Improvement of uncoupled Hartree-Fock expectation values for physical properties
Hartree-Fock calculation method as zero-order approximation for determining atomic and molecular second-order properties
PHYSICAL PROPERTY↗
SEARCH · Engineering Papers
Results for “molecular properties”
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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Mechanical Properties of LaRC(tm) SI Polymer for a Range of Molecular Weights
Mechanical testing of an advanced polyimide resin (LaRC(tm)-SI) with known variations in molecular weight was performed over a range of temperatures below the glass transition temperature. Elastic and inelastic properties were characterized as a function of molecular weight and test temperature. It was shown that notched tensile strength is a strong function of both temperature and molecular weight, whereas stiffness is only a strong function of temperature. The combined analysis of calculated yield stress and notched tensile strength indicated that low molecular weight materials tended to fail in a brittle manner, whereas high molecular weight materials exhibited ductile failure. The microphotographs of the failure surfaces also supported these findings.
Whitley, Karen S.↗
Characterizing the Impact of Oligomerization on Redox Flow Cell Performance
Abstract Redox flow batteries (RFBs) are hindered by complex failure modes, particularly crossover through the membrane, resulting in capacity fade and reduced cycling efficiencies. Redox‐active oligomers (RAOs) have recently been proposed for mitigating this phenomenon while maintaining sufficient transport properties; however, to date, few studies have quantified how the chemical and electrochemical properties of RAOs influence their performance in redox flow cells. Here, we demonstrate that oligomeric derivatives of 2,2,6,6‐tetramethylpiperidine 1‐oxyl (TEMPO) exhibit lower diffusivities than the monomeric species but retain facile charge transfer characteristics. The size‐dependent variations in mass transport rates directly translate to differences in flow cell polarization and symmetric cycling performance. Post‐mortem analyses reveal that oligomerization does not meaningfully alter decay processes as evinced by similar capacity fade across all species. Broadly, these findings corroborate and extend upon previously developed relationships between molecular size, electrochemical properties, and flow cell performance.
36 MATERIALS SCIENCE↗
Lithiation bridged molecular conducting magnets
Combining ferromagnetism and metallic conductivity has been extensively studied in contemporary materials science. However, building such multifunctionalities in molecular chemistry is particularly challenging, on which two collective properties are long considered as mutually exclusive. Here, we report molecular conducting magnet consisting of two-dimensional graphene and molecular planar magnetic networks bridged by electrochemical lithiation, exhibiting the co-existence of distinct magnetism and conductivity and magneto-electric coupling effects. Here, the room temperature magnetoresistance and magnetoelectric coupling coefficient of such complex solid reach 10.7% and 1.77 V/Oe cm, respectively, which can be further tailored by modulating the interaction between graphene and molecular magnetic network. In addition, the graphene passivation simultaneously introduces environmental stability of molecular mag-nets. The electrochemical lithiation offers a pathway towards coupling magnetism and conductivity in molecular complexes.
2D organic complexes↗
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↗
In-Silico Design of Next Generation Cellulose-Derived Packaging Materials (CRADA Final Report)
Developing sustainable solutions for single-use packaging is an important objective to combat the environmental crisis of plastics pollution. Most embodiments of cellulose-based packaging materials, including CellophaneTM, are completely biodegradable in both terrestrial and marine environments. However, petroleum-derived alternatives offer some performance advantages for metrics such as moisture barriers and mechanical properties. This project leverages molecular dynamics simulation to investigate how molecular modifications to cellulose-based polymer assemblies impact their material properties. An important performance criterion for the modified materials was to retain biodegradability; thus, modifications by naturally occurring, biodegradable additives were the focus of this study. Specifically, we developed models with xylan and lignin of varying monomeric compositions into the cellulose matrix. The mechanical properties were investigated by performing stress-strain simulations, and the water barrier and hydrophobicity were investigated by simulating the water contact angle. Our findings indicate that the incorporation of xylan into the cellulose matrix tends to increase the mechanical properties with an optimal loading of ~27 wt%. We also predict that orienting the nanoscale directionality of the xylan chains such that they are perpendicular to the cellulose fibrils will dramatically increase mechanical strength. In contrast, the incorporation of lignin tends to weaken the composite at all loadings investigated. Simulations of water contact angle predicted that coating polymers on the surface of the cellulose assembly creates a more hydrophobic surface than incorporating them throughout the matrix. Of the coatings investigated, lignin resulted in the most hydrophobic surface, followed by pectin and keratin, which both imparted modest increases in hydrophobicity. Future experimental work done by Futamura will focus on designing material prototypes to capitalize on the predictions of performance enhancement obtained from molecular modeling. While substantial progress was made by the simulations performed in this project, there still exists a vast parameter space that we were unable to investigate, including branching, functional group decoration, and degree of polymerization of polymer additives. However, the methods developed in this initial investigation will facilitate more rapid evaluation of the impact of molecular characteristics on the performance of biopolymer composite materials and thereby accelerate future materials discovery efforts in this area.
