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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Variational Autoencoder Model Toward Molecular Structure Representation Learning of Fuels

Here, in this work, a Variational Autoencoder (VAE)-based data-driven modeling framework is developed with the overarching goal of enabling fuel design. The VAE model is trained on a large dataset with several chemical species to learn a compressed latent space molecular representation. Chemical structure in the form of Simplified Molecular Input Line Entry System (SMILES) string is fed as input, encoded into the VAE latent space, and decoded back to the SMILES string using Long Short-Term Memory (LSTM) networks. Complexities of the VAE training loss function are thoroughly examined by varying the weightage (beta (𝜷) parameter) of the latent space regularization term, thereby assessing the balance between reconstruction accuracy and validity, and focusing on both accurate molecular structure reconstruction and latent space consistency. Two different strategies for 𝜷 variation are evaluated: linear annealing and cyclic annealing. In addition, the impact of total correlation adjustment and hierarchical priors is also studied with regard to the balance between reconstruction fidelity and latent space regularization, and potential issues such as posterior collapse, over-regularization, and poor disentanglement of latent variables. Overall, the best performance of the model is achieved with hierarchical priors and incrementally increasing 𝜷 from 0 to a threshold value of 0.25 over 75 epochs. The generative VAE model can be readily coupled with Quantitative Structure–Property Relationship (QSPR) analysis to develop an integrated end-to-end framework for fuel-property prediction and molecular design of novel promising fuels.

fuel design↗
NASA NTRS1991

Molecular line emission models of Herbig-Haro objects. I - H2 emission

A comprehensive model for molecular hydrogen emssion in Herbig-Haro objects that are associated with the heads of radiative stellar jets is presented by using a simple representation of the jet head as a comprising a leading bow shock and a trailing jet shock, separated by a dense layer of cool shocked gas. Attention is given to collisional excitation in a nondissociative shock and formation pumping in the molecular reformation zone behind a dissociative shock, employing detailed shock and photodissociation-region emission models that incorporate most of the relevant atomic physics and chemistry. The conditions under which each of these excitation mechanisms may be expected to contribute to the observed emission are discussed, and a general diagnostic scheme for discriminating among them is constructed. Applying this scheme to the HH 1-2 system, strong evidence for excitation by the radiation field of a fast shock is found. It is inferred that FUV pumping contributes a significant fraction of the H2 line emission, and it is shown that this can occur only if the UV pump lines are not strongly self-shielded.

Wolfire, Mark G.↗
NASA NTRS1980

Models of molecular clouds and the abundances of H2CO and HCO/+/

Observations of HCO(+) and H2CO in a sample of 13 molecular clouds have been analyzed by construction of uniform, spherical cloud models. The total densities and the abundance of HCO(+) and H2CO relative to H2 which result from these models fall into two domains: one group of clouds has a low temperature, moderate density, and high abundances; the other group has higher temperature and density, but lower abundances. The factor distinguishing these groups may be depletion onto grains in the denser sources.

Wootten, A.↗
NASA NTRS1992

Lower temperature curing thermoset polyimides utilizing a substituted norbornene endcap

Methoxycarbonyl bridgehead substituted nadic diacid monomethyl ester, when used as an endcapping monomer, lowered the cure temperature of thermoset PMR polyimides without seriously affecting other desirable properties, such as glass transition temperature and thermal oxidative stability. The C-13 CP/MAS NMR of model compounds was used to follow the cure of resin systems using both the unmodified nadic endcap and the methoxycarbonyl-substituted endcap. Rheological analysis and differential scanning calorimetry DSC also provided evidence for the lower curing nature of the substituted endcap. Two regioisomers of the bridgehead-substituted endcap were isolated, and their chemical structures were elucidated by X-ray crystallography. The model compound and molecular modeling studies conducted ruled out the possibility of regioisomeric imide formation in the substituted endcaps.

Waters, John F.↗
NASA NTRS1997

Dielectric Properties of Piezoelectric Polyimides

Molecular modeling and dielectric measurements are being used to identify mechanisms governing piezoelectric behavior in polyimides such as dipole orientation during poling, as well as degree of piezoelectricity achievable. Molecular modeling on polyimides containing pendant, polar nitrile (CN) groups has been completed to determine their remanent polarization. Experimental investigation of their dielectric properties evaluated as a function of temperature and frequency has substantiated numerical predictions. With this information in hand, we are then able to suggest changes in the molecular structures, which will then improve upon the piezoelectric response.

