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Surveyor Project Final Report: Part 1 - Project Description and Performance, Volume 1

The Surveyor Project planned and conducted seven unmanned lunar missions for which spacecraft were launched between May 1966 and January 1968. Each of the spacecraft was successfully launched with the then newly developed Atlas/Centaur vehicle which utilized for the first time a high-specific-impulse, liquid hydrogen/liquid oxygen fueled stage. Five of the spacecraft successfully soft-landed and returned a great quantity of engineering and scientific data on extensive postlanding operations, accomplishing all mission and project objectives. Four of the spacecraft soft-landed at selected mare sites to provide data which were required to support the Apollo Program. The final spacecraft was then successfully used for scientific investigation of a contrasting site in the rugged lunar highlands. Surveyor was a fully attitude-stabilized spacecraft designed to receive and execute a wide variety of earth commands, as well as to perform certain automatic functions including the critical terminal-descent and soft-landing sequences. Significant new and advanced subsystems that were developed and/or used in combination to enable Surveyor to execute the complex terminal phase of flight were: (1) a solid-propellant main retro motor, (2) throttlable liquid-propellant vernier engines (also used for midcourse velocity correction), (3) highly sensitive velocity- and altitude-sensing radars, and (4) an automatic closed-loop guidance and control system. The first Surveyor spacecraft carried a survey television camera which, together with other engineering instrumentation, obtained in-flight and postlanding data. The complement of instruments carried on later missions included various combinations of the following additional devices: (1) a soil mechanics/surface sampler instrument for picking, digging, and handling lunar surface material; (2) an alpha scattering instrument for performing a chemical analysis of the lunar surface material; and (3) magnets attached to the spacecraft for determining magnetic properties of the soil.

Jet Propulsion Laboratory

Surveyor Project Final Report: Part 1 - Project Description and Performance, Volume 2

The Surveyor Project planned and conducted seven unmanned lunar missions for which spacecraft were launched between May 1966 and January 1968. Each of the spacecraft was successfully launched with the then newly developed Atlas/Centaur vehicle which utilized for the first time a high-specific-impulse, liquid hydrogen/liquid oxygen fueled stage. Five of the spacecraft successfully soft-landed and returned a great quantity of engineering and scientific data on extensive postlanding operations, accomplishing all mission and project objectives. Four of the spacecraft soft-landed at selected mare sites to provide data which were required to support the Apollo Program. The final spacecraft was then successfully used for scientific investigation of a contrasting site in the rugged lunar highlands. Surveyor was a fully attitude-stabilized spacecraft designed to receive and execute a wide variety of earth commands, as well as to perform certain automatic functions including the critical terminal-descent and soft-landing sequences. Significant new and advanced subsystems that were developed and/or used in combination to enable Surveyor to execute the complex terminal phase of flight were: (1) a solid-propellant main retro motor, (2) throttlable liquid-propellant vernier engines (also used for midcourse velocity correction), (3) highly sensitive velocity- and altitude-sensing radars, and (4) an automatic closed-loop guidance and control system. The first Surveyor spacecraft carried a survey television camera which, together with other engineering instrumentation, obtained in-flight and postlanding data. The complement of instruments carried on later missions included various combinations of the following additional devices: (1) a soil mechanics/surface sampler instrument for picking, digging, and handling lunar surface material; (2) an alpha scattering instrument for performing a chemical analysis of the lunar surface material; and (3) magnets attached to the spacecraft for determining magnetic properties of the soil.

Jet Propulsion Laboratory

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)

Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials

Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li + , by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH – dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li + -coupled electron transfer along the PAN backbone, causing ∼10 4 times faster sequential ring-formation of the remaining nitriles. PAN’s extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.

Chahal-Crockett, Rajni [Oak Ridge National Laborat

The effect of gamma ray irradiation on few layered MoSe2: A material for nuclear and space applications

In recent years, emerging two-dimensional (2D) materials, such as molybdenum diselenide (MoSe2), have been at the center of attention for many researchers. This is due to their unique and fascinating physicochemical properties that make them attractive in space and defense applications that include shielding harsh irradiation environments. In this study, we examined the effects of gamma (γ) rays at various doses on the structural, chemical, and optical properties of MoSe2 layers. After the samples were exposed to intense gamma radiation (from a 60Co source) with various exposure times to vary the total accumulated dosage (up to 100 kGy), Raman and photoluminescence spectroscopies were used to study and probe radiation-induced changes to the samples. When compared to pristine materials, very few changes in optical properties were typically observed, indicating good robustness with little sensitivity, even at relatively high doses of gamma radiation. The imaging using scanning electron microscopy revealed a number of nano-hillocks that were connected to substrate alterations. X-ray photoelectron spectroscopies revealed that Mo’s binding energies remained the same, but Se’s binding energies blueshifted. We associated this shift with the decrease in Se vacancies that occurred after irradiation as a result of Mo atoms creating adatoms next to Se atoms. When compared to pristine materials, very few changes in optical, chemical, and structural properties were typically observed. These findings highlight the inherent resilience of MoSe2 in hostile radioactive conditions, which spurs additional research into their optical, electrical, and structural characteristics as well as exploration for potential space, energy, and defense applications.

