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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Modulating solvation interactions of deep eutectic solvents formed by ammonium salts and carboxylic acids through varying the molar ratio of hydrogen bond donor and acceptor

Deep eutectic solvents (DESs) have gained increasing popularity in separation science due to the fact that their physico-chemical properties can be easily fine-tuned by varying the type or ratio of hydrogen bond acceptor (HBA) and hydrogen bond donor (HBD). While it is well-known that the molar ratio of HBA/HBD affects the melting point of a eutectic mixture, much less is understood regarding its effect on the magnitude of individual solvation interactions. This is largely due to the fact that established solvatochromic dye methods lack sensitivity when the HBA/HBD ratio is varied slightly in a eutectic mixture. Herein, this study is the first to measure the variation of DES solvation interactions with small changes in the molar ratio of HBA/HBD using inverse gas chromatography (IGC). Solute-solvent interactions of three different DES systems comprised of ammonium salts and organic acids were examined. The probe molecules were studied for 18 eutectic mixtures of varied HBA and HBD composition. We report DES hydrogen bond basicity, hydrogen bond acidity, and dispersive-type interactions exhibited the greatest change when the molar ratio of HBA/HBD was varied in the eutectic mixture. Results from this study demonstrate that the HBA/HBD ratio can be used to modulate the solvation characteristics for this class of DESs in separations and that the stoichiometric ratio of the HBA/HBD is important in ensuring their reproducible preparation.

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

Understanding Gas Absorption in Multivalent Ionic Liquids via Solute-Solvent Interaction Analyses

Solute-solvent interactions are often evaluated to understand and explain gas solubilities. This information is regularly used to interpret gas solubility and separation within ionic liquids (ILs). Here, we use several different quantum chemical and previous molecular dynamics simulation results to show that strong solute-solvent interactions neither lead to high solubility nor to high selectivity, with respect to other solutes. Instead, the solute-solvent interaction strength with different isolated IL ions is affected by the electrostatic extremes. Also, the solute-solvent interaction with different IL molecules is strongly correlated to the molecular volumes or polarizabilities (within a series of same-anion based ILs).

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

Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track

Blockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine. We generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing. We achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Chemical interaction and compatibility of uranium mononitride and alumina forming austenitic stainless steel

Uranium mononitride (UN) and alumina forming austenitic (AFA) stainless steel are a potential fuel-cladding combination for the lead-cooled fast reactor (LFR). Chemical compatibility between UN and AFA steel needs to be verified before implementation in a nuclear reactor. Diffusion couple experiments at 823 K and 1023 K were conducted for nonirradiated UN samples in contact with as-cast (no thermally grown Al 2 O 3 ) and preoxidized (with thermally grown Al 2 O 3 ) AFA for 500 and 1000 h in an inert environment. Preoxidized AFA exhibited little to no interaction with all UN samples tested at both 823 K and 1023 K, displaying the stability and capability of the Al 2 O 3 layer to prevent chemical interaction and inter-diffusion with UN. Chemical interaction occurs between UN and as-cast AFA. At 1023 K, an aluminum and nitrogen rich phase (likely AlN) formed along the interface of as-cast AFA and UN samples. At 823 K the AlN phase was not prominently observed due to the reduced diffusivity of aluminum through AFA. The aluminum and nitrogen-enriched phase was also observed in a high temperature pressure-assisted test sample of UN and as-cast AFA thermally treated at 1373 K. Finally, in UN samples doped with a low weight percent of UO 2 (< 3 wt%), AlN was not detected along the interface at either temperatures, and an Al 2 O 3 layer likely formed along the interface and prevented further chemical interaction between UN and as-cast AFA.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Crystallographic and temperature effects in low-energy collisions for plasma–material interactions

