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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Atomistic-Scale Simulations on Graphene Bending Near a Copper Surface

Molecular insights into graphene-catalyst surface interactions can provide useful information for the efficient design of copper current collectors with graphitic anode interfaces. As graphene bending can affect the local electron density, it should reflect its local reactivity as well. Using ReaxFF reactive molecular simulations, we have investigated the possible bending of graphene in vacuum and near copper surfaces. We describe the energy cost for graphene bending and the binding energy with hydrogen and copper with two different ReaxFF parameter sets, demonstrating the relevance of using the more recently developed ReaxFF parameter sets for graphene properties. Moreover, the draping angle at copper step edges obtained from our atomistic simulations is in good agreement with the draping angle determined from experimental measurements, thus validating the ReaxFF results.

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

Determination of Molecular Structure and Dynamics of Molten Salts by Advanced Neutron and X-ray Scattering Measurements and Computer Modeling

The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Bioinspired energy absorbing material designs using additive manufacturing

Nature provides many biological materials and structures with exceptional energy absorption capabilities. Few, relatively simple molecular building blocks (e.g., calcium carbonate), which have unremarkable intrinsic mechanical properties individually, are used to produce biopolymer-bioceramic composites with unique hierarchical architectures, thus producing biomaterial-architectures with extraordinary mechanical properties. Several biomaterials have inspired the design and manufacture of novel material architectures to address various engineering problems requiring high energy absorption capabilities. For example, the microarchitecture of seashell nacre has inspired multi-material 3D printed architectures that outperform the energy absorption capabilities of monolithic materials. Using the hierarchical architectural features of biological materials, iterative design approaches using simulation and experimentation are advancing the field of bioinspired material design. However, bioinspired architectures are still challenging to manufacture because of the size scale and architectural hierarchical complexity. Notwithstanding, additive manufacturing technologies are advancing rapidly, continually providing researchers improved abilities to fabricate sophisticated bioinspired, hierarchical designs using multiple materials. This review describes the use of additive manufacturing for producing innovative synthetic materials specifically for energy absorption applications inspired by nacre, conch shell, shrimp shell, horns, hooves, and beetle wings. Potential applications include athletic prosthetics, protective head gear, and automobile crush zones.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Perimatrix of middle ear cholesteatoma: A granulation tissue with a specific transcriptomic signature

Objectives/Hypothesis: To establish comprehensive transcriptomic profiles of cholesteatoma perimatrix tissue and granulation tissue from chronic otitis media (COM) that did not develop cholesteatoma, which can indicate molecular pathways involved in the cholesteatoma perimatrix pathology and invasiveness. Study Design: Retrospective Case Series. Methods: Transcriptome data were obtained from cholesteatoma perimatrix tissue and COM granulation tissue by an Illumina iScan microarray. Differentially expressed genes (DEGs) were subsequently analyzed using both bioinformatical functional annotation and network analysis. Expression of candidate genes (MMP9 and LCN2) was validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on a larger group of samples. Results: Analysis of the transcriptome led to the identification of 169 differentially expressed genes between investigated tissues. Bioinformatic analysis suggested that most significant biological processes involving DEGs were previously described in cholesteatoma pathology. Network analysis identified ERBB2, TFAP2A, and TP63 as major hubs of the DEGs molecular network. Furthermore, it was observed that the cellular component most significantly enriched in DEGs was extracellular space containing 47 DEGs. Using qRT-PCR, it was confirmed that mRNA levels of the major extracellular hub (MMP9) are increased, whereas its interacting molecule (LCN2) mRNA levels were decreased in cholesteatoma perimatrix tissue compared to COM granulation tissue. Conclusions: The current study approach offers an overall look at molecular mechanisms that describe the cholesteatoma entity by focusing exclusively on the perimatrix processes in comparison to COM granulation tissue. The observed differences in gene expression between cholesteatoma perimatrix and COM granulation tissue could suggest novel markers potentially influenced by the perimatrix–matrix molecular interplay, which is not present in COM without cholesteatoma. Level of Evidence: NA. Laryngoscope, 130:E220–E227, 2020. © 2019 The American Laryngological, Rhinological and Otological Society, Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Molecular and Topographical Organization: Influence on Cicada Wing Wettability and Bactericidal Properties

