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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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Unveiling the lithium-ion transport mechanism in Li{sub 2}ZrCl{sub 6} Solid-State Electrolyte {ital via} deep learning-accelerated molecular dynamics simulations.

Lithium zirconium chlorides (LZCs) present a promising class of cost-effective solid electrolytes for next-generation all-solid-state batteries. The unique crystal structure of LZCs plays a crucial role in facilitating lithium-ion mobility, which further affects the electrochemical performance. To understand the underlying mechanism governing ion transport, we employed deep learning-accelerated molecular dynamics simulation on Li2ZrCl6 (trigonal alpha- and monoclinic beta-LZC), focusing specifically on the zirconium coordination environment. Our results reveal that disordered alpha-LZC exhibits the highest ionic conductivity, while beta-LZC demonstrates significantly lower conductivity, closely aligning with experimental findings. The study confirms that across all phases, lithium migration proceeds via the site-to-site hopping mechanism, where variations in site residence times critically impact the overall ionic conductivity. In alpha-LZCs, lithium ions prefer to anisotropically diffuse across interlayers as the result of a lower energy barrier, driven primarily by collective diffusion. In contrast, lithium ions in beta-LZC primarily isotropically diffuse within the intralayer, hindered by higher energy barriers and determined by individual diffusion. The variation in ZrCl6 2- octahedral unit softening, induced by the specific layered arrangement of zirconium atoms, emerges as a critical determinant of the energy barriers across the LZC phases. These atomic-scale insights into the transport processes provide valuable guidance for the rational design and optimization of LZCs-based electrolytes, accelerating their practical application in advanced energy storage technologies.

Guo, Hanzeng

Microbiological Characterization and Concerns of the International Space Station Internal Active Thermal Control System

Since January 1999, the chemical the International Space Station Thermal Control System (IATCS) and microbial state of (ISS) Internal Active fluid has been monitored by analysis of samples returned to Earth. Key chemical parameters have changed over time, including a drop in pH from the specified 9.5 +/- 0.5 ta = 58.4, an increase in the level of total inorganic carbon (TIC), total organic carbon (TOC) and dissolved nickel (Ni) in the fluid, and a decrease in the phosphate (PO,) level. In addition, silver (AS) ion levels in the fluid decreased rapidly as Ag deposited on internal metallic surfaces of the system. The lack of available Ag ions coupled with changes in the fluid chemistry has resulted in a favorable environment for microbial growth. Counts of heterotrophic bacteria have increased from less than 10 colony-forming units (CFUs)/l00 mL to l0(exp 6) to l0(exp 7) CFUs/100 mL. The increase of the microbial population is of concern because uncontrolled microbiological growth in the IATCS can contribute to deterioration in the performance of critical components within the system and potentially impact human health if opportunistic pathogens become established and escape into the cabin atmosphere. Micro-organisms can potentially degrade the coolant chemistry; attach to surfaces and form biofilms; lead to biofouling of filters, tubing, and pumps; decrease flow rates; reduce heat transfer; initiate and accelerate corrosion; and enhance mineral scale formation. The micro- biological data from the ISS IATCS fluid, and approaches to addressing the concerns, are summarized in this paper.

Monsi C Roman

Ares I-X Ground Diagnostic Prototype

The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

Machine Learning

The Future of in-Situ Sequencing-Based Microbial Monitoring: Development of a Shelf-Stable Method for Artemis and Beyond

Microbial monitoring onboard the International Space Station (ISS) is essential for assessing the efficiency of the Environmental Control and Life Support Systems (ECLSS) and providing insight into potential risk to both crew and spacecraft. Historically, this monitoring required the need to culture organisms onboard, return these cultures to Earth, and then complete the identifications, a process that would take months. Over the past decade, and through numerous payloads, advances in molecular biology have enabled in-flight microbial identifications using nanopore sequencing. The swab-to-sequencer method resulting from these efforts was transitioned from research to operations for microbial monitoring under the Crew Health Care Systems (CHeCS) BioMole. Collectively, these accomplishments have propelled the swab-to-sequencer method to be selected as the Microbial Surface Monitor (MSM) for Gateway, as well as a payload on Artemis IV. However, the lack of cold stowage availability for Artemis requires modifications to the entire method due to the thermal instability of the reagents required for sample preparation. To achieve this, new development, optimization, and validations were undertaken. Key considerations included enzyme concentration, buffer compatibility, and equal or enhanced sensitivity and specificity. At each step, thorough side-by-side comparisons with the current ISS method were performed. The development of a robust shelf-stable method will ensure continued sequencing-based microbial monitoring for Artemis and beyond, providing data in near real-time, enhancing risk response time, and yielding clear insight into the microbiome of spacecraft.

