Results for “Low-Boom Technology” — Page 71

NASA NTRS2026

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↗

NASA NTRS2003

Ultra-High-Temperature Ceramics Evaluated for Aeropropulsion Use

Ultra-high-temperature ceramics (UHTC) are a group of materials consisting of zirconium diboride (ZrB2) or hafnium diboride (HfB2) plus silicon carbide (SiC), and in some instances, carbon (C). They offer a combination of properties that make them candidates for airframe leading edges on sharp-bodied reentry vehicles. These UHTCs perform well in the environment for such applications (i.e., air at low pressures). The purpose of this study at the NASA Glenn Research Center was to examine three of these materials under conditions more representative of a propulsion environment: that is, higher oxygen partial pressure and total pressure. Relatively long, multiple-exposure cycles were emphasized. We completed an in-house study of ZrB2 plus 20 vol% SiC (abbreviated as ZS), ZrB2 plus 14 vol% SiC and 30 vol% C (ZSC), and SCS-9a SiC fiber-reinforced ZrB2 plus 20 vol% SiC (ZSS). HfB2-based compositions were not included in the study because of their high cost. The capability of UHTC for propulsion applications must be compared with that of mature, available, and commercially used ceramics such as silicon nitride (e.g., AS-800) to put things in proper perspective. In terms of mechanical properties, UHTCs fall short in terms of strength and fracture toughness. At about 1300 C, the creep resistance of ZS appears to be superior to the creep resistance reported for AS-800. However, the stress rupture life for Si3N4 under stress and temperature conditions similar to those used in this study is measured in hundreds of hours. Because of oxidation, ZS could not achieve such lives. In terms of oxidation resistance, acceptable amounts of material recession in 1 hour to thousands of hours, depending on the specific propulsion application, are on the order of 100 to 300 mm. This converts to an acceptable range of parabolic recession rate constants kp" of approximately less than or equal to 10(exp -1) to 10(exp -2) square millimeters per hour for a 1-hr application. For a 100-hr application, an acceptable range of kp" would be less than or equal to those values divided by 100. For the more oxidation resistant ZS material, measured parabolic recession rate constants were 4.7 x 10(exp -3) millimeters per hour at 1327 C, 7.8 x 10(exp -2) square millimeters per hour at 1627 C, and 1.3 millimeters per hour at 1927 C. Thus, recession rate constants for ZS are acceptable at 1327 C for a 1-hr application, but here silicon nitride is a superior material. At 1627 C, ZS oxidation is marginal for a 1-hr application, but dimensional growth would be an issue. In a 100-hr application, ZS cannot be considered at any temperature. Our cursory examination of thermal shock, both from a theoretical and experimental viewpoint, indicated that the ZS and ZSC UHTCs are inferior to AS-800 silicon nitride. On the basis of this limited study, UHTCs are not ready to be considered as aeropropulsion materials for any applications longer than a few minutes. Current materials suffer from aggressive oxidation and moisture attack (Quynhgiao Nguyen, NASA Glenn, and Raymond C. Robinson, QSS Group, Inc., Cleveland, OH, 2002, private communication), and they are susceptible to thermal shock. For long-term propulsion applications, major improvements in environmental durability are needed. Work is in progress to improve the oxidation resistance of UHTC materials.

Stanley R Levine↗

DOE OSTI2026

Pinning ångström-size solid ionic channels for rare-earth element separation

High-purity rare-earth elements are essential for modern technologies, yet current solvent extraction processes are energy-intensive and environmentally harmful because of inadequate selectivity and ligand toxicity. Although combining size exclusion and binding affinity can improve lanthanide separation, the role of long-range confinement remains underexplored. Here we report lanthanide separation in aqueous systems using extremely confined manganese oxide solid ionic channels with optimized layer spacing. Different lanthanides induce distinct solid-state phase transformations in manganese oxide, creating a strong driving force for separation. Two lanthanide groups, differing by ~1.4 Å in spacing, were identified and confirmed to be stable by density functional theory. The narrower confinement of heavier Group II lanthanides improves cross-group separation by increasing the dehydration barrier for lighter Group I lanthanides without inducing strong binding. Here, we further developed a strategy to pin the confinement dimensions and enhance same-group separation, increasing enrichment factors for La–Nd and La–Pr pairs from 1.6 ± 0.1 and 1.5 ± 0.1 to 5.4 ± 0.1 and 4.2 ± 0.1, respectively.