The interaction of plasma with materials is critical for the fundamental understanding of non-equilibrium processes and their wide application. Recent achievements in fusion energy research emphasize the importance of this problem. Because modelling and predicting plasma–material interactions (PMI) require considering a tremendous number of single plasma particle–surface interaction events, this type of modelling was, until recently, possible only within a binary collision approximation (BCA). The BCA approach considers materials as uniform temperature-insensitive media. The research presented here addresses the PMI problem within an atomistic-based approach for the first time at a statistically significant level. Approximately 10 5 molecular dynamics trajectories were generated for 100 eV deuterium ions interacting with a tungsten surface. The research demonstrated the critical importance of incorporating the discrete lattice structure of matter into the model. Deuterium penetration depth and fraction of backscattered deuterium ions strongly depend on the surface orientation, the impact incident ion directions, and the ions’ initial positions. On average, the BCA-based calculations underestimate the penetration depth by a factor of two or more, and the fraction of backscattered atoms is overestimated by a factor of two or more. As a result, increasing the material temperature from 500 to 3000 K reduces penetration depth by about 30% and increases the fraction of backscattered atoms by 250%.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effect of TiN coating on suppressing Ce-Fe interaction under irradiation

Advanced cladding is critical for fast reactors with the adequate thermal conductivity, mechanical stability and radiation tolerance of the cladding base material, corrosion resistance and high temperature coolant compatibility of the cladding surface, and chemical stability of the cladding inner wall against fuel cladding chemical interaction (FCCI). The preliminary results of recent ion irradiation studies of two diffusion-couple samples of cerium (Ce)/oxide-dispersion strengthened steel (ODS) and Ce/TiN/ODS, irradiated with 80 MeV xenon (Xe) ions to 100 displacements per atom (dpa) at 500°C, are summarized. Significant Ce-Fe interaction occurred in the Ce/ODS sample, and no noticeable Ce-Fe interaction was found in the Ce/TiN/ODS sample. It shows the effectiveness of 1-µm TiN diffusion barrier coated by the pulsed laser deposition on suppressing Ce-Fe interaction, a major contributor to FCCI in cladding. Here, density function theory (DFT) calculations of the impurity diffusivities of Ce and Fe within the Ti sublattice of TiN were performed to assist a mechanistic understanding of the experimental results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

A machine learning-based interaction force model for non-spherical and irregular particles in low Reynolds number incompressible flows

In this study, interaction force of non-spherical particles in low Reynolds number gas-solid flow is investigated by neural network approaches. An artificial neural network (ANN) model is developed to correlate the non-spherical particle shape and the flow conditions with the interaction force. To define the particle shape, spherical harmonic expansion is applied. Furthermore, variational autoencoder model is then used to extract latent geometric features. The latent vector is utilized as an input with the Reynolds number for the ANN. The interaction force data, which is used as output data of the ANN, is obtained by particle resolved direct numerical simulation for 5200 non-spherical particles. The proposed model enables unsupervised extraction for non-spherical particle shapes and accurate predictions on the interaction force without heavy computation. This study provides the model that can explain complicated shapes of particles and be applied to a large scale, computational fluid dynamics simulation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Local atomic environment analysis of short and long-range solute-solute interactions in a symmetric tilt grain boundary

We develop an efficient molecular-statics algorithm for predicting local solute-solute interaction effects on grain-boundary segregation. This algorithm is applied to the segregation and interaction of Ni and Cu solutes in a Σ9 (221) symmetric tilt grain boundary in Ag. It is found that the strength of interaction between two solutes directly correlates with the change of average segregation energy in the local atomic environment of a fixed grain-boundary solute. It is shown that local interaction effects at grain boundaries can be either attractive or repulsive wherein long-range attractive effects increase the propensity for solute cluster nucleation. This study underscores the atomic nature of grain-boundary solute segregation and provides a tool that could yield meaningful insight into heterogeneous solute segregation phenomena in polycrystalline alloys beyond their dilute limit.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Shaker-structure interaction modeling and analysis for nonlinear force appropriation testing

