Aldol condensation of mixed oxygenates on TiO 2
Kinetic studies of aldol condensation of mixtures on TiO 2 reveal strong suppression of acetone self-condensation in the presence of acetaldehyde.
Oliphant, Brandon Elliott↗
SEARCH · Engineering Papers
Results for “self organization”
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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High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning
Monolayer films have shown promise as a lubricating layer to reduce friction and wear of mechanical devices with separations on the nanoscale. These films have a vast design space with many tunable properties that can affect their tribological effectiveness. For example, terminal group chemistry, film composition, and backbone chemistry can all lead to films with significantly different tribological properties. This design space, however, is very difficult to explore without a combinatorial approach and an automatable, reproducible, and extensible workflow to screen for promising candidate films. Here, using the Molecular Simulation Design Framework (MoSDeF), a combinatorial screening study was performed to explore 9747 unique monolayer films (116 964 total simulations) and a machine learning (ML) model using a random forest regressor, an ensemble learning technique, to explore the role of terminal group chemistry and its effect on tribological effectiveness. The most promising films were found to contain small terminal groups such as cyano and ethylene. The ML model was subsequently applied to screen terminal group candidates identified from the ChEMBL small molecule library. Approximately 193 131 unique film candidates were screened with approximately a five order of magnitude speed-up in analysis compared to simulation alone. The ML model was thus able to be used as a predictive tool to greatly speed up the initial screening of promising candidate films for future simulation studies, suggesting that computational screening in combination with ML can greatly increase the throughput in combinatorial approaches to generate in silico data and then train ML models in a controlled, self-consistent fashion.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Helical Organic and Inorganic Polymers
Despite being a staple of synthetic plastics and biomolecules, helical polymers are scarcely studied with Gaussian-basis-set ab initio electron-correlated methods on an equal footing with molecules. This article introduces an ab initio second-order many-body Green’s-function [MBGF(2)] method with nondiagonal, frequency-dependent Dyson self-energy for infinite helical polymers using screw-axis-symmetry-adapted Gaussian-spherical-harmonics basis functions. Together with the Gaussian-basis-set density-functional theory for energies, analytical atomic forces, translational-period force, and helical-angle force, it can compute correlated energy, quasiparticle energy bands, structures, and vibrational frequencies of an infinite helical polymer, which smoothly converge at the corresponding oligomer results. These methods can handle incommensurable structures, which have an infinite translational period and are hard to characterize by any other method, just as efficiently as commensurable structures. We apply them to polyethylene (2/1 helix), polyacetylene (Peierls’ system), and polytetrafluoroethylene (13/6 helix) to establish the quantitative accuracy of MBGF(2)/cc-pVDZ in simulating their (angle-resolved) ultraviolet photoelectron spectra, and of B3LYP/cc-pVDZ or 6-31G** in reproducing their structures, infrared and Raman band positions, phonon dispersions, and (coherent and incoherent) inelastic neutron scattering spectra. We then predict the same properties for infinitely catenated chains of nitrogen or oxygen and discuss their possible metastable existence under ambient conditions. They include planar zigzag polyazene (N2)x (Peierls’ system), 11/3-helical isotactic polyazane (NH)x, 9/4-helical isotactic polyfluoroazane (NF)x, and 7/2-helical polyoxane (O)x as potential high-energy-density materials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Machine learning for accuracy in density functional approximations
Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. In this paper, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Design of light- and chemically responsive protein assemblies through host-guest interactions
Host-guest (HG) interactions have been widely used to build responsive materials and molecular machines owing to their inherently dynamic nature, interaction specificity, and responsiveness to diverse stimuli. Here, in this work, we have set out to exploit these advantages of HG chemistry in the design of dynamic protein assemblies, using a C 4 symmetric protein, C98 RhuA, as a building block. We show that a C98 RhuA variant individually modified with β-cyclodextrin (βCD) (host) or azobenzene (guest) functionalities can specifically pair with each other to form highly ordered 1D and 2D assemblies. Association and dissociation of βCD RhuA- azo RhuA assemblies can be controlled by UV and visible light as well as by small-molecule modulators of βCD-azobenzene interactions. Kinetics analyses reveal that βCD RhuA- azo RhuA nanotubes assemble without a nucleation barrier, a highly unusual occurrence for helical supramolecular systems. Taken together, our findings provide a compelling example for achieving complex structural and dynamic outcomes in protein assembly through simple chemical design.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Tailoring the Near-Surface Environment of Rh Single-Atom Catalysts for Selective CO 2 Hydrogenation
For this study, we used a combination of experimental spectroscopies, density functional theory calculations, and CO 2 hydrogenation studies to investigate the effects of modifying single-atom Rh 1 /TiO 2 catalysts with functionalized phosphonic acid monolayers. We found that the deposition of specific amine-functionalized ligands resulted in an ~8× increase in site-specific CO 2 reduction turnover frequency at 150 °C and a ~2× increase at 250 °C. On-stream stability also improved following ligand deposition. The effect of the modifier on reactivity was highly sensitive to the proximity of the amine functional group to the surface, which was controlled by adjusting the length of the phosphonic acid tail. Furthermore, deposition of alkyl phosphonic acids without an amine functional group resulted in blocked CO 2 adsorption and a near-complete loss of catalytic activity. Infrared spectroscopy studies suggested that the amine group provided binding sites for CO 2 that enabled hydrogenation when the amine was positioned near a Rh1 site. Phosphonic acid-modified catalysts also exhibited high selectivity to CO over the series product methane; the selectivity effect was traced to modification of the Rh1 sites to favor CO desorption. Phosphonic acid deposition resulted in 80–90% loss of accessible Rh1 sites, likely due to blocking by tail groups. However, even with the loss of sites, under low-temperature reaction conditions, the rates of CO 2 hydrogenation were improved with the coatings, indicating that the remaining sites are highly efficient. Organic functionalization of the supports for atomically dispersed catalysts offers the opportunity to precisely control the positioning of functional groups in the vicinity of a well-defined active site, potentially enabling an additional level of control over active site design.