Ounaies, Z.↗
DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
NASA NTRS2016

Molecular Dynamics Modeling of Carbon Nanotube Composite Fracture Using ReaxFF

Carbon nanotube (CNT) fiber reinforced composites with specific tensile strengths and moduli approaching those of aerospace grade carbon fiber composites have recently been reported. This achievement was enabled by the emerging availability of high N/tex yarns in kilometer-scale quantities. While the production of this yarn is an impressive advance, its strength is still much lower than that of the individual CNTs comprising the yarn. Closing this gap requires understanding load transfer between CNTs at the nanometer dimensional scale. This work uses reactive molecular dynamics simulations to gain an understanding at the nanometer scale of the key factors that determine CNT nanocomposite mechanical performance, and to place more realistic upper bounds on the target properties. While molecular dynamics simulations using conventional force fields can predict elastic properties, the ReaxFF reactive forcefield can also model fracture behavior because of its ability to accurately describe bond breaking and formation during a simulation. The upper and lower bounds of CNT composite properties are investigated by comparing systems composed of CNTs continuously connected across the periodic boundary with systems composed of finite length CNTs. These lengths, effectively infinite for the continuous tubes and an aspect ratio of 13 for the finite length case, result from practical limitations on the number of atoms that can be included in a simulation. Experimentally measured aspect ratios are typically on the order of 100,000, so the calculated results should represent upper and lower limits on experimental mechanical properties. Finally, the effect of various degrees of covalent crosslinking between the CNTs and amorphous carbon matrix is considered to identify the amount of CNT-matrix covalent bonding that maximizes overall composite properties.

Jensen, Benjamin D.↗
NASA NTRS1976

Inadequacy of the statistical many-body model for molecular infrared absorption in the far wings

It is known that the infrared absorption coefficient of CO2 in the far wings is far less than what is derived from the assumption of a Lorentzian absorption profile. Sorgen and Ben-Aryeh (1972) tried to show that by incorporating the statistical many-body model into impact theory, the discrepancy between the Lorentzian absorption profile and the experimental infrared absorption coefficient can be removed. This paper attempts to show that the high frequency or short-time property of the dipole-dipole interaction cannot be adequately explained by the many-body model; in other words, the statistical model as conventionally understood is not applicable to infrared spectral lines in the far wings.

Fowler, B. W.↗
NASA NTRS1995

Models and molecular approaches to assessing the effects of the microgravity environment on vertebrate development

The extent to which gravity, and especially the lack thereof, can affect normal development in higher organisms is poorly understood. Underlying this question is the assumption that normal development depends on the embryo's ability to maintain a programmed temporal and spatial coordination of morphogenetic events. There are several reports documenting the apparently normal development of several vertebrate species, including mammals, under conditions of exposure to space flight during various periods of the development process. Evidence to the contrary also exists and it is therefore likely that some alterations in morphology do occur in a microgravity environment. Although subsequent development may appear overtly normal, more subtle abnormalities result. In all studies, the evaluation is restricted by the few numbers of specimens that can be examined and the relatively insensitive techniques for assessing potentially subtle effects. In the present discussion, we summarize some observations of mammalian development made in microgravity and consider which stages might be expected to be differentially sensitive to altered gravity conditions. While we emphasize mammalian development, we discuss the suitability of another model system for examining such effects in a cross-species context. Furthermore, we consider recent developments in our understanding of the molecular genetic program regulating embryogenesis that could serve as markers for assessing perturbations of development.

Cosmos 1129 Project↗
DOE OSTI2026

Shadow molecular dynamics for flexible multipole models

Shadow molecular dynamics provide an efficient and stable atomistic simulation framework for flexible charge models with long-range electrostatic interactions. Shadow molecular dynamics simulations are driven by approximate “shadow” Born–Oppenheimer potentials for which the exact charges and forces are directly accessible without relying on costly (and approximate) iterative solvers. While previous implementations have been limited to atomic monopole charge distributions, we extend this approach to flexible multipole models. We derive detailed expressions for the shadow energy functions, potentials, and force terms, explicitly incorporating monopole–monopole, dipole–monopole, and dipole–dipole interactions. In our formulation, both atomic monopoles and atomic dipoles are treated as extended dynamical variables alongside the propagation of the nuclear degrees of freedom. We demonstrate that introducing the additional dipole degrees of freedom preserves the stability and accuracy previously seen in monopole-only shadow molecular dynamics simulations. In addition, we present a shadow molecular dynamics scheme where the monopole charges are held fixed while the dipoles remain flexible. Our extended shadow dynamics provide a framework for stable, computationally efficient, and versatile molecular dynamics simulations involving long-range interactions between flexible multipoles. This is of particular current interest in combination with machine-learned interatomic potentials, including long-range electrostatic interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

ECUT: Energy Conversion and Utilization Technologies program - Biocatalysis research activity

The activities of the Biocatalysis Research Activity are organized into the Biocatalysis and Molecular Modeling work elements and a supporting planning and analysis function. In the Biocatalysis work element, progress is made in developing a method for stabilizing genetically engineered traits in microorganisms, refining a technique for monitoring cells that are genetically engineered, and identifying strains of fungi for highly efficient preprocessing of biomass for optimizing the efficiency of bioreactors. In the Molecular Modeling work element, a preliminary model of the behavior of enzymes is developed. A preliminary investigation of the potential for synthesizing enzymes for use in electrochemical processes is completed. Contact with industry and universities is made to define key biocatalysis technical issues and to broaden the range of potential participants in the activity. Analyses are conducted to identify and evaluate potential concepts for future research funding.

