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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

The Hawaii Imaging Fabry-Perot Interferometer (HIFI)

At Mauna Kea Observatory, researchers conducted optical, imaging spectrophotometric studies of selected active galaxies using both the Canada-France-Hawaii 3.6m and University of Hawaii 2.2m telecopes (Tully, Bland and Cecil 1988). To maximize spatial resolution, researchers select galaxies independent of luminosity but known to possess interesting morphologies or high-velocity, extranuclear ionized gas (Walker 1968; Rubin and Ford 1968). They study both the large-scale patterns produced in IR-luminous, starburst systems (e.g., M82, NGC 253, NGC 6240) and those with compact, but spatially extended, circumnuclear, narrow line regions (e.g., M51, NGC 1068, NGC 4151). Current studies are restricted to the optical (SII), (NII) and (OIII) lines and the brightest Balmer recombination lines. These lines are, in principle, sufficient to constrain the dynamical structure and dominant excitation mechanism of the ionized component.

Bland, Jonathan↗
DOE OSTI2024

Moduli axions, stabilizing moduli, and the large field swampland conjecture in heterotic M-theory

We compute the F- and D-term potential energy for the dilaton, complex structure, and Kähler moduli of realistic vacua of heterotic M-theory compactified on Calabi-Yau threefolds where, for simplicity, we choose ℎ 1,1 = ℎ 2,1 = 1. However, the formalism is immediately applicable to the “universal” moduli of Calabi-Yau threefolds with ℎ 1,1 = ℎ 1,2 > 1 as well. The F-term potential is computed using the nonperturbative complex structure, gaugino condensate and “world sheet instanton” superpotentials in theories in which the hidden sector contains an anomalous U⁡(1) structure group. The Green-Schwarz anomaly cancellation induces inhomogeneous “axion” transformations for the imaginary components of the dilaton and Kähler modulus—which then produce a D-term potential. V D is a function of the real components of the dilaton and Kähler modulus (s and t) that is minimized and precisely vanishes along a unique line in the s–t plane. Excitations transverse to this line have a mass m anom which is an explicit function of t. The F-term potential energy is then evaluated along the V D = 0 line. For values of t small enough that m anom ≳ M U —where M U is the compactification scale—we plot V F for a realistic choice of coefficients as a function of the Pfaffian parameter p. We find values of p for which V F has a global minimum at negative or zero vacuum density or a metastable minimum with positive vacuum density. In all three cases, the s, t, and associated “axion” moduli are completely stabilized. Finally, we show that, for any of these vacua, the large t behavior of the potential energy satisfies the “large scalar field” Swampland conjecture.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Complex orders and chirality in the classical Kitaev-Γ model

It is well recognized that the low-energy physics of many Kitaev materials is governed by two dominant energy scales, the Ising-type Kitaev coupling 𝐾 and the symmetric off-diagonal Γ coupling. An understanding of the interplay between these two scales is therefore the natural starting point toward a quantitative description that includes subdominant perturbations that are inevitably present in real materials. This study focuses on the classical 𝐾−Γ model on the honeycomb lattice, with a specific emphasis on the region 𝐾< 0 and Γ > 0 , which is the most relevant for the available materials and which remains enigmatic in both quantum and classical limits, despite much effort. We employ large-scale Monte Carlo simulations on specially designed finite-size clusters and unravel the presence of a complex multisublattice magnetic order in a wide region of the phase diagram, whose structure is characterized in detail. We show that this order can be quantified in terms of a coarse-grained scalar-chirality order, featuring a counterrotating modulation on the two spin sublattices. Here, we also provide a comparison to previous studies and discuss the impact of quantum fluctuations on the phase diagram.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Hydrogen Based Energy Storage System for Integration with Dispatchable Power Generator (Phase I Feasibility Study)

