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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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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design of Multicomponent Peptide Fibrils with Ordered and Programmable Compositional Patterns

Advanced applications of biomacromolecular assemblies require a stringent degree of control over molecular arrangement, which is a challenge to current synthetic methods. Here we used a neighbor-controlled patterning strategy to build multicomponent peptide fibrils with an unprecedented capacity to manipulate local composition and peptide positions. Eight peptides were designed to have regulable nearest neighbors upon co-assembly, which, by simulation, afforded 412 different patterns within fibrils, with varied compositions and/or peptide positions. The fibrils with six prescribed patterns were experimentally constructed with high accuracy. The controlled patterning also applies to functionalities appended to the peptides, as exemplified by arranging carbohydrate ligands at nanoscale precision for protein recognition. Importantly, this study offers a route to molecular editing of inner structures of peptide assemblies, prefiguring the uniqueness and richness of patterning-based material design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

Fluid Physics and Macromolecular Crystal Growth in Microgravity

The molecular structure of biological macromolecules is important in understanding how these molecules work and has direct application to rational drug design for new medicines and for the improvement and development of industrial enzymes. In order to obtain the molecular structure, large, well formed, single macromolecule crystals are required. The growth of macromolecule crystals is a difficult task and is often hampered on the ground by fluid flows that result from the interaction of gravity with the crystal growth process. One such effect is the bulk movement of the crystal through the fluid due to sedimentation. A second is buoyancy driven convection close to the crystal surface. On the ground the crystallization process itself induces both of these flows.

Pusey, M.↗
NASA NTRS1991

The solution of radiative transfer problems in molecular bands without the LTE assumption by accelerated lambda iteration methods

An iterative method based on the use of approximate transfer operators, which was designed initially to solve multilevel NLTE line formation problems in stellar atmospheres, is adapted and applied to the solution of the NLTE molecular band radiative transfer in planetary atmospheres. The matrices to be constructed and inverted are much smaller than those used in the traditional Curtis matrix technique, which makes possible the treatment of more realistic problems using relatively small computers. This technique converges much more rapidly than straightforward iteration between the transfer equation and the equations of statistical equilibrium. A test application of this new technique to the solution of NLTE radiative transfer problems for optically thick and thin bands (the 4.3 micron CO2 band in the Venusian atmosphere and the 4.7 and 2.3 micron CO bands in the earth's atmosphere) is described.

Kutepov, A. A.↗
DOE OSTI2021

Nonintuitive Surface Self-Assembly of Functionalized Molecules on Ag(111)

The fabrication of nanomaterials involves selfordering processes of functional molecules on inorganic surfaces. To obtain specific molecular arrangements, a common strategy is to equip molecules with functional groups. However, focusing on the functional groups alone does not provide a comprehensive picture. Especially at interfaces, processes that govern self-ordering are complex and involve various physical and chemical effects, often leading to unexpected structures, as we showcase here on the example of a homologous series of quinones on Ag(111). Naively, one could expect that such quinones, which all bear the same functionalization, form similar motifs. In salient contrast, our joint theoretical and experimental study shows that profoundly different structures are formed. Using a machine-learning-based structure search algorithm, we find that this is due to a shift of the balance of three antagonizing driving forces: adsorbate-substrate interactions governing adsorption sites, adsorbate-adsorbate interactions favoring close packing, and steric hindrance inhibiting certain otherwise energetically beneficial molecular arrangements. The theoretical structures show excellent agreement with our experimental characterizations of the organic/ inorganic interfaces, both for the unit cell sizes and the orientations of the molecules within. The nonintuitive interplay of similarly important interaction mechanisms will continue to be a challenging aspect for the design of functional interfaces. With a detailed examination of all driving forces, we are, however, still able to devise a design principle for self-assembly of functionalized molecules.

structure prediction↗
NASA NTRS2011

Experimental and Modeling Studies of the Combustion Characteristics of Conventional and Alternative Jet Fuels. Final Report

The objectives of this project have been to develop a comprehensive set of fundamental data regarding the combustion behavior of jet fuels and appropriately associated model fuels. Based on the fundamental study results, an auxiliary objective was to identify differentiating characteristics of molecular fuel components that can be used to explain different fuel behavior and that may ultimately be used in the planning and design of optimal fuel-production processes. The fuels studied in this project were Fischer-Tropsch (F-T) fuels and biomass-derived jet fuels that meet certain specifications of currently used jet propulsion applications. Prior to this project, there were no systematic experimental flame data available for such fuels. One of the key goals has been to generate such data, and to use this data in developing and verifying effective kinetic models. The models have then been reduced through automated means to enable multidimensional simulation of the combustion characteristics of such fuels in real combustors. Such reliable kinetic models, validated against fundamental data derived from laminar flames using idealized flow models, are key to the development and design of optimal combustors and fuels. The models provide direct information about the relative contribution of different molecular constituents to the fuel performance and can be used to assess both combustion and emissions characteristics.

