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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Determining Desirable Cursor Control Device Characteristics for NASA Exploration Missions

The Crew Exploration Vehicle (CEV) that will travel to the moon and Mars, and all future Exploration vehicles and habitats will be highly computerized, necessitating an accurate method of interaction with the computers. The design of a cursor control device will have to take into consideration g-forces, vibration, gloved operations, and the specific types of tasks to be performed. The study described here is being undertaken to begin identifying characteristics of cursor control devices that will work well for the unique Exploration mission environments. The objective of the study is not to identify a particular device, but to begin identifying design characteristics that are usable and desirable for space missions. Most cursor control devices have strengths and weaknesses; they are more appropriate for some tasks and less suitable for others. The purpose of this study is to collect some initial usability data on a large number of commercially available and proprietary cursor control devices. A software test battery was developed for this purpose. Once data has been collected using these low-level, basic point/click/drag tasks, higher fidelity, scenario-driven evaluations will be conducted with a reduced set of devices. The standard tasks used for testing cursor control devices are based on a model of human movement known as Fitts law. Fitts law predicts that the time to acquire a target is logarithmically related to the distance over the target size. To gather data for analysis with this law, fundamental, low-level tasks are used such as dragging or pointing at various targets of different sizes from various distances. The first four core tasks for the study were based on the ISO 9241-9:(2000) document from the International Organization for Standardization that contains the requirements for non-keyboard input devices. These include two pointing tasks, one dragging and one tracking task. The fifth task from ISO 9241-9, the circular tracking task was not used because it is a movement that is not applicable to most of the applications used on aviation displays. Additionally, we opted to add a multi-size and multi-distance pointing task, and two ecologically more valid tasks which included text selection, and interaction with drop down menus, sliders, and checkboxes. The Visual Basic test battery tracks the task and trial numbers, measures the pointing, tracking or dragging time, as well as the number and types of errors. The testing session includes a practice set for each input device, then the randomized 7 tasks, and finally a questionnaire about the device. This is repeated for all the devices tested within a session. The experiment is a within-subjects design, with participants returning for multiple sessions to test additional devices. The input devices will be compared based on objective performance data from the tasks, as well as subjective feedback and ratings on the questionnaire.

Aniko Sandor↗
NASA NTRS2024

Flow Cytometry Methods to Monitor Immune System Dysregulation in Astronauts

Persistent immune system dysregulation has been documented to occur in astronauts participating in orbital spaceflight onboard the International Space Station. The phenomenon consists of reductions in T and NK cell function, altered cytokine profiles, persistent inflammation, and the subclinical reactivation of latent herpesviruses. In select crewmembers the dysregulation does actually lead to clinical symptoms, primarily atypical allergy or atopic dermatitis/zoster. Flow cytometry has served a central role defining the ‘immune assessment’ panel of assays that allow monitoring of astronauts. The cytometry assays which have been utilized include: 1. Peripheral leukocyte subsets 2. T cell function 3. Monocyte function 4. NK cell function 5. Intracellular cytokine analysis 6. Virus-specific T cell number (tetramer assay) 7. Virus-specific T cell function (peptide stimulation) 8. Leukocyte-bacterial challenge cytometry 9. Cytometric bead/multiplex array (soluble proteins) The use of these assays has been validated through various ISS flight investigations to define, to varying degrees, both in-flight, and post-flight immune system alterations. The kinetics of the dysregulation through the various phases of spaceflight, as well as post-flight recovery, have also been documented. To allow the science to occur within the orbital constraints of a spaceflight investigation, particular sample collection and processing techniques were developed compatible with the delays associated with terrestrial processing of in-flight samples. A subset of the assays has been adapted to routine monitoring of astronauts via a NASA ‘ISS Standard Measures’ activity, with the data from a specific crew then provided to all science investigators for that particular mission. This battery of cytometry assays has also been applied, through ground investigations, to several terrestrial ‘spaceflight analog’ populations. The purpose was to validate the analog which most closely replicates the in-flight observed pattern of alterations, generally believed to be winterover at an Antarctica station. To assist in determination of clinical risk, the assay panel has also been applied to investigations of various terrestrial patient populations, particularly zoster patients. As NASA is initiating crewed lunar missions via the ‘Artemis’ program, deployment of a miniaturized, microgravity-compatible flow cytometer, would be extremely beneficial to allow real time monitoring of crewmembers. Real time medical data could influence use of several countermeasures options during deep space missions. Several such instruments have been developed and validated to varying degrees of success. Assay details and summary findings across the various flight and ground platforms will be presented, as will current status in developing such technology for in-flight use.