This project examined the feasibility of integrating hydrogen generation, storage, and use as a means to decarbonize campus activities while retaining the ability to utilize the existing natural gas fired combined heat and power system installed at the campus of the University of California @ Irvine. Analysis of specific potential sites for the integrated system identified a location adjacent to the existing central plant which resulted in minimization of interconnections. A strategy based on use of commercial electrolyzers and gas storage was identified. Primary technology advancements are required for the gas turbine to accommodate higher levels of hydrogen and the integrated controls. The project indicated challenges for adopting the proposed strategy with the present rates and constraints. The availability of a relatively low-cost biogas resource by the campus already decarbonizes the gas turbine to some extent. In the absence of this resource, procurement of electricity directly from large scale renewable operations could facilitate lower electricity costs. Additional solar resources on campus could also help in this regard. The gas turbine cannot be operated below 50% capacity due to air permit constraints. Using the otherwise curtailed gas turbine operation to generate hydrogen via electrolysis by consuming natural gas is not highly efficient and therefore leads to relatively high costs of electricity returned. Several scenarios demonstrate potential for effective decarbonization, yet most involve lower and lower capacity factor for the legacy gas turbine which is not a good use of the asset. A small gas turbine output with higher efficiency operation would help. As would ability to export electricity to the grid. Certainly current rate structures and operational scenarios are less attractive than other possible future structures which should be pushed for in the future.

03 NATURAL GAS↗
DOE OSTI2020

10 MWE CDCL Large Pilot Plant – pre-FEED Study

Coal Direct Chemical Looping (CDCL) is an advanced oxy-combustion technology that has the potential to substantially reduce the energy penalty and the cost of electricity (COE) for coal-fired power generation with CO₂ capture. The Babcock & Wilcox Company (B&W) and The Ohio State University (OSU) have been collaborating on the development of an iron oxide oxygen-carrier based chemical looping technology for clean power generation with inherent carbon capture. In this process, coal is dried and pulverized prior to being transported into a moving-bed reducer. In the reducer, coal reacts with the oxygen-carrier particles, forming combustion byproducts, predominantly CO₂ and H₂O, while reducing the iron oxide oxidation state from Fe₂O₃ to a mixture of FeO and Fe. The reduced state particles are then transported to a combustor reactor and re-oxidized with air. Following the oxidation, the oxygen-carrier particles are regenerated, and a large amount of heat is released for steam production. The produced steam is sent to a turbine for electricity generation. Meanwhile, the CO₂–rich stream leaving the reducer is cooled, cleaned, and compressed for subsequent pipeline transportation and sequestration. By combining air separation and fuel conversion into a single system, the CDCL technology enables the intensification of oxy-combustion processes by eliminating the energy and cost intensive cryogenic air separation unit and thereby results in higher overall plant efficiencies and lower COE’s. The use of a moving-bed reducer results in high conversions of volatile hydrocarbons and high CO₂ purity, which reduces the cost of downstream CO₂ purification for sequestration or utilization. The Babcock & Wilcox Company in collaboration with The Ohio State University, Johnson & Matthey, The Electric Power Research Institute, and Dover Light & Power completed a Preliminary Front-End Engineering and Design (Pre-FEED) study of a 10 MWe coal-direct chemical looping (CDCL) pilot plant. The planned system is a modular 10 MWe CDCL large pilot facility consisting in 4 modules of 2.5 MWe each, working in parallel and to be hosted within the current structure at the City of Dover’s Municipal Power Plant. The CDCL system can achieve auto-thermal operation and includes a sub-critical steam cycle for power generation. The pilot system was designed to demonstrate full commercial operation at a reduced scale. The coal distribution per plan area is a representative slice of larger commercial arrangements. The system includes a CO₂ recycle system, but it does not include a compression system. The large pilot includes all the environmental control equipment and oxygen carrier and ash handling systems. As part of the project, the Team performed laboratory testing and carried out multiple pilot test campaigns to obtain design and performance information at the 250 kWth CDCL pilot facility at the Babcock & Wilcox Company’s Research Center. The Team demonstrated sustained operations at designed coal inputs, high coal conversion, high CO₂ purity, heat generation on the combustor, low carbon carryover between reactors and low particle attrition. Emissions generated in the reducer reactor were identified as SO₂ and NO x . The commercial manufacturing cost of oxygen carrier particle was evaluated by JM. A particle manufacturing report was generated and submitted to the DOE. Based on the results from the pilot tests and the pre-FEED design efforts, a techno-economic analysis was performed. The study shows that the CDCL process is a promising carbon-friendly technology capable of producing electricity with high efficiency. The estimated COE of the supercritical CDCL plant is $83.3 / MWh, which meets DOE’s target of less than 30% increase in COE when compared to a supercritical PC plant without CO₂ capture. This is the lowest among the existing carbon capture technologies (post-combustion and oxy-combustion) for fossil fuel power plant. CDCL is evaluated to be the most promising technology for carbon capture from the economic aspect.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1991

