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DOE OSTI2025

Growth of tetragonal PtO by molecular-beam epitaxy and its integration into β-Ga 2 O 3 Schottky diodes

We demonstrate the epitaxial growth of tetragonal platinum monoxide (PtO) on MgO, TiO 2 , and β-Ga 2 O 3 single-crystalline substrates by ozone molecular-beam epitaxy. We provide synthesis routes and derive a growth diagram under which PtO films can be synthesized by physical vapor deposition. A combination of electrical transport and photoemission spectroscopy measurements, in conjunction with density functional theory calculations, reveal PtO to be a degenerately doped p-type semiconductor with a bandgap of E g ≈ 1.6 eV. Spectroscopic ellipsometry measurements are used to extract the complex dielectric function spectra, indicating a transition from free-carrier absorption to higher photon energy transitions at E ≈ 1.6 eV. Using tetragonal PtO as an anode contact, we fabricate prototype Schottky diodes on n-type Sn-doped β-Ga 2 O 3 substrates and extract Schottky barrier heights of ϕ B > 2.2 eV.

Hensling, Felix V. E. [Cornell Univ., Ithaca, NY (↗

NASA NTRS1978

Development of sputtering process to deposit stoichiometric zirconia coatings for the inside wall of regeneratively cooled rocket thrust chambers

Thermal barrier coatings of yttria stabilized zirconia and zirconia-ceria mixtures were deposited by RF reactive sputtering. Coatings were 1-2 mils thick, and were deposited on copper cylinders intended to simulate the inner wall of a regeneratively cooled thrust chamber. Coating stoichiometry and adherence were investigated as functions of deposition parameters. Modest deposition rates (approximately 0.15 mil/hr) and subambient sustrate temperatures (-80 C) resulted in nearly stoichiometric coatings which remained adherent through thermal cycles between -196 and 400 C. Coatings deposited at higher rates or substrates temperatures exhibited greater oxygen deficiences, while coatings deposited at lower temperatures were not adherent. Substrate bias resulted in structural changes in the coating and high krypton contents; no clear effect on stoichiometry was observed.

Busch, R.↗

NASA NTRS1990

Vertical bloch line memory

Vertical Bloch Line (VBL) memory is a recently conceived, integrated, solid-state, block-access, VLSI memory which offers the potential of 1Gbit/sq cm real storage density, gigabit per second data rates, and sub-millisecond average access times simultaneously at relatively low mass, volume, and power values when compared to alternative technologies. VBL's are micromagnetic structures within magnetic domain walls which can be manipulated using magnetic fields from integrated conductors. The presence or absence of VBL pairs are used to store binary information. At present, efforts are being directed at developing a single-chip memory using 25Mbit/sq cm technology in magnetic garnet material which integrates, at a single operating point, the writing, storage, reading, and amplification functions needed in a memory. This paper describes the current design architecture, functional elements, and supercomputer simulation results which are used to assist the design process. The current design architecture uses three metal layers, two ion implantation steps for modulating the thickness of the magnetic layer, one ion implantation step for assisting propagation in the major line track, one NiFe soft magnetic layer, one CoPt hard magnetic layer, and one reflective Cr layer for facilitating magneto-optic observation of magnetic structure. Data are stored in a series of elongated magnetic domains, called stripes, which serve as storage sites for arrays of VBL pairs. The ends of these stripes are placed near conductors which serve as VBL read/write gates. A major line track is present to provide a source and propagation path for magnetic bubbles. Writing and reading, respectively, are achieved by converting magnetic bubbles to VBL's and vice versa. The output function is effected by stretching a magnetic bubble and detecting it magnetoresistively. Experimental results from the past design cycle created four design goals for the current design cycle. First, the bias field ranges for the stripes and the major line needed to be matched. Second, the magnetic field barrier between the stripe and the read/write gates needed to be reduced. Third, current conductor routing needed to be improved to reduce occurrences of open-circuiting, short-circuiting, and eddy-current shielding. Fourth, a modified Co-alloy was needed with an increased coercivity and controlled magnetization to allow VBL stabilization to occur without affecting stripe stability.