Meeks, Ellen↗
DOE OSTI2020

Molecular-Level Behavior of Imidazolium-Based Ionic Liquid Mixtures

Understanding the molecular-level organization of anions and cations in a mixture of different ionic liquids (ILs) is challenging, but it can be very important for designing solvents and IL-based membrane materials. In this work, we perform all-atom molecular dynamics (MD) simulations to understand the intermolecular interactions and structuring of both neat and mixed IL compositions containing 1-benzyl-3-methylimidazolium [ZMIM + ], 1-butyl-3-methylimidazolium [BMIM + ], bistriflimide [Tf 2 N – ], and tetrafluoroborate [BF 4 – ]. We observe very strong underlying molecular-level migrations in these mixtures, and this tends to mainly involve the anion species. As compared to the systems with a single anion, the mixed anions lead to large increases/decreases in the radial distribution function peak heights, whereas the cation mixing is relatively benign. The [BF 4 – ] anions have a strong tendency to displace the [Tf 2 N – ] anions in the mixtures, and this is seen with respect to both [BMIM + ] and [ZMIM + ].

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

A Prototype Tool for Assessing Forward Contamination from Space Suits

Crewed exploration missions dramatically increase the capability for large-scale sample collection and return activities, but they also increase the possibility and likelihood of forward contamination. Systematic research on forward contamination from uncrewed spacecraft has steadily progressed since the Viking missions, but parallel research on contamination from space suits has not. Current space suits have leakage rates as high as 100 cc gas/min., but it is unclear how many or what types of microbes are exiting the suits along with this gas. The Human Forward Contamination Assessment team at NASA's Johnson Space Center (JSC) has developed a prototype swab tool that is capable of maintaining sterility during pressure changes associated with entering and exiting vacuum. The primary objective of recent Extravehicular Activity (EVA) Swab Kit testing is to characterize the type of microorganisms typically found on spacesuit external surfaces under suit differential pressure conditions. Most human-associated microorganisms can fit through a 0.5 to 1.0 μm gap. Understanding potential leak paths will inform future hardware design decisions. Knowing which types of microorganisms may leak from EVA suits provides a basis for subsequent studies to characterize the viability of those organisms under destination conditions, as well as how far they might spread through natural or human-influenced processes. The results of EVA suit molecular microbial community analyses will inform NASA exploration mission operations and hardware design, and help close Strategic Knowledge Gap B5, Forward Contamination to Mars.

Rucker, M.↗
DOE OSTI2022

Population balance models for polymer upcycling: signatures of the mechanism in the molecular weight evolution

Chemical and catalytic upcycling processes could help realize a circular plastics economy, but current models for testing mechanistic hypotheses and designing catalysts remain primitive. This work shows how proposed catalytic mechanisms can be incorporated into population balance models to predict the time evolution of molecular weight distributions. We develop models for homogeneous and heterogeneous catalysts, including catalysts that cut at chain ends and catalysts that cut at random locations. For heterogeneous catalysts, we illustrate the effect of adsorption constants that depend on polymer chain length. Here, we discuss ongoing efforts and challenges in measuring and modeling the time evolving molecular weight distributions in polymer upcycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

A facility for the simulation of low orbit atmospheric oxygen bombardment

A molecular beam facility to simulate the space environment of a spacecraft at low orbit was designed with the intent of studying the effect on the properties of optical elements of oxygen atoms impacting at orbital velocity. The four-stage differentially pumped molecular beam facility includes a variety of oxygen atom beam sources which cover a wide range of velocities (1 km/sec to approximately 8 km/sec), in addition to the ultra-clean experimental environmental of an ultra-high vacuum chamber and an optical diagnostic set-up. The primary oxygen atom beam source used to obtain the 8 km/sec O atoms is an arc heated source. It consists of a modified commercially available plasma torch. The modifications include attachments which provide for a nozzle which is used to expand the atomic beam into the vacuum system, and exhaust channels to dispose of excess torch gas. The torch operates in the 'nontransferred' mode of operation, that is the electric arc is confined within the torch. A plasma is formed in helium by a dc arc. A small amount of O2 is injected downstream from the arc where it is thermally dissociated by the hot He into oxygen atoms. The high temperature and isentropic expansion give the oxygen atoms their velocity. Using seeded beam techniques, oxygen atom beams of approximately 3.5 and approximately 1.5 km/sec, respectively, are obtained.

