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1,437 records · Page 33

Development and Validation of a High-Vacuum Thermal Conductivity Testbed for Aerospace Interface Materials

Spacecraft thermal margins depend on the temperature penalty of installed interfaces, yet catalog conductivity omits bondline thickness, mating surfaces, preload, and environment. The Testbed for Advanced Interface Materials in Vacuum (TAIMV) addresses this engineering-data gap by converting ambient/vacuum temperature fields from a four-coupon stack into quantities usable in spacecraft thermal models. Its 17-node steady-state model resolves axial conduction, parasitic fixture paths, grease-filled contact, radiation, and ambient convection. Four monolithic checks gave axial heat-rate ratios of 0.90–1.02, and Braycote calibration self-recovery gave 2.20% casewise mean absolute percentage error (MAPE) and 2.85% maximum difference. With transferable fixture terms frozen, Krytox LVP tested cross-material transfer against a manufacturer-derived external relation. The six Krytox cases gave 2.28% MAPE, 5.10% maximum difference, and full-field residual root-mean-square values of 0.553 °C ambient and 1.306 °C vacuum. Installed-joint resistance spanned 6.39–7.15 × 10⁻⁴ m²·K/W for Braycote and 4.09–4.49 × 10⁻⁴ m²·K/W for Krytox, corresponding to 2.33–6.66 K per modeled interface over the tested heat-flux range. TAIMV therefore supplies directly usable installed-joint resistance and conductance, plus apparent installed conductivity and explicitly model-conditioned grease conductivity/contact terms.

heat transfer

Cobalt-free and high-rate stable 5V lithium nickel manganese oxide spinel cathodes enabled via surface oxygen vacancies

Spinel LiNi 0.5 Mn 1.5 O 4 offers both the high-rate, low-cost and safety advantages of LiFePO 4 and the high energy density of LiNiₓMnᵧCo₁₋ₓ₋ᵧO₂ and LiNiₓCoᵧAlzO₂ cathodes. However, the large operating voltage of these materials induces electrolyte oxidation, which degrades the interface and drives Mn dissolution. These reactions are further exacerbated at high rates due to temperature rise. In this study, we discover that ammoniacal treatment followed by annealing introduces a high density of oxygen vacancies in the “near-surface region” of LiNi 0.5 Mn 1.5 O 4 particles. These vacancies release electrons changing the oxidation state of Mn and suppressing its tendency to oxidize the electrolyte. Further, these vacancies enhance the electrode’s electronic conductivity (by ∼3-fold) and Li + diffusivity (by ∼2-fold) greatly improving charge transport, especially when operated at high rates. This results in an across-the-board improvement in self-discharge, specific capacity, energy density, rate capability, coulombic efficiency and cycling stability. When cycled at ∼200 mA g −1 , the capacity fade averaged over 3000 cycles for the surface vacancy-enriched material is ∼0.0167% per cycle compared to an order of magnitude higher fade rate for the baseline material. In conclusion, these findings reveal the potential of targeted surface oxygen vacancy doping to develop cobalt-free and high energy density cathodes that tolerate fast charging and deliver improved cycle life.

Cobalt-free cathodes

Factors Influencing Gas Evolution from High‐Nickel Layered Oxide Cathodes in Lithium‐Based Batteries

Abstract Gas evolution from high‐nickel layered oxide cathodes (>90% Ni) remains a major issue for their practical application. Gaseous species, such as CO 2 , O 2 , and CO, that are evolved at high states of charge (SOC) worsen the overall safety of batteries, as pressure build‐up within the cell may lead to cell rupture. Since these gasses are produced during cathode degradation, tracking the formation of gasses is also important in diagnosing cathode failure. Online electrochemical mass spectrometry (OEMS) is a powerful in situ technique to study gas evolution from the cathode during high‐voltage charge. However, the differences in the OEMS experimental setups between different groups make it challenging to compare results between groups. In this perspective, the various factors that influence gas evolution based on the OEMS results collected in this group are presented. The focus is on the conditions that lead to gas release, with a particular emphasis on reactive oxygen formation and subsequent chemical reactions with the electrolyte. Promising strategies, such as electrolytes, compositional tuning, and surface coatings that are effective at suppressing gas evolution from the cathode are highlighted. Critical insights into mitigating cathode degradation and gas evolution are provided to guide the development of safer, high‐energy batteries.