Brian Crucian↗
NASA NTRS2002

Validation of International Space Station Electrical Performance Model via On-orbit Telemetry

The first U.S. power module on International Space Station (ISS) was activated in December 2000. Comprised of solar arrays, nickel-hydrogen (NiH2) batteries, and a direct current power management and distribution (PMAD) system, the electric power system (EPS) supplies power to housekeeping and user electrical loads. Modeling EPS performance is needed for several reasons, but primarily to assess near-term planned and off-nominal operations and because the EPS configuration changes over the life of the ISS. The System Power Analysis for Capability Evaluation (SPACE) computer code is used to assess the ISS EPS performance. This paper describes the process of validating the SPACE EPS model via ISS on-orbit telemetry. To accomplish this goal, telemetry was first used to correct assumptions and component models in SPACE. Then on-orbit data was directly input to SPACE to facilitate comparing model predictions to telemetry. It will be shown that SPACE accurately predicts on-orbit component and system performance. For example, battery state-of-charge was predicted to within 0.6 percentage points over a 0 to 100 percent scale and solar array current was predicted to within a root mean square (RMS) error of 5.1 Amps out of a typical maximum of 220 Amps. First, SPACE model predictions are compared to telemetry for the ISS EPS components: solar arrays, NiH2 batteries, and the PMAD system. Second, SPACE predictions for the overall performance of the ISS EPS are compared to telemetry and again demonstrate model accuracy.

Jannette, Anthony G.↗
NASA NTRS2008

Progress of Ongoing NASA Lithium-Ion Cell Verification Testing for Aerospace Applications

A Lithium-ion Verification and Validation Program with the purpose to assess the capabilities of current aerospace lithium-ion (Li-ion) battery cells to perform in a low-earth-orbit (LEO) regime was initiated in 2002. This program involves extensive characterization and LEO life testing at ten different combinations of depth-of-discharge, temperature, and end-of-charge voltage. The test conditions selected for the life tests are defined as part of a statistically designed test matrix developed to determine the effects of operating conditions on performance and life of Li-ion cells. Results will be used to model and predict cell performance and degradation as a function of test operating conditions. Testing is being performed at the Naval Surface Warfare Center/Crane Division in Crane, Indiana. Testing was initiated in September 2004 with 40 Ah cells from Saft and 30 Ah cells from Lithion. The test program has been expanded with the addition of modules composed of 18650 cells from ABSL Power Solutions in April 2006 and the addition of 50 Ah cells from Mine Safety Appliances Co. (MSA) in June 2006. Preliminary results showing the average voltage and average available discharge capacity for the Saft and Lithion packs at the test conditions versus cycles are presented.

McKissock, Barbara I.↗
DOE OSTI2026

BMINN: Learning chemical potentials and parameters from voltage data for multi-phase battery modeling

Free-energy landscapes and chemical potentials govern the dynamics of phase transitions, transport, and stability in functional materials, yet they remain experimentally inaccessible under realistic operating conditions. Here we introduce a Bayesian model-integrated neural network (BMINN) that embeds physics-based formulations of non-autonomous partial differential-algebraic equations into probabilistic learning. This approach reconstructs hidden thermodynamics directly from macroscopic current-voltage data, providing quantitative access to metastable states, staging transitions, and energy barriers without synchrotron probes. Demonstrated on lithium-graphite electrodes, BMINN recovers full Gibbs free-energy landscapes with fidelity validated against operando X-ray diffraction. The framework generalizes across dynamical regimes, enabling accurate voltage prediction, internal state estimation, and inference of governing parameters. Beyond batteries, BMINN exemplifies a broadly applicable strategy for learning missing physics in multiphase, non-equilibrium systems, offering a new pathway to uncover hidden thermodynamic functions across condensed matter and materials physics.

