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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
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. Buoyancy driven convection results from density differences between the bulk solution and fluid close to the crystal surface which has been depleted of macromolecules due to crystal growth. Schlieren photograph of a growing lysozyme crystal illustrating a 'growth plume' resulting from buoyancy driven convection. Both sedimentation and buoyancy driven convection have a negative effect on crystal growth and microgravity is seen as a way to both greatly reduce sedimentation and provide greater stability for 'depletion zones' around growing crystals. Some current crystal growth hardware however such as those based on a vapor diffusion techniques, may also be introducing unwanted Marangoni convection which becomes more pronounced in microgravity. Negative effects of g-jitter on crystal growth have also been observed. To study the magnitude of fluid flows around growing crystals we have attached a number of different fluorescent probes to lysozyme molecules. At low concentrations, less than 40% of the total protein, the probes do not appear to effect the crystal growth process. By using these probes we expect to determine not only the effect of induced flows due to crystal growth hardware design but also hope to optimize crystallization hardware so that destructive flows are minimized both on the ground and in microgravity.

Pusey, M.↗
DOE OSTI2025

Quantum chemically calculated Abraham parameters for quantifying and predicting polymer hydrophobicity

The leakage and accumulation of plastic in the environment is a significant and growing problem with numerous detrimental impacts and has led to a push toward the design and development of more environmentally benign materials. To this end, we have developed a quantum chemistry-based model for predicting the mobility of polymer materials from molecular structure. Hydrophobicity is used as a surrogate for mobility given that hydrophobic interactions drive much of the partitioning of contaminants in and out of various environmentally relevant compartments. To model polymer hydrophobicity, we adjusted a previously developed Quantum Chemically Calculated Abraham Parameter model to calculate Abraham parameters of small molecules from molecular structure information. The resulting model predicted the octanol-water partition coefficient (K OW ) of polymer repeating units with a root mean square error (RMSE) of 0.48 (log scale). Additionally, the hydrophobicity of high molecular weight polymer materials was captured through solubility parameters and Nile red staining experiments from the literature and predicted with RMSEs of 1.21 (J/cc) 0.5 and 3.42 nm, respectively. Finally, to test the environmental applicability of the model, the relative adsorption capacity of three polymers was predicted and used to unify sorption isotherms across multiple sorbates and polymer sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

PySIDT: Subgraph Isomorphic Decision Trees for Molecular Property Prediction

Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.

Johnson, Matthew Sean [Sandia National Laboratorie↗
NASA NTRS1984

Large-scale structure of molecular gas in Heiles Cloud 2 - A remarkable rotating ring

The J = 1 - 0 transition of (C-13)O over a 3 sq deg region in Heiles Cloud 2 has been mapped using the Five College Radio Astronomy Observatory 14 m telescope. The complete map contains 3600 individual spectra of which 2400 were sampled with 1 arcmin spacing. The map suggests that the structure of Heiles Cloud 2 is dominated by a quasi-equilibrium rotating ring similar to those found in numerical calculations of the gravitational collapse of a rotating cloud. Within this ring, several dense condensations have been identified and partially mapped in C(O-18). These subcondensations, among which is the dense filament TMC-1, probably result from the instability of the ring to fragmentation and have masses on the order of the jeans mass. Thus, they are marginally unstable to further collapse and may be the precursors of fragments that will eventually form stars.

Schloerb, F. P.↗
NASA NTRS1990

The effect of thermal damage on the mechanical properties of polymer regrinds

Reprocessed polymers are subjected to high processing temperatures that result in the breakdown of molecular chains and changes in the molecular structures. These phenomena are reflected in the mechanical properties of materials. Practically every regrind is seen as a new material. These experiments deal with the molding, regrinding, and reprocessing of test specimens for the study of their mechanical properties. The comparative test data from each recycled material would give students an insight of the molecular structures and property degradation. Three important rheological and mechanical properties such as melt flow, impact strength, and flexural strength are to be determined. These properties play key roles in the selection of engineering materials. The material selected for demonstration was Makrolon 3000L, a polycarbonate thermoplastic from Bayer AG. The thermal degradation due to repeated processing is reflected in the decrease in molecular weight and breakdown of molecular chains causing increase in melt flow. The Izod-impact resistance and the flexural strength deteriorate gradually.