Materials Science

Collapse of magnetized white dwarfs as site of heavy-element formation and kilonova signal

We present the first end-to-end calculation connecting the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf to observable kilonova signatures, combining two-dimensional (2D) general-relativistic neutrino-magnetohydrodynamic simulations, followed by radiation hydrodynamics with in-situ nuclear network and 2D Monte Carlo radiative transfer with spatially resolved heating rates. Unlike all previous unmagnetized AIC models – which predicted proton-rich, $^{56}$Ni-dominated ejecta – strong magnetic fields eject ${\approx }\, 0.2\, \mathrm{ M}_\odot$ of neutron-rich material ($\langle Y_e \rangle \sim 0.24$) on dynamical time-scales, before neutrino irradiation can raise the electron fraction, enabling strong r-process nucleosynthesis up to and beyond the third peak. The resulting kilonova is lanthanide-rich ($X_{\rm lan} \approx 8~{{\ \rm per\ cent}}$) and dominated by near-infrared emission. We compute synthetic light curves in the Large Synoptic Survey Telescope and J ames Webb Space Telescope bands and find striking agreement, without parameter tuning, between the observations of AT 2023vfi/GRB 230307A and our broadband light curves for polar viewing angles. These results establish magnetized AIC as a viable channel for heavy r-process element production and a compelling progenitor candidate for long-duration gamma-ray bursts with kilonova signatures.

MHD

Salt‐Assisted Vapor–Liquid–Solid Growth of 1D van der Waals Materials

The method of salt-assisted vapor–liquid–solid (VLS) growth is introduced to synthesize 1D nanostructures of trichalcogenide van der Waals (vdW) materials, exemplified by niobium trisulfide (NbS 3 ). The method uses a unique catalyst consisting of an alloy of Au and an alkali metal halide (NaCl) to enable rapid and directional growth. High yields of two types of NbS 3 1D nanostructures, nanowires and nanoribbons, each with sub-ten nanometer diameter, tens of micrometers length, and distinct 1D morphology and growth orientation are demonstrated. Strategies to control the location, size, and morphology of growth, and extend the growth method to synthesize other transition metal trichalcogenides, NbSe 3 and TiS 3 , as nanowires are demonstrated. Finally, the role of the Au–NaCl alloy catalyst in guiding VLS synthesis is described and the growth mechanism based on the relationships measured between structure (growth orientation, morphology, and dimensions) and growth conditions (catalyst volume and growth time) is discussed. These results introduce opportunities to expand the library of emerging 1D vdW materials to make use of their unique properties through controlled growth at nanoscale dimensions.

1D van der Waals material

The Operational NASA Anomaly Gas Analyzer and Exploration Follow-Ons

The NASA Anomaly Gas Analyzer (AGA) is the culmination of nearly ten years of advancement of core technology originally developed by Vista Photonics through the Small Business Innovation Research (SBIR) program and expanded using NASA program funding. The AGA is a portable, battery operated, optical gas detection instrument for continuous monitoring of H 2 O, CO 2 , O 2 , CO, NH 3 , HCN, HF, HCl in the spacecraft environment. Real time, in-situ monitored, gas concentrations are communicated at 1 Hz through a built-in display on-orbit and additionally through a serial interface on the ground. The instruments function over the typical range of temperatures and pressures required for the spacecraft environment. A ten-year operational life is targeted. Seven AGA instruments are currently deployed on the International Space Station and two Orion-specific units are manifested for Artemis 2. A variation of the operational AGA is under development for lunar Human Landing Systems. A wider calibrated operating pressure envelope is required in this application. Otherwise, the instruments straightforwardly address lessons learned from the original AGA by improving aspects of thermal control, ruggedness, and ease-of-use. A subset of AGA-developed sensed gases (H 2 O, CO 2 , O 2 ) is the subject of the Primary Constituent Monitor (PCM) development for the Habitation and Logistics Outpost (HALO) destined for lunar orbit. Two PCMs will be installed in HALO as part of the environmental control loop where they will interface with vehicle power and communications. While the basic sensor techniques are unchanged from the AGA, these instruments have been radiation hardened to survive for many years in the harsh target environment. Current development status for these instruments will be presented along with recent developments of a naval submarine variant.