The evolution of void-filled cosmological structures

1D, 2D, and 3D simulations are used here to investigate the salient features in the evolution of void-filled cosmological structures in universes with arbitrary values of Omega. It is found that the growth of a void as a function of time decreases significantly at the time corresponding to Omega = 0.5. In models constructed in 2D and 3D, suitable initial conditions lead to cellular structure with faceted voids similar to those observed in redshift surveys. Matter compressed to planes flows more rapidly toward condensations at the intersections than would be expected for spherical infall. The peculiar streaming velocities for void diameters of 5000 km/s should be observable. The simulations provide a more physical basis and dynamics for the bubbly and Voronois tesselation models used to derive statistical properties of cellular large-scale structure.

Regos, Eniko↗
DOE OSTI2026

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

2D materials↗
DOE OSTI2022

Ratchet, swivel, tilt and roll: a complete description of subunit rotation in the ribosome

Protein synthesis by the ribosome requires large-scale rearrangements of the ‘small’ subunit (SSU; ~1 MDa), including inter- and intra-subunit rotational motions. However, with nearly 2000 structures of ribosomes and ribosomal subunits now publicly available, it is exceedingly difficult to design experiments based on analysis of all known rotation states. To overcome this, we developed an approach where the orientation of each SSU head and body is described in terms of three angular coordinates (rotation, tilt and tilt direction) and a single translation. By considering the entire RCSB PDB database, we describe 1208 fully-assembled ribosome complexes and 334 isolated small subunits, which span >50 species. This reveals aspects of subunit rearrangements that are universal, and others that are organism/domain-specific. For example, we show that tilt-like rearrangements of the SSU body (i.e. ‘rolling’) are pervasive in both prokaryotic and eukaryotic (cytosolic and mitochondrial) ribosomes. As another example, domain orientations associated with frameshifting in bacteria are similar to those found in eukaryotic ribosomes. Together, this study establishes a common foundation with which structural, simulation, single-molecule and biochemical efforts can more precisely interrogate the dynamics of this prototypical molecular machine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Probing the 𝑗 dependence of angular distributions and 𝑁=20 shell rigidity via the 36 S (𝑝,𝑑) 35 S reaction

An investigation of the N=20 36 S nucleus has been performed through a detailed study of the 3 6S (p,d)3 5S neutron-removal reaction, employing a 66-MeV proton beam at iThemba Laboratory for Accelerator Based Sciences and an innovative target design. Using the high-resolution K = 600 magnetic spectrometer, 98 states in 3 5S were identified up to 16-MeV excitation energy, including 47 previously unobserved states. Angular distributions and spectroscopic factors, including isobaric analog-state contributions, were extracted for 81 levels. A pronounced j dependence in the angular distributions of ℓ=2 states provides refined insights into the spin-orbit splitting. Finite-range adiabatic distorted-wave approximation calculations qualitatively reproduce the observed j dependence. Comparisons of the measured 1d 5/2 spectroscopic strength distribution with large-scale shell-model and ab initio calculations show good agreement overall, and the robustness of the N=20 shell closure in 36 S is confirmed when comparing the relatively low fp orbital occupancies in 40 Ca and 3 6S across the Fermi surface. This study underscores the utility of neutron-removal reactions in probing nuclear structure and the Fermi surface of sd nuclei and beyond. The findings advance our understanding of shell evolution and offer constraining data for theoretical models.

20 ≤ A ≤ 38↗
DOE OSTI2025

Electronic structure theory with molecular point group symmetries on quantum annealers

Quantum computation has the potential to revolutionize quantum chemistry through major speedups in computation times and an exponential reduction in computational resources. Here, we combine the symmetry-adapted Jordan–Wigner encoding based on the full Boolean symmetry group $\mathbb{Z}$$^{k}_{2}$ with our new implementation of the Xia–Bian–Kais (XBK) method for improving the efficiency of electronic structure theory calculations on quantum annealers, particularly by reducing the number of qubits needed to achieve the same accuracy. By providing a more extensive symmetry-adapted encoding (SAE) than previous work, we are able to simulate molecules larger than those previously reported that have been studied using methods developed for quantum annealers and without using an active space. We calculated the potential energy surfaces of H 2 , LiH, He 2 , H 2 O, O 2 , N 2 , Li 2 , F 2 , CO, BH 3 , NH 3 , and CH 4 , with the largest molecule in the STO-6G basis set requiring 16 qubits with our SAE, and compared them with full configuration interaction results. The application of SAE to the XBK method provides an exponential reduction in the size of the Hilbert space and scales well with the size of the problem. It does not introduce significant additional errors for even or large values of a key variational parameter that determines the number of ancilla qubits used in the XBK method’s Hamiltonian embedding, or for certain molecules such as He 2 and H 2 O. Here, we provide an explanation for this behavior and a recommendation on the usage of our method. In addition, we briefly discuss the potential of extracting electronic excited states from our method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