Katti, R.↗

DOE OSTI2024

Optimizing Nonaqueous Sodium–Polysulfide Redox-Flow Batteries: The Role of Solvation Effects with Glyme Solvents

Nonaqueous redox-flow batteries (NARFBs) that use economical alkali metals and the corresponding metal polysulfides are highly attractive for grid-scale energy storage. Although sodium–sulfur systems have been recognized as promising candidates and have been the focus of many studies due to their high earth abundance and energy density, an understanding of the role of the solvation chemistry of commonly used glyme solvents is missing. Herein, we report a systematic investigation into the solvation effects of glyme-based Na-S electrolytes through comprehensive physiochemical experiments and Density Functional Theory (DFT) simulations. Our findings revealed, on one hand, that an optimal coordination strength between glymes and Na + could maintain a relatively smooth Na + diffusion. On the other hand, glyme solvents with extended chain lengths shift the reduction potential of S 8 2– negatively to elevate the formation barrier of undesirable short-chain polysulfides (S n 2– , n ≤ 4) that have high membrane permeability. This solvation phenomenon not only mitigates capacity fading but also extends the operational longevity of the Na-S NARFBs. In conclusion, the results underscore the critical roles of balanced solvent–cation interactions and controlled redox potentials in improving the stability and efficiency of Na-S NARFB systems, marking a significant advancement in the development of sustainable energy storage solutions.

25 ENERGY STORAGE↗

DOE OSTI2026

SEED: Semantic Energy Exploration and Discovery

The Bioenergy Knowledge Discovery Framework (KDF) hosts a vast repository of specialized data, yet traditional keyword-based search methods often struggle to provide direct answers, requiring significant domain expertise and manual effort to filter through raw documents. To overcome these barriers, this software introduces a semantic search engine that enables both specialists and non-specialists to query the KDF using natural language. By shifting from rigid keyword matching to intent-based retrieval, the tool automatically identifies and ranks the most relevant sources within the database. The system functions by processing natural language queries to extract the most pertinent information, delivering an AI-generated plain-language summary alongside exact supporting quotes from retrieved documents. This integrated approach provides users with immediate, evidence-based answers while eliminating the need for exhaustive manual review. By surfacing direct insights and contextual evidence, the software enhances the usability of existing KDF resources and democratizes access to complex bioenergy data. Ultimately, this semantic search solution accelerates the discovery process and supports faster, more informed decision-making across the bioenergy sector.

Pan, Meiyu (Melrose) [Oak Ridge National Laborator↗

NASA NTRS1992

Metric transition

This report describes NASA's metric transition in terms of seven major program elements. Six are technical areas involving research, technology development, and operations; they are managed by specific Program Offices at NASA Headquarters. The final program element, Institutional Management, covers both NASA-wide functional management under control of NASA Headquarters and metric capability development at the individual NASA Field Installations. This area addresses issues common to all NASA program elements, including: Federal, state, and local coordination; standards; private industry initiatives; public-awareness initiatives; and employee training. The concluding section identifies current barriers and impediments to metric transition; NASA has no specific recommendations for consideration by the Congress.

Source record↗

NASA NTRS2020

Enabling Assurance in the MBSE Environment

A number of specific benefits that fit within the hallmarks of effective development are realized with implementation of model-based approaches to systems and assurance. Model Based Systems Engineering (MBSE) enabled by standardized modeling languages (e.g., SysML®) is at the core. These benefits in the context of spaceflight system challenges can include [1]: • Improved management of complex development • Reduced risk in the development process • Improved cost management • Improved design decisions With appropriate modeling techniques the assurance community also can improve early oversight and insight into project development. NASA has shown the basic constructs of SysML in an MBSE environment offer several key advantages, within a Model Based Mission Assurance (MBMA) initiative [2, 3]. These include the following: • Model viewpoints that promote rapid and systematic assessment of requirements coverage, hazard tagging and risk management • Embedded safety assessments for launch vehicles • Deployment of model assisted development of reliability products - Failure Modes and Effects Analyses (FMEAs) and Fault Trees • Test Planning • Validation and Verification of complex functions • Support of Assurance Case development for complex systems In addition, while there are benefits to be harvested, there is a realization that these do not come without effort and cost. Enabling model-based approaches requires structure, not only in an organizational context, but in a modeling context as well. There can be a steep learning curve and costs associated to train skilled modelers. But, on the other hand, not all of the assurance community need to be modelers. Models themselves must conform to ontologies that enable assurance. This places constraints upon the models and modelers. Optimums have yet to be developed where resources and constraints on modeling must be traded off in the organization and modeling efforts for projects. A number of barriers need to be overcome, as well, which pose challenges to the developers of the software that supports MBSE/MBMA. Information and data must be made to flow seamlessly through the life cycle. Because there is a wide variety of tools used in the community, to avoid the problems of the past of silos, delays, and diverging interests, information should flow among these tools to support the “single source of truth” paradigm of MBSE. This will greatly facilitate MBMA and advancement of assurance functions.