Kundu, Nikhil K.↗
NASA NTRS2017

Ionic Polyimides: New High Performance Polymers for Additive Manufacturing

There is currently a very limited set of engineering polymers that have been demonstrated as viable for use in 3-D printing. Additive manufacturing of custom components will require a much larger array of polymers, especially those with physical, thermal, chemical, and mechanical properties that can be tailor-made. The development of ‘Ionic Polyimides’ offers a solution to this shortage by combining the well understood and widely accepted properties of conventional polyimides, with a new approach to polymer synthesis. Polyimides and polymeric ionic liquids (poly(ILs)) are at the forefront of advanced polymer materials, each with their own set of advantages and disadvantages. While it is clear that more types of polymer materials are needed for fused deposition modeling (FDM) additive manufacturing, there is a need to explore these classes of materials. The synthesis process developed by the Bara Research Group at the University of Alabama allows full control over polymer structure, nanostructure, thermal, electrical, and physical properties making them a prime candidate for use in the additive manufacturing process. Furthermore, the new process allows us to tailor-make a high strength polymer that can be used to fabricate filament feedstock instead of pellets for 3D printing. The primary objective of this proposal is to determine the relationship between molecular structure, physical properties, and performance of ionic polyimides. Further, we seek to determine their utility as materials suitable for additive manufacturing of components used in aerospace vehicles, with an emphasis on characterizing and simulating their thermal behaviors and properties. This proposal addresses the need for fundamental research on a customizable polymer filament feedstock for 3-D printing with tailor-made properties potentially making it superior to the commercial blends offered in industry today. The deliverables for this project are the creation of a database that will detail the relationships between the molecular structure and physical properties for the ionic polyimide of interest (e.g. Tg/Tm (Glass Transition Temperature divided by Melting Point)) relative to different ionic polyimide structures). This new database will provide a “road map” to the development of the first generation of materials and ultimately proof-of-concept.

Jackson, Enrique↗
NASA NTRS2001

Constitutive Modeling of Nanotube-Reinforced Polymer Composite Systems

In this study, a technique has been proposed for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT). Since the polymer molecules are on the same size scale as the nanotubes, the interaction at the polymer/nanotube interface is highly dependent on the local molecular structure and bonding. At these small length scales, the lattice structures of the nanotube and polymer chains cannot be considered continuous, and the bulk mechanical properties of the SWNT/polymer composites can no longer be determined through traditional micromechanical approaches that are formulated using continuum mechanics. It is proposed herein that the nanotube, the local polymer near the nanotube, and the nanotube/polymer interface can be modeled as an effective continuum fiber using an equivalent-continuum modeling method. The effective fiber retains the local molecular structure and bonding information and serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composites with various nanotube sizes and orientations. As an example, the proposed approach is used for the constitutive modeling of two SWNT/polyethylene composite systems, one with continuous and aligned SWNT and the other with discontinuous and randomly aligned nanotubes.

Odegard, Gregory M.↗
NASA NTRS2004

Constitutive Modeling of Nanotube-Reinforced Polymer Composite Systems

In this study, a technique has been proposed for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT). Since the polymer molecules are on the same size scale as the nanotubes, the interaction at the polymer/nanotube interface is highly dependent on the local molecular structure and bonding. At these small length scales, the lattice structures of the nanotube and polymer chains cannot be considered continuous, and the bulk mechanical properties of the SWNT/polymer composites can no longer be determined through traditional micromechanical approaches that are formulated using continuum mechanics. It is proposed herein that the nanotube, the local polymer near the nanotube, and the nanotube/polymer interface can be modeled as an effective continuum fiber using an equivalent-continuum modeling method. The effective fiber retains the local molecular structure and bonding information and serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composites with various nanotube sizes and orientations. As an example, the proposed approach is used for the constitutive modeling of two SWNT/polyethylene composite systems, one with continuous and aligned SWNT and the other with discontinuous and randomly aligned nanotubes.

Odegard, Gregory M.↗
DOE OSTI2026

On the Prospect of Chemically Transferable Coarse-Grained Electronic Models for Soft Materials

Electronic coarse-graining (ECG) methods predict quantum-mechanical electronic properties directly from coarse-grained (CG) molecular configurations, enabling electronic predictions at mesoscale length scales. Here, we present a diagnostic assessment of the feasibility of chemically transferable ECG models across a broad polymer-relevant chemical space using all-atom, united-atom, and Martini-scale representations. While high-resolution ECG models achieve near-quantitative accuracy, we show that chemically transferable ECG at the Martini resolution fails because the CG force field does not sample the same configurational distribution of local molecular structure as that underlying the DFT-parameterized ECG model. We demonstrate that our proposed Element-Count-Label (ECL) representation, which augments Martini beads with explicit stoichiometric data, significantly improves chemical generalization across diverse polymer chemistries. However, we find that even with improved chemical resolution, the model cannot recover electronic property distributions that are absent from the configurational space sampled by the CG force field. These results demonstrate that chemically transferable ECG requires future Martini-like force fields to explicitly preserve quantum chemistry–compatible local molecular structure in addition to thermodynamic and structural fidelity.