Wilcox, R.↗
NASA NTRS2014

Ab Initio Modeling of Molecular Radiation

Radiative emission from excited states of atoms and molecules can comprise a significant fraction of the total heat flux experienced by spacecraft during atmospheric entry at hypersonic speeds. For spacecraft with ablating heat shields, some of this radiative flux can be absorbed by molecular constituents in the boundary layer that are formed by the ablation process. Ab initio quantum mechanical calculations are carried out to predict the strengths of these emission and absorption processes. This talk will describe the methods used in these calculations using, as examples, the 4th positive emission bands of CO and the 1g+ 1u+ absorption in C3. The results of these calculations are being used as input to NASA radiation modeling codes like NeqAir, HARA and HyperRad.

spectroscopy↗
DOE OSTI2025

Applying deep learning methods to develop new models of molecular charge transfer, nonadiabatic dynamics, and nonlinear spectroscopy in the condensed phase

Photon- and field-induced charge transfer has central importance in the generation and storage of electricity, the novel properties of materials, photo-induced catalysis, and electro-optic activity (e.g., photovoltaic cells, fuel cells, and organic chromophores for use in optical fibers and light-emission diodes). These non-equilibrium electronic and chemical transformations are probed by ultrafast, nonlinear spectroscopies. Accurate simulations play a crucial role in our ability to understand, optimize, and control these transformations. This project applies modern deep learning and machine learning (ML) methods to dramatically improve models of electronic dynamics, electronic-nuclear dynamics, and spectroscopic measurements for improved simulations of chemistry in complex environments, far from equilibrium phenomena, and processes in extreme environments, such as materials exposed to strong or resonant fields. This project develops accurate neural net models that go beyond predictive capability to also provide new insight into the fundamental physics underlying electron and nuclear dynamics. To achieve its objectives, this project explores and develops customized versions of high-capacity deep learning algorithms/models. These techniques are developed with an emphasis on fundamental chemical insight, not just predictive accuracy, to assist the development of the next generation of quantum simulation methods.

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

Beyond real: alternative unitary cluster Jastrow models for molecular electronic structure calculations on near-term quantum computers

Near-term quantum devices require wavefunction ansätze that are expressive while also of shallow circuit depth in order to both accurately and efficiently simulate molecular electronic structure. While the unitary coupled cluster ansatz (e.g., UCCSD) has become a standard, the high gate count associated with the implementation of this limits its feasibility on noisy intermediate-scale quantum (NISQ) hardware. k -Fold unitary cluster Jastrow (uCJ) ansätze mitigate this challenge by providing O( kN 2 ) circuit scaling and favorable linear depth circuit implementation. Previous work has focused on the real orbitalrotation (Re-uCJ) variant of uCJ, which allows an exact (Trotter-free) implementation. Here we extend and generalize the k -fold uCJ framework by introducing two new variants, Im-uCJ and g-uCJ, which incorporate imaginary and fully complex orbital rotation operators, respectively. Similar to Re-uCJ, both of the new variants achieve quadratic gate-count scaling. Our results focus on the simplest k = 1 model, and show that the uCJ models frequently maintain energy errors within chemical accuracy (∼1 kcal mol −1 ). Both g-uCJ and Im-uCJ are more expressive in terms of capturing electron correlation and are also more accurate than the earlier Re-uCJ ansatz. We further show that Im-uCJ and g-uCJ circuits can also be implemented exactly, without any Trotter decomposition. Numerical tests using k = 1 on H 2 , H 3 + , Be 2 , C 2 H 4 , C 2 H 6 and C 6 H 6 in various basis sets confirm the practical feasibility of these shallow Jastrow-based ansätze for applications on near-term quantum hardware.

Tkachenko, Nikolay V. [University of California, B↗
DOE OSTI2025

Empirical evidence that glucan-interacting amino acid side chains within the transmembrane channel collectively facilitate cellulose synthase function

The fundamental mechanism of cellulose synthesis is widely conserved across Kingdoms and depends on cellulose synthases, which are processive, dual-function, family 2 glycosyltransferases (GT-2). These enzymes polymerize glucose on the cytoplasmic side of the plasma membrane and export the glucan chain to the cell surface through an integral transmembrane (TM) channel. Structural studies of active plant cellulose synthases (CESAs) have revealed interactions between the nascent glucan chain and the side chains of polar, charged, and aromatic amino acid residues that line the TM channel. However, the functional consequences of modifying these side chains have not been tested in vivo in CESAs or other processive GT-2s. To test this, we used an established in vivo assay based on genetic complementation of CESA5 in the moss, Physcomitrium patens. For accurate prediction of glucan-interacting amino acid residues, we generated a complete homotrimeric molecular model of PpCESA5 using a combination of homology and de novo modeling. All-atom molecular dynamics-based analyses of contact metrics and interaction energy identified 23 amino acid residues with high propensity to interact with the nascent glucan chain within the TM channel or on the apoplastic surface of PpCESA5. Mutating any one of 18 of these amino acid residues to alanine, thereby removing their side chains, abolished or impaired CESA function, with the strongest effects observed upon the loss of charged amino acid side chains. This provides direct evidence to support the hypothesis that multiple amino acid residues collectively maintain a smooth energy landscape within the TM channel to facilitate glucan translocation.

59 BASIC BIOLOGICAL SCIENCES↗