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Structural Elucidation of a Polypeptoid Chain in a Crystalline Lattice Reveals Key Morphology-Directing Role of the N-Terminus
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Photosynthetically-powered phototactic active nematic liquid crystal fluids and gels
Abstract One of the most ancient forms of life dating to ~3.5 billion years ago, cyanobacteria are highly abundant organisms that convert light into energy and motion, often within conjoined filaments and larger colonies that attract a great deal of interest but their active nematic behavior remained unexplored. Here we demonstrate how light causes a spontaneous self-assembly of two- and three-dimensional active nematic states of cyanobacterial filaments, with a plethora of topological defects. We quantify light-controlled evolutions of orientational and velocity order parameters during the transition between disordered and orientationally ordered states of photosynthetic active matter, as well as the subsequent active nematic’s fluid-gel transformation. Patterned illumination and foreign inclusions with different shapes interact with cyanobacterial active nematics in nontrivial ways while inducing interfacial boundary conditions and fractional boojum defects. Our phototactic model system promises opportunities to systematically explore fundamental properties and technological utility of the liquid crystalline active matter.
Repula, Andrii↗
Pursuing excitonic energy transfer with programmable DNA-based optical breadboards
Nanoscale dye-based excitonic systems assembled on DNA origami in solution excited by a laser. Dyes engage in cascaded FRET with exciton movement guided by programmed elements engaging in homo- and hetero-energy transfer.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Spin-free formulation of the multireference driven similarity renormalization group: A benchmark study of first-row diatomic molecules and spin-crossover energetics
We report a spin-free formulation of the multireference (MR) driven similarity renormalization group (DSRG) based on the ensemble normal ordering of Mukherjee and Kutzelnigg (1997). This ensemble averages over all microstates of a given total spin quantum number, and therefore, it is invariant with respect to SU(2) transformations. As such, all equations may be reformulated in terms of spin-free quantities and they closely resemble those of spin-adapted closed-shell coupled cluster (CC) theory. The current implementation is used to assess the accuracy of various truncated MR-DSRG methods (perturbation theory up to third order and iterative methods with single and double excitations) in computing the constants of 33 first-row diatomic molecules. The accuracy trends for these first-row diatomics are consistent with our previous benchmark on a small subset of closed-shell diatomic molecules. We then present the first MR-DSRG application on transition-metal complexes by computing the spin splittings of the [Fe(H 2 O) 6 ] 2+ and [Fe(NH 3 ) 6 ] 2+ molecules. A focal point analysis (FPA) shows that third-order perturbative corrections are essential to achieve reasonably converged energetics. The FPA based on the linearized MR-DSRG theory with one- and two-body operators and up to a quintuple- ζ basis set predicts the spin splittings of [Fe(H 2 O) 6 ] 2+ and [Fe(NH 3 ) 6 ] 2+ to be –35.7 and –17.1 kcal mol –1 , respectively, showing good agreement with the results of local CC theory with singles, doubles, and perturbative triples.
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Microchemomechanical devices using DNA hybridization
Significance With simple DNA origami lever arms arranged in hinges and accordion structures, we amplify the nanometer displacements from DNA hairpin zippers to 4-μm motion, easily observable and quantified in real space and real time with conventional optical microscopy. Mechanically pulling a bead tethered on the accordion end, we measure high-energy recovery and retraction speeds up to 50 μm/s. On longer time scales, we have also opened and closed the hinges with light and heat. DNA nanotechnology, and particularly DNA origami, combined with colloids and emulsions can provide powerful architectures. The present study is a step toward activating such colloidal/cellular scale devices using DNA as a power source/fuel. We envision artificial active flagella, cilia, micropumps, and other cellular scale devices.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Many-body effects for the Mg 2s XPS of MgO
The energy separation of the higher lying cation XPS binding energies, BEs, for MgO is examined. It is shown that the Hartree–Fock BEs overestimate the separation of the Mg BE(2s) and BE(2p), because an important many-body effect is neglected in the determination of the Hartree–Fock BEs. Once the many-body effect is taken into account, there is good agreement between theory and the XPS measurement. The character of this atomic many-body effect is established in terms of a nearly degenerate configuration that is needed to describe the wavefunction when an Mg 2s electron is ionized. Further, the results provide additional evidence of the ionic character of the MgO crystal. Given the atomic character of the many-body effect, it is likely to apply also to the BE separations of other closed shell oxides.