Christian G Mena

Integrated Computational Materials Engineering (ICME) Capability Maturity Levels for Ecosystems Enabling Digital Transformation

Digital engineering (DE) and integrated computational materials engineering (ICME) are widely recognized as critical enablers of faster, more affordable, and more reliable aerospace systems. However, many organizations have struggled to realize the promised return on investment (ROI) from digital initiatives. A primary reason is the absence of a shared, decision-focused framework that distinguishes simple digitization of existing workflows from true digital transformation that fundamentally changes how engineering decisions are made. This paper introduces an ICME capability maturity framework that fills this gap. The framework defines six cumulative ICME capability maturity levels (CMLs), explicitly tied to decision authority, engineering integration, optimization, and uncertainty management across material, process, structure, and performance scales. It is designed to complement established readiness metrics such as technology readiness levels (TRLs), manufacturing readiness levels (MRLs), and integration readiness levels (IRLs), by addressing a missing dimension: the conditions required for model-informed decision authority across scales. A unifying figure and capability table illustrate the six-level ICME Capability Maturity Framework, showing how organizations progress from digitization—with limited or negative ROI—to true digital transformation, where ICME-enabled workflows deliver measurable improvements in decision quality, cycle time, risk reduction, and reuse. The framework is intended for both technical practitioners and executive leadership, providing a common language to assess current state, guide roadmaps, align software ecosystem investments, and set realistic expectations for digital transformation outcomes. A regulatory-relevant statement clarifying the relationship between ICME capability and existing certification frameworks is provided.

ICME

Strong gradient neoclassical transport in the plateau regime

Strong gradient regions in tokamaks such as the pedestal or internal transport barriers are regions of reduced turbulence where neoclassical transport can play a dominant role. In pedestals, gradient lengths comparable to the ion poloidal gyroradius have been measured. Standard neoclassical theory can miss important strong gradient effects in these regions because it assumes that the gradient length scales of density, temperature and potential are larger than the ion poloidal gyroradius. We extend plateau regime neoclassical theory into regions of gradients of the order of the ion poloidal gyroradius to capture strong gradient effects on transport processes in the pedestal and internal transport barriers. The fundamental idea behind our new framework is to keep a scale separation between the orbit widths and the gradient length scales by performing a large aspect ratio expansion. In the plateau regime, strong gradients cause poloidal variation that is in–out as well as up–down asymmetric. We study two different test cases assuming either radial force balance or the absence of turbulence and show that strong gradient effects can enhance or reduce standard neoclassical theory predictions in the plateau regime in strong gradient regions.

fusion plasma

Time-Resolved Neutron Imaging for Hydrogen Uptake in Subsurface Lithologies

Geologic hydrogen production and underground storage are increasingly important for meeting rising energy demands while providing clean-combustion advantages. However, hydrogen’s high diffusivity and propensity for leakage through porous media necessitate direct evaluation of its transport behavior in subsurface materials. Whereas X-ray microcomputed tomography (μCT) studies often employ contrast agents or surrogate gases, this study leverages neutron transmission radiography/CT to observe hydrogen migration in situ. This work represents the first demonstration of real-time neutron radiography of hydrogen migration in reservoir and caprock lithologies. Cylindrical cores of Indiana limestone, Amherst Gray sandstone, and Tumey shale were subjected to constant-pressure hydrogen charging and scanned in real time using high-resolution neutron radiography. Results indicate immediate hydrogen infiltration in sandstone and limestone, with homogeneous distribution detected throughout their pore structure. In contrast, hydrogen remained largely absent from fine-grained shale under the same pressure, except in an apparently localized fracture zone, where neutron signatures confirmed the presence of hydrogen. Subsequent neutron CT of the sandstone sample, using image subtraction against an uncharged reference, corroborated hydrogen distribution patterns. Even under lowpressure, single-phase conditions, distinct neutron imaging signatures of hydrogen were achieved. These preliminary findings underscore the potential of neutron imaging for advancing subsurface hydrogen migration research.

