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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Probing Molecular Packing of Amorphous Pharmaceutical Solids Using X-ray Atomic Pair Distribution Function and Solid-State NMR

The structural investigation of amorphous pharmaceuticals is of paramount importance in comprehending their physicochemical stability. However, it has remained a relatively underexplored realm primarily due to the limited availability of high-resolution analytical tools. Here in this study, we utilized the combined power of X-ray pair distribution functions (PDFs) and solid-state nuclear magnetic resonance (ssNMR) techniques to probe the molecular packing of amorphous posaconazole and its amorphous solid dispersion at the molecular level. Leveraging synchrotron X-ray PDF data and employing the empirical potential structure refinement (EPSR) methodology, we unraveled the existence of a rigid conformation and discerned short-range intermolecular C–F contacts within amorphous posaconazole. Encouragingly, our ssNMR 19 F– 13 C distance measurements offered corroborative evidence supporting these findings. Furthermore, employing principal component analysis on the X-ray PDF and ssNMR data sets enabled us to gain invaluable insights into the chemical nature of the intermolecular interactions governing the drug–polymer interplay. These outcomes not only furnish crucial structural insights facilitating the comprehension of the underlying mechanisms governing the physicochemical stability but also underscore the efficacy of synergistically harnessing X-ray PDF and ssNMR techniques, complemented by robust modeling strategies, to achieve a high-resolution exploration of amorphous structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Advanced supramolecular design for direct ink writing of soft materials

The exciting advancements in 3D-printing of soft materials are changing the landscape of materials development and fabrication. Among various 3D-printers that are designed for soft materials fabrication, the direct ink writing (DIW) system is particularly attractive for chemists and materials scientists due to the mild fabrication conditions, compatibility with a wide range of organic and inorganic materials, and the ease of multi-materials 3D-printing. Inks for DIW need to possess suitable viscoelastic properties to allow for smooth extrusion and be self-supportive after printing, but molecularly facilitating 3D printability to functional materials remains nontrivial. While supramolecular binding motifs have been increasingly used for 3D-printing, these inks are largely optimized empirically for DIW. Hence, this review aims to establish a clear connection between the molecular understanding of the supramolecularly bound motifs and their viscoelastic properties at bulk. Herein, extrudable (but not self-supportive) and 3D-printable (self-supportive) polymeric materials that utilize noncovalent interactions, including hydrogen bonding, host–guest inclusion, metal–ligand coordination, micro-crystallization, and van der Waals interaction, have been discussed in detail. In particular, the rheological distinctions between extrudable and 3D-printable inks have been discussed from a supramolecular design perspective. Examples shown in this review also highlight the exciting macroscale functions amplified from the molecular design. Challenges associated with the hierarchical control and characterization of supramolecularly designed DIW inks are also outlined. The perspective of utilizing supramolecular binding motifs in soft materials DIW printing has been discussed. Finally, this review serves to connect researchers across disciplines to develop innovative solutions that connect top-down 3D-printing and bottom-up supramolecular design to accelerate the development of 3D-print soft materials for a sustainable future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Harness the power of atomistic modeling and deep learning in biofuel separation

Biofuels offer a remarkable, sustainable energy source for a future of clean energy. The development of efficient biofuel separation plays a crucial role in achieving cost-effective utilization of biofuel. In this chapter, we provide an overview of the recent advancements in atomistic-level modeling and deep learning in the rational design of novel, efficient biofuel separation. The fundamental principles of quantum and statistical mechanics are covered in appropriate detail to highlight their underlying differences in theory. The methodologies of several molecular representations and deep learning algorithms applicable to biofuel separation are briefly demonstrated as well. The applications, successes, and risks of employing density functional theory, ab initio molecular dynamics, classical molecular dynamics, and deep learning are provided to showcase their recent accomplishments in biofuel separation as well as potential improvements in both methodology and application. Lastly, a vision for the future growth of these methods is illustrated.

deep learning, artificial intelligence, biofuels, ↗
DOE OSTI2023

An unexpected hydratase synthesizes the green light-absorbing pigment fucoxanthin