Arnold, G. S.↗
DOE OSTI2026

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential

A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.

MLIPs↗
DOE OSTI2025

Coarse-grained molecular dynamics simulation of solvent-dependent cellulose nanofiber interactions

Associations between cellulose are important both in biofuel production and in the use of cellulose for biomaterials. Cellulose nanofibers (CNFs) are sustainable, strong, light-weight alternatives to traditional materials in manufacturing, but are challenging to obtain due to irreversible aggregation in solution during preparative fibrillation. Therefore, it is imperative to understand the underlying factors driving aggregation with a view to designing solvents that can effectively compete with interfiber interactions, hence reducing aggregation. Molecular dynamics (MD) simulation at atomic detail can provide useful information on local interactions. However, the length and timescales accessible are too short to fully capture association processes. Here, we provide a method for accessing the longer length and timescales required using coarse-grained (CG) MD simulations with a MARTINI force field to calculate the interaction behavior of CNFs in three selected solvents: NaOH-urea-water, acetone, and neat water. The CG results are consistent with our prior all-atom MD and with previous experimental results. While acetone is found not to be an effective solvent, urea and ionic moieties in NaOH-urea-water not only solvate the fibrils but also improve the confinement of water molecules around them as shown by the solvent residence times and mean-square displacements. Overall, the presence of urea and ions reduces the likelihood of aggregation in multi-CNF systems relative to neat water irrespective of whether the hydrophobic or hydrophilic CNF surfaces are interacting. In conclusion, the CG method shows clear promise for selecting potential high-performance solvents for experimental prioritization in bioenergy and biomaterials research in a relatively fast manner as well as for understanding the aggregation and rheological behavior of CNF-solvent systems.

aggregation↗
NASA NTRS2013

Thermal Control Using Liquid-Metal Bridge Switches

A short term effort (3-months) was undertaken to demonstrate the feasibility of a novel method to locally control the heat transfer rate and demonstrate the potential to achieve a turndown ratio of approximately 10:1. The technology had to be demonstrated to be at a TRL of 2-3, with a plan to advance it to a TRL 5-6. Here, we show that the concept recently developed in our laboratory, namely the pinned-contact, double droplet switch made by overfilling a hole drilled in a suitable substrate can be implemented with a low-melting temperature metal. When toggled near a second substrate, a liquid bridge can be reversibly connected or disconnected, on demand. We have shown experimentally that liquid-metal bridge switches can be made from gallium with a suitable choice of substrate materials, activation strategies, and control techniques. Individual as well as arrays of gallium bridge switches were shown to be feasible and can be robustly controlled. The very short response time of the bridge connection and disconnection (on the order of 1 millisecond) provides for utility in a wide range of applications. The liquid bridge switches may be controlled actively or passively. We have shown through computations and analysis that liquid bridge switches provide locally large turndown ratios (on the order of 103:1), so a relatively sparse packing of them would be needed to obtain the desired turndown ratio of 10:1. For the laboratory demonstrations, pressure activation was utilized. Simple designs for a passive control strategy are presented which are highly attractive for several reasons, including i) large turndown ratio, ii) no solid-moving parts, and iii) stable operation. Finally, we note that passive systems do not require any electronics for their control. This along with the relatively small molecular weight of candidate materials for the system, makes for a robust design outside of Earth?s magnetic field, where spacecraft are subject to significant radiation bombardment.

Hirsa, Amir H.↗
DOE OSTI2022

Comprehensive view of microscopic interactions between DNA-coated colloids

Abstract The self-assembly of DNA-coated colloids into highly-ordered structures offers great promise for advanced optical materials. However, control of disorder, defects, melting, and crystal growth is hindered by the lack of a microscopic understanding of DNA-mediated colloidal interactions. Here we use total internal reflection microscopy to measure in situ the interaction potential between DNA-coated colloids with nanometer resolution and the macroscopic melting behavior. The range and strength of the interaction are measured and linked to key material design parameters, including DNA sequence, polymer length, grafting density, and complementary fraction. We present a first-principles model that screens and combines existing theories into one coherent framework and quantitatively reproduces our experimental data without fitting parameters over a wide range of DNA ligand designs. Our theory identifies a subtle competition between DNA binding and steric repulsion and accurately predicts adhesion and melting at a molecular level. Combining experimental and theoretical results, our work provides a quantitative and predictive approach for guiding material design with DNA-nanotechnology and can be further extended to a diversity of colloidal and biological systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

Contamination design of a Scientific Instrument Protective Enclosure for the Hubble Space Telescope Servicing Mission

A Scientific Instrument Protective Enclosure (SIPE) was designed to accommodate second generation science instruments (SIs) for the Hubble Space Telescope (HST) First Servicing Mission (FSM). One of the main design drivers for the SIPE is to provide a protective environment for the SIs against particulate and molecular contaminants that pose a viable threat to the SI performance. The focus of this paper will detail the methodology incorporated in the design of the SIPE to provide a controlled environment for SI protection at the launch site, during pre-launch/launch activities, and during on-orbit operations in the Shuttle bay.