25 ENERGY STORAGE↗
DOE OSTI2024

A sustainable cobalt separation with validation by techno-economic analysis and life-cycle assessment

Sustainable, cost-effective cobalt/nickel separations chemistry contributes to the realization of economically competitive lithium-ion battery recycling, as well as primary mining of cobalt and nickel. Such improvements can address supply chain challenges for cobalt, a critical element. Herein, we disclose a simple method for separating Co/Ni by second coordination-sphere molecular recognition. Selective cobalt precipitation is achieved using carbonate ions in an ammonia solution due to the outer-sphere, hydrogen bonding interactions between [Co(NH 3 ) 6 ] 3+ and CO 3 2− , evaluated with density functional theory calculations. We demonstrate this method on mixtures of Co/Ni chlorides comprising a 10-fold excess of Ni and provide comparisons with ore-processing systems. High purities (99.4(3)% Co; 98.2(4)% Ni) and recoveries (77(8)% Co; ∼100% Ni) were observed for both Co- and Ni-enriched products using optimized conditions. In conclusion, this method is potentially economically competitive based on initial techno-economic analysis (TEA) and life-cycle assessment (LCA) that also illustrate advantages in terms of sustainability.

cobalt↗
NASA NTRS1989

Multi-mission Ni-H2 battery cell for the 1990's

A sufficient production, test and operational database is now available to permit design technology optimization for the next decade. The evolved battery cell design features standardized technology intended to support multiple type missions (e.g., both GEO and LEO). Design analyses and validation test cells demonstrate improved performance plus attractive specific-energy characteristics will be achieved.

Miller, Lee↗
NASA NTRS1989

Multi-mission Ni-H2 battery cells for the 1990's

A sufficient production, test and operational database is now available to permit design technology optimization for the next decade. The evolved battery cell design features standardized technology intended to support multiple type missions (e.g., both GEO and LEO). Design analysis and validation test cells demonstrate that improved performance plus attractive specific-energy characteristics will be achieved.

Miller, Lee↗
NASA NTRS1992

Validation of astronaut psychological select-in criteria

An optional astronaut selection strategy would select-in individuals on the basis of personality attributes associated with superior performance. Method: A test battery, the Astronaut Personal Characteristics Inventory (ASTROPCI) was developed which assesses positive and negative components of achievement, motivation, and interpersonal orientations and skills. The battery was administered to one hundred three astronaut candidates and sixty-six current U.S. Shuttle astronauts. To determine performance, a series of conceptual areas related to space flight performance were defined. Astronauts rated their peers on each of these dimensions. Ratings were obtained on all eighty-four current astronauts (excluding those selected in 1990). In addition to peer ratings, supervisor assessments of the same dimensions were obtained for each astronaut. Results: Cluster and factor analysis techniques were employed to isolate subgroups of astronauts. Those astronauts with both high achievement needs and interpersonal skills were most often rated among the top five by their peers and least often rated among the lowest five. A number of scales discriminated between astronauts rated high and low on one or more performance dimensions. Conclusions: The results parallel findings from the personality assessment of individuals in other demanding professions, including aircraft pilots and research scientists, suggesting that personality factors are significant determinants to performance in the space environment.

