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At least 181 records · Page 10

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NASA NTRS2009

Prediction of Material Properties of Nanostructured Polymer Composites Using Atomistic Simulations

Atomistic models of epoxy polymers were built in order to assess the effect of structure at the nanometer scale on the resulting bulk properties such as elastic modulus and thermal conductivity. Atomistic models of both bulk polymer and carbon nanotube polymer composites were built. For the bulk models, the effect of moisture content and temperature on the resulting elastic constants was calculated. A relatively consistent decrease in modulus was seen with increasing temperature. The dependence of modulus on moisture content was less consistent. This behavior was seen for two different epoxy systems, one containing a difunctional epoxy molecule and the other a tetrafunctional epoxy molecule. Both epoxy structures were crosslinked with diamine curing agents. Multifunctional properties were calculated with the nanocomposite models. Molecular dynamics simulation was used to estimate the interfacial thermal (Kapitza) resistance between the carbon nanotube and the surrounding epoxy matrix. These estimated values were used in a multiscale model in order to predict the thermal conductivity of a nanocomposite as a function of the nanometer scaled molecular structure.

Hinkley, J.A.↗

DOE OSTI2024

Composition-Nanoarchitecture-Performance Analysis of High Energy Density Electrodeposited Silicon for Lithium-Ion Battery Anodes

Electrodeposition of silicon (Si) was previously demonstrated as a promising method for fabricating 3D-structured lithium-ion battery anodes. However, the relationship between the electrochemical performance and chemical composition of the relatively impure electrodeposited silicon is not well understood. Here, we report the electrodeposition of a Si-dominant active material (EDEP-Si) onto 3D-structured nickel (Ni) scaffolds and systematically compare the electrochemical properties, elemental composition, atomistic Si coordination, and molecular structure of EDEP-Si with high-purity amorphous Si grown via static chemical vapor deposition. Despite the considerable amount of carbon (9–11 at %) and oxygen (42–44 at %) present in EDEP-Si, the cycling stability and high reversible specific capacity are remarkably similar to those of CVD-Si on a silicon basis (~2400 mA h/g-Si after 100 cycles). The primary difference is that EDEP-Si exhibits reduced cycling efficiency over the first 10–20 cycles. Reactions between carbon and, more importantly, oxygen in EDEP-Si with lithium are likely responsible for the reduced early cycle performance and lower capacity of the total deposit. Finally, our observations suggest ultrapure Si is not necessary for high electrochemical access to reversible charge storage, although limiting the presence of incorporated impurity species would improve energy density and first cycle efficiency.

25 ENERGY STORAGE↗

NASA NTRS2004

Predicting the Influence of Nano-Scale Material Structure on the In-Plane Buckling of Orthotropic Plates

A multi-scale analysis of the structural stability of a carbon nanotube-polymer composite material is developed. The influence of intrinsic molecular structure, such as nanotube length, volume fraction, orientation and chemical functionalization, is investigated by assessing the relative change in critical, in-plane buckling loads. The analysis method relies on elastic properties predicted using the hierarchical, constitutive equations developed from the equivalent-continuum modeling technique applied to the buckling analysis of an orthotropic plate. The results indicate that for the specific composite materials considered in this study, a composite with randomly orientated carbon nanotubes consistently provides the highest values of critical buckling load and that for low volume fraction composites, the non-functionalized nanotube material provides an increase in critical buckling stability with respect to the functionalized system.

Gates, Thomas S.↗

NASA NTRS2002

Equivalent-Continuum Modeling With Application to Carbon Nanotubes

A method has been proposed for developing structure-property relationships of nano-structured materials. This method serves as a link between computational chemistry and solid mechanics by substituting discrete molecular structures with equivalent-continuum models. It has been shown that this substitution may be accomplished by equating the vibrational potential energy of a nano-structured material with the strain energy of representative truss and continuum models. As important examples with direct application to the development and characterization of single-walled carbon nanotubes and the design of nanotube-based devices, the modeling technique has been applied to determine the effective-continuum geometry and bending rigidity of a graphene sheet. A representative volume element of the chemical structure of graphene has been substituted with equivalent-truss and equivalent continuum models. As a result, an effective thickness of the continuum model has been determined. This effective thickness has been shown to be significantly larger than the interatomic spacing of graphite. The effective thickness has been shown to be significantly larger than the inter-planar spacing of graphite. The effective bending rigidity of the equivalent-continuum model of a graphene sheet was determined by equating the vibrational potential energy of the molecular model of a graphene sheet subjected to cylindrical bending with the strain energy of an equivalent continuum plate subjected to cylindrical bending.