Chemical engineering↗

DOE OSTI2025

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗

NASA NTRS2026

Highly Porous Polyimide Gel for Use as Battery Separator with Room Temperature Ionic Liquid Electrolytes

Advanced aerospace vehicular concepts require advances in many existing technologies, including space power and energy storage systems. Batteries represent one of the major areas in need of improvement, both in terms of energy density and safety, with growing concerns over the fire safety of commercial lithium-ion batteries. This has prompted efforts to develop nonflammable battery components, namely the electrolyte and separator. Existing commercial lithium-ion batteries utilize polyolefin microporous membranes as separators with an electrolyte consisting of a lithium salt dissolved in a mixture of cyclic carbonate solvents. This separator/electrolyte combination has ionic conductivities in the range of 10 −2 to 10 −3 S/cm. However, the cyclic carbonate solvents are inherently flammable. Room-temperature ionic liquids (RTILs) appear to be a safer alternative. They offer good ionic conductivities and are inherently nonvolatile and nonflammable, giving them a safety advantage. However, many promising RTILs for battery electrolytes are not compatible with commercial polyolefin separator materials. Alternative separator materials, such as polyimides, are non-flammable and are capable of accepting RTILs into their structure. Polyimide gels, with a composition of 4,4′-oxydianiline, 3,3′,4,4′-tetracarboxylic dianhydride and cross-linked with Desmodur N3300A, possess an open-porous, fibrillar network architecture which offers a high degree of porosity (typically greater than 85% porosity) for lithium-ion transport and conduction, as well as good mechanical properties. Furthermore, these polyimide gels are compatible with selected imidazolium-based RTILs. Nonflammable separator/electrolyte systems with room-temperature conductivities in the range of 10 −3 S/cm have been evaluated. It has been demonstrated that 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide was the most promising among six RTILs screened, in terms of both ionic conductivity and constant current cycling.

Polyimide↗

NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗

NASA NTRS2026

Dynamic Regulation of Sub-Atmospheric Pressure for Constant and Cyclic Gas Loads During Testing of Spacesuit Components

New iterations of the various subsystems within the spacesuit will benefit from a new sorbent technology. For example, sorbents used in the Trace Contaminant Control (TCC) and the Rapid Cycle Amine (RCA) systems within the Exploration Portable Life Support System (xPLSS), part of the Extra-Vehicular Mobility Unit (xEMU). For proper validation, the sub-atmospheric pressure needs to be maintained within a simulated 2 ft 3 spacesuit volume. The traditional approach, which involves placing the entire vent loop within a hypobaric chamber, is not practical for the widespread testing of components and prototypes, as these specialized chambers are costly and not widely available. A two-stage regulator based sub-atmospheric pressure system is presented in this work. The method regulates the pressure based on pressure differentials between the pressure regulation pump, the test system, and the ambient environment. The performance of this system is demonstrated using data collected during a 150+ hour non-regenerative TCC sorbent evaluation, several 24-hour regenerative TCC sorbent evaluations with different regeneration cycles, and an 8-hour RCA sorbent evaluation, all under xEMU operating conditions. For regulation, the inlet regulator was set to propagate a small leak to increase the stability of the system as the gas load from the testing system changes. It was also found that controlling the input flow rate that replaces the material lost during regeneration is critical for ensuring the stability of the system. This system provided excellent pressure regulation, without adjustments, for constant loads during shorter time evaluations (hours), while longer time evaluations (days) are easily obtainable with periodic regulator adjustments. A second method is under development to address longer-term stability and to automate pressure regulation. It will incorporate flow and pressure measurements to dynamically control a set of electronically controlled proportional valves for adjusting the pumping speed and air bleed supply.