Evans, John W.↗

NASA NTRS2001

Nano-Transistor Modeling: Two Dimensional Green's Function Method

Two quantum mechanical effects that impact the operation of nanoscale transistors are inversion layer energy quantization and ballistic transport. While the qualitative effects of these features are reasonably understood, a comprehensive study of device physics in two dimensions is lacking. Our work addresses this shortcoming and provides: (a) a framework to quantitatively explore device physics issues such as the source-drain and gate leakage currents, DIBL (Drain Induced Barrier Lowering), and threshold voltage shift due to quantization, and b) a means of benchmarking quantum corrections to semiclassical models (such as density-gradient and quantum-corrected MEDICI).

Svizhenko, Alexei↗

DOE OSTI2025

Vacancy-Dependent Diffusion Mechanism in Oxygen-Defective SrFeO 3 Perovskite Materials: First-Principles Density Functional Theory and Experimental Approach

Understanding oxygen diffusion at the atomic scale in SrFeO 3−δ perovskites is crucial for developing oxygen storage materials with optimal performance. Such materials are required to have high stability, corrosion resistance, and acceptable oxygen storage capacity at moderate operating temperatures and pressures. Here, in this study, we used first-principles density functional theory and thermogravimetric analysis to study the vacancy-dependent oxygen diffusion in oxygen-deficient SrFeO 3−δ (δ = 0, 0.065, 0.125, 0.25, 0.5) perovskites. The electronic structures, including the partial- and spin-resolved density of states, for different SrFeO 3−δ phases were calculated and compared with available experimental and theoretical results. By mapping the migration pathways, we investigated diffusion mechanisms and calculated the energy barriers for oxygen diffusion in cubic, orthorhombic, and brownmillerite phases of SrFeO 3−δ perovskites. Using the calculated energy barriers, we deduced the diffusion time scales and diffusion coefficients within SrFeO 3−δ . A diffusion coefficient on the order of 10 –8 m 2 /s was obtained for SrFeO 2.875 . We experimentally investigated the roles of temperature and oxygen partial pressures on the redox kinetics and deduced the kinetics rate and diffusion density, which agreed well with the calculated values for the density of diffusing oxygen vacancy in the lattice. Our results showed that the energy barrier tends to reduce at higher oxygen concentrations. Our results serve as an important guideline for designing oxygen storage materials with optimal redox kinetics.

chemical looping with oxygen uncoupling (CLOU)↗

DOE OSTI2026

A framework and tool for designing cost-effective, resilient, and circular net-zero supply chains under uncertainty with an application to multilayer plastic films

While 55% of Fortune 500 companies have committed to achieving net-zero emissions and/or zero-waste operations by 2035, only 2% are currently on track, revealing a critical gap between ambition and action. Designing supply chains that reduce both emissions and waste is a complex non-intuitive, multi-objective challenge, compounded by the high costs of new technologies and the need for resilient, profitable solutions. This paper aims to address this challenge by presenting a generic framework and multi-objective optimization formulation for designing cost-effective, circular, and resilient supply chains under uncertainty, implemented through a user-friendly decision-support tool with intuitive data visualization capabilities, enabling communication of results to both technical and non-technical stakeholders. We demonstrate the application of this framework in the context of multilayer plastic films (barrier films), which are widely used in food packaging and composite materials. The model quantifies trade-offs across three objectives: minimizing global warming potential, maximizing circularity, and minimizing cost. A key contribution of this work is the explicit modeling of technological resilience, the ability of supply chains to maintain function under disruption. In the cost-minimization case, the resilience constraint makes the design approximately three times more expensive in the short-term metric, but shifts the system from relying on a single recovery pathway to a portfolio of four recovery pathways, improving the robustness of the optimization solution under uncertainty. Lastly, we introduce TranZero, a decision-support tool that integrates material flow analysis, hotspot identification, and optimization-based scenario planning to support net-zero and circularity decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Metal–Ligand Cooperativity via Exchange Coupling Promotes Iron- Catalyzed Electrochemical CO 2 Reduction at Low Overpotentials