Odegard, Gregory M.↗

DOE OSTI2025

Generalizable, fast, and accurate DeepQSPR with fastprop

Abstract Quantitative Structure–Property Relationship studies (QSPR), often referred to interchangeably as QSAR, seek to establish a mapping between molecular structure and an arbitrary target property. Historically this was done on a target-by-target basis with new descriptors being devised to specifically map to a given target. Today software packages exist that calculate thousands of these descriptors, enabling general modeling typically with classical and machine learning methods. Also present today are learned representation methods in which deep learning models generate a target-specific representation during training. The former requires less training data and offers improved speed and interpretability while the latter offers excellent generality, while the intersection of the two remains under-explored. This paper introduces , a software package and general Deep-QSPR framework that combines a cogent set of molecular descriptors with deep learning to achieve state-of-the-art performance on datasets ranging from tens to tens of thousands of molecules. provides both a user-friendly Command Line Interface and highly interoperable set of Python modules for the training and deployment of feedforward neural networks for property prediction. This approach yields improvements in speed and interpretability over existing methods while statistically equaling or exceeding their performance across most of the tested benchmarks. is designed with Research Software Engineering best practices and is free and open source, hosted at github.com/jacksonburns/fastprop.

Burns, Jackson W. (ORCID:0000000206579426)↗

NASA NTRS1972

Infrared and Raman spectroscopic studies of structural variations in minerals from Apollo 11, 12, 14 and 15 samples, volume 3

Infrared and Raman vibrational spectroscopic data, yielding direct information on molecular structure, were obtained for single grains ( 150 microns) of minerals, basalts, and glasses isolated from Apollo 11, 12, 14, and 15 rock and dust samples, and for grains in Apollo 14 polished butt samples. From the vibrational data, specification substitutions were determined for the predominant silicate minerals of plagioclase, pyroxene, and olivine. Unique spectral variations for grains of K-feldspar, orthopyroxene, pyroxenoid, and ilmenite were observed to exceed the ranges of terrestrial samples, and these variations may be correlatable with formation histories. Alpha-quartz was isolated as pure single grains, in granitic grains composited with sanidine, and in unique grains that were intimately mixed with varying amounts of glass. Accessory minerals of chromite and ulvospinel were isolated as pure grains and structurally characterized from their distinctive infrared spectra. Fundamental vibrations of the SiO4 tetrahedra in silicate minerals were used to classify bulk compositions in dust sieved fractions, basalt grains and glass particles, and to compare modal characteristics for maria, highland and rille samples. No hydrated minerals were found in any of the samples studied, indicating anhydrous formation conditions.

Estep, P. A.↗

DOE OSTI2025

Structural and functional analyses of SARS-CoV-2 Nsp3 and its specific interactions with the 5’ UTR of the viral genome

ABSTRACT Non-structural protein 3 (Nsp3) is the largest open reading frame encoded in the SARS-CoV-2 genome, essential for the formation of double-membrane vesicles (DMV) wherein viral RNA replication occurs. We conducted an extensive structure-function analysis of Nsp3 and determined the crystal structures of the ubiquitin-like 1 (Ubl1), nucleic acid binding (NAB), β-coronavirus-specific marker (βSM) domains, and a sub-region of the Y domain of this protein. We show that the Ubl1, ADP-ribose phosphatase (ADRP), human SARS Unique (HSUD), NAB, and Y domains of Nsp3 bind the 5’ UTR of the viral genome and that the Ubl1 and Y domains possess affinity for recognition of this region, suggesting high specificity. The Ubl1-Nucleocapsid (N) protein complex binds the 5’ UTR with greater affinity than the individual proteins alone. Our results suggest that multiple domains of Nsp3, particularly Ubl1 and Y, shepherd the 5’ UTR of the viral genome during translocation through the DMV membrane, priming the Ubl1 domain to load the genome onto N protein. IMPORTANCE The largest protein encoded by the SARS-CoV-2 genome is Nsp3. In infected cells, this multi-domain protein forms a pore structure in the virus-induced double-membrane vesicles (DMV). We have incomplete data on Nsp3 molecular structure, and here, we describe crystal structures for multiple domains of Nsp3. It is thought that newly replicated viral RNA transits through the DMV pore; however, we possess incomplete data on which regions of Nsp3 actually interact with RNA. Here, we present data showing that five domains of Nsp3 interact with the 5’ UTR of the SARS-CoV-2 RNA, including the Y domain for which no function has ever been discovered. These data suggest that the pore structure plays an active role in recognizing the terminal end of the genome, transiting and loading the viral RNA onto the cytoplasmic nucleocapsid protein. These data help expand our knowledge of Nsp3 structure and function and the SARS-CoV-2 replication cycle.