Nicholas F Materer↗

DOE OSTI2026

The SPT-deep Cluster Catalog: Sunyaev–Zel’dovich Selected Clusters from Combined SPT-3G and SPTpol Measurements over 100 Square Degrees

We present a catalog of 500 galaxy cluster candidates in the SPT-Deep field: a 100 deg$^{2}$ field that combines data from the SPT-3G and SPTpol surveys to reach noise levels of 3.0, 2.2, and 9.0 μK-arcmin at 95, 150, and 220 GHz, respectively. Candidates are selected via the thermal Sunyaev–Zel’dovich (SZ) effect with a minimum significance of ξ = 4.0, resulting in a catalog of purity ∼89%. Optical data from the Dark Energy Survey and infrared data from the Spitzer Space Telescope are used to confirm 442 cluster candidates. The clusters span 0.12 < z ≲ 1.8 and 1.0 × 10$^{14}$M$_{⊙}$/h$_{70}$ < M$_{500c}$ < 8.7 × 10$^{14}$M$_{⊙}$/h$_{70}$. The sample’s median redshift is 0.74, and the median mass is 1.7 × 10$^{14}$M$_{⊙}$/h$_{70}$; these are the lowest median mass and highest median redshift of any SZ-selected sample to date. We assess the effect of infrared emission from cluster member galaxies on cluster selection by performing a joint fit to the infrared dust and tSZ signals by combining measurements from SPT and overlapping submillimeter data from Herschel/SPIRE. We find that at high redshift (z > 1), the tSZ signal is reduced by $17.9_{−3.2}^{+3.8}$%$(3.8_{−0.7}^{+0.9}$%$)$ at 150 GHz (95 GHz) due to dust contamination. We repeat our cluster finding method on dust-nulled SPT maps and find the resulting catalog is consistent with the nominal SPT-Deep catalog, suggesting dust contamination does not significantly impact the SPT-Deep selection function; we attribute this lack of bias to the inclusion of the SPT 220 GHz band.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2026

In-suit CO2 Washout Test System (ICWTS) for CO2 Washout Verification in Spacesuits

Since the time of Mercury, Gemini, and Apollo, NASA has been performing CO 2 washout verification of spacesuits with Human in the Loop (HITL) test methods. Classically, the only instrumentation both with the accuracy and response time necessary was that of external mass spectrometers or medical gas analyzers fed by a long capillary line from the oro-nasal region within the suit. The helmet CO 2 washout configuration including the challenges posed by variation of a suited human subject frequently created difficulty in capturing adequate breath by breath data. For example, a nasal cannula could be worn with reasonable comfort however it posed the following challenges: (1) impeded the test subject’s ability to do a proper Valsalva maneuver; (2) frequently provided a corrupted waveform with relative movement; (3) precluded the ability to evaluate the Flow Weighted Average (FWA) at subject interface. A mouthpiece could be used in lieu of a cannula but posed challenges as well: (1) created potential disturbances of the flow field; (2) precluded the test subject from speaking during usage; and (3) presented comfort issues limiting the duration of test points. These challenges made it impractical to use a mouthpiece for anything other than short lab ambient environment tests. Technology development and NASA investment have afforded new capabilities to address some of these measurements providing improved data collection and are implemented in the In-suit CO 2 Washout Test System (ICWTS) which provides suit inlet/outlet pressure, temperature, relative humidity, partial pressure of oxygen, partial pressure of CO 2 , and flow measurement coupled with the acquisition of the inspired PPCO 2 including the ability for FWA measurement. This test system, coupled with use of the In-suit Respiration Mannequin Assembly (IRMA) and Computational Fluid Dynamics (CFD) combine to provide a full picture of the in-suit oro-nasal flow field and effectiveness of CO 2 washout in a spacesuit design.

Colin Campbell↗

DOE OSTI2026

Maximizing dynamic range and performance of anatase TiO 2 ECRAM through structure and programming

Here, in this study, we investigate the structure-dependent modulation characteristics of all-solid-state three-terminal electrochemical random-access memory (ECRAM) based on an anatase Li x TiO 2 channel. By directly comparing “asymmetric” and “symmetric” ECRAM device architectures, we reveal significant insight into the impact of a non-zero gate-drain open-circuit voltage and its influence on voltage vs. current-controlled gating. We also explore the impact of potentiation/depression write parameters on the symmetry, linearity, and dynamic range of the device response. Together, initial results from optimizing structure and programming approaches yielded unprecedented G max /G min ratios of >1,000 for ECRAM and hundreds of tunable memory states with excellent linearity and symmetry. Simulations based on these ECRAM devices further illustrate the promise of this analog memory technology, achieving near 2% classification error in the MNIST digit recognition benchmark for a range of training parameters compared to a theoretical best of 1.66% and outperforming other device models extracted from the literature.