Numerous natural surfaces have micro/nanostructures that result in extraordinary functionality, such as superhydrophobicity, self-cleaning, antifogging, and antimicrobial properties. One such example is the cicada wing, where differences in nanopillar geometry and composition among species can impact and influence the degree of exhibited properties. To understand the relationships between surface topography and chemical composition with multifunctionality, the wing properties of Neotibicen pruinosus (superhydrophobic) and Magicicada cassinii (hydrophobic) cicadas are investigated at time points after microwave-assisted extraction of surface molecules to characterize the chemical contribution to nanopillar functionality. Electron microscopy of the wings throughout the extraction process illustrates nanoscale topographical changes, while concomitant changes in hydrophobicity, bacterial fouling, and bactericidal properties are also measured. Extract analysis reveals the major components of the nanostructures to be fatty acids and saturated hydrocarbons ranging from C17 to C44. Effects on the antimicrobial character of a wing surface with respect to the extracted chemicals suggest that the molecular composition of the nanopillars plays both a direct and an indirect role in concert with nanopillar geometry. The data presented not only correlates the nanopillar molecular organization to macroscale functional properties, but it also presents design guidelines to consider during the replication of natural nanostructures onto engineered substrates to induce desired properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Regulation of Electron Cloud Density by Electronic Effects of Substituents to Optimize Photocatalytic H 2 Evolution of Carbon Dots

Carbon dots (CDs) have a wide light absorption range, which are promising candidates for photocatalytic water splitting H 2 evolution, but they show low activity for hydrogen evolution reaction (HER) due to the slow transfer efficiencies of photogenerated carriers. The electron cloud density of photocatalyst is essential for the separation and migration of photogenerated carriers. In this study, the effect mechanism of electron cloud density regulated by the substituents with different electronic effects on the photocatalytic HER of glucose-based CDs is clarified. CDs-SO 3 H and CDs-OH are first obtained by introducing electron-drawing group (–SO 3 H) and electron-donating group (–OH) using a tailoring post-processing strategy. Experimental results show that the H 2 yield catalyzed by CDs-SO 3 H is 89.95 µmol•g –1 in 4 h, which is about four times that of CDs, and 7.4 times that of CDs-OH. The –SO 3 H induces a much negative energy band and high electron cloud density on CDs edges, promoting the separation and transfer of photogenerated carriers; while the CDs-OH exhibits a high positive charge density and an upward energy band, hindering the surface complexation of electron-hole pairs and HER. Furthermore, this study will provide an insight into the design of CDs catalysts with efficient photocatalytic HER at a molecular level.

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

Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach. In this work, we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets. Firstly, we develop a novel coarse-graining method, to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets. Inspired by the weighted essentially non-oscillatory (WENO) scheme, the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil, then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities. Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion. In the first phase, we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties. Then, in the second phase, the material damage criterion is learnt as a smoothed step function from the data with fractures. As a result, a peridynamics surrogate is obtained. As a continuum model, our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training, and hence allows for substantial reductions in computational cost compared with MD. We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene. Our tests show that the proposed data-driven model is robust and generalizable, in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Chloride Insertion Enhances the Electrochemical Oxidation of Iron Hydroxide Double-Layer Hydroxide into Oxyhydroxide in Alkaline Iron Batteries

Rechargeable alkaline iron batteries that constitute environmentally benign electrolytes and earth-abundant industrial materials are desirable green solutions for large-scale energy storage. As one of the most abundant metal elements in the earth’s crust, iron (Fe) can satisfy nearly all criteria for low-cost and safe battery electrodes. However, challenges in achieving reversible Fe redox impede their extensive implementation in modern energy supply systems. Here, this study revealed that Cl-anion insertion into Fe(OH) 2 layered double hydroxide (LDH) formed a green rust intermediate phase with the formula [Fe 2 2+ Fe 1 3+ (HO – ) 6 ] + [Cl] – , which assisted a high Fe(OH) 2 /FeOOH conversion reaction (64.7%) and improved cycling stability. This new iron redox chemistry was validated by operando X-ray diffraction, electrochemical testing, X-ray absorption spectroscopy (XAS), X-ray photoelectron spectroscopy (XPS) analysis, scanning transmission electron microscopy–energy-dispersive X-ray spectroscopy (STEM-EDS) mapping, and molecular dynamics (MD) simulations. Our study provides new insight into designing LDH materials for high-capacity alkaline iron batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cyclic Peptides for Lanthanide Binding