Rose, R. M.↗
DOE OSTI2024

Aerial drone fleet deployment optimization with endogenous battery replacements for direct delivery of time-sensitive products

Aerial drones offer a distinct potential to reduce the delivery time and energy consumption for the delivery of time-sensitive and small products. However, there is still a need in the relevant industry to understand the performance of drone-based delivery under different business needs and drone operating conditions. We studied a drone deployment optimization problem for direct delivery of time-sensitive products with release dates to customers maintaining a specified time window. This paper presents a new mixed-integer programming model, new valid inequalities, a new greedy heuristic algorithm, and a Genetic algorithm to help business owners optimally schedule and route their drone fleet minimizing the required fleet size, the required number of additional batteries, and total energy consumption. A realistic feature of the optimization method is that instead of replacing the drone battery after each return to the depot, it keeps track of the remaining energy in the drone battery and decides on battery replacements accounting for the drone routing and the user-specified minimum required battery energy. Numerical results based on real data from drone flight tests and prepared food delivery industry provide insights into the effect of different practical drone operating parameters on the required fleet size, the required number of battery replacements, and energy consumption. Here, results demonstrate that the proposed heuristic algorithm substantially outperforms the accelerated CPLEX in runtime while sacrificing the solution quality by a small amount. Additionally, results show that using a mixed fleet of hexacopter and quadcopter drones reduces the total energy consumption by 48.52% compared to using a homogeneous fleet of only hexacopters.

Drone energy consumption↗
DOE OSTI2026

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential

A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.

MLIPs↗
DOE OSTI2025

Five-volt-class high-capacity all-solid-state lithium batteries

Advances in battery technology have been impeded by the voltage constraints of electrolytes. Here, in this study, we present a high-energy all-solid-state battery design featuring >5 V operation and an ultrahigh areal capacity of 35.3 mAh cm −2 ; these attributes were enabled by a highly conductive and ultrahigh-voltage stable fluoride solid electrolyte, LiCl–4Li 2 TiF 6 (1.7 × 10 −5 S cm −1 at 30 °C). LiCl–4Li 2 TiF 6 shields high-voltage spinel oxide cathodes, achieving 106 mAh g −1 at 2C with 75.2% retention over 500 cycles for LiNi 0.5 Mn 1.5 O 4 , sharply contrasting with the conventional LiNbO 3 counterpart, which decomposes and fails to prevent detrimental interfacial degradation. The efficacy of LiCl–4Li 2 TiF 6 is validated across various systems, including LiCoMnO 4 , LiFe 0.5 Mn 1.5 O 4 and pouch-type LiNi 0.5 Mn 1.5 O 4 ||Li (or Ag–C) all-solid-state batteries, and further demonstrated by operability down to 2.3 V with 258 mAh g −1 and ultrathick 1.8-mm electrodes. This shielding layer with >5 V stability introduces a transformative design paradigm by revisiting the previously forbidden high-voltage cathodes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

FY24 Advanced Computing HPC Annual Report for allocation "vtocei"

This project aims to elucidate the mechanisms underlying the formation of the cathodeelectrolyte interphase (CEI) and its impact on the performance of Li-ion batteries during electrochemical cycling. Our approach integrates advanced multiscale modeling with multimodal characterization to offer a comprehensive understanding of CEI dynamics. We employ a validated multiscale modeling framework to analyze microstructure-dependent transport properties, alongside joint theory-experiment protocols for detailed resolution of interfacial chemistry via spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Advanced Manufacturing of Cathode Materials for Lithium-ion Batteries

Original objectives (per the Statement of Project Objectives) centered on developing and translating a continuous pilot process for cathode materials production while targeting (i) a 29% manufacturing cost reduction, (ii) an 82% energy consumption reduction for cathode production, and (iii) a doubling of manufacturing productivity. Planned validation included characterization at appropriate analytical facilities and electrochemical performance evaluation progressing from half-cells to pouch-cell formats, with a pathway to kilogram-scale production of finished cathode materials for representative testing. Scope evolution: During execution, the project team identified that the surfactant-enabled chemistry offered high selectivity for lithium precipitation from brine sources. A formal scope revision shifted the final project year from cathode manufacturing development to direct lithium extraction/lithium recovery, while maintaining the overarching intent of cost reduction and process simplification relevant to the battery supply chain.