AIHWKit↗

NASA NTRSDate not supplied

Numerical Investigation of Heat Transfer and Fluid Flow within Electrochemical Hydrogen Peroxide Generation Unit

Long-term manned space missions require the onboard production of disinfectants essential for maintaining crew health and supporting life systems. Currently, disinfection aboard the International Space Station (ISS) relies on disposable wetted wipes, which are regularly resupplied from Earth. This approach imposes a significant burden on resupply logistics, storage, and waste management. To address these challenges and support future missions, efforts are underway to develop an in-situ solution that electrochemically generates hydrogen peroxide disinfectant using onboard resources. In collaboration with NASA, Faraday Technology, Inc. has advanced this concept through a series of Small Business Innovation Research (SBIR) projects, resulting in the development of a Peroxide Generation Unit (PGU). The PGU can produce up to 3 wt.% hydrogen peroxide on-demand at a rate of 1 liter per day, providing a sustainable alternative to Earth-dependent supplies. The resulting aqueous hydrogen peroxide (H₂O₂) is an effective disinfectant, safe for crew use, compatible with spacecraft systems, and free from volatiles, off-gassing, or residues. This innovation offers a reliable, efficient solution for onboard disinfection, reducing dependence on Earth-based resupply while ensuring the health and safety of space crews. Generating hydrogen peroxide at the required rate needs high voltages and currents, exceeding 20V and 2A respectively, which leads to significant heat generation from Joule heating. This temperature rise poses a risk to sensitive system components, especially critical and expensive membranes that can degrade under thermal stress. To mitigate this risk, the thermal, fluid, and electrical flows within the system are modeled computationally using the commercial software COMSOL. The numerical simulations are validated against experimental data from both sub-scale and alpha-scale systems. Once verified, the model is employed to identify thermal hotspots, investigate their underlying causes, and explore solutions to prevent them.

Life Support Systems (LSS)↗

NASA NTRS2026

Performance Evaluation of Intravehicular Activity Spacesuit Without the Use of a Liquid Cooling Garment

The Orion Crew Survival Systems (OCSS) suit is equipped with safety technology that protects the crew during launch and re-entry and Intravehicular Activities (IVA). It was designed to be used with a Liquid Cooling Garment (LCG), an undergarment with tubes that circulate water to remove excess heat from a crew member. The objective of this study is to determine if the Modified Advanced Crew Escape Suit (MACES), which has very similar material, assembly, and pressure characteristics as the OCSS suit, can be used without the LCG to maintain the crew within their heat storage requirements where exceedances can lead to cognitive and physiological impairment. Testing was completed for both hot and cold environments where test subjects wore varying configurations of the MACES suit ensemble without the LCG. The tests were conducted in a temperature and humidity-controlled chamber with four test subjects ranging from extra small to large. Target metabolic rates were reached using an arm ergometer. To represent the different suit configurations seen in the concept of operations, the suit was tested with visor-down, visor-up, and without helmet and gloves. The test data was analyzed to determine how the environment, test subject size, metabolic rate, and suit configuration affected heat storage. Furthermore, the test data was used to correlate the METMAN model, a transient metabolic man program that simulates the heat transfer within a crew member’s body and from a crew member to the surrounding environment. The METMAN correlation showed good agreement between predicted heat storage and test data at the end of the test duration, with a coefficient of determination (R 2 ) value of 0.8999 for visor-down cases and R 2 of 0.8902 for visor-up and helmet off cases. A correlated METMAN model allows for the analysis and prediction of IVA suit performance without an LCG in additional scenarios.

Spacesuit↗

NASA NTRS2026

Performance Evaluation of Intravehicular Activity Spacesuit Without the Use of a Liquid Cooling Garment

The Orion Crew Survival Systems (OCSS) suit is equipped with safety technology that protects the crew during launch and re-entry and Intravehicular Activities (IVA). It was designed to be used with a Liquid Cooling Garment (LCG), an undergarment with tubes that circulate water to remove excess heat from a crew member. The objective of this study is to determine if the Modified Advanced Crew Escape Suit (MACES), which has very similar material, assembly, and pressure characteristics as the OCSS suit, can be used without the LCG to maintain the crew within their heat storage requirements where exceedances can lead to cognitive and physiological impairment. Testing was completed for both hot and cold environments where test subjects wore varying configurations of the MACES suit ensemble without the LCG. The tests were conducted in a temperature and humidity-controlled chamber with four test subjects ranging from extra small to large. Target metabolic rates were reached using an arm ergometer. To represent the different suit configurations seen in the concept of operations, the suit was tested with visor-down, visor-up, and without helmet and gloves. The test data was analyzed to determine how the environment, test subject size, metabolic rate, and suit configuration affected heat storage. Furthermore, the test data was used to correlate the METMAN model, a transient metabolic man program that simulates the heat transfer within a crew member’s body and from a crew member to the surrounding environment. The METMAN correlation showed good agreement between predicted heat storage and test data at the end of the test duration, with a coefficient of determination (R 2 ) value of 0.8999 for visor-down cases and R 2 of 0.8902 for visor-up and helmet off cases. A correlated METMAN model allows for the analysis and prediction of IVA suit performance without an LCG in additional scenarios.

Human Thermal Modeling↗

NASA NTRS2026

In-suit CO 2 Washout Test System (ICWTS) for CO 2 Washout Verification in Spacesuits

Since the time of Mercury, Gemini, and Apollo, NASA has been performing CO 2 washout verification of spacesuits with Human in the Loop (HITL) test methods. Classically, the only instrumentation both with the accuracy and response time necessary was that of external mass spectrometers or medical gas analyzers fed by a long capillary line from the oro-nasal region within the suit. The helmet CO 2 washout configuration including the challenges posed by variation of a suited human subject frequently created difficulty in capturing adequate breath by breath data. For example, a nasal cannula could be worn with reasonable comfort however it posed the following challenges: (1) impeded the test subject’s ability to do a proper Valsalva maneuver; (2) frequently provided a corrupted waveform with relative movement; (3) precluded the ability to evaluate the Flow Weighted Average (FWA) at subject interface. A mouthpiece could be used in lieu of a cannula but posed challenges as well: (1) created potential disturbances of the flow field; (2) precluded the test subject from speaking during usage; and (3) presented comfort issues limiting the duration of test points. These challenges made it impractical to use a mouthpiece for anything other than short lab ambient environment tests. Technology development and NASA investment have afforded new capabilities to address some of these measurements providing improved data collection and are implemented in the In-suit CO 2 Washout Test System (ICWTS) which provides suit inlet/outlet pressure, temperature, relative humidity, partial pressure of oxygen, partial pressure of CO 2 , and flow measurement coupled with the acquisition of the inspired PPCO 2 including the ability for FWA measurement. This test system, coupled with use of the In-suit Respiration Mannequin Assembly (IRMA) and Computational Fluid Dynamics (CFD) combine to provide a full picture of the in-suit oro-nasal flow field and effectiveness of CO 2 washout in a spacesuit design.

Colin Campbell↗

DOE OSTI2026

Selectivity mechanisms of ion intercalation in Prussian blue analogs

Prussian blue analogs (PBAs) are a family of materials with facile, reversible, and selective ion transport capability for various ions via electrochemical intercalation, owing to their vacancy structure. The large tunable compositional space of PBAs allows for manipulation of intercalation behavior and selectivity by controlling structural vacancy level through choice of transition metal centers and modifications to the synthesis process. However, a lack of understanding of the mechanisms of ion selectivity hinders the material’s design process. Here, for this work, we investigated the origins of ion selectivity using a model PBA, copper hexacyanoferrate, and focused on eight technologically and biologically prominent ions, for which we determined a sequence of selectivity: Rb + > K + > Na + > Ba 2+ > Sr 2+ ≈ Ca 2+ > Mg 2+ > Li + . We provide electrochemical, structural, and redox evidence of strong correlation between the ion identity, the dominant charge-compensating redox, and preferred occupancy site. Specifically, using synchrotron anomalous X-ray diffraction (AXRD), we reveal that monovalent ions exhibit significant association with the corner sites of the unit cell and iron redox, whereas divalent ions display affinity toward the center site with higher ratios of copper redox. Informed by selectivity results, we applied CuHCFe to Li purification and achieved 99.9% purity. Our findings demonstrate an approach to elucidating ion intercalation behavior in order to distinguish and manipulate material properties to optimize separation performance.