Lanthanide ions are difficult to separate from one another due to their similar chemical properties. The discovery of lanthanide-binding peptides and proteins in nature has led to an increased interest in the possibility of utilizing the strong binding of peptides to lanthanide ions for their separations; as such, there has been an effort to identify or design peptides with improved lanthanide binding and selectivity toward particular lanthanide ions. Here, in this study, we designed and characterized lanthanide-binding cyclic peptides (LBCPs) with molecular dynamics simulations, electronic structure calculations, and emission spectroscopy. Luminescent decay measurements were done to determine the number of water molecules coordinated to the Eu 3+ ion in Eu-LBCP complexes and compare to the predicted number of water molecules by computation to assess the lanthanide-binding affinity of LBCPs. Measured stability constants show binding of the LBCPs to the Eu 3+ ion with stronger than micromolar affinity. We were able to identify multiple peptides that selectively bind to middle lanthanides. We describe the structural basis of the lanthanide-binding selectivity trend with strongest binding to the middle lanthanides, followed by the heavier lanthanides, and finally to the lighter ions.

ions↗
DOE OSTI2024

Nanoconfinement of Carbon Dioxide within Interfacial Aqueous/Ionic Liquid Systems

Nanoporous, gas-selective membranes have shown encouraging results for the removal of CO 2 from flue gas, yet the optimal design for such membranes is often unknown. Therefore, we used molecular dynamics simulations to elucidate the behavior of CO 2 within aqueous and ionic liquid (IL) systems ([EMIM][TFSI] and [OMIM][TFSI]), both confined individually and as an interfacial aqueous/IL system. We found that within aqueous systems the mobility of CO 2 is reduced due to interactions between the CO 2 oxygens and hydroxyl groups on the pore surface. Within the IL systems, we found that confinement has a greater effect on the [EMIM][TFSI] system as opposed to the [OMIM][TFSI] system. Paradoxically, the larger and more asymmetrical [OMIM]+ molecule undergoes less efficient packing, resulting in fewer confinement effects. Finally, free energy surfaces of the nanoconfined aqueous/IL interface demonstrate that CO 2 will transfer spontaneously from the aqueous to the IL phase.

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

Morphological Transitions of a Photoswitchable Aramid Amphiphile Nanostructure

Self-assembly of small amphiphilic molecules in water can lead to nanostructures of varying geometries with pristine internal molecular organization. Here we introduce a photoswitchable aramid amphiphile (AA), designed to exhibit extensive hydrogen bonding and robust mechanical properties upon self-assembly, while containing a vinylnitrile group for photoinduced cis-trans isomerization. We demonstrate spontaneous self-assembly of the vinylnitrile-containing AA in water to form nanoribbons. Upon UV irradiation, trans-to-cis isomerizations occur concomitantly with a morphological transition from nanoribbons to nanotubes. The nanotube structure persists in water for over six months, stabilized by strong and collective intermolecular interactions. We demonstrate that the nanoribbon-to-nanotube transition is reversible upon heating and that switching between states can be achieved repeatedly. Finally, we use electron microscopy to capture the transition and propose mechanisms for nanoribbon-to-nanotube rearrangement and vice versa. This stability and switchability of photoresponsive AA nanostructures make them viable for a range of future applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Molecular Interaction Regulates the Performance and Longevity of Defect Passivation for Metal Halide Perovskite Solar Cells

Defect passivation constitutes one of the most commonly used strategies to fabricate highly efficient perovskite solar cells (PSCs). However, the durability of the passivation effects under harsh operational conditions has not been extensively studied regardless of the weak and vulnerable secondary bonding between the molecular passivation agents and perovskite crystals. Here, we incorporated strategically designed passivating agents to investigate the effect of their interaction energies on the perovskite crystals and correlated these with the performance and longevity of the passivation effects. We unraveled that the passivation agents with a stronger interaction energy are advantageous not only for effective defect passivation but also to suppress defect migration. The prototypical PSCs treated with the optimal passivation agent exhibited superior performance and operational stability, retaining 81.9 and 85.3% of their initial performance under continuous illumination or nitrogen at 85 °C after 1008 h, respectively, while the reference device completely degraded during that time. Furthermore, this work provides important insights into designing operationally durable defect passivation agents for perovskite optoelectronic devices.