Abstract The ketocarotenoid fucoxanthin and its derivatives can absorb blue–green light enriched in marine environments. Fucoxanthin is widely adopted by phytoplankton species as a main light-harvesting pigment, in contrast to land plants that primarily employ chlorophylls. Despite its supreme abundance in the oceans, the last steps of fucoxanthin biosynthesis have remained elusive. Here, we identified the carotenoid isomerase-like protein CRTISO5 as the diatom fucoxanthin synthase that is related to the carotenoid cis–trans isomerase CRTISO from land plants but harbors unexpected enzymatic activity. A crtiso5 knockout mutant in the model diatom Phaeodactylum tricornutum completely lacked fucoxanthin and accumulated the acetylenic carotenoid phaneroxanthin. Recombinant CRTISO5 converted phaneroxanthin into fucoxanthin in vitro by hydrating its carbon–carbon triple bond, instead of functioning as an isomerase. Molecular docking and mutational analyses revealed residues essential for this activity. Furthermore, a photophysiological characterization of the crtiso5 mutant revealed a major structural and functional role of fucoxanthin in photosynthetic pigment–protein complexes of diatoms. As CRTISO5 hydrates an internal alkyne physiologically, the enzyme has unique potential for biocatalytic applications. The discovery of CRTISO5 illustrates how neofunctionalization leads to major diversification events in evolution of photosynthetic mechanisms and the prominent brown coloration of most marine photosynthetic eukaryotes.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Theoretical Investigation of the Oxygen Reduction Reaction over Platinum Catalysts Supported by Multi-Edged Vertically Aligned Carbon Nanofiber for Electrocatalyst Preparation

Vertically aligned carbon nanofibers (VACNFs) are promising supports for oxygen reduction reaction (ORR) electrocatalysts in fuel cells. Although experimentally these catalytic systems have shown great potential, there is lack of molecular understanding of the catalytic sites and reaction mechanisms. This work investigated the origin of the ORR reactivities of the platinum catalysts on multi-edged VACNFs (Pt/VACNF) using a multiscale modeling approach combining Density Functional Theory (DFT) and classical Molecular Dynamics (MD) simulations. Based on the ReaxFF potential, here all nanoscale Pt particles (Pt 55 , P 100 , and Pt 147 ) are stabilized by the open edges located axially along the VACNF walls. The calculated first-shell coordination numbers, CN, of surface Pt atoms are 6.63, 7.27, and 7.85, respectively, suggesting that the percentage of low coordination sites increases as the particle size decreases. The adsorption energies of OOH, O, and OH on Pt-55 were systematically probed using DFT calculations. These adsorption energies retain a linear correlation against the generalized coordination numbers ($\overline{CN}$). For Pt nanoparticles supported on VACNF, we found that the OOH and OH bind stronger than on Pt (111) by 0.14 and 0.17 eV, respectively, which can hinder the ORR activity with lower limiting potential than Pt (111). Our theoretical prediction is in good agreement with the linear sweeping voltammetry that revealed a left shift of the half-wave potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Benchmarking boron carbide equation of state using computation and experiment