Microbiology↗

NASA NTRS1994

Phenylethynyl-Terminated Polyimides

Phenylethynyl-terminated polyimides exhibit properties suitable for films, moldings, adhesives, and composite-material matrices. Polyimides synthesized at various molecular weights, selected to obtain desirable properties for specific applications. Thermally cured to form cross-linked molecular structures typically increasing resistance to solvents, glass-transition temperatures, and moduli of elasticity. Also have low molecular weights and low melt viscosities for easier processing into composites and adhesive bonds.

Jensen, Brian J.↗

NASA NTRS2001

Equivalent-Continuum Modeling of Nano-Structured Materials

A method has been developed for modeling structure-property relationships of nano-structured materials. This method serves as a link between computational chemistry and solid mechanics by substituting discrete molecular structures with an equivalent-continuum model. It has been shown that this substitution may be accomplished by equating the vibrational potential energy of a nano-structured material with the strain energy of representative truss and continuum models. As an important example with direct application to the development and characterization of single-walled carbon nanotubes, the model has been applied to determine the effective continuum geometry of a graphene sheet. A representative volume element of the equivalent-continuum model has been developed with an effective thickness. This effective thickness has been shown to be similar to, but slightly smaller than, the interatomic spacing of graphite.

Odegard, Gregory M.↗

NASA NTRS2003

Photonic Interrogation and Control of Nano Processes

My research activities for the summer of 2003 consisted of two projects: One project was concerned with determining a method for predicting the static and dynamic assembly properties of nano-structures using laser tweezers. The other project was to investigate the generation of Laguerre-Gaussian modes using a spatial light modulator incorporated into an optical tweezers system. Concerning the first project, I initially pursued the approach suggested by my NASA colleague Dr. Art Decker. This approach involved mimicking the model of the structure of atomic nucleus for the assembly of 1 to 100 atoms using allowed quadruple transitions induced by orbital angular momentums of a Laguerre- Gaussian (Doughnut) laser mode. After realizing the inaptness of the nuclear model with the nanostructure model as far as the binding forces and transitions were concerned, I focused on using quantum dot modei. This model was not attuned also for the host lattice influences the electronic structure of the quantum dot. Thus one other option that I decided to pursue was the approach of molecular quantum mechanics. In this approach the nanostructure is treated as a large (10-100 nm) molecule constructed from single element or multi-elements. Subsequent to consultation with Dr. Fred Morales, a chemical engineer at NASA GRC, and Dr. David Ball, a computational chemist at Cleveland State University, I acquired a molecular-quantum computation software, Hyperchem 7.0. This software allows simulation of different molecular structures as far as their static and dynamic behaviors are concerned. The time that I spent on this project was about eight weeks. Once this suitable approach was identified, I realized the need to collaborate with a computational quantum chemist to pursue searching for stable nanostructures in the range of 10-100 nm that we can be assembled using laser tweezers. The second project was about generating laser tweezers that possess orbital angular momentum. As shown, we were able to generate laser tweezers modes of different orbital angular momentum using a spatial light modulator incorporated into a laser tweezers system. The motivation for investigating these types of modes stems from being able to spin particles at high speeds and also to orient two particles in separate traps and then join them together. Also, there has been recent intense interest on fundamental physics research on orbital angular momentum of light. The fact that circularly polarized light may have associated with it angular momentum that relates to the spin of individual photons (spin 0 for the plane polarized light, spin +1 for the right-circularly polarized light and spin -1 for the left-circularly polarized light) was first demonstrated by Beth in 1936. Orbital angular momentum is, however, distinct from spin in that the spin angular momentum of light is intrinsically linked to the behavior of the electric field in the light whereas orbital angular momentum is a consequence of inclined wavefronts. In 1992 L. Allen, et al showed that the Laguerre-Gaussian (LG) modes could possess well-defined orbital angular momentum that can exceed 1 planck's constant, i.e. l plancks constant per photon, where l is the azimuthal index of the mode.