36 MATERIALS SCIENCE↗
Transport properties in the atmosphere of Jupiter
The calculation of transport properties near the surface of a probe entering the atmosphere of Jupiter is discussed for (1) transport properties in the pure Jovian atmosphere, (2) transport properties for collisions between monatomic carbon atoms, including the effect of excited electronic states, (3) transport properties at the boundaries for mixing of the pure Jovian atmosphere and the atmosphere due to the injection of gaseous ablation products, and (4) transport properties for interactions involving some of the molecular ablation products. The transport properties were calculated using the kinetic theory of gases. Transport collision integrals were calculated for only a limited set of empirical and semiempirical interaction potentials. Since the accuracy of the fit of these empirical potentials to the true potential usually determines the accuracy of the calculation of the transport properties, the various interaction potentials used in these calculations are discussed.
Biolsi, L., Jr.↗
Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces
The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for instance, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3–55 atoms with mean absolute errors in the range of 0.11–0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure–property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal–metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3–55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The interpenetration polymer network in a cement paste–waterborne epoxy system
The formation of the interpenetrating polymer network (IPN) structure within the cement-polymer system has been revealed by experiments from 2 dimensional to 3-dimensional scales. However, the microstructure design and performance prediction of IPN as a function of specific C-S-H/polymer components or ingredients' parameters e.g. water to cement ratios (w/c), polymer to cement ratios (p/c), monomer components, degree of polymerization (DP), etc. is by far not available. Here we developed a mesoscale model for IPN visualization based on the Flory-Huggins interaction theory which was applied to cement science for the first time. All the ingredients in the micro-structure were considered as soluble beads with rational sizes based on their properties obtained by molecular dynamic methods. The interaction parameters of each bead were then determined based on their element ratios and chemical backbones. The model was validated with the waterborne epoxy-cement material (WECM) in which a novel waterborne epoxy resin (WEP) was prepared and impregnated. The verification results on the 2D-3D scale show that the developed model predicts the WECM's IPN structures by rule and line concerning DP, w/c, and p/c in the mixture. The C-S-H beads were progressively scaled in size which alters the C-S-H texture to have completely different dissolution characteristics. Beads of diameter ~6 Å are more unstable and soluble which enable them to form a continuous phase in water or a composite structure with WEP. In contrast, beads with diameters larger than 10 Å have different properties with stronger nucleation effects. The results also suggest the impregnation content of WEP in cement-based material should be limited to 10% vol. to prevent the polymer IPN from decomposing into discrete clusters. The application of Flory-Huggins theory in cement-based composites demonstrates great potential in performance prediction and microstructure design.