`SkyPy`: A package for modelling the Universe

SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides functions that sample realisations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models using a YAML-based configuration syntax, while task scheduling and data dependencies are handled internally and the modular design allows users to interface with external software. SkyPy is developed and maintained by a diverse community of domain experts with a focus on software sustainability and interoperability. By fostering development, it provides a framework for correlated simulations of a range of cosmological probes including galaxy populations, large scale structure, the cosmic microwave background, supernovae and gravitational waves. Version 0.4 implements functions that model various properties of galaxies including luminosity functions, redshift distributions and optical photometry from spectral energy distribution templates. Future releases will provide additional modules, for example, to simulate populations of dark matter halos and model the galaxy-halo connection, making use of existing software packages from the astrophysics community where appropriate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Scalable slot-die coating of phyllosilicate membranes for selective ion separations

Abstract Two-dimensional (2D) materials have recently drawn attention as candidate materials for molecular-scale membrane separations due to their tunable nanoscale interlayer properties. Phyllosilicates, a broad class of naturally abundant 2D clay minerals, offer significant advantages over synthetic 2D materials, including low cost, stability, and environmental compatibility. While these properties make phyllosilicates attractive for industrial-scale nanofiltration applications, phyllosilicate-based membranes have, to date, only been fabricated at the lab scale via vacuum filtration. Scalable fabrication methods are essential to advance the technical maturity of phyllosilicate membranes and bring these promising materials closer to large-scale adoption. Herein, we have successfully scaled up phyllosilicate (vermiculite) membrane fabrication via slot-die coating and roll-to-roll coating of an ethylenediamine–vermiculite (EDAVM) mixture onto nylon. The coated membranes are 1–2 μm $ \unicode{x03BC} \mathrm{m} $ mu m in thickness and exhibit similar structure and performance to vacuum-filtered EDAVM membranes. The membranes also show selectivity for monovalent ions over multivalent ions in binary salt mixtures. This work represents a major step toward scaling up phyllosilicate membranes for industrial ion separation applications such as resource recovery from water.

Booth, Austin [Princeton University]↗
DOE OSTI2026

The SPT-3G+ Experiment on the South Pole Telescope

Observations of the cosmic microwave background (CMB) offer an unparalleled opportunity to advance our understanding of fundamental physics. SPT-3G+ is an upgraded receiver for the arcminute-resolution South Pole Telescope (SPT) that plans to deploy in late 2028. SPT-3G+ will increase the CMB mapping speed of SPT by nearly an order of magnitude over the currently installed SPT-3G receiver. SPT-3G+ will have ~24,000 transition-edge sensor (TES) bolometers in two frequency bands with center frequencies at 95 GHz and 150 GHz that will be read out with microwave multiplexing. SPT-3G+ will measure the CMB lensing spectrum and galaxy clusters to constrain the growth of structure, dark matter, and dark energy. SPT-3G+ will also reach critical thresholds on inflationary constraints by combining data with BICEP/Keck, forming the South Pole Observatory (SPO). BICEP/Keck has deep degree-angular scale measurements but is currently delensing-limited, while SPT-3G+ will provide deep lensing measurements. Forecasts show that SPO will reach an uncertainty on the tensor-to-scalar ratio $r$ of $\sigma(r) \sim 1.2\times 10^{-3}$ by 2034. A detection at these levels would provide evidence of inflation and probe new physics at grand unified theory energy scales, while no detection would exclude large classes of models and shift the scientific paradigm describing the early universe. I will give an overview of SPT-3G+ including its design and current status.