Air Monitoring

Evaluation of Howard A. Hanson Dam Juvenile Fish Passage and Survival Study: Downstream Passage and Survival (Acoustic Telemetry) (Task Final Report)

The Downstream Passage and Survival (Acoustic Telemetry) task was one of several tasks for the Evaluation of Howard A. Hanson Dam (HAHD) Juvenile Fish Passage and Survival study. For this task, a juvenile fish passage and survival study was conducted at HAHD from March 10, 2024 through June 27, 2024 for arrays in the HAHD Reservoir and Green River, and through July 9, 2024 for the arrays in the Duwamish River. Fish releases occurred over four times from March through May. Active tag (acoustic telemetry) technology was used to provide biological baseline information for the passage and survival of juvenile Puget Sound (PS) Chinook salmon (Oncorhynchus tshawytscha). Results will be used by biologists, engineers, resource managers, and regional decision-makers to inform the engineering design of the new fish passage facility (FPF) at HAHD. However, hatchery sub-yearling PS Chinook salmon of the appropriate size for tag implantation during the study period (> 95 mm in fork length, Geist et al. 2018) were unavailable. Therefore, yearling Coho salmon (O. kisutch) were used as a surrogate species for this acoustic telemetry study.

13 HYDRO ENERGY

Magnetically and optically active edges in phosphorene nanoribbons

Abstract Nanoribbons, nanometre-wide strips of a two-dimensional material, are a unique system in condensed matter. They combine the exotic electronic structures of low-dimensional materials with an enhanced number of exposed edges, where phenomena including ultralong spin coherence times 1,2 , quantum confinement 3 and topologically protected states 4,5 can emerge. An exciting prospect for this material concept is the potential for both a tunable semiconducting electronic structure and magnetism along the nanoribbon edge, a key property for spin-based electronics such as (low-energy) non-volatile transistors 6 . Here we report the magnetic and semiconducting properties of phosphorene nanoribbons (PNRs). We demonstrate that at room temperature, films of PNRs show macroscopic magnetic properties arising from their edge, with internal fields of roughly 240 to 850 mT. In solution, a giant magnetic anisotropy enables the alignment of PNRs at sub-1-T fields. By leveraging this alignment effect, we discover that on photoexcitation, energy is rapidly funnelled to a state that is localized to the magnetic edge and coupled to a symmetry-forbidden edge phonon mode. Our results establish PNRs as a fascinating system for studying the interplay between magnetism and semiconducting ground states at room temperature and provide a stepping-stone towards using low-dimensional nanomaterials in quantum electronics.

Science & Technology - Other Topics

SERENE: Saturn Enceladus Return Explorer with Nuclear Electric Propulsion

A ‘quick’ Enceladus sample return mission concept was developed based on the scientist recommendations at the recent ‘Accelerating Space Science with Nuclear Technology Workshop’. The Nuclear Electric Propulsion spacecraft assumed a follow-on 40 kWe nuclear reactor using the demonstrated 40 kWe Fission Surface Power system, expected in the early 2030s. The NEP vehicle also utilized a set of NEXT-C ion thrusters as well as planned Artemis commercial launchers. By launching the 40 kW NEP vehicle on a Starship and adding the propellants of 15 tankers, the 27t probe could be sent on a direct trajectory to Saturn (no Earth or Jupiter flybys) where NEP was used for Saturn capture, spiral down, spiral up and return to the Earth. A small lander obtained the surface Enceladus sample. Using the 40 kW NEP provided a round-trip time of only 16.5 years. A second option was more attractive from a science perspective whereby the NEP vehicle would deliver a large, 6t chemical lander to low Enceladus orbit where it would grab and return a sample to Earth (similar to the recent Orbilander design but in reverse). After deploying the lander, the NEP vehicle would stay in Saturn space performing a moon tour by orbiting four more moons and mapping the large moon of Titan. This option took slightly longer (18.5 yrs) due to the chemical return leg limitations. Both options demonstrated the agility, payload capability, and sample return goals the workshop recommended. An all-chemical option with two stages was roughly analyzed but took 21.5 yrs and required a Jupiter gravity assist.