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

Mechanistic Investigation of Molybdenum Disulfide Defect Photoluminescence Quenching by Adsorbed Metallophthalocyanines

Lattice defects play an important role in determining the optical and electrical properties of monolayer semiconductors such as MoS 2 . Although the structures of various defects in monolayer MoS 2 are well studied, little is known about the nature of the fluorescent defect species and their interaction with molecular adsorbates. In this study, the quenching of the low-temperature defect photoluminescence (PL) in MoS 2 is investigated following the deposition of metallophthalocyanines (MPcs). The quenching is found to significantly depend on the identity of the phthalocyanine metal, with the quenching efficiency decreasing in the order CoPc > CuPc > ZnPc, and almost no quenching by metal-free H 2 Pc is observed. Futher, time-correlated single photon counting (TCSPC) measurements corroborate the observed trend, indicating a decrease in the defect PL lifetime upon MPc adsorption, and the gate voltage-dependent PL reveals the suppression of the defect emission even at large Fermi level shifts. Density functional theory modeling argues that the MPc complexes stabilize dark negatively charged defects over luminescent neutral defects through an electrostatic local gating effect. These results demonstrate the control of defectbased excited-state decay pathways via molecular electronic structure tuning, which has broad implications for the design of mixeddimensional optoelectronic devices.

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

Modeling separation of lanthanides via heterogeneous ligand binding

Individual lanthanide elements have physical/electronic/magnetic properties that make each useful for specific applications. Several of the lanthanides cations (Ln 3+ ) naturally occur together in the same ores. They are notoriously difficult to separate from each other due to their chemical similarity. Predicting the Ln 3+ differential binding energies (ΔΔE) or free energies (ΔΔG) at different binding sites, which are key figures of merit for separation applications, will help design of materials with lanthanide selectivity. We apply ab initio molecular dynamics (AIMD) simulations and density functional theory (DFT) to calculate ΔΔG for Ln 3+ coordinated to ligands in water and embedded in metal–organic frameworks (MOFs), and ΔΔE for Ln 3+ bonded to functionalized silica surfaces, thus circumventing the need for the computational costly absolute binding (free) energies ΔG and ΔE. Perturbative AIMD simulations of water-inundated simulation cells are applied to examine the selectivity of ligands towards adjacent Ln 3+ in the periodic table. Static DFT calculations with a full Ln 3+ first coordination shell, while less rigorous, show that all ligands examined with net negative charges are more selective towards the heavier lanthanides than a charge-neutral coordination shell made up of water molecules. Amine groups are predicted to be poor ligands for lanthanide-binding. Finally, we also address cooperative ion binding, i.e., using different ligands in concert to enhance lanthanide selectivity.

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

Engineering tertiary chirality in helical biopolymers

Tertiary chirality describes the handedness of supramolecular assemblies and relies not only on the primary and secondary structures of the building blocks but also on topological driving forces that have been sparsely characterized. Helical biopolymers, especially DNA, have been extensively investigated as they possess intrinsic chirality that determines the optical, mechanical, and physical properties of the ensuing material. Here, we employ the DNA tensegrity triangle as a model system to locate the tipping points in chirality inversion at the tertiary level by X-ray diffraction. We engineer tensegrity triangle crystals with incremental rotational steps between immobile junctions from 3 to 28 base pairs (bp). We construct a mathematical model that accurately predicts and explains the molecular configurations in both this work and previous studies. Our design framework is extendable to other supramolecular assemblies of helical biopolymers and can be used in the design of chiral nanomaterials, optically active molecules, and mesoporous frameworks, all of which are of interest to physical, biological, and chemical nanoscience.

Science & Technology - Other Topics↗
DOE OSTI2025

Discovery of unconventional and nonintuitive self-assembling peptide materials using experiment-driven machine learning

Prediction of peptide secondary structure is challenging because of complex molecular interactions, sequence-specific behavior, and environmental factors. Traditional design strategies, based on hydrophobicity and structural propensity, can be biased and could indeed prevent discovery of interesting, diverse, and unconventional peptides with desired nanostructure assembly. Using β sheet formation in pentapeptides as a case study, we used an integrated high-throughput experimental workflow and an artificial intelligence–driven active learning framework to improve prediction accuracy of self-assembly. By focusing on sequences where machine learning (ML) predictions deviate from conventional design strategies, we synthesized and tested 268 pentapeptides, successfully finding 96 forming β sheet assemblies, including unconventional sequences (e.g., ILFSM, LMISI, MITIY, MISIW, and WKIYI) not predicted by traditional methods. Our ML models outperformed conventional β sheet propensity tables, revealing useful chemical design rules. A web interface is provided to facilitate community access to these models. This work highlights the value of ML-driven approaches in overcoming the limitations of current peptide design strategies.

Talluri, Y. Nissi [Indian Inst. of Technology (IIT↗