Chemistry

Electromagnetic Melt Processing: A Pathway to New Additive Manufacturing Technologies for Functional High-Performance Thermoplastics

In this study, we apply the electromagnetic (EM) melt processing of thermoplastics on an innovative EM field-driven powder bed fusion additive manufacturing (AM) concept for high-performance functional parts: Selective Microwave Melting/Sintering (SMM/SMS). This technique leverages the EM susceptibility of carbon nanotube-coated polymer micro-pellets to achieve rapid, localized heating and powder fusion. Thus, selective microwave melting (SMM) was used to fabricate multilayer specimens made of recycled polyphenylene sulfide (rPPS) and carbon nanotubes (CNTs). The resulting SMM specimens exhibited very good interlayer integrity, localized fusion at pellet boundaries, and tolerable residual porosity, indicating effective fusion and acceptable consolidation. CNT-rich interphases were retained after irradiation, generating anisotropic electrically active network pathways and enabling conductivity enhancement at low filler content. At only 1.0 wt% CNT, the specimens exhibited electrical conductivity approximately three orders of magnitude higher than neat rPPS. Dynamic mechanical analysis showed improved viscoelastic response relative to neat rPPS, while tensile testing confirmed that the SMM-processed specimens retained practical mechanical integrity despite localized voids. These results demonstrate that SMM can effectively consolidate EM susceptible thermoplastic powder beds while preserving their segregated conductive networks. This may become a scalable route for producing multifunctional thermoplastic parts with low filler loadings, tunable anisotropy, and structured materials and parts. Overall, the findings suggest that EM field-based AM can help overcome key limitations of conventional thermoplastic processing by enabling scalable, energy-efficient fabrication of nanostructured composites and expanding AM to a broader range of resins, including high-performance thermoplastics with customized functional properties.

Powder bed fusion

An Ultra-long Life, High-performance, Flexible Li-CO2Battery Based on Multifunctional Carbon Electrocatalysts

Integrating CO2 utilization and renewable energy delivery/storage, the rechargeable Li–CO2 battery has been considered as a promising candidate for next-generation secondary batteries. However, high-performance catalyst(s) for efficient formation and decomposition of the discharge product, Li2CO3, are an imperative part of a Li–CO2 battery. The development of flexible Li–CO2 batteries extends their applications into compliant and wearable devices/systems, but at the same time imposes a big challenge for battery fabrication and lifetime enhancement. In this study, a rechargeable quasi-solidus flexible Li–CO2 battery was designed and fabricated using highly active N,S-doped carbon nanotubes (N,S-doped CNTs) as the cathode catalyst, and a smart polymer gel as the flexible electrolyte. This newly-developed flexible Li–CO2 battery exhibited a capacity as high as 23560 mAh g−1 based on the catalyst mass and an ultra-long lifetime of up to 538 cycles with excellent mechanical flexibility. This work provides a platform for the design and development of high-performance flexible Li–CO2 batteries from low-cost, earth-abundant, carbon-based multifunctional cathode catalysts.

Superior stability

Using scalable computer vision to automate high-throughput semiconductor characterization

Abstract High-throughput materials synthesis methods, crucial for discovering novel functional materials, face a bottleneck in property characterization. These high-throughput synthesis tools produce 10 4 samples per hour using ink-based deposition while most characterization methods are either slow (conventional rates of 10 1 samples per hour) or rigid (e.g., designed for standard thin films), resulting in a bottleneck. To address this, we propose automated characterization (autocharacterization) tools that leverage adaptive computer vision for an 85x faster throughput compared to non-automated workflows. Our tools include a generalizable composition mapping tool and two scalable autocharacterization algorithms that: (1) autonomously compute the band gaps of 200 compositions in 6 minutes, and (2) autonomously compute the environmental stability of 200 compositions in 20 minutes, achieving 98.5% and 96.9% accuracy, respectively, when benchmarked against domain expert manual evaluation. These tools, demonstrated on the formamidinium (FA) and methylammonium (MA) mixed-cation perovskite system FA 1−x MA x PbI 3 , 0 ≤ x ≤ 1, significantly accelerate the characterization process, synchronizing it closer to the rate of high-throughput synthesis.

Science & Technology - Other Topics

Spacecraft Fire Safety Predictions using Verified Saffire Model

A model developed using Fire Dynamics Simulator (FDS) that aimed to determine the effect of a fire in a spacecraft was validated by data collected during the Saffire campaign. The model used inlet and outlet temperatures and CO 2 concentrations of the Saffire payload where fire spread was taking place to determine the amount of heat and combustion products that made it into Northrop Grumman’s Cygnus vehicle. The model was then validated using six remote sensors in various places in the vehicle, as well as a far field device (FFD) in the open zenith section that was representative of average vehicle values. The current work focuses on using the model to predict fire safety scenarios. One simulation aimed to determine the fate of HCl, which sticks to surfaces. The model prediction showed that the HCl was removed from the atmosphere rapidly. This compared well against the FFD data in the Saffire VI campaign event where a bottle of 5% HCl was released into the vehicle. An additional simulation where the Environmental Control and Life Support System (ECLSS) was shut off once the FFD reached 5 ppm of HCl showed that HCl stayed in the atmosphere considerably longer. Continuing the simulation with the ECLSS activated and after temperatures returned to their initial conditions, resulted in a rapid removal of HCL similar to that observed in the original HCl release scenario model. Finally, a simulation that used the heat release rate from a lithium-ion battery test to determine the effect it would have on a spacecraft was performed. This simulation used a heat addition rate that is considerably higher than what was determined from the burning of solid fuels in the Saffire campaign and hence produced a non-trivial temperature increase in more locations within the vehicle.