Nuclear Electric Propulsion

A Quantitative Phase Analysis by Neutron Diffraction of Conventional and Advanced Aluminum Alloys Thermally Conditioned for Elevated-Temperature Applications

As the issue of climate change becomes more prevalent, engineers have focused on developing lightweight Al alloys capable of increasing the power density of powertrains. The characterization of these alloys has been focused on mechanical properties and less on the fundamental response of microstructures to achieve these properties. Therefore, this study assesses the quality of the microstructure of two high-temperature Al alloys (A356 + 3.5RE and Al-8Ce-10Mg), comparing them to T6 A356. These alloys underwent thermal conditioning at 250 and 300 °C for 200 h. Time-of-flight neutron diffraction experiments were performed before and after conditioning. The phase evolution was quantified using Rietveld refinement. It was found that the Si phase grows significantly (13–24%) in T6 A356, A356 + 3.5RE, and T6 A356 + 3.5RE alloys, which is typically correlated with a reduction in mechanical properties. Subjecting the A356 3.5RE alloy to a T6 heat treatment stabilizes the orthorhombic Al4Ce3Si6 and monoclinic β-Al5FeSi phases, making them resistant to thermal conditioning. These two phases are known for enhancing mechanical properties. Additionally, the T6 treatment reduced the vol.% of the cubic Al20CeTi2 and hexagonal ᴨ-Al9FeSi3Mg5 phases by 13% and 23%, respectively. These phases have detrimental mechanical properties. The Al-8Ce-10Mg alloy cubic β-Al3Mg2 phase showed significant growth (82–101%) in response to conditioning, while the orthorhombic Al11Ce3 phase remained stable. The growth of the beta phase is known to decrease the mechanical properties of this alloy. These efforts give valuable insight into how these alloys will perform and evolve in demanding high-temperature environments.

Chemistry

Molecules to Masterpieces: Bridging Materials Science and the Arts

Art and materials innovation have always been intertwined, dating back to the earliest human creations. In modern times, however, the increasing specialization of materials science often restricts artists' access to cutting-edge materials. Here, the materials science aspects of an art-science collaboration between artist Kimsooja and the Wiesner Lab at Cornell University, are detailed. The project involves the development of a custom-made iridescent block copolymer coating by means of self-assembly, originally applied to transparent window panels of a façade for the ≈14 m tall art installation: A Needle Woman: Galaxy Is a Memory, Earth is a Souvenir by artist Kimsooja. After several exhibitions in the US and Europe, the installation is now part of the permanent museum collection at Yorkshire Sculpture Park in Wakefield, UK. Full characterization of the solution blade-cast coatings show shear aligned, standing up lamellar morphologies that behave as volume-phase gratings with periodicities between 300 and 400 nm. Coatings are also applied to foldable (origami) paper and converted into iridescent porous ceramic materials. Furthermore, it is hoped this work inspires and informs communities across materials science, the arts, and architecture.

Architectural nanomaterials

Advanced blade-shaped thermal energy storage device: Development and application

Thermal energy storage (TES) using phase change materials (PCMs) is a promising approach for capturing and reusing excess thermal energy, yet widespread adoption is limited by low thermal conductivity, bulky configurations, and inadequate scalability. Here, this study presents a modular, blade-shaped TES prototype designed to address these challenges. The device integrates a lightweight aluminum shell, an embedded serpentine coil for active or passive heat exchange, and a cost-effective corrugated metal mesh for enhanced PCM thermal conductivity. With thickness-to-length and thickness-to-width ratios of 0.03 and 0.08, respectively, the blade-shaped TES achieves a compact, modular form factor suitable for space-constrained applications. Experimental testing demonstrated the efficient charge and discharge behavior of blade-shaped TES, capturing PCM superheating, phase-change transitions, and subcooling dynamics, with charging and discharging efficiencies of 94.9% and 94.6%, respectively. Also, the system can potentially achieve higher energy density than that of conventional TES designs. When integrated into a household refrigerator during the study, three blade-shaped TES modules successfully shifted 100% of peak-time compressor operation to off-peak hours, reducing energy consumption while maintaining more stable compartment temperatures. The blade-shaped TES's thin geometry, modularity, and enhanced thermal performance support scalable deployment across residential, commercial, and industrial applications, providing a versatile, cost-effective solution for high-efficiency, demand-flexible thermal energy management.