Nonlinear force appropriation is an extension of its linear counterpart where sinusoidal excitation is applied to a structure with a modal shaker and phase quadrature is achieved between the excitation and response. While a standard practice in modal testing, modal shaker excitation has the potential to alter the dynamics of the structure under test. Previous studies have been conducted to address several concerns, but this work specifically focuses on a shaker-structure interaction phenomenon which arises during the force appropriation testing of a nonlinear structure. Under pure-tone sinusoidal forcing, a nonlinear structure may respond not only at the fundamental harmonic but also potentially at sub- or superharmonics, or it can even produce aperiodic and chaotic motion in certain cases. Shaker-structure interaction occurs when the response physically pushes back against the shaker attachment, producing non-fundamental harmonic content in the force measured by the load cell, even for pure tone voltage input to the shaker. This work develops a model to replicate these physics and investigates their influence on the response of a nonlinear normal mode of the structure. Experimental evidence is first provided that demonstrates the generation of harmonic content in the measured load cell force during a force appropriation test. This interaction is replicated by developing an electromechanical model of a modal shaker attached to a nonlinear, three-mass dynamical system. Several simulated experiments are conducted both with and without the shaker model in order to identify which effects are specifically due to the presence of the shaker. Finally, the results of these simulations are then compared to the undamped nonlinear normal modes of the structure under test to evaluate the influence of shaker-structure interaction on the identified system’s dynamics.

42 ENGINEERING↗
DOE OSTI2023

Tuning the Interaction between Platinum Single Atoms and Ceria by Zirconia Doping for Efficient Catalytic Ammonia Oxidation

Aiming at the development of an efficient NH 3 oxidation catalyst to eliminate the harmful NH 3 slip from the stationary flue gas denitrification system and diesel exhaust aftertreatment system, a facile ZrO 2 doping strategy was proposed to construct Pt 1 /Ce x Zr 1–x O 2 catalysts with a tunable Pt-CeO 2 interaction strength and Pt–O–Ce coordination environment. According to the results of systematic characterizations, Pt species supported on Ce x Zr 1–x O 2 were mainly in the form of single atoms when x ≥ 0.7, and the strength of the Pt-CeO 2 interaction and the coordination number of Pt–O–Ce bond (CN Pt–O–Ce ) on Pt 1 /Ce x Zr 1–x O 2 showed a volcanic change as a function of the ZrO 2 doping amount. Here, it was proposed that the balance between the reasonable concentration of oxygen defects and limited surface Zr–O x species well accounted for the strongest Pt-CeO 2 interaction and the highest CN Pt–O–Ce on Pt/Ce 0.9 Zr 0.1 O 2 . It was observed that the Pt/Ce 0.9 Zr 0.1 O 2 catalyst exhibited much higher NH 3 oxidation activity than other Pt/Ce x Zr 1–x O 2 catalysts. The mechanism study revealed that the Pt 1 species with the stronger Pt-CeO 2 interaction and higher CN Pt–O–Ce within Pt/Ce 0.9 Zr 0.1 O 2 could better activate NH 3 adsorbed on Lewis acid sites to react with O 2 thus resulting in superior NH 3 oxidation activity. This work provides a new approach for designing highly efficient Pt/CeO 2 based catalysts for low-temperature NH 3 oxidation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multipole Expansion of Atomic Electron Density Fluctuation Interactions in the Density-Functional Tight-Binding Method

The accuracy of the density-functional tight-binding (DFTB) method in describing noncovalent interactions is limited due to its reliance on monopole-based spherical charge densities. In this study, we present a multipole-extended second-order DFTB (mDFTB2) method that takes into account atomic dipole and quadrupole interactions. Furthermore, we combine the multipole expansion with the monopole-based third-order contribution, resulting in the mDFTB3 method. To assess the accuracy of mDFTB2 and mDFTB3, we evaluate their performance in describing noncovalent interactions, proton transfer barriers, and dipole moments. Here, our benchmark results show promising improvements even when using the existing electronic parameters optimized for the original DFTB3 model. Both mDFTB2 and mDFTB3 outperform their monopole-based counterparts, DFTB2 and DFTB3, in terms of accuracy. While mDFTB2 and mDFTB3 perform comparably for neutral and positively charged systems, mDFTB3 exhibits superior performance over mDFTB2 when dealing with negatively charged systems and proton transfers. Overall, the incorporation of the multipole expansion significantly enhances the accuracy of the DFTB method in describing noncovalent interactions and proton transfers.