36 MATERIALS SCIENCE↗
ORNL_AISD_DL-HLgap
This dataset provides supplementary molecular dataset of Deep Learning Workflow for the Inverse Design of Molecules with Specific Optoelectronic Properties. The dataset comprises three main directories such as GDB-9_dataset, Low_HL_Gap_dataset, and High_HL_Gap_dataset which individually has csv files, smiles_txt files, pdb files and xyz files containing information of molecular structures, properties and coordinates generated from deep learning workflow using generative model, surrogate model and DFTB calculation results. GDB-9_dataset contains the molecular data extracted from the original GDB-9 dataset with additional data of DFTB HL gap, surrogate HL gap and molecular property analysis. (the number of atoms, aromaticity and double bond equivalent) Low_HL_Gap_dataset and High_HL_Gap_dataset contains series of dataset for different generations with further split to train and test dataset that were obtained from the iterative workflow described in the manuscript. Additional directory Chemiscope_visualization in Low_HL_Gap_dataset directory contains compressed json files to visualize molecules using chemiscope.org page or application to help readers examine generated molecules.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Perspective on Lewis Acid‐Base Interactions in Emerging Batteries
Lewis acid-base interactions are common in chemical processes presented in diverse applications, such as synthesis, catalysis, batteries, semiconductors, and solar cells. The Lewis acid-base interactions allow precise tuning of material properties from the molecular level to more aggregated and organized structures. This review will focus on the origin, development, and prospects of applying Lewis acid-base interactions for the materials design and mechanism understanding in the advancement of battery materials and chemistries. The covered topics relate to aqueous batteries, lithium-ion batteries, solid-state batteries, alkali metal-sulfur batteries, and alkali metal-oxygen batteries. In this review, the Lewis acid-base theories will be first introduced. Thereafter the application strategies for Lewis acid-base interactions in solid-state and liquid-based batteries will be introduced from the aspects of liquid electrolyte, solid polymer electrolyte, metal anodes, and high-capacity cathodes. The underlying mechanism is highlighted in regard to ion transport, electrochemical stability, mechanical property, reaction kinetics, dendrite growth, corrosion, and so on. Last but not least, perspectives on the future directions related to Lewis acid-base interactions for next-generation batteries are like to be shared.
Lewis acid-base interactions↗
Can Polyelectrolyte Mechanical Properties be Directly Modulated by an Electric Field? A Molecular Dynamics Study
Multifunctionality in polymers facilitates their application in emerging technologies. Electrical fields are a preferred stimulus because of the speed and ease of application to bulk polymers. While a wide range of electrically triggered actuators are developed, and electrically controlled adhesion between gels is demonstrated, modification of bulk mechanical properties via electrical stimuli remains elusive. Polymers with covalently incorporated ionic charge (polyelectrolytes) should be well suited to achieving this goal since the mechanical properties depend on electrostatic interactions and these charges are intrinsically susceptible to electric fields. Molecular dynamics simulations are utilized here to investigate whether electric fields can modulate the mechanical properties of polyelectrolytes and to understand the governing mechanisms. Mechanical property modulation by electric field is found to be sensitive to the charge distribution—charges must be tightly attached to the polymer backbone, and responsivity is greater if a single backbone contains both positive and negative charges. The dominant mechanisms are reorientation and stretching of the polymer chains, which also elongate the ionic clusters to maintain strong electrostatic interactions throughout deformation. Furthermore, these insights are critical for future experimental realization of polymers with electric field regulated mechanical properties.
36 MATERIALS SCIENCE↗
Effects of high energy radiation on the mechanical properties of epoxy-graphite fiber reinforced composites
In an effort to elucidate the changes in molecular structural and mechanical properties of epoxy/graphite fiber composites upon exposure to ionizing radiation in a simulated space environment, spectroscopic and surface properties of tetraglycidyl-4,4'-diamino diphenyl methane (TGDDM) red with diamino diphenyl sulfone (DDS) and T-300 graphite fiber were investigated following exposure to ionizing radiation. Cobalt-60 gamma radiation and 1/2 MeV electrons were used as radiation sources. The system was studied using electron spin resonance (ESR) spectroscopy, infrared absorption spectroscopy, contact angle measurements, and electron spectroscopy for chemical analysis.
