, and Tanimoto similarities were used to quantify the similarity and diversity between the original and generated molecular structures. Also, saliency maps for the generated surfactants were produced to identify the features explaining the property values. Lastly, molecular dynamics simulations were used to validate the stability of the generated molecules. The results showed that the proposed framework can effectively produce valid molecules within the set property threshold value.

36 MATERIALS SCIENCE↗

Validation of Framework Code Approach to a Life Prediction System for Fiber Reinforced Composites

The grant was conducted by the MMC Life Prediction Cooperative, an industry/government collaborative team, Ohio Aerospace Institute (OAI) acted as the prime contractor on behalf of the Cooperative for this grant effort. See Figure I for the organization and responsibilities of team members. The technical effort was conducted during the period August 7, 1995 to June 30, 1996 in cooperation with Erwin Zaretsky, the LERC Program Monitor. Phil Gravett of Pratt & Whitney was the principal technical investigator. Table I documents all meeting-related coordination memos during this period. The effort under this grant was closely coordinated with an existing USAF sponsored program focused on putting into practice a life prediction system for turbine engine components made of metal matrix composites (MMC). The overall architecture of the NMC life prediction system was defined in the USAF sponsored program (prior to this grant). The efforts of this grant were focussed on implementing and tailoring of the life prediction system, the framework code within it and the damage modules within it to meet the specific requirements of the Cooperative. T'he tailoring of the life prediction system provides the basis for pervasive and continued use of this capability by the industry/government cooperative. The outputs of this grant are: 1. Definition of the framework code to analysis modules interfaces, 2. Definition of the interface between the materials database and the finite element model, and 3. Definition of the integration of the framework code into an FEM design tool.

Gravett, Phillip↗

Automation of the ICME Workflow Incorporating Material Digital Twins at Different Length Scales Within a Robust Information Management System

Recent successes in Integrated Computational Materials Engineering (ICME) have demonstrated the potential in designing fit-for-purpose materials for a given application in a cost and time efficient manner. However, the material design process must contain a level of automation in the material decision process, implementing some optimization algorithms, to truly enable the full benefits of ICME, particularly when considering materials at multiple length/time scales. In this work, we will demonstrate how the GRC ICME schema and Python framework automates a workflow that captures, analyzes, maintains, and disseminates the digital footprint in the context of tailoring resin material at the nanoscale of a woven composite Y-joint at the macroscale for an Aurora D8 double bubble fuselage. This digital footprint incorporates the interaction of both structural digital twins and material twins at various length scales.

Brandon L. Hearley↗

Orbital Engineering Band Degeneracy in a Dual-Square Carbon-Oxide Framework

Electron band degeneracies in momentum space give rise to exotic quantum phenomena that have sparked intense interest in condensed matter physics and materials science. Nodal-lines─isolines in k-space formed by the incidental touching of two bands that share the same energy but belong to discrete eigenstates─arise in the presence of symmetries that preclude effective hybridization. Despite recent advances in the design, bottom-up assembly, and engineering of exotic electronic states in graphene nanomaterials, the extension of this approach to access synthetic two-dimensional (2D) quantum materials derived from metal- or covalent-organic frameworks (COFs) has lagged behind. Here we present a molecular orbital engineering approach for designing and fabricating an edge-centered dual square lattice within a π-conjugated 2D-tetraoxa[8]circulene (2D-TOC) COF. First-principles calculations and scanning tunnelling spectroscopy reveal the emergence of Frontier states at the center of a 3 × 3 lattice that give rise to Dirac nodal-lines in 2D-TOC. Our findings not only provide a general guide for the design of conjugated COFs with custom tailored electronic properties from molecular fragments but enable the exploration of emergent topological phenomena in synthetic 2D materials with potential application for high-speed, low-power data processing, transmission, and storage.