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

COCOMO2: A Coarse-Grained Model for Interacting Folded and Disordered Proteins

Biomolecular interactions are essential in many biological processes, including complex formation and phase separation processes. Coarse-grained computational models are especially valuable for studying such processes via simulation. Here, we present COCOMO2, an updated residue-based coarse-grained model that extends its applicability from intrinsically disordered peptides to folded proteins. This is accomplished with the introduction of a surface exposure scaling factor, which adjusts interaction strengths based on solvent accessibility, to enable the more realistic modeling of interactions involving folded domains without additional computational costs. COCOMO2 was parametrized directly with solubility and phase separation data to improve its performance on predicting concentration-dependent phase separation for a broader range of biomolecular systems compared to the original version. COCOMO2 enables new applications including the study of condensates that involve IDPs together with folded domains and the study of complex assembly processes. COCOMO2 also provides an expanded foundation for the development of multiscale approaches for modeling biomolecular interactions that span from residue-level to atomistic resolution.

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

Correction to “COCOMO2: A Coarse-Grained Model for Interacting Folded and Disordered Proteins”

Biomolecular interactions are essential in many biological processes, including complex formation and phase separation processes. Coarse-grained computational models are especially valuable for studying such processes via simulation. Here, we present COCOMO2, an updated residue-based coarse-grained model that extends its applicability from intrinsically disordered peptides to folded proteins. This is accomplished with the introduction of a surface exposure scaling factor, which adjusts interaction strengths based on solvent accessibility, to enable the more realistic modeling of interactions involving folded domains without additional computational costs. COCOMO2 was parametrized directly with solubility and phase separation data to improve its performance on predicting concentration-dependent phase separation for a broader range of biomolecular systems compared to the original version. COCOMO2 enables new applications including the study of condensates that involve IDPs together with folded domains and the study of complex assembly processes. COCOMO2 also provides an expanded foundation for the development of multiscale approaches for modeling biomolecular interactions that span from residue-level to atomistic resolution.

Molecular interactions↗
DOE OSTI2024

Probing Interactions between Adsorbed Polymers and γ-Al 2 O 3 Using Solid-State NMR

The interactions between polymers and metal oxide surfaces affect the physical properties of polymer composites and the selectivity of catalysts used for plastic conversion. Gauging the strengths of these interactions and how they depend on adsorption conformations and polymer structure is nevertheless quite challenging. Herein, we evaluate whether a recently introduced dynamic nuclear polarization-based surface-to-atom distance measurement method can be used to gauge the specific interactions between five vinyl polymers and an oxide support (alumina). The adsorption conformations of polymer monolayers were studied using site-specific 13 C{ 27 Al} rotational-echo saturation-pulse double-resonance (RESPDOR) experiments. The method is effective in revealing the average distance between the adsorbed polymer and the surface, as well as the fraction of the monomers that are adsorbed. Polymers that possess larger side chains are more weakly adsorbed, as evidenced by their formation of more numerous loop and tail structures. In conclusion, the measured RESPDOR dephasing data further reveals that polymer adsorption conformations are largely disordered and involve few hydrogen bonding interactions.

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

Complex pH-Dependent Interactions between Weak Polyelectrolyte Block Copolymer Micelles and Molecular Fluorophores