08 HYDROGEN

Three Dimensionally Woven Mid-Density Carbon Phenolic (3MDCP) is a Novel Single Piece Ablative TPS for Extreme Entry Environments

Three Dimensionally Woven Mid-Density Carbon Phenolic (3MDCP) is robust, single piece, carbon phenolic ablative thermal protection system under development at NASA Ames Research Center initially for the Mars Sample Return Earth Entry System (MSR EES). The MSR EES requirements drove the need for TPS with no seams, capable of surviving the highest entry conditions for any NASA Earth return capsule with heat fluxes >2000 W/cm2 and pressures >1.5 atmospheres. To produce 3MDCP required development of new weaving infrastructure to enable weaving of preforms large enough to form into a single piece heatshield. It required development of forming techniques to transform a flat woven panel into a sphere cone shape and enhanced infusion processes to support larger scale infusion of resin into the formed preforms. A rigorous performance testing campaign was conducted to develop and validate the materials thermal response model used to determine the required material thickness and to demonstrate the material can survive the extreme entry conditions. The end of the development effort (end of FY26) will result in a TPS at Technical Readiness Level (TRL) 6 and Manufacturing Readiness Level (MRL) 6+ for the MSR EES mission and a mature system ready to support other missions. This poster will provide a snapshot of where 3MDCP is in its development phase.

Ablator

Probing room temperature indirect and minimum direct band gaps of h-BN

Abstract Hexagonal boron nitride (h-BN) has attracted considerable interest as an ultrawide bandgap (UWBG) semiconductor. Experimental studies focused on the detailed near band-edge structure of h-BN at room temperature are still lacking. We report a direct experimental measurement of the near band-edge structure performed on h-BN quasi-bulk wafers via photocurrent excitation spectroscopy (PES). PES resolved the band-to-band transitions near M- and K-points in the Brillion zone (BZ), from which the room temperature indirect band gap of E g M K ∼6.02 eV, minimum direct bandgap at M-point of E g M = 6.36 eV and next lowest direct energy bandgap at K-point of E g K = 6.56 eV , have been simultaneously determined for the first time experimentally. The measured energy differences between K- and M-points in the conduction band minimum (CBM) and valence band maximum (VBM) are Δ E C M K = 0.54 eV and Δ E V M K = 0.34 eV, respectively, in good agreement with the calculation results. Significantly differing from its III-nitride wurtzite counterparts, in which only electrons and holes in the conduction and valence band extremes at the Γ-point are predominantly involved in the optical and transport processes, the results highlighted that charge carriers associated with both M- and K-valleys control to the optical excitation, recombination and charge transport processes in h-BN.

Physics

Boron Nitride-Driven Strengthening of Aluminum Composites via Friction Stir Processing

Friction stir welding and processing (FSW/P) has emerged as an effective solid-state joining technique for fabricating metal matrix composites (MMCs), offering improved mechanical properties through refined microstructural evolution. In this study, an aluminum-boron nitride nanoparticle (Al-BNNP) composite was synthesized via FSW, and its indentation-based mechanical properties were systematically evaluated. Microhardness mapping across the weld cross-section revealed a progressive increase in hardness toward the stir zone (SZ), attributed to severe plastic deformation, dynamic recrystallization (DRX), and the reinforcing effect of BNNPs. Profilometry-based indentation plastometry (PIP) inferred yield strength (YS) demonstrates a 47.8% increase compared to the base metal (BM) and a 75% improvement compared to FSP pure aluminum reported in literature. This enhancement is attributed to strengthening mechanisms, including grain boundary pinning, load transfer, and increased dislocation density. The strain rate sensitivity (SRS) measurements at the nanoscale demonstrated a substantial decrease in the SZ, correlated with ultrafine grain structures and strong BNNP-matrix interactions. Activation volume analysis revealed a significant reduction in the SZ, suggesting that dislocation motion is increasingly restricted by dislocation-dislocation and dislocation-particle interactions. These findings suggest that incorporating BNNPs in FSW/P enables tailoring the microstructure without thermal degradation of the secondary particles, thereby significantly enhancing the mechanical performance of aluminum composites, particularly for structural applications in aerospace and automotive industries.

Aluminum

Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)

This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.