Fornes, R. E.↗
Pathways to fluorescence via restriction of intramolecular motion in substituted tetraphenylethylenes
The design of materials with enhanced luminescence properties is a fast-developing field due to the potential applicability of these materials as light-emitting diodes or for bioimaging. A transparent way to enhance the emission properties of interesting molecular candidates is blocking competing and unproductive non-radiative relaxation pathways by the restriction of intramolecular motions. Rationalized functionalization is an important possibility to achieve such restrictions. Using time-dependent density functional theory (TD-DFT) based on the ωB97XD functional and the semiempirical tight-binding method including long-range corrections (TD-LC-DFTB), this work investigates the effect of functionalization of the paradigmatic tetraphenylethylene (TPE) on achieving restricted access to conical intersections (RACI). Photodynamical surface hopping simulations have been performed on a larger set of compounds including TPE and ten functionalized TPE compounds. Functionalization has been achieved by means of electron-withdrawing groups, bulky groups which block the relaxation channels via steric hindrance and groups capable of forming strong hydrogen bonds, which restrict the motion via the formation of hydrogen bond channels. Most of the investigated functionalized TPE candidates show ultrafast deactivation to the ground state due to their still existing structural flexibility, but two examples, one containing –CN and –CF 3 groups and a second characterized by a network of hydrogen bonds, have been identified as interesting candidates for creating efficient luminescence properties in solution.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Exploring the Effects of Node Topology, Connectivity, and Metal Identity on the Binding of Nerve Agents and Their Hydrolysis Products in Metal–Organic Frameworks
Recent studies have shown that metal–organic frameworks (MOFs) built from hexanuclear M(IV) oxide cluster nodes are effective catalysts for nerve agent hydrolysis, where the properties of the active sites on the nodes can strongly influence the reaction energetics. The connectivity and metal identity of these M6 nodes can be easily tuned, offering extensive opportunities for computational screening to predict promising new materials. Thus, we used density functional theory (DFT) to examine the effects of node topology, connectivity, and metal identity on the binding energies of multiple nerve agents and their corresponding hydrolysis products. By computing an optimization metric based on the relative binding strengths of key hydrolysis reaction species (water, agent, and bidentate-bound products), we predicted optimal M6 nodes for hydrolyzing specific nerve agent and simulant molecules, where our results are in qualitative agreement with observed experimental trends. This analysis highlighted the notion that no single metal or node topology is optimal for all possible organophosphates, suggesting that MOFs should be selected based on the agent of interest. Using the large amount of data generated from our DFT calculations, we then derived quantitative structure–activity relationship (QSAR) models to help explain the complex trends observed in the binding energies. Through linear regression, we identified the most important descriptors for describing the binding of nerve agents and their hydrolysis products to M6 nodes. These results suggested that both molecular and node properties, including both structural and chemical features, collectively contribute to the binding energetics. By performing a thorough statistical analysis, we showed that our QSAR models are capable of making quantitatively accurate binding energy predictions for nerve agents and their hydrolysis products in a wide variety of M(IV)-MOFs. In conclusion, the insights gained herein can be used to guide future experiments for the synthesis of MOFs with enhanced catalytic activity for organophosphate hydrolysis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Envelope structure on 700 AU scales and the molecular outflows of low-mass young stellar objects
Aperture synthesis observations of HCO+ J = 1-0, 13CO 1-0, and C18O 1-0 obtained with the Owens Valley Millimeter Array are used to probe the small-scale (5" approximately 700 AU) structure of the molecular envelopes of a well-defined sample of nine embedded low-mass young stellar objects in Taurus. The interferometer results can be understood in terms of: (1) a core of radius approximately or less than 1000 AU surrounding the central star, possibly flattened and rotating; (2) condensations scattered throughout the envelope that may be left over from the inhomogeneous structure of the original cloud core or that may have grown during collapse; and (3) material within the outflow or along the walls of the outflow cavity. Masses of the central cores are 0.001-0.1 M (solar), and agree well with dust continuum measurements. Averaged over the central 20" (3000 AU) region, an HCO+ abundance of 4 x 10(-8) is inferred, with a spread