Biological and heterogeneous catalysts for the electrochemical CO 2 reduction reaction (CO 2 RR) often exhibit a high degree of electronic delocalization that serves to minimize overpotential and maximize selectivity over the hydrogen evolution reaction (HER). Here, we report a molecular iron(II) system that captures this design concept in a homogeneous setting through the use of a redox non-innocent terpyridine-based pentapyridine ligand (tpyPY2Me). As a result of strong metal-ligand exchange coupling between the Fe(II) center and ligand, [Fe(tpyPY2Me)] 2+ exhibits redox behavior at potentials 640 mV more positive than the isostructural [Zn(tpyPY2Me)] 2+ analog containing the redox-inactive Zn(II) ion. This shift in redox potential is attributed to the requirement for both an open-shell metal ion and a redox non-innocent ligand. The metal-ligand cooperativity in [Fe(tpyPY2Me)] 2+ drives the electrochemical reduction of CO 2 to CO at low overpotentials with high selectivity for CO 2 RR (>90%) and turnover frequencies of 100,000 s -1 with no degradation over 20 h. The decrease in the thermodynamic barrier engendered by this coupling also enables homogeneous CO 2 reduction catalysis in water without compromising selectivity or rates. Synthesis of the two-electron reduction product, [Fe(tpyPY2Me)] o , and characterization by X-ray crystallography, Mössbauer spectroscopy, X-ray absorption spectroscopy (XAS), variable temperature NMR, and density functional theory (DFT) calculations, support assignment of an open-shell singlet electronic structure that maintains a formal Fe(II) oxidation state with a doubly reduced ligand system. Furthermore, this work provides a starting point for the design of systems that exploit metal-ligand cooperativity for electrocatalysis where the electrochemical potential of redox non-innocent ligands can be tuned through secondary metal-dependent interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

How the Bioinspired Fe 2 Mo 6 S 8 Chevrel Breaks Electrocatalytic Nitrogen Reduction Scaling Relations

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy- and CO 2 -intensive Haber–Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe–S–Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe–S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Furthermore, our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

10 SYNTHETIC FUELS↗

DOE OSTI2020

Ion diffusion coefficients in poly(3-alkylthiophenes) for energy conversion and biosensing: role of side-chain length and microstructure

Conductive polymers are promising materials as active elements for energy storage and conversion devices due to mixed ion–electron conduction. The ion diffusion coefficient is a relative measure of the efficacy of ion transport, allowing for comparison between materials and electrochemical conditions. In this work, diffusion coefficients of hexafluorophosphate (PF6–) counterions in poly(3-alkylthiophene) (P3AT) materials are measured as a function of both side-chain length and microstructure using electrochemical impedance spectroscopy (EIS). For semi-crystalline films, the diffusion coefficient is found to be anomalous and nearly independent of applied electrochemical potential. Here, the anomalous behavior of diffusion indicates that spin casting yields compact films with an enthalpic barrier to ion transport, attributed to ionic trapping. Diffusion coefficient values ~10 –11 cm 2 s –1 were measured for all films, indicating interchain spacing, in the absence of strong intermolecular interactions with the electrolyte, is not a viable design strategy to control ion transport. For the prototypical system of poly(3-hexylthiophene), we observe almost no potential dependence in ion transport for regioregular and regiorandom films of comparable molecular weight, with both exhibiting anomalous diffusion. Alternatively, changing the microstructure of poly(3-hexylthiophene) to a mostly amorphous, ion-imprinted structure yields ~500× increase in the diffusion coefficient to ~2 × 10 –8 cm 2 s –1 at 0.8 V vs. Ag/Ag + with behavior closer to ordinary diffusion. Collectively, these results indicate new insight into ion transport in conductive polymers, where ionic trapping effects can be mitigated through electrodeposition protocols over post-synthesis processing (i.e. spin coating).

14 SOLAR ENERGY↗

DOE OSTI2026

Leveraging chiral induced spin selectivity to improve the efficiency and selectivity of electrocatalytic reduction

Energy production is a fundamental pillar of modern society, but it remains heavily reliant on fossil fuel combustion, which leads to environmental degradation and resource depletion. Electrocatalytic reduction reactions (ERRs) offer a cleaner alternative by functioning under mild conditions, eliminating the need for high temperatures or pressures. However, their widespread adoption is hindered by challenges such as low efficiency, inadequate selectivity, and sluggish kinetics. Here, the introduction of chiral-induced spin selectivity (CISS) offers a promising strategy to address these limitations by reducing energy barriers in reactions involving spin-sensitive intermediates or transition states. By leveraging CISS, ERR pathways can be manipulated to favor desired reactions, enhance product yield, and suppress unwanted byproducts, improving selectivity. Beyond reducing the impact of competing side reactions, CISS also enhances the kinetics of ERRs by accelerating reaction rates and lowering the energy barriers associated with multi-electron transfer steps. Thanks to its straightforward and versatile application, CISS shows significant potential in optimizing well-studied ERRs, such as the hydrogen evolution reaction (HER) and carbon dioxide reduction reaction (CO2RR), facilitating the future transition of these technologies from research laboratories to commercial energy plants worldwide.