Hedgeland, Randy J.↗
DOE OSTI2023

Machine Learning Models for Predicting Molecular UV–Vis Spectra with Quantum Mechanical Properties

Accurate understanding of Ultraviolet–visible (UV–Vis) spectra is critical for highthroughput design of compounds for drug discovery. Experimentally determining UV–Vis spectra can become expensive when dealing with a large quantity of novel molecules. This provides us an opportunity to drive computational advances in molecular property predictions using quantum mechanics and machine learning. In this work, we use both Quantum Mechanically (QM) predicted and measured UV–Vis spectra as input to modify four different machine learning architectures: UVvis-SchNet, UVvis- DTNN, UVvis-Transformer, and UVvis-MPNN. Here we find that the UVvis-MPNN model outperforms the other models when using optimized 3D coordinates and QM predicted spectra as input features. This model has the highest performance for predicting UVVisible spectra with a training RMSE of 0.06 and validation RMSE of 0.08.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Theoretical research program to study chemical reactions in AOTV bow shock tubes

The main focus was the development, implementation, and calibration of methods for performing molecular electronic structure calculations to high accuracy. These various methods were then applied to a number of chemical reactions and species of interest to NASA, notably in the area of combustion chemistry. Among the development work undertaken was a collaborative effort to develop a program to efficiently predict molecular structures and vibrational frequencies using energy derivatives. Another major development effort involved the design of new atomic basis sets for use in chemical studies: these sets were considerably more accurate than those previously in use. Much effort was also devoted to calibrating methods for computing accurate molecular wave functions, including the first reliable calibrations for realistic molecules using full CI results. A wide variety of application calculations were undertaken. One area of interest was the spectroscopy and thermochemistry of small molecules, including establishing small molecule binding energies to an accuracy rivaling, or even on occasion surpassing, the experiment. Such binding energies are essential input to modeling chemical reaction processes, such as combustion. Studies of large molecules and processes important in both hydrogen and hydrocarbon combustion chemistry were also carried out. Finally, some effort was devoted to the structure and spectroscopy of small metal clusters, with applications to materials science problems.

Taylor, Peter R.↗
DOE OSTI2024

Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network

Recent advances in machine learning (ML) are expediting materials discovery and design. One significant challenge facing ML for materials is the expansive combinatorial space of potential materials formed by diverse constituents and their flexible configurations. This complexity is particularly evident in molecular mixtures, a frequently explored space for materials, such as battery electrolytes. Owing to the complex structures of molecules and the sequence-independent nature of mixtures, conventional ML methods have difficulties in modeling such systems. Here, we present MolSets, a specialized ML model for molecular mixtures, to overcome the difficulties. Representing individual molecules as graphs and their mixture as a set, MolSets leverages a graph neural network and the deep sets architecture to extract information at the molecular level and aggregate it at the mixture level, thus addressing local complexity while retaining global flexibility. We demonstrate the efficacy of MolSets in predicting the conductivity of lithium battery electrolytes and highlight its benefits in the virtual screening of the combinatorial chemical space. Published by the American Physical Society 2024

Zhang, Hengrui (ORCID:0000000231831654)↗
DOE OSTI2021

Atomistic-Scale Simulations on Graphene Bending Near a Copper Surface

Molecular insights into graphene-catalyst surface interactions can provide useful information for the efficient design of copper current collectors with graphitic anode interfaces. As graphene bending can affect the local electron density, it should reflect its local reactivity as well. Using ReaxFF reactive molecular simulations, we have investigated the possible bending of graphene in vacuum and near copper surfaces. We describe the energy cost for graphene bending and the binding energy with hydrogen and copper with two different ReaxFF parameter sets, demonstrating the relevance of using the more recently developed ReaxFF parameter sets for graphene properties. Moreover, the draping angle at copper step edges obtained from our atomistic simulations is in good agreement with the draping angle determined from experimental measurements, thus validating the ReaxFF results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