33 ADVANCED PROPULSION SYSTEMS

Technology & Design Innovations to Maximize the Reduction Effect on DCFC Unit Cost Economics (Max‐REDUCE)

With the high cost and reliability issues of DCFC infrastructure the project specifically addressed the needs of innovating on the AC to DC power conversion. We proved the integration of a new power module into existing charger units, and that theoretical educational work on single stage energy conversion is commercially viable, and a reduced cost compared to existing methods. Our A sample shown 3 PH 480VAC 60hz to 350VDC 8.5kW power transfer, and our software and simulation proved efficiency greater than 97% from 20kW to > 60kW, over the DC output voltage range 200 – 1200V. The project was stopped before we could implement B sample and execute full power testing, validation and integration into a demonstration charger (budget period 3).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Aerothermal Shape Optimization of Actively-Cooled Battery Packs Using Conjugate Heat Transfer

Thermal management for battery is important for electric aircraft because battery temperature is critically important to vehicle safety, and it also has direct impact on the efficiency of the battery system. Because ambient air is a readily available resource for aircraft, this paper considers an active cooling concept with forced convection of ambient air through the battery pack. Conjugate heat transfer analysis is used to solve the coupled aero-thermal problem, which consists of a finite-volume computational fluid dynamics solver for the fluid domain, and a conduction heat transfer solver for the solid domain. A mixed Neumann and Dirichlet boundary condition is developed for the fluid-solid interface, which allows the solid domain to completely submerge in the fluid domain. A gradient-based optimization method is adopted, and the discrete adjoint approach implemented in DAFoam is used to efficiently compute the gradients. The aero-thermal coupling for primal analysis and gradient computation is handled using the OpenMDAO-based MPhys framework. A constant heat source is prescribed for the battery cells, and the battery shape (design variable) is optimized to minimize cooling pump power and battery weight (composite objective function) while keeping the battery temperature below a threshold (constraint). The optimized design achieves a 44.6% and 1.5% reduction in the cooling pump power and battery weight, respectively, and the maximal temperature constraint is satisfied. This work has the potential to reduce battery-pack weight, improve performance, and reduce the weight of thermal management systems for electric vertical take-off and landing aircraft.

heat transfer

Ionic Interdiffusion at Cathode|Solid-Electrolyte Interface: A Machine Learning–Assisted Multiscale Investigation and Mitigation Strategies

Future lithium batteries are expected to use solid electrolytes to achieve higher energy density and fast charge capabilities. However, most solid electrolytes are thermodynamically unstable against layered oxide cathodes. In this study, the stability of LiCoO2 (LCO) cathode with Li10GeP2S12 (LGPS) solid electrolyte is investigated using ab initio molecular dynamics (AIMD) and machine learning molecular dynamics (MLMD). The propensity of ionic interdiffusion, formation of a passivating interphase layer, and corresponding decay in cell performance is addressed using a continuum model. Large-scale MLMD simulations confirm that the LCO|LGPS interface permits interdiffusion of cobalt (Co) and other ionic species, leading to the formation and growth of a resistive interphase and to dramatic capacity fade even in the first cycle. We examine the literature evidence that incorporating a thin layer of LiNb0.5Ta0.5O3 (LNTO) between LCO and LGPS prevents the interdiffusion of ions. Atomistic simulations suggest that substituting lithium (Li) in LNTO with Co is thermodynamically unfavorable, thereby inhibiting ionic interdiffusion. The stable Nb5+/Ta5+ states form a rigid metal-oxide framework, which consequently also prevents the substitution of niobium (Nb) or tantalum (Ta). However, continuum-level analysis suggests that the higher mechanical stiffness of LNTO can lead to interfacial delamination between the LCO and LNTO. This phenomenon reduces the effectiveness of the protective layer. This paper, therefore, highlights the need to develop novel interlayers that balance low ionic interdiffusion with low mechanical stiffness.

Ncube, Musawenkosi K.