14 SOLAR ENERGY↗

DOE OSTI2025

16 O + 16 O fusion at sub-coulomb energies

A simple optical model (OPM) method using non-monotonic (NM) potentials characterized by a repulsive core from the microscopic theory of the Pauli-led energy-density functional (EDF) has been developed to investigate the 16 O + 16 O fusion at sub-Coulomb energies relevant to the oxygen burning. Here, the study involves the analysis of the experimental fusion cross-section (FCS) data in energy range 6.92 ≤ E cm ≤ 13.83 MeV, which includes the Coulomb barrier region E cm = 10.0–11.92 MeV. Apart from an excellent description of the existing FCS data in the studied energy range, the associated hindrance, characterized by the S-factor reaching a maximum and then gradually falling off at lower energies, so far suggested empirically for the system, is reproduced down to 4 MeV for the first time in the simple OPM. An S-factor maximum of S 0 = 3.15 × 10 25 MeV.b at E 0 = 7.14 MeV is observed with T ≃ 2.6 GK, which conforms to the values reported for quiescent and explosive burning. Our reaction rate, deduced from the NM potential, compares well with the Caughlan and Fowler data. Dominant partial waves implicit in the observed maximum S-factor in the studied Gamow range are also explored. Our present findings, with the success of NM potentials, suggest that the nucleus–nucleus potential is non-monotonic.

16O+16O↗

NASA NTRS1993

TARGET: Rapid Capture of Process Knowledge

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper.

Ortiz, C. J.↗

NASA NTRS2019

Developing High-Throughput Organ-On-A-Chip Models to Investigate the Effects of Ionizing Radiation on the Central Nervous System

One of the main health risks in human space exploration is central nervous system (CNS) damage by ionizing radiation. Irradiation with simulated GCRs or their components, or high doses of low-LET radiation such as gamma rays, in animal models has been shown to cause neuronal damage together with glial cell activation and neuroinflammation and has been associated with prolonged cognitive and behavioral dysfunction. The extent of CNS damage in response to any insult, including ionizing radiation, is partially regulated by the blood-brain barrier (BBB), which enables immune cells to enter the CNS. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal death, immune responses and oxidative stress, and thus could serve as a robust CNS-specific target for countermeasure development. However, studies on BBB permeability and astrocyte functions in regulating CNS responses to ionizing radiation have been limited, especially in human tissue/organ analogs. Therefore, we have established a high throughput 3D organ-on-a-chip system to study human CNS functions in response to ionizing radiation, with the eventual goal of adapting it to spaceflight missions. We utilized commercially available OrganoPlate system (Mimetas, Inc.) seeded with primary or induced pluripotent stem cell-derived human cells for developing 3D neuronal-astrocytic and BBB models. We investigated both immediate and delayed CNS dose responses to 0.5-1 Gy X-rays by measuring BBB permeability and morphology, and astrocyte activation. We have also quantified secreted markers of oxidative stress and cell viability. In the future, we are planning to monitor dendritic, axonal and synaptic changes in neurons, evaluate the combined exposures to simulated microgravity and ionizing radiation, and compare the responses to low and high-LET ionizing radiation. We anticipate these studies could indicate novel cellular and mechanistic targets for countermeasure developments to improve CNS functions in astronauts.

Malkani, Sherina↗

NASA NTRS2022

Adapting a Trusted AI Framework to Space Mission Autonomy

As artificial intelligence (AI) is increasingly pro- posed for new and future capabilities in space missions, the question of how to trust AI-enabled space autonomy has been explored. Recently, a collaboration between The Aerospace Corporation (Aerospace) and NASA’s Jet Propulsion Labora- tory (JPL) investigated how Aerospace’s Trusted AI Frame- work could be applied to two JPL projects that planned on lev- eraging AI for critical autonomous tasks. This combined effort led to many insights in the practical implementation of trusted AI along with considerable updates to the Trusted AI Frame- work that tailored its topic threads to space exploration. This document cohesively summarizes the enhanced framework as tailored to space missions as well as estimation of the level of trust required as a function of mission criticality and key stakeholders. The goal of this work is to provide a set of best practices to inform autonomy researchers, flight engineers, mission and proposal reviewers, and instrument and mission principal investigators (PI’s) to drive AI-based autonomy that maximizes trust and lowers the barriers to mission adoption for both science and engineering applications.

Amini, Rashied↗