Amphiphilic block copolymers with weak polyelectrolyte blocks can assemble stimulus-responsive nanostructures and interfaces. Applications of these materials in drug delivery, biomimetics, and sensing largely rely on the well-understood swelling of polyelectrolyte chains upon deprotonation, often induced by changes in pH or ionic strength. This deprotonation can also tune interfacial interactions between the polyelectrolyte blocks and surrounding solution, an effect which is less studied than morphological swelling of polyelectrolytes but can be just as critical for intended function. Here, we investigate whether the pH-driven morphological response of polyelectrolyte-bearing nanostructures also affects the interactions of these nanostructures with molecules in solution, using micelles of a short-chain polybutadiene-block-poly(acrylic acid) (pBd–pAA) as a model system. Here we introduce a Förster resonance energy transfer (FRET) approach to probe interactions between micelles and fluorescent molecular solutes as a function of solution pH. As expected, the pAA corona of these pBd–pAA micelles increases in thickness monotonically as a function of pH. However, FRET efficiency, which provides a metric of the spatial proximity of fluorescently labeled micelles and freely diffusing fluorophores, exhibits complex nonmonotonic behavior as a function of pH, indicating that the average separation of micelles and acceptor fluorophores is not strictly correlated with micelle swelling. Dialysis experiments quantify the affinity of fluorophores for micelles as a function of pH, confirming that changes in FRET are driven almost entirely by the pH-dependent affinity of the pAA block for the investigated molecular fluorophores, not simply by a shape change of the pAA corona. This study provides key insights into the interfacial interactions between weak-polyelectrolyte-bearing nanostructures and molecular solutes, of importance for the development of their stimulus-responsive applications.

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

Reassembly of Peptide Nanofibrils on Live Cell Surfaces Promotes Cell–Cell Interactions

Nature regulates cellular interactions through the cell-surface molecules and plasma membranes. Despite advances in cell-surface engineering with diverse ligands and reactive groups, modulating cell–cell interactions through scaffolds of the cell-binding cues remains a challenging endeavor. Here, we assembled peptide nanofibrils on live cell surfaces to present the ligands that bind to the target cells. Surprisingly, with the same ligands, reducing the thermal stability of the nanofibrils promoted cellular interactions. Characterizations of the system revealed a thermally induced fibril disassembly and reassembly pathway that facilitated the complexation of the fibrils with the cells. Using the nanofibrils of varied stabilities, the cell–cell interaction was promoted to different extents with free-to-bound cell conversion ratios achieved at low (31%), medium (54%), and high (93%) levels. Further, this study expands the toolbox to generate desired cell behaviors for applications in many areas and highlights the merits of thermally less stable nanoassemblies in designing functional materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Understanding the Impacts of Support–Polymer Interactions on the Dynamics of Poly(ethyleneimine) Confined in Mesoporous SBA-15

Supported amines are a promising class of CO 2 sorbents offering large uptake capacities and fast uptake rates. Additionally, among supported amines, poly(ethyleneimine) (PEI) physically impregnated in the mesopores of SBA-15 silica is widely used. Within these composite materials, the chain dynamics and morphologies of PEI strongly influence the CO 2 capture performance, yet little is known about chain and macromolecule mobility in confined pores. Here, we probe the impact of the support–PEI interactions on the dynamics and structures of PEI at the support interface and the corresponding impact on CO 2 uptake performance, which yields critical structure–property relationships. The pore walls of the support are grafted with organosilanes with different chemical end groups to differentiate interaction modes (spanning from strong attraction to repulsion) between the pore surface and PEI. Combinations of techniques, such as quasi-elastic neutron scattering (QENS), 1 H T 1 –T 2 relaxation correlation solid-state NMR, and molecular dynamics (MD) simulations, are used to comprehensively assess the physical properties of confined PEI. We hypothesized that PEI would have faster dynamics when subjected to less attractive or repulsive interactions. However, we discover that complex interfacial interactions resulted in complex structure–property relationships. Indeed, both the chain conformation of the surface-grafted chains and of the PEI around the surface influenced the chain mobility and CO 2 uptake performance. By coupling knowledge of the dynamics and distributions of PEI with CO 2 sorption performance and other characteristics, we determine that the macroscopic structures of the hybrid materials dictate the first rapid CO 2 uptake, and the rate of CO 2 sorption during the subsequent gradual uptake stage is determined by PEI chain motions that promote diffusive jumps of CO 2 through PEI-packed domains.

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

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