Kidder, Katherine M [Department of Chemistry; Univ↗
NASA NTRS2003

Giant Molecular Cloud Structure and Evolution

Bodenheimer and Burkert extended earlier calculations of cloud core models to study collapse and fragmentation. The initial condition for an SPH collapse calculation is the density distribution of a Bonnor-Ebert sphere, with near balance between turbulent plus thermal energy and gravitational energy. The main parameter is the turbulent Mach number. For each Mach number several runs are made, each with a different random realization of the initial turbulent velocity field. The turbulence decays on a dynamical time scale, leading the cloud into collapse. The collapse proceeds isothermally until the density has increased to about 10(exp 13) g cm(exp -3). Then heating is included in the dense regions. The nature of the fragmentation is investigated. About 15 different runs have been performed with Mach numbers ranging from 0.3 to 3.5 (the typical value observed in molecular cloud cores is 0.7). The results show a definite trend of increasing multiplicity with increasing Mach number (M), with the number of fragments approximately proportional to (1 + M). In general, this result agrees with that of Fisher, Klein, and McKee who published three cases with an AMR grid code. However our results show that there is a large spread about this curve. For example, for M=0.3 one case resulted in no fragmentation while a second produced three fragments. Thus it is not only the value of M but also the details of the superposition of the various velocity modes that play a critical role in the formation of binaries. Also, the simulations produce a wide range of separations (10-1000 AU) for the multiple systems, in rough agreement with observations. These results are discussed in two conference proceedings.

Hollenbach, David↗
DOE OSTI2024

Determining the Crosslinking and Degradation Reaction Kinetics in Photovoltaic Encapsulants Using Accelerated Aging: Preprint

Degradation of photovoltaic (PV) module encapsulant mechanical characteristics that lead to embrittlement and delamination remains a cause of failure in solar installations. A multiscale reliability model based on detailed molecular degradation reaction kinetics was previously published, connecting the encapsulant mechanical properties (elastic modulus, yield strength, and adhesion energy) to the degraded molecular structure and interfacial bond density to adjacent solar cell and glass substrates. The model, developed primarily for poly(ethylene-co-vinyl acetate) (EVA) encapsulants, remains to be experimentally validated. Determining the degradation and crosslinking kinetics of alternative encapsulants, such as polyolefin elastomer (POE) and EVA/POE/EVA composites (EPE), can further generalize the model. Importantly, the activation energy for crosslinking of fully cured PV encapsulant products from temperature or UV is presently unknown or unavailable. In this work, we subject EVA, POE, and EPE encapsulants to a set of accelerated aging conditions, varying the temperature, UV intensity, and relative humidity. We use DSC, FTIR, and Soxhlet extraction (gel content) to characterize the encapsulants' changing molecular structure. This allows for determination of the photochemical degradation and crosslinking kinetics of the encapsulants. Preliminary results show an increase in gel content (crosslinking) and a decrease in crystallinity of EVA, POE, and EPE encapsulants under hot-aerobic (90 deg C, 22% RH) and hot-anaerobic (90oC, sealed in N2 air) accelerated aging, even in the absence of UV and crosslinking initiating agents. For a least squares regression with an assumed first-order crosslinking kinetics, the crosslinking rate parameters were computed for the three encapsulants under hot-aerobic and hot-anaerobic aging conditions. FTIR analysis showed insignificant encapsulant degradation for hot-aerobic and hot-anaerobic aging, demonstrating the critical role of UV and moisture in accelerating degradation. Aging conditions with UV exposure and elevated humidity are presently in progress.

adhesion↗
NASA NTRS2012

Radiation Shielding Materials Containing Hydrogen, Boron, and Nitrogen: Systematic Computational and Experimental Study