Boron carbide ( B 4 C ) is of both fundamental scientific and practical interest due to its structural complexity and how it changes upon compression, as well as its many industrial uses and potential for use in inertial confinement fusion (ICF) and high-energy density physics experiments. Here, we report the results of a comprehensive computational study of the equation of state (EOS) of B 4 C in the liquid, warm dense matter, and plasma phases. Our calculations are cross-validated by comparisons with Hugoniot measurements up to 61 megabar from planar shock experiments performed at the National Ignition Facility (NIF). Our computational methods include path integral Monte Carlo, activity expansion, as well as all-electron Green's function Korringa-Kohn-Rostoker and molecular dynamics that are both based on density functional theory. We calculate the pressure-internal energy EOS of B 4 C over a broad range of temperatures ( ~ 6 × 10 3 – 5 × 10 8 K) and densities (0.025–50 g / cm 3 ). We assess that the largest discrepancies between theoretical predictions are ≲ 5 % near the compression maximum at 1– 2 × 10 6 K. This is the warm-dense state in which the K shell significantly ionizes and has posed grand challenges to theory and experiment. By comparing with different EOS models, we find a Purgatorio model (LEOS 2122) that agrees with our calculations. The maximum discrepancies in pressure between our first-principles predictions and LEOS 2122 are ~ 18 % and occur at temperatures between 6 × 10 3 – 2 × 10 5 K, which we believe originate from differences in the ion thermal term and the cold curve that are modeled in LEOS 2122 in comparison with our first-principles calculations. To account for potential differences in the ion thermal term, we have developed three new equation-of-state models that are consistent with theoretical calculations and experiment. We apply these new models to 1D hydrodynamic simulations of a polar direct-drive NIF implosion, demonstrating that these new models are now available for future ICF design studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Charge Transport Characteristics of Molecular Electronic Junctions Studied by Transition Voltage Spectroscopy

The field of molecular electronics is prompted by tremendous opportunities for using a single-molecule and molecular monolayers as active components in integrated circuits. Until now, a wide range of molecular devices exhibiting characteristic functions, such as diodes, transistors, switches, and memory, have been demonstrated. However, a full understanding of the crucial factors that affect charge transport through molecular electronic junctions should yet be accomplished. Remarkably, recent advances in transition voltage spectroscopy (TVS) elucidate that it can provide key quantities for probing the transport characteristics of the junctions, including, for example, the position of the frontier molecular orbital energy relative to the electrode Fermi level and the strength of the molecule–electrode interactions. These parameters are known to be highly associated with charge transport behaviors in molecular systems and can then be used in the design of molecule-based devices with rationally tuned electronic properties. This article highlights the fundamental principle of TVS and then demonstrates its major applications to study the charge transport properties of molecular electronic junctions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence–function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning ~400 My of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Combined Machine Learning and Molecular Dynamics Reveal Two States of Hydration of a Single Functional Group of Cationic Polymeric Brushes

The state of hydration of a macromolecular system regulates a plethora of different properties of such a system. In this article, we develop a novel machine learning (ML) approach, based on the unsupervised clustering algorithm, for probing the hydration behavior of the {N(CH 3 ) 3 } + functional group of the PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] polyelectrolyte (PE) brush system. The PE brushes and the brush-supported water molecules and counterions (chloride ions) are first described using all-atom molecular dynamics (MD) simulations. The simulation data is subsequently used in our ML framework to identify that (1) the {N(CH 3 ) 3 } + functional groups of the PMETAC brushes have two distinct hydration states with one state (state 1) being characterized by less structured water molecules and the other state (state 2) being characterized by more structured water molecules and (2) an enhancement in the brush grafting density leads to the progressive dissapparenace of state 2. An increase in the grafting density increases the number of chloride counterions in a given volume around the {N(CH 3 ) 3 } + functional group and increases the number of shared water molecules between the {N(CH 3 ) 3 } + and Cl - . The chloride counterions are associated with a hydration layer with much less structured water molecules. Therefore, with an increase in the grafting density, an increase in the percentage of shared water molecules leads to the prevalence of the hydration state [of the {N(CH 3 ) 3 } + moiety] with less structured water molecules. Finally, we explain how the present findings are commensurate with two key previous related results, namely a significantly large chloride ion mobility inside the PMETAC brush layer and the {N(CH 3 ) 3 } + -Cl - average distance remaining independent of the PMETAC brush grafting density. Furthermore, we anticipate that the combined ML-MD-simulation approach proposed in this study can be adapted to probe other soft matter systems to reveal new insights of the underlying mechanisms of emergent phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Trapping Ca + inside a molecular cavity: computational study of the potential energy surfaces for Ca + -[ n ]cycloparaphenylene, n = 5–12