25 ENERGY STORAGE↗
DOE OSTI2026

An immersed interface method for microstructure-scale electrochemical battery models: numerical formulation and performance portable implementation

We present the numerical formulation, verification, and performance portable implementation of an immersed interface method for microstructure scale electrochemical modeling of batteries. The innovation in this approach is the resolution of chemical species and electrostatic potential discontinuities at active interfaces without the use of interface conforming unstructured grids. A unified formulation on Cartesian grids for all domains (electrodes and electrolyte) is used with interfacial flux conditions applied using volume fraction or “color” function gradients. We have developed one dimensional and two dimensional test cases with analytic solutions for electrochemical modeling using which we verified the consistency and accuracy of our scheme. Our solver is also validated against solutions from a macroscale model and an unstructured multi-subdomain solver for a full lithium ion cell. We then demonstrated the utility of our solver on an image-based complex battery electrode microstructure at high charging rate. Our technique also exhibits good scalability on distributed memory architectures using central processing units (CPU), with problem sizes up to 1.8 billion degrees of freedom and with 5400 ranks. Initial performance studies of our open-source performance portable solver showed about 70 times speed up using a graphics processing unit (GPU) compared to single compute core for a problem with 4 million cells.

25 ENERGY STORAGE↗
DOE OSTI2024

Improving the Freight Productivity of a Heavy-Duty, Battery Electric Truck by Intelligent Energy Management

This project aimed to enhance the range and reduce the operating costs of battery electric Class 8 trucks traveling over 250 miles daily. This was achieved through the development and implementation of an intelligent-Energy Management System (i-EMS) that leverages vehicle and operations data, physics-aware machine learning algorithms, and vehicle-to-cloud (V2C) connectivity. The project hypothesized that advanced machine learning algorithms and real-time data analytics could significantly improve the energy efficiency and range of these trucks. Key objectives included developing a physics-aware machine learning algorithm, implementing an i-EMS with V2C connectivity and physics-aware spatial data analytics (PSDA), and validating the system’s effectiveness with fleet partners HEB Companies and Murphy Logistics. Extensive data collection from vehicle operations, including vehicle characteristics, road conditions, and payload, was conducted. A machine learning algorithm was developed to predict energy consumption and enable proactive decision-making. The i-EMS was implemented on two Volvo VNR BEVs, with operators receiving charging and routing recommendations. Charging stations were installed at depot locations in Texas and Minnesota, with an additional on-route charger in Minnesota. Significant findings included a 14% range improvement for Murphy Logistics on a highway-driving eco-route and a 22% range improvement for HEB Companies on a city-driving eco-route. The i-EMS utilized rule-based methods and physics-based algorithms to predict and reduce energy consumption, with real-time monitoring and analysis through V2C connectivity enabling proactive decision-making. The project demonstrated the feasibility and economic viability of battery electric Class 8 trucks for long-haul operations, showcasing the potential of physics-aware machine learning in optimizing energy management. The successful implementation of the i-EMS in real-world scenarios validates its practical application and effectiveness, paving the way for the widespread adoption of battery electric vehicles in the freight transportation industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Analysis and Control of a Three-Port Converter with High-Frequency AC Link for Hybrid Unmanned/Autonomous Aerial Vehicles

In this study, a three-port resonant converter with a high-frequency isolation link for hybrid unmanned/autonomous aerial vehicle (UAV/AAV) applications is analyzed. The rectified engine-generator set output supplies the first input ports while the other is connected to a battery energy storage system. Input ports consist of half-bridge high-frequency inverters, whereas output port utilizes a semi-bridgeless active rectifier. This rectifier is formed by replacing rectifier low-side diodes with active switching devices. A phase-shift duty-cycle control is implemented for switching signals to regulate the power share and flow between ports. The proposed control system implemented achieves zero voltage switching (ZVS), reduces switching losses, and minimum current flow optimization ensures regulation in a wide range of output power. Compared to the existing bidirectional pulse width modulation (PWM) converters, the proposed system decreases the number of power conversion stages and provides centralized control without needing communications between the ports. The proposed control technique operating in closed-loop control achieves the power flow between ports under various load conditions. Finally, theoretical analysis demonstrates the proposed converter’s viability and laboratory experimental validations at 500 W full power.

33 ADVANCED PROPULSION SYSTEMS↗