Jassemnejad, Baha↗

DOE OSTI2024

Small‐Molecule Mixed Ionic‐Electronic Conductors for Efficient N‐Type Electrochemical Transistors: Structure‐Function Correlations

Abstract The fundamental challenge in electron‐transporting organic mixed ionic‐electronic conductors (OMIECs) is simultaneous optimization of electron and ion transport. Beginning from Y6‐type/U‐shaped non‐fullerene solar cell acceptors, we systematically synthesize and characterize molecular structures that address the aforementioned challenge, progressively introducing increasing numbers of oligoethyleneglycol (OEG; g) sidechains from 1 g to 3 g, affording OMIECs 1gY, 2gY, and 3gY, respectively. The crystal structure of 1gY preserves key structural features of the Y n series: a U‐shaped/planar core, close π–π molecular stacking, and interlocked acceptor groups. Versus inactive Y6 and Y11, all of the new glycolated compounds exhibit mixed ion‐electron transport in both conventional organic electrochemical transistor (cOECT) and vertical OECT (vOECT) architectures. Notably, 3gY with the highest OEG density achieves a high transconductance of 16.5 mS, an on/off current ratio of ~10 6 , and a turn‐on/off response time of 94.7/5.7 ms in vOECTs. Systematic optoelectronic, electrochemical, architectural, and crystallographic analysis explains the superior 3gY‐based OECT performance in terms of denser n gY OEG content, increased crystallite dimensions with decreased long‐range crystalline order, and enhanced film hydrophilicity which facilitates ion transport and efficient redox processes. Finally, we demonstrate an efficient small‐molecule‐based complementary inverter using 3gY vOECTs, showcasing the bioelectronic applicability of these new small‐molecule OMIECs.

Cho, Yongjoon↗

DOE OSTI2024

Small‐Molecule Mixed Ionic‐Electronic Conductors for Efficient N‐Type Electrochemical Transistors: Structure‐Function Correlations

Cho, Yongjoon↗

DOE OSTI2025

Impact of Halogen Groups on the Properties of PEA–Based 2D Pb–Sn Halide Perovskites

Tuning broad emission in 2D Pb–Sn halide perovskites (HPs) is essential for advancing optoelectronic applications, particularly for color-tunable and white-light-emitting devices. This broad emission is linked to structural factors, such as defects and phase segregation of the Pb component within the Pb–Sn system, which are strongly influenced by the molecular structure and chemical properties of spacer cations. Atomic tuning of the spacers via halogenation opens up a new way to fine-tune the molecular properties, enabling further augmentations of HP functionalities. Nevertheless, the distinct broad emission's sensitivity to spacer chemistry remains underexplored. Here, halogenation's influence is systematically investigated on 2D HP emission characteristics using a high-throughput workflow. These findings reveal that the F-containing phenethylammonium (4F-PEA) spacer narrows the broadband PL, whereas Cl broadens it. Through a correlative study, it is found that 4F-PEA reduces not only the local phase segregation but also the defect levels and microstrains in 2D HPs. This is likely attributed to the manifestation of less lattice distortion via stronger surface coordination of the dipole-augmented 4F-PEA. Furthermore, these results highlight halogenation as a key factor in modulating phase segregation and defect density in 2D Pb–Sn HPs, offering a promising pathway to tune the emission for enhanced optoelectronic performance.

2D Pb-Sn halide perovskites↗

DOE OSTI2025

Paired Neural Network for Matching Experimental and Predicted Infrared Spectra

Here, we present a novel machine learning (ML)-based scoring technique for determining the similarity between experimental and predicted infrared (IR) spectra for identification purposes. IR spectroscopy is a powerful technique used to identify the molecular structure and composition of a sample by measuring the unique vibrational frequency pattern of the molecule’s functional groups. Molecular identifications are often made by comparing experimental and reference spectra. However, the limited number of reference spectra available in spectral libraries can confound the identification process. Alternative identification procedures rely on in silico techniques to simulate spectra for a wide range of molecules. However, scoring spectral similarity between an experimental query and computationally predicted reference remains a significant challenge. Our proposed ML-based scoring technique overcomes these barriers by accurately and efficiently determining spectral similarity.