Ion trap quantum computing utilizes electronic states of atomic ions such as Ca + to encode information on to a qubit. To explore the fundamental properties of Ca + inside molecular cavities, we describe here a computational study of Ca + bound inside neutral [n]-cycloparaphenylenes (n = 5–12), often referred to as “nanohoops”. This ab initio study characterizes optimized structures, harmonic vibrational frequencies, potential energy surfaces, and ion molecular orbital distortion as functions of increasing nanohoop size. Here the results of this work provide a first step in guiding experimental studies of the spectroscopy of these ion-molecular cavity complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

HVEM structures and mutants reveal distinct functions of binding to LIGHT and BTLA/CD160

HVEM is a TNF (tumor necrosis factor) receptor contributing to a broad range of immune functions involving diverse cell types. It interacts with a TNF ligand, LIGHT, and immunoglobulin (Ig) superfamily members BTLA and CD160. Assessing the functional impact of HVEM binding to specific ligands in different settings has been complicated by the multiple interactions of HVEM and HVEM binding partners. To dissect the molecular basis for multiple functions, we determined crystal structures that reveal the distinct HVEM surfaces that engage LIGHT or BTLA/CD160, including the human HVEM–LIGHT–CD160 ternary complex, with HVEM interacting simultaneously with both binding partners. Based on these structures, we generated mouse HVEM mutants that selectively recognized either the TNF or Ig ligands in vitro. Knockin mice expressing these muteins maintain expression of all the proteins in the HVEM network, yet they demonstrate selective functions for LIGHT in the clearance of bacteria in the intestine and for the Ig ligands in the amelioration of liver inflammation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

DNA Strand Displacement Driven Molecular Additive Manufacturing (DSD-MAM)

The goal of this project was to validate two-dimensional molecular printers, initially selfassembled from DNA and then actuated by externally driven cycles of DNA strand displacement, as prototype integrated nanosystems for molecular additive manufacturing. Novel functionalities of these nanomachines were explored during this project, including the following: nanometer-precision positioning mechanisms based on DNA strand displacement with multivalent interactions for discrete stepping or else diffusive capture; integration of independently moving layers of DNA origami to achieve 2D controllable motion; integration of spatial positioning with deposition functionality. The principal importance of this project was to provide an essential step in the development of a new technology for atomically precise manufacturing. Our first generation molecular 2D printer offers several advantages over conventional DNA-origami patterning, such as faster prototyping, faster dynamic rearrangement of patterns, and the ability to respond with feedback. We anticipate that our first-generation molecular printers may inspire future generations of molecular printers with iterative improvements in robustness and throughput. Potential applications of atomically precise manufacturing include the following: photovoltaics; photosynthetic and fuel cells; thermoelectrics and anisotropic heat spreaders; solid-state lighting; molecular electronic and plasmonic circuits; selectively preamble membranes; self-repairing materials with high strength-to-weight and fracture resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

How well do self-interaction corrections repair the overestimation of static polarizabilities in density functional calculations?

Herein, we examine the effect of removing self-interaction error (SIE) on the calculation of molecular polarizabilities in the local spin density (LSDA) and generalized gradient approximations (GGA). To this end, we utilize a database of 132 molecules taken from a recent benchmark study [Hait and Head-Gordon, Phys. Chem. Chem. Phys. , 2018, 20 , 19800] to assess the influence of SIE on polarizabilities by comparing results with accurate reference data. Our results confirm that the general overestimation of molecular polarizabilities by these density functional approximations can be attributed to SIE. However, removing SIE using the Perdew–Zunger self-interaction-correction (PZ-SIC) method, implemented using the Fermi–Löwdin Orbital SIC approach, leads to an underestimation of molecular polarizabilities, showing that PZ-SIC overcorrects when combined with LSDA or GGA. Application of a recently proposed locally scaled SIC [Zope, et al., J. Chem. Phys. , 2019, 151 , 214108] is found to provide more accurate polarizabilities. We attribute this to the ability of the local scaling scheme to selectively correct for SIE in the regions of space where the correction is needed most.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Coupling and Decoupling between Stickers and Backbones in Associating Polymers with Terminally Functionalized Side Chains