Value of Geothermal Energy Storage for Supply-Side and Demand-Side Applications

This report presents the results of a study examining the value potential for geothermal energy storage (GES), a long-duration energy storage resource that stores thermal and/or geomechanical energy in the subsurface. GES could benefit the overall U.S. power system by temporally shifting electricity generation (supply-side) or meeting building heating and cooling load (demand-side). This report analyzes supply-side and demand-side opportunities independently because of differences in applications and models. Currently there is significant uncertainty about the development costs for GES, with only a limited number of demonstration plants for electric energy storage and building heating and cooling storage developments. In this report, we estimate the value of supply-side and demand-side GES to the bulk power system in the contiguous United States. Because of the significant uncertainty about GES development costs, this analysis does not consider GES deployment costs but instead focuses on the value of GES to the U.S. electricity system. The estimated values of GES provide reference points for economically competitive commercial cost targets. Supply-side GES is modeled as part of an enhanced geothermal system (EGS) generation plant in NREL's Regional Energy Deployment System (ReEDS) capacity expansion model (Ho et al. 2021). In contrast to conventional geothermal plants, which generate constant power, EGS plants have unique features that may allow for in-reservoir energy storage for flexible generation. Demand-side GES for heating and cooling, including seasonal hot and cold storage and short-duration heat pump storage, is incorporated into a price-taker model using Cambium electricity marginal cost projections. To establish an upper bound for the value of GES, analysis focused on favorable scenarios for storage with high generation from zero marginal cost, variable renewable energy resources. High penetrations of variable renewable energy generation can increase hourly electricity price variability, which increases the value of temporal energy arbitrage for storage technologies like GES.

15 GEOTHERMAL ENERGY

Nonlocal Effect of Percolated Particle Networks on Viscoelasticity of Polymer–Filler Nanocomposites: A Mesoscale Simulation Study

With nanoparticles (NPs) as fillers, polymer nanocomposites (PNCs) usually exhibit enhanced mechanical properties. However, a direct connection between the microscopic structural relaxation and macroscopic mechanical properties of PNCs remains to be established. To investigate the micro-to-macro connection, we develop a mesoscale model, in which the NPbridging polymer chains are represented by a dynamic bonded interaction between NPs, and the bulk polymer matrix is implicitly modeled by overdamped Langevin dynamics. Extensive equilibrium simulations are performed to quantify the microscopic dynamics of model PNCs. Systematic analyses of modified Rouse dynamics, dynamic structure factor, and relaxation modulus uncover that the microscopic relaxation dynamics of PNCs are significantly decelerated across different length scales because of nonlocal effects of percolated particle networks a phenomenon that has not been adequately captured in prior simulation studies. We find that NPvolume- fraction and NP-bonding-energy barrier are the two critical variables that affect bulk viscoelasticity the most. The proposed mesoscale model is versatile and provides a powerful framework for studying structure−property relations of different PNCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Design and Modeling of the Charge Readout of a SiMOS Quantum Dot with a Single Electron Transistor and CryoCMOS

Single electron spin qubits trapped in SiMOS quantum dots are a promising technology for scaling to thousand- or million-qubit systems due to their compatibility with mature CMOS manufacturing processes. A readout system that combines a single electron transistor with a custom cryogenic CMOS amplification and digitization chain offers key advantages by avoiding the use of bulky RF components or room-temperature interconnects. We present design techniques and simulation results for an optimized qubit-SET cryoCMOS interface, culminating in the design of the QNDR1 ASIC, the first cryogenic readout ASIC designed under the Quandarum project, which targets the development of a many-channel spin qubit based detector for use in high energy physics.

Quinn, Adam [Fermilab] (ORCID:0009000605056371)

Ramp-release experiments for strength measurements: Strain-rate dependence

This paper presents an enhanced analysis method for investigating material properties at high strain rates, extending the capability of established experimental techniques to gain more information. The ramp-release method has been applied to many experiments reported at high (≈10 5 − 10 6 s −1 ) strain-rates. More recent data gathered at the National Ignition Facility (NIF) has enabled higher (≈10 8 s −1 ) strain-rates to be studied. Here, we present an initial application of ramp-release analysis to NIF ramp-compression data, illustrating both the opportunities and the practical challenges of extending these methods to laser-driven platforms. The higher strain-rates accessed at the NIF mean that there is more strain-rate enhancement to strength, and the experimental configuration means that this enhancement is more readily seen in the data. This is enabled by the capability of avoiding peak-compression attenuation through the sample thickness with a designed hold period made possible by the pulse-shaping capability of NIF. We propose that this combination of experimental conditions and an enhanced analysis method enables the strain-rate enhancement to strength to be studied, and potentially for this to inform physics models at smaller scales than the continuum.

36 MATERIALS SCIENCE