Neural Network↗

DOE OSTI2025

Advancing molecular machine learning representations with stereoelectronics-infused molecular graphs

Molecular representation is a critical element in our understanding of the physical world and the foundation for modern molecular machine learning. Previous molecular machine learning models have used strings, fingerprints, global features and simple molecular graphs that are inherently information-sparse representations. However, as the complexity of prediction tasks increases, the molecular representation needs to encode higher fidelity information. This work introduces a new approach to infusing quantum-chemical-rich information into molecular graphs via stereoelectronic effects, enhancing expressivity and interpretability. Learning to predict the stereoelectronics-infused representation with a tailored double graph neural network workflow enables its application to any downstream molecular machine learning task without expensive quantum-chemical calculations. We show that the explicit addition of stereoelectronic information substantially improves the performance of message-passing two-dimensional machine learning models for molecular property prediction. We show that the learned representations trained on small molecules can accurately extrapolate to much larger molecular structures, yielding chemical insight into orbital interactions for previously intractable systems, such as entire proteins, opening new avenues of molecular design. Finally, we have developed a web application (simg.cheme.cmu.edu) where users can rapidly explore stereoelectronic information for their own molecular systems.

Boiko, Daniil A↗

DOE OSTI2025

Synthesis, structure, and stability of a novel 2 H -azirine under pressure

We have synthesized 2,3-diphenyl-2H-azirine, a strained unsaturated heterocyclic compound, and examined its high-pressure behavior to above 10 GPa using diamond anvil cell techniques. Single crystal X-ray diffraction at ambient conditions reveals that the crystal structure is hexagonal and consists of interesting helices surrounding voids in the structure. A continuous shift of the Raman and infrared vibrational spectra with increasing pressure is observed, indicating that the molecular structure is preserved to at least 8 GPa at room temperature. High-pressure synchrotron powder X-ray diffraction shows that the hexagonal structure persists, with a smooth compression of the a and c parameters to 10 GPa. The structural stability under pressure is attributed to the reduction in void size within the helical framework despite the inherent strain and reactivity of the molecule. The channels in the structure could encapsulate small molecules for gas or energy storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1994

High temperature arc-track resistant aerospace insulation

The topics are presented in viewgraph form and include the following: high temperature aerospace insulation; Foster-Miller approach to develop a 300 C rated, arc-track resistant aerospace insulation; advantages and disadvantages of key structural features; summary goals and achievements of the phase 1 program; performance goals for selected materials; materials under evaluation; molecular structures of candidate polymers; candidate polymer properties; film properties; and a detailed program plan.

Dorogy, William↗

NASA NTRS2004

Macromolecular Crystallization in Microgravity

The key concepts that attracted crystal growers, macromolecular or solid state, to microgravity research is that density difference fluid flows and sedimentation of the growing crystals are greatly reduced. Thus, defects and flaws in the crystals can be reduced, even eliminated, and crystal volume can be increased. Macromolecular crystallography differs from the field of crystalline semiconductors. For the latter, crystals are harnessed for their electrical behaviors. A crystal of a biological macromolecule is used instead for diffraction experiments (X-ray or neutron) to determine the three-dimensional structure of the macromolecule. The better the internal order of the crystal of a biological macromolecule then the more molecular structure detail that can be extracted. This structural information that enables an understanding of how the molecule functions. This knowledge is changing the biological and chemical sciences with major potential in understanding disease pathologies. Macromolecular structural crystallography in general is a remarkable field where physics, biology, chemistry, and mathematics meet to enable insight to the basic fundamentals of life. In this review, we examine the use of microgravity as an environment to grow macromolecular crystals. We describe the crystallization procedures used on the ground, how the resulting crystals are studied and the knowledge obtained from those crystals. We address the features desired in an ordered crystal and the techniques used to evaluate those features in detail. We then introduce the microgravity environment, the techniques to access that environment, and the theory and evidence behind the use of microgravity for crystallization experiments. We describe how ground-based laboratory techniques have been adapted to microgravity flights and look at some of the methods used to analyze the resulting data. Several case studies illustrate the physical crystal quality improvements and the macromolecular structural advances. Finally, limitations and alternatives to microgravity and future directions for this research are covered.

Snell, Edward H.↗