Simon, Sara M. [Fermilab] (ORCID:0009000006683584)↗
DOE OSTI2025

Extremely Scalable Distributed Computation of Contour Trees via Pre-Simplification

Contour trees offer an abstract representation of the level set topology in scalar fields and are widely used in topological data analysis and visualization. However, applying contour trees to large-scale scientific datasets remains challenging due to scalability limitations. Recent developments in distributed hierarchical contour trees have addressed these challenges by enabling scalable computation across distributed systems. Building on these structures, advanced analytical tasks—such as volumetric branch decomposition and contour extraction—have been introduced to facilitate large-scale scientific analysis. Despite these advancements, such analytical tasks substantially increase memory usage, which hampers scalability. In this paper, we propose a pre-simplification strategy to significantly reduce the memory overhead associated with analytical tasks on distributed hierarchical contour trees. We demonstrate enhanced scalability through strong scaling experiments, constructing the largest known contour tree—comprising over half a trillion nodes with complex topology—in under 15 minutes on a dataset containing 550 billion elements.

Li, Mingzhe [University of Utah]↗
DOE OSTI2023

Improving Mathematical Exposition of an Industrial-Scale Linear Program

Industrial-scale models require considerable setup time; hence, once built, they are used in myriad ways to consider closely related cases. In practice, the code for these models frequently evolves without appropriate notational choices, largely as a result of the lengthy development time of, and the number of individuals contributing to, their formulation. This leads to inefficiencies and obfuscates model structures that might be leveraged to expedite solutions. In this paper, we advocate for an emerging literature on model formulation “best practices” and present the reformulation of a widely used industrial-scale linear program. The efficient mathematical expression of this linear program, used to plan capacity expansion in the energy sector, allows for greater transparency of model structures and enhanced ability to identify computational performance improvements, as well as a lucid interpretation of its solutions. This type of formulation is employed in several mathematical programming courses at our university as an example of the advantages of best practices; the model more broadly is used widely to inform policy in the U.S. energy sector.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

NASA Tech Briefs, January 2012

Contents of this issue are: (1) Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments (2) Handheld Universal Diagnostic Sensor (3) Large-Area Vacuum Ultraviolet Sensors (4) Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures (5) Health-Enabled Smart Sensor Fusion Technology (6) Extended-Range Passive RFID and Sensor Tags (7) Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks (8) Self-Healing, Inflatable, Rigidizable Shelter (9) Improvements in Cold-Plate Fabrication (10) Technique for Radiometer and Antenna Array Calibration - TRAAC (11) Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment (12) Programmable Digital Controller (13) Use of CCSDS Packets Over SpaceWire to Control Hardware (14) Key Decision Record Creation and Approval Module (15) Enhanced Graphics for Extended Scale Range (16) Debris Examination Using Ballistic and Radar Integrated Software (17) Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) (18) Integration Manager (19) Eclipse-Free-Time Assessment Tool for IRIS (20) Automated and Manual Rocket Crater Measurement Software (21) MATLAB Stability and Control Toolbox Trim and Static Stability Module (22) Patched Conic Trajectory Code (23) Ring Image Analyzer (24) SureTrak Probability of Impact Display (25) Implementation of a Non-Metallic Barrier in an Electric Motor (26) Multi-Mission Radioisotope Thermoelectric Generator Heat Exchangers for the Mars Science Laboratory Rover (27) Uniform Dust Distributor for Testing Radiative Emittance of Dust-Coated Surfaces (28) MicroProbe Small Unmanned Aerial System (29) Highly Stable and Active Catalyst for Sabatier Reactions (30) Better Proton-Conducting Polymers for Fuel-Cell Membranes (31) CCD Camera Lens Interface for Real-Time Theodolite Alignment (32) Peregrine 100-km Sounding Rocket Project (33) SOFIA Closed- and Open-Door Aerodynamic Analyses (34) Sonic Thermometer for High-Altitude Balloons (35) Near-Infrared Photon-Counting Camera for High-Sensitivity Observations (36) Integrated Optics Achromatic Nuller for Stellar Interferometry (37) High-Speed Digital Interferometry (38) Ultra-Miniature Lidar Scanner for Launch Range Data Collection (39) Shape and Color Features for Object Recognition Search (40) Explanation Capabilities for Behavior-Based Robot Control (41) A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks (42) Quality Control Method for a Micro-Nano-Channel Microfabricated Device (43) Corner-Cube Retroreflector Instrument for Advanced Lunar Laser Ranging (44) Electrospray Collection of Lunar Dust (45) Fabrication of a Kilopixel Array of Superconducting Microcalorimeters with Microstripline Wiring Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators (46) Coherent Detector for Near-Angle Scattering and Polarization Characterization of Telescope Mirror Coatings

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