of a factor of 3 between the different sources. Reanalysis of previously presented single-dish data yields an HCO+ abundance of (5.0 +/- 1.7) x 10(-9), which may indicate an average increase by a factor of a few on the smaller scales sampled by the interferometer. Part of this apparent abundance variation could be explained by contributions from extended cloud emission to the single-dish C18O lines, and uncertainties in the assumed excitation temperatures and opacities. The properties of the molecular envelopes and outflows are further investigated through single-dish observations of 12CO J = 6-5, 4-3, and 3-2, 13CO 6-5 and 3-2, and C18O 3-2 and 2-1, obtained with the James Clerk Maxwell and IRAM 30 m telescopes, along with the Caltech Submillimeter Observatory. Ratios of the mid-J CO lines are used to estimate the excitation temperature, with values of 25-80 K derived for the gas near line centre. The outflow wings show a similar range, although Tex is enhanced by a factor of 2-3 in at least two sources. In contrast to the well-studied L1551 IRS 5 outflow, which extends over 10' (0.4 pc), seven of the remaining eight sources are found to drive 12CO 3-2 outflows over < or = 1' (0.04 pc); only L1527 IRS has a well-developed outflow of some 3'(0.12 pc). Estimates are obtained for the outflow kinetic luminosity, Lkin, and the flow momentum rate, FCO, applying corrections for line opacity and source inclination. The flow force FCO correlates with the envelope mass and with the 2.7 mm flux of the circumstellar disk. Only a weak correlation is seen with Lbol, while none is found with the relative age of the object as measured by integral Tmb(HCO+ 3-2)dV/Lbol. These trends support the hypothesis that outflows are driven by accretion through a disk, with a global mass infall rate determined by the mass and density of the envelope. The association of compact HCO+ emission with the walls of the outflow cavities indicates that outflows in turn influence the appearance of the envelopes. It is not yet clear, however, whether they are actively involved in sweeping up envelope material, or merely provide a low-opacity pathway for heating radiation to reach into the envelope.
NASA Discipline Exobiology↗
Structural and antibacterial properties of NSAID-loaded ultra-high molecular weight polyethylene
Peri-articular delivery of pain medication in joint arthroplasty has the potential to address post-operative pain and decrease the use of systemic opioids. Additionally, the sustained release from a delivery vehicle may be especially impactful in the initial post-operative period when pain is most severe. We recently described a novel approach for the sustained intra-articular delivery of an analgesic (bupivacaine) from an ultra-high molecular weight polyethylene (UHMWPE) bearing surface. A secondary but very significant effect of incorporating bupivacaine in UHMWPE was its antibacterial effect against Staphylococcal species, which are associated with the majority of periprosthetic joint infections. Here, we report on the structure, properties, elution characteristics and antibacterial properties of UHMWPE loaded with the non-steroidal anti-inflammatory drug (NSAID) — tolfenamic acid. We showed that 6 wt% drug loading was optimal for eluting clinically relevant intra-articular and systemic concentrations, for maintaining mechanical properties at a clinically relevant level, and for providing anti-colonization potential against low risk (planktonic) and high risk (biofilm forming) Staphylococcal species. We determined the osteoblast response to the tolfenamic acid-loaded UHMWPE to evaluate the cytotoxicity profile of this novel material. Tolfenamic acid-loaded UHMWPE has the potential to be used as a part of multimodal pain management therapy following arthroplasty and may provide prophylaxis for periprosthetic infection.
36 MATERIALS SCIENCE↗
Chemical design of electronic and magnetic energy scales of tetravalent praseodymium materials
Lanthanides in the trivalent oxidation state are typically described using an ionic picture that leads to localized magnetic moments. The hierarchical energy scales associated with trivalent lanthanides produce desirable properties for e.g., molecular magnetism, quantum materials, and quantum transduction. Here, we show that this traditional ionic paradigm breaks down for praseodymium in the tetravalent oxidation state. Synthetic, spectroscopic, and theoretical tools deployed on several solid-state Pr 4+ -oxides uncover the unusual participation of 4f orbitals in bonding and the anomalous hybridization of the 4f 1 configuration with ligand valence electrons, analogous to transition metals. The competition between crystal-field and spin-orbit-coupling interactions fundamentally transforms the spin-orbital magnetism of Pr 4+ , which departs from the J eff = 1/2 limit and resembles that of high-valent actinides. Our results show that Pr 4+ ions are in a class on their own, where the hierarchy of single-ion energy scales can be tailored to explore new correlated phenomena in quantum materials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