The key objectives of this study are to investigate, both computationally and experimentally, which forms, compositions, and layerings of hydrogen, boron, and nitrogen containing materials will offer the greatest shielding in the most structurally robust combination against galactic cosmic radiation (GCR), secondary neutrons, and solar energetic particles (SEP). The objectives and expected significance of this research are to develop a space radiation shielding materials system that has high efficacy for shielding radiation and that also has high strength for load bearing primary structures. Such a materials system does not yet exist. The boron nitride nanotube (BNNT) can theoretically be processed into structural BNNT and used for load bearing structures. Furthermore, the BNNT can be incorporated into high hydrogen polymers and the combination used as matrix reinforcement for structural composites. BNNT's molecular structure is attractive for hydrogen storage and hydrogenation. There are two methods or techniques for introducing hydrogen into BNNT: (1) hydrogen storage in BNNT, and (2) hydrogenation of BNNT (hydrogenated BNNT). In the hydrogen storage method, nanotubes are favored to store hydrogen over particles and sheets because they have much larger surface areas and higher hydrogen binding energy. The carbon nanotube (CNT) and BNNT have been studied as potentially outstanding hydrogen storage materials since 1997. Our study of hydrogen storage in BNNT - as a function of temperature, pressure, and hydrogen gas concentration - will be performed with a hydrogen storage chamber equipped with a hydrogen generator. The second method of introducing hydrogen into BNNT is hydrogenation of BNNT, where hydrogen is covalently bonded onto boron, nitrogen, or both. Hydrogenation of BN and BNNT has been studied theoretically. Hyper-hydrogenated BNNT has been theoretically predicted with hydrogen coverage up to 100% of the individual atoms. This is a higher hydrogen content than possible with hydrogen storage; however, a systematic experimental hydrogenation study has not been reported. A combination of the two approaches may be explored to provide yet higher hydrogen content. The hydrogen containing BNNT produced in our study will be characterized for hydrogen content and thermal stability in simulated space service environments. These new materials systems will be tested for their radiation shielding effectiveness against high energy protons and high energy heavy ions at the HIMAC facility in Japan, or a comparable facility. These high energy particles simulate exposure to SEP and GCR environments. They will also be tested in the LaRC Neutron Exposure Laboratory for their neutron shielding effectiveness, an attribute that determines their capability to shield against the secondary neutrons found inside structures and on lunar and planetary surfaces. The potential significance is to produce a radiation protection enabling technology for future exploration missions. Crew on deep space human exploration missions greater than approximately 90 days cannot remain below current crew Permissible Exposure Limits without shielding and/or biological countermeasures. The intent of this research is to bring the Agency closer to extending space missions beyond the 90-day limit, with 1 year as a long-term goal. We are advocating a systems solution with a structural materials component. Our intent is to develop the best materials system for that materials component. In this Phase I study, we have shown, computationally, that hydrogen containing BNNT is effective for shielding against GCR, SEP, and neutrons over a wide range of energies. This is why we are focusing on hydrogen containing BNNT as an innovative advanced concept. In our future work, we plan to demonstrate, experimentally, that hydrogen, boron, and nitrogen based materials can provide mechanically strong, thermally stable, structural materials with effective radiation shielding against GCR, SEP, and neutrons.

Radiation↗
DOE OSTI2024

Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties

The chemical properties of oils are vital in the design of microemulsion systems. The hydrophilic–lipophilic difference equation used to predict microemulsions’ phase behavior expresses the oils’ physiochemical properties as the equivalent alkane carbon number (EACN). The experimental determination of EACN requires knowledge of the temperature dependence of the microemulsion system and the effects of different surfactant concentrations. Thus, the experimental determination is time-intensive and tedious, requiring days to months for proper separations. Furthermore, the experiments require high purity of chemicals because microemulsions are sensitive to impurities. Our work focuses on the quick and reliable predictions of the EACN with machine learning (ML) models. Due to the immaturity of ML chemical predictions, we compare three graph neural networks (GNNs) and a gradient-boosted tree algorithm, known as XGBoost. The GNNs use the molecular structures represented as simplified molecular-input line-entry system (SMILES) codes for the initial input, which allows us to assess whether geometry optimization is necessary for reliable results. The XGBoost model also begins with the SMILES representations of the molecules but uses molecular descriptors instead of geometry optimizations. As a result, the best model tested (crystal graph convolutional neural network with Merck molecular force field-94) has an error of 1.15 EACN units of the true EACN for unknown data with the errors skewed toward zero and an R² score of 0.9

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

Multiscale Analysis of Delamination of Carbon Fiber-Epoxy Laminates with Carbon Nanotubes

A multi-scale analysis is presented to parametrically describe the Mode I delamination of a carbon fiber/epoxy laminate. In the midplane of the laminate, carbon nanotubes are included for the purposes of selectively enhancing the fracture toughness of the laminate. To analyze carbon fiber epoxy carbon nanotube laminate, the multi-scale methodology presented here links a series of parameterizations taken at various length scales ranging from the atomistic through the micromechanical to the structural level. At the atomistic scale molecular dynamics simulations are performed in conjunction with an equivalent continuum approach to develop constitutive properties for representative volume elements of the molecular structure of components of the laminate. The molecular-level constitutive results are then used in the Mori-Tanaka micromechanics to develop bulk properties for the epoxy-carbon nanotube matrix system. In order to demonstrate a possible application of this multi-scale methodology, a double cantilever beam specimen is modeled. An existing analysis is employed which uses discrete springs to model the fiber bridging affect during delamination propagation. In the absence of empirical data or a damage mechanics model describing the effect of CNTs on fracture toughness, several tractions laws are postulated, linking CNT volume fraction to fiber bridging in a DCB specimen. Results from this demonstration are presented in terms of DCB specimen load-displacement responses.

Riddick, Jaret C.↗