Fire Safety

A butterfly-shaped acceptor with rigid skeleton and unique assembly enables both efficient organic photovoltaics and high-speed organic photodetectors

ABSTRACT It remains challenging to design efficient bifunctional semiconductor materials in organic photovoltaic and photodetector devices. Here, we report a butterfly-shaped molecule, named WD-6, which exhibits low energy disorder and small reorganization energy due to its enhanced molecular rigidity and unique assembly with strong intermolecular interaction. The binary photovoltaic device based on PM6:WD-6 achieved an efficiency of 18.41%. Notably, an efficiency of 19.42% was achieved for the ternary device based on PM6:BTP-eC9:WD-6. Moreover, the photodetection device based on WD-6 demonstrated an ultrafast response speed (205 ns response time at λ of 820 nm) and a high cutoff frequency of −3 dB (2.45 MHz), surpassing the values of most commercial Si photodiodes. Based on these findings, we showcased an application of the WD-6-based photodetection device in high-speed optical communication. These results offer valuable insights into the design of organic semiconductor materials capable of simultaneously exhibiting high photovoltaic and photodetective performance.

Science & Technology - Other Topics

A novel compact end-loaded piston cylinder cell for high pressure neutron scattering up to 5 GPa

Here, a miniature sized end-loaded piston cylinder cell with radial side windows for neutron scattering experiments is described. The principle of the bicone-shaped cylinders used was first presented by McWhan in 1974. The present cell is of compact portable design yet significantly enlarges the scattering angles. Its small size allows neutron scattering experiments at low temperatures. The bicone-shaped cylinders are made from various ceramics or a highly neutron-transmissive Ni-free Cr–Mo–V steel. Successful neutron scattering experiments up to 5 GPa have been demonstrated on the CORELLI single-crystal diffractometer and the VISION vibrational spectrometer of the Spallation Neutron Source at the Oak Ridge National Laboratory.

Neutrons

High-Q superconducting lumped-element resonators for low-mass axion searches

Low-frequency superconducting lumped-element resonators have recently attracted significant attention in the context of axion dark matter searches. Here, we present the design and implementation of a fixed-frequency superconducting resonator operating near 250 kHz, possessing an inductor volume of ∼1 liter and achieving an unloaded quality factor Q ≈ 2.1 × 10 6 . This resonator represents a significant improvement over the state of the art and informs the design of searches for low-mass axions.

Bosons

Development of a high fidelity CFD model for solvent evaporation and transport in porous structure during battery electrode drying

An efficient battery manufacturing process is the key to the mass production of Electric Vehicles (EV), in which drying is one of the most energy-intensive steps significantly influencing the battery cell performance. An accurate 3D CFD model for drying is essential for predicting the drying mechanism and optimizing its parameters. By optimizing the drying process, it is possible to reduce energy consumption and cost during battery manufacturing, minimize binder loading and maximize active material loading to achieve superior electrochemical performances and facilitate wider and faster public adoption of EV. This project aims to optimize the drying process during electrode manufacturing by leveraging high-fidelity, porous electrode simulations for solvent evaporation. By optimizing this process, we seek to reduce energy consumption during battery manufacturing, while minimizing binder loading and maximizing active material loading, with the overall goal of enhancing electrical vehicle performance.

Horner, Jeffrey Scott [Sandia National Laboratorie

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database

Atomic- and Molecular-Scale Interphase Engineering for High-Performance Solid-State Batteries

Solid-state batteries (SSBs) promise a decisive advance beyond conventional Li-ion systems, yet their development remains constrained by persistent solid–solid interfacial instabilities that degrade performance and durability. Interfaces between solid electrolytes and both cathodes and Li metal often exhibit poor wettability, limited physical contact, and high charge–transfer resistance, leading to chemical decomposition, mechanical failure, and impedance growth. Overcoming these limitations requires interphase engineering with atomic-scale precision—capabilities that conventional coating methods cannot reliably deliver. Atomic layer deposition (ALD) and molecular layer deposition (MLD) uniquely meet this need by enabling ultrathin, conformal, and composition-tunable films that stabilize reactive surfaces, suppress parasitic reactions, and regulate Li-metal morphology. Importantly, this Perspective highlights ALD/MLD systems that have already demonstrated effectiveness in liquid-electrolyte cells and discusses how these validated strategies can be deliberately translated to solid-state architectures. By grounding future directions in experimentally proven concepts rather than speculative hypotheses, we outline how atomic- and molecular-scale design principles can accelerate the development of robust, high-performance SSB technologies.

atomic and molecular layer deposition