Dirac nodal line semimetal↗

Tuning Surface Adhesion Using Grayscale Electron-beam Lithography

Surface texturing of manufactured products tailors their properties, such as friction, adhesion, biocompatibility, or fluid interactions. However, advancements in this area are largely the result of trial-and-effort testing and generally lack a science-guided framework for determining the surface topography that will optimize performance. The present investigation explores grayscale electron-beam lithography as a means to create multiscale surface patterns to control surface performance. Here, we created and characterized a set of surface textures on a silicon wafer; the textures were superpositions of sine waves of varying wavelengths and amplitudes. First, the multiscale topography of the patterned surface was characterized, using profilometry and atomic force microscopy, to understand its fidelity to the designed-in pattern. The results of this analysis demonstrated how grayscale lithography accurately controlled the lateral size of features but was less precise on the vertical height of the surface, and also introduced inherent roughness below the scale of patterning. Second, a micromechanical tester was used to characterize the adhesion of the surfaces with large-scale polished silicon spheres. The results showed that adhesion could be tailored, with significant contribution from all of the designed-in length scales of topography. The strength of adhesion did not correlate with conventional roughness parameters but could be accurately modeled using simple numerical integration. Taken together, this investigation demonstrates the promise and challenges of grayscale e-beam lithography with multiscale patterns as a method for the tailoring of surface performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Predicting Si-Anode Calendar Life Using Machine Learning: Correlating Electrolyte Properties and Electrochemical Signals

This study evaluates novel electrolytes tailored for Si-containing anodes to promote calendar-life. Drawing inspiration from advancements in electrolytes for Li-metal cells, the work investigates correlations between predicted electrolyte properties and measured electrochemical performance using several machine-learning models. By leveraging machine learning and advanced modeling techniques, this study aims to establish predictive frameworks that accelerate calendar-aging experiments and inform rational electrolyte design for Si-containing cells. In the present study, fifteen different electrolytes are evaluated in a Si-containing cell using an accelerated calendar-life protocol. For each electrolyte considered, 87 properties (features) from the Advanced Electrolyte Model were produced to identify key property/performance relationships. In this study, the best performing electrolytes were generally those formulations that included non-coordinating fluoroether solvents, and the most predictive features for long-term calendar-life were features related to salt concentration and electrolyte viscosity as well as early capacity, ionic conductivity, and Coulombic efficiency measurements. The framework developed in this study correlating electrolyte properties to measured electrochemical performance is expected to accelerate electrolyte design for Si-containing anodes and ultimately enable high-energy-density, long-life Li-ion batteries.

25 - ENERGY STORAGE↗

Testing a Run-Time Assurance Framework Coupled with Integrated Risk Mitigation Capabilities for Autonomous Urban UAS Flights

The In-Time Aviation Safety Management System (IASMS) Concept of Operations (ConOps) envisions new capabilities to monitor, assess, and mitigate flight safety risks. Systems will be tailored to mission type, vehicle/equipage type, operational environment, and safety risk tolerance. Within an IASMS framework, several capabilities may be implemented spanning three operational phases (pre-flight, in-flight, and post-flight/off-line); and consisting of lower level functions and information services which may reside onboard the aircraft, on third-party server(s), and/or on ground/operator station(s). Each capability will be designed to produce and disseminate safety-relevant information; perform detection, diagnosis, and prediction of unsafe situations; and/or execute mitigation actions when hazardous events warrant such changes. This paper focuses on recent testing of airborne capabilities that demonstrate inflight aspects of the overarching concept for autonomous unmanned aircraft systems (UAS) operations in urban environments. A flight test architecture is described that applies run-time assurance principles (e.g., executes independent of the unassured autopilot), real-time risk assessment, and a technique to execute contingencies if necessary either automatically or via pilot intervention. Several tests using small UAS were conducted to verify the assured in-flight risk mitigation capability. The paper draws significantly from a larger NASA technical report and recent prior conference papers, providing additional details. Data is analyzed for two representative flights to illustrate the performance for various sequential and simultaneous hazards used during testing. During each automated flight, several hazards are encountered at various points along the flight path. At each point, the hazard is mitigated by the system, with the vehicle then continuing to subsequent points. The paper concludes with lessons-learned regarding relevant aspects of the overarching IASMS concept and how it may be updated and further advanced in the future.

population activity↗

Failure Mode and Effects Analysis (FMEA) for Photovoltaic Inverter

Photovoltaic (PV) inverters are critical yet vulnerable components in modern energy systems, often acting as reliability bottlenecks that increase the levelized cost of energy (LCOE). To address this, this paper presents a comprehensive Failure Mode and Effects Analysis (FMEA) tailored for PV inverters. Leveraging field data and literature, we identify failure-prone components, such as capacitors,, and relays, and prioritize their risks based on quantitative Risk Priority Numbers (RPNs). The analysis reveals that surge-induced MOV short circuits, capacitor degradation, and environmental cooling fan failures dominate the risk profile. These findings provide a targeted framework for reliability improvement, guiding future efforts in predictive diagnostics, design optimization, and accelerated life testing strategies.