Blade-shaped

Making Plasticized Polymer Electrolytes Stable Against Sodium Metal for High‐Energy Solid‐State Sodium Batteries

Solid polymer electrolytes based on plastic crystals are promising for solid-state sodium metal (Na 0 ) batteries, yet their practicality has been hindered by the notorious Na 0 -electrolyte interface instability issue, the underlying cause of which remains poorly understood. Here, in this study, by leveraging a model plasticized polymer electrolyte based on conventional succinonitrile plastic crystals, we uncover its failure origin in Na 0 batteries is associated with the formation of a thick and non-uniform solid electrolyte interphase (SEI) and whiskery Na 0 nucleation/growth. Furthermore, we design a new additive-embedded plasticized polymer electrolyte to manipulate the Na 0 deposition and SEI formulation. For the first time, we demonstrate that introducing fluoroethylene carbonate (FEC) additive into the succinonitrile-plasticized polymer electrolyte can effectively protect Na 0 against interfacial corrosion by facilitating the growth of dome-like Na 0 with thin, amorphous, and fluorine-rich SEIs, thus enabling significantly improved performances of Na//Na symmetric cells (1,800 h at 0.5 mA cm −2 ) and Na//Na 3 V 2 (PO 4 ) 3 full cells (93.0 % capacity retention after 1,200 cycles at 1 C rate in coin cells and 93.1 % capacity retention after 250 cycles at C/3 in pouch cells at room temperature). Our work provides valuable insights into the interfacial failure of plasticized polymer electrolytes and offers a promising solution to resolving the interfacial instability issue.

25 ENERGY STORAGE

SERFE Ground Unit EVA Series After Three Year Spacesuit Stowage Period

NASA’s spacesuit government reference design for returning to the Moon is called the Exploration Extravehicular Mobility Unit (xEMU). The xEMU subassembly that provides life support, such as oxygen and thermal control, is the Portable Life Support System (PLSS). Inside the PLSS is a new technology that NASA wanted to test to provide cooling to the crew during EVAs (ExtraVehicular Activity). This technology is called the Spacesuit Water Membrane Evaporator (SWME). In order to test SWME in an improved thermal control loop (TCL) both on Earth and in Space, the Spacesuit Evaporation Rejection Flight Experiment (SERFE) was created. The Ground unit, or testbed at Johnson Space Center (JSC), tested the cooling technology in Earth’s gravity, while the Flight unit, or payload on the International Space Station (ISS), tested the cooling technology in micro-gravity. Since fluids flow differently in micro-gravity, testing in both environments would provide important data for improving cooling performance during EVAs. Both units completed 25 simulated EVAs with the same settings so SWME performance on the ground could be compared to the ISS. The Flight unit was completed first and performed EVAs on the ISS between 2020 and 2022. The Ground unit performed EVAs between 2021 and 2022. When the Flight unit came back from the ISS, it was taken apart for analysis. This analysis looked at how well SWME was able to maintain its heat rejection capability after various dwell times, such as a 90 day Airlock Coolant Loop Recovery (ALCLR) cycle, when the Extravehicular Mobility Unit (EMU) currently on the ISS would normally need maintenance. After a three year simulated spacesuit dwell, the Ground unit performed another EVA series in 2025 to test SWME’s shelf life. The results from this test series will inform mission planning as NASA plans to go back to the Moon and beyond.

Michael Lewandowski

Liquified SO 2 induced solid/cathode electrolyte interphase for lithium ion batteries

Formation of robust solid/cathode electrolyte interphases (S/CEI) is vital for long-term stability and high-performance operation of lithium-ion batteries (LIBs), particularly under high voltage regimes. However, engineering electrochemically stable S/CEIs that effectively suppress interfacial side reactions remains a key challenge. Herein, we introduce a liquefied sulfur dioxide (SO 2 )– ionic liquid complex as a fluorine-free multifunctional electrolyte additive for the first time that significantly improves the formation of sulfate/sulfite-rich S/CEI layers at both graphite and NMC811 interfaces. The unique SO 2 -N coordination with a 1,2,4-triazolide-based ionic liquid enables homogeneous SO 2 dissolution, resulting in controlled SO 2 decomposition during the initial electrochemical cycle. This decomposition yields sulfur-rich interphase species that stabilize the electrolyte-electrode interface, reduce impedance growth, and lessen electrolyte decomposition. Electrochemical tests show significantly improved cycle life, reduced polarization, and increased Coulombic efficiency for both anodes and cathodes. XPS confirms the presence of SO 2 -derived surface species that contribute to interfacial stability. In conclusion, this approach highlights a new direction for interphase engineering using liquefied gas additives and opens pathways for sulfur-based S/CEI chemistry in advanced battery systems.

Graphite

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra