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NASA NTRS1995

A review of nickel hydrogen battery technology

This paper on nickel hydrogen batteries is an overview of the various nickel hydrogen battery design options, technical accomplishments, validation test results and trends. There is more than one nickel hydrogen battery design, each having its advantage for specific applications. The major battery designs are individual pressure vessel (IPV), common pressure vessel (CPV), bipolar and low pressure metal hydride. State-of-the-art (SOA) nickel hydrogen batteries are replacing nickel cadmium batteries in almost all geosynchronous orbit (GEO) applications requiring power above 1 kW. However, for the more severe low earth orbit (LEO) applications (greater than 30,000 cycles), the current cycle life of 4000 to 10,000 cycles at 60 percent DOD should be improved. A NASA Lewis Research Center innovative advanced design IPV nickel hydrogen cell led to a breakthrough in cycle life enabling LEO applications at deep depths of discharge (DOD). A trend for some future satellites is to increase the power level to greater than 6 kW. Another trend is to decrease the power to less than 1 kW for small low cost satellites. Hence, the challenge is to reduce battery mass, volume and cost. A key is to develop a light weight nickel electrode and alternate battery designs. A common pressure vessel (CPV) nickel hydrogen battery is emerging as a viable alternative to the IPV design. It has the advantage of reduced mass, volume and manufacturing costs. A 10 Ah CPV battery has successfully provided power on the relatively short lived Clementine Spacecraft. A bipolar nickel hydrogen battery design has been demonstrated (15,000 LEO cycles, 40 percent DOD). The advantage is also a significant reduction in volume, a modest reduction in mass, and like most bipolar designs, features a high pulse power capability. A low pressure aerospace nickel metal hydride battery cell has been developed and is on the market. It is a prismatic design which has the advantage of a significant reduction in volume and a reduction in manufacturing cost.

Smithrick, John J.↗

DOE OSTI2026

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗

DOE OSTI2026

Full-core high-burnup BWR LOCA fuel performance analysis and FFRD susceptibility

The susceptibility of the boiling water reactor (BWR) Limerick Unit 1 to fuel fragmentation, relocation, and dispersal during a postulated large-break loss-of-coolant accident (LBLOCA) was calculated using a multiphysics framework. The simulations include full-core, rod-resolved neutronic, thermal hydraulic, and fuel performance models using the VERA, TRACE, and BISON codes. This work focused on the transient BISON simulations, which include both the normal operation and LBLOCA periods in the same simulations. Cladding integrity was assessed using two correlations that are included with BISON. make page break Several new BWR-specific features were recently added to BISON. This work represents the first time these features have been included in a core-scale set of simulations. This study hence evaluates the performance of these new models for an operating reactor with realistic operating conditions. Simulation results showed that cladding integrity was maintained (i.e., no rods burst). Finally, future work to improve BWR and PWR predictions using this framework is suggested.

BISON↗

DOE OSTI2026

Impacts of Multidimensional Progenitor Perturbations on Core-collapse Supernova Explosions

Numerical studies of core-collapse supernovae have demonstrated the importance of nonradial motions in precollapse progenitors on the explosion outcome. We use the Chimera neutrino radiation hydrodynamics code running seven two-dimensional simulations of 15 M⊙ progenitors with different progenitor structures introduced by different one- and two-dimensional precollapse stellar evolution environments to examine the impacts of stellar structure and nonspherical motion in the precollapse progenitor on the development of explosions. We compare the explosion evolution of these models in terms of shock dynamics, diagnostic energy, neutrino heating, accretion, explosion geometry, nuclear abundances, and turbulent convection. We also analyze how stochastic variation impacts our simulations. Contrary to results reported in prior studies examining the impacts of multidimensional progenitors, we observe similar shock revival times and explosion development in our simulations despite differences in initial compositions and structures. We find no discernible impact from the accretion of nonradial perturbations from a multi-D progenitor onto the stalled shock in the revival and strength of explosion, as fully developed neutrino-driven convection behind the stalled shock is similar for all our models. For models with physically sourced noise in the iron core, a strong oscillation of the shock occurs after bounce and deflects infall laterally, and accelerates the saturation of the lateral turbulent kinetic energy. An examination of model stochasticity shows that any prior expected impacts on explosive outcome due to convection-related perturbations lie below the detectable threshold of numerical variation.

Chen, Chien-Hui [North Carolina State University]↗

DOE OSTI2026

A Tutorial on Bayesian analysis of linear shock compression data

Gas gun and other shock compression experiments often produce shock wave velocity measurements that are linearly associated with particle velocity. Traditionally, this empirical relationship is quantified with a single Hugoniot curve that is estimated using least squares regression. However, for downstream modeling and simulation tasks, it is often more useful to have multiple Hugoniot curves in the pressure–volume plane that are consistent with the data. We employ Bayesian uncertainty quantification methods as a framework for propagating measurement uncertainty through to model parameters and predictions. Specifically, this Tutorial shows how to sample multiple Hugoniot curves in the pressure–volume plane that are consistent with the shock wave-particle velocity measurements in a two-step Bayesian approach. First, we obtain an analytical expression for the posterior distribution of the linear model parameters using Bayesian linear regression. Second, we propagate samples from the posterior distribution through the Rankine–Hugoniot equations to yield Hugoniot curves in the pressure–volume plane. The procedure is demonstrated with publicly available data on argon, copper, and nickel, and compared against bootstrapping and linear regression. The Bayesian procedure is shown to be interpretable, computationally inexpensive, and less sensitive than an alternative bootstrapping approach to the removal of the point in the copper dataset that has the largest particle velocity. As a Tutorial on Bayesian methodology for the shock compression community, we provide several derivations and explanations that make this paper self-contained, and make all code and data available at github.com/llnl/BALSCD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

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↗

NASA NTRS2026

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↗

NASA NTRS1993

Enhanced Decoding for the Galileo S-Band Mission

A coding system under consideration for the Galileo S-band low-gain antenna mission is a concatenated system using a variable redundancy Reed-Solomon outer code and a (14,1/4) convolutional inner code. The 8-bit Reed-Solomon symbols are interleaved to depth 8, and the eight 255-symbol codewords in each interleaved block have redundancies 64, 20, 20, 20, 64, 20, 20, and 20, respectively (or equivalently, the codewords have 191, 235, 235, 235, 191, 235, 235, and 235 8-bit information symbols, respectively). This concatenated code is to be decoded by an enhanced decoder that utilizes a maximum likelihood (Viterbi) convolutional decoder; a Reed Solomon decoder capable of processing erasures; an algorithm for declaring erasures in undecoded codewords based on known erroneous symbols in neighboring decodable words; a second Viterbi decoding operation (redecoding) constrained to follow only paths consistent with the known symbols from previously decodable Reed-Solomon codewords; and a second Reed-Solomon decoding operation using the output from the Viterbi redecoder and additional erasure declarations to the extent possible. It is estimated that this code and decoder can achieve a decoded bit error rate of 1 x 10 -7 at a concatenated code signal-to-noise ratio of 0.76 dB. By comparison, a threshold of 1.17 dB is required for a baseline coding system consisting of the same (14,1/4) convolutional code, a (255,223) Reed-Solomon code with constant redundancy 32 also interleaved to depth 8, a one-pass Viterbi decoder, and a Reed Solomon decoder incapable of declaring or utilizing erasures. The relative gain of the enhanced system is thus 0.41 dB. It is predicted from analysis based on an assumption of infinite interleaving that the coding gain could be further improved by approximately 0.2 dB if four stages of Viterbi decoding and four levels of Reed-Solomon redundancy are permitted. Confirmation of this effect and specification of the optimum four-level redundancy profile for depth-8 interleaving is currently being done.

S Dolinar↗

DOE OSTI2026

Asymmetric pathways for lithium extraction and recovery based on the two-phase equilibrium of layered oxides

Electrochemical intercalation offers a promising platform for Li + extraction. However, only limited types of electrode materials have been investigated. The challenge to broaden and tailor materials for electrochemical intercalation-based Li + extraction lies in the lack of understanding of material’s response upon co-intercalation of multiple ions, therefore, paired process design to enable reversible Li + extraction and recovery. Here, we showcase the design of asymmetric ion pathways for Li + extraction and recovery for host material with complex Li + and Na + interaction using layered cobalt oxide as a model material. The two-phase equilibrium of Na 0.48 CoO 2 and Li 0.94 CoO 2 governs Li + selectivity when a high depth of intercalation is achieved (low vacancy level). We show that the relative rate between ion exchange and intercalation is critical to determine the ion pathways. The relationship can be quantitatively compared using the average pseudo ion exchange rate (C pseudoIX ) and the intercalation rate (C inter ). The ion pathways at the three regimes with C pseudoIX > C inter , C pseudoIX ~ C inter , and C pseudoIX < C inter are constructed. By selecting the optimized ion pathway and particle size, we demonstrate 9.7×10 4 Li + selectivity with 99% purity Li + recovery from an initial 1:1000 Li: Na molar ratio solution using 115 mAh/g specific capacity.

electrochemistry↗

NASA NTRSDate not supplied

Technology Readiness Assessment for Stirling Power Convertor

Stirling-based power conversion system could represent a critical enabling technology for future NASA missions, offering significantly enhanced power efficiency over traditional thermoelectric systems. To ensure the successful infusion of this technology into deep space and planetary surface missions, a rigorous evaluation of its maturity and associated risks is essential. The objective of this Technology Readiness Assessment (TRA) is to determine the current technology readiness level (TRL) of the Stirling power convertor and identify key technical risks and challenges associated with its maturation and potential infusion into a targeted flight system. The evaluation process will rigorously follow the NASA TRA procedure: (1) determining the requirements that underpin the design, function, and performance; (2) finding and listing all new technology elements (NTEs) and critical technology elements (CTEs); (3) identifying the level of integration assumed for the assessment; and (4) assessing the TRL for each NTE and CTE. The overall subassembly TRL will then be determined via a roll-up using the “weakest link” criterion, culminating in a final (5) assessment of risks to further progression of maturity. This paper will present the results of a comprehensive technology readiness assessment (TRA) conducted on the Stirling-based dynamic power conversion subassembly, excluding the radioisotope heat source. The paper will also describe a detailed breakdown of the TRL roll-up and a matrix of identified risks and recommended mitigation paths, along with identified key technical risks and challenges to achieve the required long-duration performance. Key Words: Radioisotope Power Conversion, Technology Readiness Assessment

Radioisotope Power Conversion↗

DOE OSTI2023

High Sulfur Loading and Capacity Retention in Bilayer Garnet Sulfurized‐Polyacrylonitrile/Lithium‐Metal Batteries with Gel Polymer Electrolytes

The cubic‐garnet (Li 7 La 3 Zr 2 O 12 , LLZO) lithium–sulfur battery shows great promise in the pursuit of achieving high energy densities. The sulfur used in the cathodes is abundant, inexpensive, and possesses high specific capacity. In addition, LLZO displays excellent chemical stability with Li metal; however, the instabilities in the sulfur cathode/LLZO interface can lead to performance degradation that limits the development of these batteries. Therefore, it is critical to resolve these interfacial challenges to achieve stable cycling. Here, an innovative gel polymer buffer layer to stabilize the sulfur cathode/LLZO interface is created. Employing a thin bilayer LLZO (dense/porous) architecture as a solid electrolyte and significantly high sulfur loading of 5.2 mg cm −2 , stable cycling is achieved with a high initial discharge capacity of 1542 mAh g −1 (discharge current density of 0.87 mA cm −2 ) and an average discharge capacity of 1218 mAh g −1 (discharge current density of 1.74 mA cm −2 ) with 80% capacity retention over 265 cycles, at room temperature (22 °C) and without applied pressure. Achieving such stability with high sulfur loading is a major step in the development of potentially commercial garnet lithium–sulfur batteries.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Database↗

NASA NTRS2014

Analytical Model for Steady Flow through a Finite Channel with One Porous Wall with Arbitrary Variable Suction or Injection

This paper presents an exact solution of two-dimensional laminar flow through a finite length channel with one porous wall. It improves upon previous solutions by (1) satisfying the no-slip boundary condition at the channel dead end, (2) adding a turbulent term to the porous wall boundary condition, (3) allowing for arbitrary variable suction or injection across the porous wall, and (4) model validation against new cryogenic liquid hydrogen and oxygen experimental data. Of particular interest in the current work is the modeling of cryogenic propellant flow through a porous liquid acquisition device (LAD) screen and channel inside a propellant tank. First, a detailed review of the literature is presented for previously attempted solutions to channel flow with one porous wall. Next, the governing equations, boundary conditions, and model assumptions are used to derive the analytical flow solution and present general model results for pressure and velocity fields within the channel. Then, the model solution is compared with horizontal LAD channel flow data in liquid oxygen as well as vertical LAD channel flow data in an inverted outflow configuration in liquid hydrogen. Model results are used to update the static cryogenic bubble point pressure model with a dynamic bubble point term which factors in enhanced convection and cooling at the screen during propellant outflow. Convective heat transfer at the LAD screen during outflow is also quantified by comparing model and data. The new analytical flow solution with the dynamic bubble point model is shown to compare well with available cryogenic experimental data

Navier Stokes Equations↗

DOE OSTI2026

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗

DOE OSTI2026

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗

NASA NTRS1960

Ranger Spacecraft

The thermal-control philosophy of the spacecraft currently under development by the Jet Propulsion Laboratory is design by passive means to maintain all components within the tolerances specified by cognizant engineers. Due to the complexity of the configurations, calculations are) of necessity, fairly generalized and final design is based upon tests in an environmental chamber. The Ranger series spacecraft is designed with a basic structure which is common to all models, with additional hardware to suit the individual mission. This basic structure of Rangers A-1 and A-2 is seen as the hexagonal instrument section, the erectable solar panels, the movable antenna, and the omniantenna. The Ranger A-1 and A-2 configuration is for engineering tests and space-exploration, with the scientific instrumentation isolation requirement dictating the spread-out design. The spacecraft stands 12 feet high, weighs 700 to 800 pounds, and has an internal power of 150 watts. Rangers A-3, A-4, and A-5 are designed to rough land a capsule on the moon. For these, a capsule and retrorocket replace the scientific instruments, occupying the space inside the tower structure. The spacecraft must survive many environments. Chronologically they are: 1) Folded configuration inside an aerodynamic shroud on the pad. 2) Thermal flux from shroud aerodynamically heated during boost phase. 3) Coasting up to 30 minutes attached to Agena stage after booster and shroud are separated. 4) Agena stage burning. 5) Coasting and tumbling after separation from Agena until it passes from earth's shadow. 6) Upon reaching sunlight, panels open and begin sun acquisition. 7) Antenna seeks earth after spacecraft locks onto sun. 8) Space phase- "steady state" with vehicle's vertical axis locked on sun, communicating with earth. The philosophy is to design for the sun-acquired mode, making allowances for the transient conditions.

T. O. Thostesen↗

DOE OSTI2024

Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