14 SOLAR ENERGY↗

Fully Homomorphic Encryption

This code implements a Fully Homomorphic Encryption (FHE) system, enabling secure computation on encrypted data without requiring decryption. It supports encryption, decryption, and homomorphic operations like matrix multiplication and addition. This code is adaptable for integrating FHE into linear-time invariant (LTI) systems, including digital control and filtering. With proper configuration from subject matter expertise, encrypted system parameters and signals can be manipulated to perform tasks like state updates, output calculations, and convolution in the encrypted domain. By preserving the structure of LTI systems while ensuring privacy, the framework facilitates secure applications in areas such as autonomous systems, signal processing, and industrial automation. The code initializes the encryption system using parameters provided in the env dictionary. These parameters include the ciphertext modulus, key dimension, plaintext fixed-point scaling factor, and noise bound. During initialization, a secret key is generated, which is essential for encrypting and decrypting data securely. The modular design allows users to tailor these parameters to specific use cases or security requirements. The code implements multiple cryptographic schemes. The learning with errors (LWE) encryption method encodes cleartext message to their plaintext fixed-point representation then encrypted into ciphertext space with additive noise. This noise ensures the security of the scheme, relying on the computational hardness of the LWE problem. The code also includes the Gentry-Sahai-Waters (GSW) scheme based off the LWE problem. Homomorphic matrix multiplication is performed between the LWE and GSW to encrypted data. This is achieved using a decomposition function on the LWE ciphertext during the multiplication operation. For higher-dimensional data, the code includes a method to encrypt entire matrices (GSWMat) using GSW encryption. These encrypted matrices can then be used for homomorphic matrix multiplications (MatMult). The decryption function uses the secret key to recover the original plaintext, removing the added noise and scaling that was originally applied during encryption.

Lois, Roberts [Idaho National Laboratory (INL), Id↗

A Multi-Dimensional Benefit Assessment of Automated Mobility Platforms (AMP) for Large Facilities

Automated Mobility Platform (AMP) is a general term for intelligently managed passenger mobility systems that leverage automation and electrification to improve system performance and sustainability through the integration of real-time data streams with advanced decision-making processes tailored for use in large facilities. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for passengers with reduced mobility [PRMs]) and sustainability - both of which are important metrics often neglected during the engineering design process. Therefore, to evaluate systems and inform critical decisions more effectively, a holistic evaluation framework is proposed that includes equity, sustainability, and infrastructure perspectives - referred to as a multidimensional benefit assessment. More specifically, the following analysis focuses on: (1) mobility, with emphasis on travel time and accessibility within an airport, contrasting existing systems with the proposed AMP system; (2) equity analysis, specifically to the PRM community, but with an eye to the whole of society; (3) energy consumption and greenhouse gas (GHG) emissions associated with intra-airport mobility, comparing and contrasting modes as well as impacts on overall airport operations efficiency; and (4) fundamental changes in building design enabled by AMPs for larger and more flexible, functional, and energy-efficient structures.

ADVANCED PROPULSION SYSTEMS↗

Effect of Methyl Groups on Formation of Ordered or Layered Graphitic Materials from Aromatic Molecules

Abstract Developing functionally complex carbon materials from small aromatic molecules requires an understanding of how the chemistry and structure of its constituent molecules evolve and crosslink, to achieve a tailorable set of functional properties. Here, molecular dynamics (MD) simulations are used to isolate the effect of methyl groups on condensation reactions during the oxidative process and evaluate the impact on elastic modulus by considering three monodisperse pyrene‐based systems with increasing methyl group fraction. A parameter to quantify the reaction progression is designed by computing the number of new covalent bonds formed. Utilizing the previously developed MD framework, it is found that increasing methylation leads to an almost doubling of bond formation, a larger fraction of the new bonds oriented in the direction of tensile stress, and a higher basal plane alignment of the precursor molecules along the direction of tensile stress, resulting in enhanced tensile modulus. Additionally, via experiments, it is demonstrated that precursors with a higher fraction of methyl groups result in a higher alignment of molecules. Moreover, increased methylation results in the lower spread of single molecule alignment which may lead to smaller variations in tensile modulus and more consistent properties in carbon materials derived from methyl‐rich precursors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineering Privacy at the Edge: A Practical Guide to Differential Privacy in System Architectures