Prussian blue analog↗

DOE OSTI2024

CatTestHub: A benchmarking database of experimental heterogeneous catalysis for evaluating advanced materials

The ability to quantitatively compare newly evolving catalytic materials and technologies is hindered by the widespread availability of catalytic data collected in a consistent manner. While certain catalytic chemistries have been widely studied across decades of scientific research, quantitative comparisons based on literature information is hindered by variability in reaction conditions, types of reported data, and reporting procedures. Here, we present CatTestHub, an open-access database dedicated to benchmarking experimental heterogeneous catalysis data. Combining systematically reported catalytic activity data for selected probe chemistries, with relevant material characterization and reactor configuration information, the database provides a collection of catalytic benchmarks for distinct classes of active site functionality. Through key choices in data access, availability, and traceability, CatTestHub seeks to balance the fundamental information needs of chemical catalysis and the FAIR data design principles. Details of the database architecture and the means through which to navigate it are presented, highlighting examples of catalytic insights readily drawn from the available benchmarking data. In its current iteration, CatTestHub spans over 250 unique experimental data points, collected over 24 solid catalysts, that facilitated the turnover of 3 distinct catalytic chemistries. Here, a roadmap is presented through which to expand the open-access platform that serves as a community wide benchmark, primarily through continuous addition of kinetic information on select catalytic systems by members of the heterogeneous catalysis community at large.

Benchmark↗

DOE OSTI2025

Physicochemical and biological characterization of a bispecific antibody in a CrossMab/KIH format that targets EGFR and VEGF-A

Introduction Bispecific antibodies (BsAbs) are a class of antibody therapeutics engineered in various molecular formats to bind two distinct antigens and potentially mediate multiple biological effects. These molecular formats are tailored to mediate specific mechanisms of action and possess unique physicochemical and biological properties that are necessary to assure product quality. In ovarian cancer (OC), both EGFR- and VEGF-A-mediated signaling pathways are often upregulated and cooperate to promote tumor growth and angiogenesis. Thus, inhibiting of EGFR- and VEGF-A pathways with a BsAb may provide synergistic anti-tumor activity. Methods Using publicly available sequences and applying immunoglobulin domain crossover (CrossMab) and knobs-into-holes (KIH) technologies, we generated a BsAb to simultaneously bind EGFR and VEGF-A (designated as anti-EGFR/VEGF-A BsAb). This BsAb served as a model for physiochemical and biological characterization of quality attributes that would be critical for the BsAb’s mechanisms of action. Our goal was to gain fundamental insights into BsAbs designed to target a receptor with one arm and a soluble ligand with the other, to support bioassay development and inform quality control strategies. Results Our data demonstrated that the CrossMab/KIH platform successfully produced a correctly assembled BsAb during cell culture. Characterization confirmed that the anti-EGFR/VEGF-A BsAb bound both EGFR and VEGF-A with comparable activity and affinity to the respective parental monoclonal antibodies. Functionally, the BsAb disrupted both EGF/EGFR and VEGF-A/VEGFR2 signaling pathways in OC and human umbilical vein endothelial cell (HUVEC) models. Furthermore, the BsAb effectively blocked angiogenic signaling driven by VEGF-A secreted from OC cells in a paracrine manner. Discussion Based on the combinatorial mechanism of action and our characterization findings, we concluded that two or more bioassays may be needed to accurately assess the activity of both arms of this type of BsAb.

Immunology↗

DOE OSTI2026

Search for soft unclustered energy patterns produced in association with a W or Z boson in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search for a Higgs boson produced in association with a W or Z boson and decaying via a soft unclustered energy pattern (SUEP) is presented. The analysis is based on proton-proton collision data corresponding to an integrated luminosity of 138 fb −1 collected between 2016 and 2018 at the LHC. Final states with a leptonic W or Z boson decay associated with a high multiplicity of low-momentum charged particles are explored for the first time. The results show no significant excess over the standard model background expectation. Limits are set on the production cross section of a Higgs boson that decays to a SUEP, for a range of parameters of the SUEP model. Material is provided to facilitate further interpretation of the results.

CMS↗