Associating polymers have recently attracted tremendous attention as self-healing polymers due to the dynamic reversibility of sticker association–dissociation processes. These sticker dynamics inevitably slow significantly as segmental dynamics decelerate below the glass transition temperature that limits the operational temperatures of associating polymers. Using broadband dielectric spectroscopy on a new set of associating polymers composed side chains of various lengths and terminal carboxylic-acid sticker functionality, we discovered an unexpected decoupling near the glass transition (T g ) between the slower backbone and fast sticker motions. These two motions have distinct activation energies for the motion of the sulfur linkage adjacent to the backbone (~22 to 26 kJ/mol) and the carboxylic acid groups (~5 to 8 kJ/mol). A second decoupling appears in the polymer with the longest side chain length at T g – 20 K, reflecting the dynamics of various carboxylic acid binding configurations. Furthermore, our findings open the door to design associating polymers with the capability of sticker association/dissociation at low temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Bidentate Lewis bases are preferred for passivation of MAPbI 3 surfaces: A time-domain ab initio analysis

We report chemical passivation is a predominant approach to inhibit intrinsic defects responsible for electron–hole recombination in perovskite solar cells. Using time-domain density functional theory combined with nonadiabatic molecular dynamics, we demonstrate defect passivation by separation of electrons and holes in metal halide perovskites (MHPs), and show that bidentate ligands exhibit the best performance. Defects in traditional semiconductors create deep midgap states, and passivation eliminates these states. In contrast, common defects produce no deep midgap states in MHPs. Instead, defects localize electrons and holes around defect sites, enhancing electron–hole interaction. Defect passivation in MHPs acts to separate charges, decreasing electron–hole and charge–phonon interactions, and increasing charge lifetimes. Bidentate ligands work best, because they can passivate both unsaturated chemical bonds created due to vacancy defects. Bidentate ligands with spatially separated binding sites are preferred, since they provide better match to the sparse inorganic lattice of MHPs. Similar to the Lewis base ligands, water also acts as a ligand and extends charge lifetimes, with the oxygen atom donating its lone electron pair to the defect site. However, water accelerates chemical degradation of MHPs. The binding energy of most ligands is larger than that of water, and therefore, the ligands displace water, increase MHP stability and prolong carrier lifetimes. The established physical mechanism of defect passivation, and the specific principles guiding the choice of passivating molecules advance our understanding of the exceptional properties of MHPs and suggest routes for further improvement of MHP performance in solar energy and optoelectronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Atomistic simulations of the thermal conductivity of liquids

We present a method based on sinusoidal approach to equilibrium molecular dynamics (SAEMD) to compute the thermal conductivity of liquids Similar to nonequilibrium molecular dynamics, and unlike equilibrium simulations based on the Green-Kubo formalism, the method only requires the calculation of forces and total energies. The evaluation of heat fluxes and energy densities is not necessary, thus offering the promise of efficiently implementing first principles simulations based on density functional theory or deep molecular dynamics. Our approach is a generalization of SAEMD for solids, where the thermal conductivity is computed in the steady state, instead of a transient regime, thus properly taking into account diffusive terms in the heat equation. We present results for liquid water at ambient conditions and under pressure and discuss simulation requirements to obtain converged values of the thermal conductivity as a function of size and simulation time.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermal Neutron Scattering Research and Development at Oak Ridge National Laboratory [Slides]

This presentation provides an overview of the project, specifically describing how neutron cross sections can be broken up into several regions. It also discusses how thermal scattering law (TSL) $\textit{S(α, β)}$ is related to dynamic structure factor $\textit{S(q, E)}$ and how $\textit{S(q, E)}$ can be broken up into 2 primary components, incoherent and coherent, and how it can be calculated in several ways, including density functional theory (DFT) and molecular dynamics (MT). Additionally, it states that ENDF currently stores coherent elastic (Bragg edges), incoherent elastic and incoherent inelastic. Also discussed are the experimental capabilities, evaluations, and uncertainty quantification of the project.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