The rapid expansion of distributed and edge computing platforms—spanning autonomous vehicles, IoT sensors, and healthcare monitors—has heightened concerns about data privacy. Differential Privacy (DP) offers a rigorous mathematical framework to protect sensitive information while retaining analytical utility. This tutorial introduces the foundations of DP for both numerical and categorical datasets and extends the discussion to correlation-aware techniques tailored for structured and high-dimensional data. Hands-on demonstrations will begin with the PETINA (Privacy prEservaTIoN Algorithms) package for numerical data and continue with MIC-DP (Maximum Information Correlated Differential Privacy) for tabular data. Designed for researchers and practitioners in secure systems, embedded architectures, and AI accelerators, the tutorial emphasizes practical and scalable methods for integrating DP into real-world system designs.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗

PV-BESS DC-Series Integration for Regulated DC Systems

DC-series integration introduces a novel approach to seamlessly integrate a solar photovoltaic (PV) array and a battery energy storage (BES) in series. This system, referred to as the PV-integrated battery energy storage system—dc series (PVBESS-DCS), simplifies integration and enhances power density by leveraging the inherent voltage-source characteristics of batteries and adopting the concept of partial power processing. However, addressing voltage variations of a PV array and a BES under different operational conditions remains a challenge to apply the PVBESS-DCS to a regulated dc system, where the dc-bus voltage is fixed. This article proposes a PVBESS-DCS solution tailored for regulated dc systems. Within this framework, we present a controllable series voltage source compensating for the voltage differences between the PV and BES sources and the dc bus. Thus, the system can perform PV maximum power point tracking and curtailment control while charging and discharging BES and connected to a regulated dc bus. Additionally, we present a single-stage multiport partial power processing dc–dc converter designed for the proposed PVBESS-DCS. It utilizes a triple active bridge dc–dc converter topology. Finally, this article presents operating principles, control strategies, simulation results, and experimental findings of the proposed PVBESS-DCS for regulated dc systems.

25 ENERGY STORAGE↗

Evaluation of a Shuttle Derived Vehicle (SDV) for Cargo Transportation

In this new era of space exploration, a host of launch vehicles are being examined for possible use in transporting cargo and crew to low Earth orbit and beyond. Launch vehicles derived from the Space Shuttle Program (SSP), known as Shuttle Derived Vehicles (SDVs), are prime candidates for heavy-lift duty because of their potential to minimize non-recurring costs and because the Shuttle can leverage off proven high-performance flight systems with established ground and flight support. To determine the merits of SDVs, a detailed evaluation was performed. This evaluation included a trade study and risk assessment of options based on performance, safety reliability, cost, operations, and evolution. The purpose of this paper is to explain the approach, processes, and tools used to evaluate launch vehicles for heavy lift cargo transportation. The process included defining the trade space, characterizing the concepts, analyzing the systems, and scoring the options. The process also included a review by subject experts from NASA and industry to compare past and recent study data and assess the risks. A set of technical performance measures (TPMs) was generated based on the study requirements and constraints. Tools such as INTROS and POST were used to calculate performance, FIRST was used for prediction of reliability, and other software packages, both commercial and NASA-owned, were applied to study the trade space. By following a clear process and using the right tools a thorough assessment was performed. An SDV can be classified as either a side-mount vehicle (SMV) or an in-line vehicle OLV). An SMV is a Space Shuttle where the Orbiter is replaced by a cargo carrier. An ILV is comprised of a modified Shuttle External Tank (ET) with engines mounted to the bottom and cargo mounted atop. For both families of vehicles, Solid Rocket Boosters (SRBs) are attached to the ET. The first derivate of Shuttle is defined as the vehicle with minimum changes necessary to transform the Space Shuttle into an SDV. Deltas from the first derivate were also formulated to study more SDV options. Examples of deltas include replacing the SRBs with larger and/or more SRBs, adding an upper stage, increasing the size of the ET, changing the engines, and modifying the elements. Challenges for SDV range from tailoring infrastructure to meeting the exploration schedule. Although SDV is based on the Space Shuttle, it still includes development risk for designing and building a Cargo Carrier. There are also performance challenges in that Shuttle is not optimized for cargo-only missions, but it is a robust system built on reusability. Balancing the strengths and weaknesses of the Shuttle to meet Lunar and Mars mission objectives provides the framework for an informative trade study. SDV was carefully analyzed and the results of the study provide invaluable data for use in the new exploration initiative.

Roman, Jose M.↗