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Nanoparticle self-assemblies with modern complexity
Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.
36 MATERIALS SCIENCE↗
Site-Selective Real-Time Observation of Bimolecular Electron Transfer in a Photocatalytic System Using L-Edge X-Ray Absorption Spectroscopy
Here, time-resolved X-ray absorption spectroscopy has been utilized to monitor the bimolecular electron transfer in a photocatalytic water splitting system. This has been possible by uniting the local probe and element specific character of X-ray transitions with insights from high-level ab initio calculations. The specific target has been a heteroleptic [Ir III (ppy) 2 (bpy)] + photosensitizer, in combination with triethylamine as a sacrificial reductant and Fe 3 (CO) 12 as a water reduction catalyst. The relevant molecular transitions have been characterized via high-resolution Ir L-edge X-ray absorption spectroscopy on the picosecond time scale and restricted active space self-consistent field calculations. The presented methods and results will enhance our understanding of functionally relevant bimolecular electron transfer reactions and thus will pave the road to rational optimization of photocatalytic performance.
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Effect of Isomorphic Metal Substitution on the Fenton and Photo-Fenton Degradation of Methylene Blue Using Fe-Based Metal–Organic Frameworks
Not provided.
membrane, carbon capture, materials and chemistry ↗
Rate Enhancement of Acid-Catalyzed Alcohol Dehydration by Supramolecular Organic Capsules
The presence of a (sub)nanometric environment has been demonstrated to enhance the rate of homogeneous acid-catalyzed reactions. Conventionally, such catalysts are constructed by directly embedding a catalytically active acid site into the structure of a porous material, linking the acid properties with the properties of the embedding solid. Here, a holoenzyme mimicking approach was used, in which a self-assembled hexameric resorcinarene capsule (1.4 nm 3 cavity) acts like an apoenzyme that transforms into a catalytically active site by hosting hydrated HCl as a cofactor. This capsule binds the hydronium ion together with cyclohexanol (CyOH) and catalyzes the dehydration to cyclohexene with enhanced rates that are 2 orders of magnitude higher than those in the unconstrained environment. Kinetic analysis shows that cyclohexanol dehydration proceeds via an E2 mechanism on hydrated HCl in the unconstrained environment, while the constrained environment of the active capsule induces the stabilization of an ionic intermediate, allowing an E1 mechanism to dominate. By comparison with the reaction in zeolite environments, we show that the direct chemical environment of the capsule or a zeolite wall exerts only a minor direct influence. The volume constraint increases the reaction rate by inducing a larger activation entropy, indicating the stabilization of a later transition state in the E1 mechanism, as well as a higher reaction space of the carbenium ion constituting the transition state.
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A Non-aqueous H 3 PO 4 Electrolyte Enables Stable Cycling of Proton Electrodes
A non-aqueous proton electrolyte is devised by dissolving H 3 PO 4 into acetonitrile. The electrolyte exhibits unique vibrational signatures from stimulated Raman spectroscopy. Such an electrolyte exhibits unique characteristics compared to aqueous acidic electrolytes: 1) higher (de)protonation potential for a lower desolvation energy of protons, 2) better cycling stability by dissolution suppression, and 3) higher Coulombic efficiency owing to the lack of oxygen evolution reaction. Two non-aqueous proton full cells exhibit better cycling stability, higher Coulombic efficiency, and less self-discharge compared to the aqueous counterpart.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
PDFDataExtractor: A Tool for Reading Scientific Text and Interpreting Metadata from the Typeset Literature in the Portable Document Format
The layout of portable document format (PDF) files is constant to any screen, and the metadata therein are latent, compared to mark-up languages such as HTML and XML. No semantic tags are usually provided, and a PDF file is not designed to be edited or its data interpreted by software. However, data held in PDF files need to be extracted in order to comply with opensource data requirements that are now government-regulated. In the chemical domain, related chemical and property data also need to be found, and their correlations need to be exploited to enable data science in areas such as data-driven materials discovery. Such relationships may be realized using text-mining software such as the “chemistry-aware” natural-language-processing tool, ChemDataExtractor; however, this tool has limited data-extraction capabilities from PDF files. This study presents the PDFDataExtractor tool, which can act as a plug-in to ChemDataExtractor. It outperforms other PDF-extraction tools for the chemical literature by coupling its functionalities to the chemical-named entityrecognition capabilities of ChemDataExtractor. The intrinsic PDF-reading abilities of ChemDataExtractor are much improved. The system features a template-based architecture. This enables semantic information to be extracted from the PDF files of scientific articles in order to reconstruct the logical structure of articles. While other existing PDF-extracting tools focus on quantity mining, this template-based system is more focused on quality mining on different layouts. PDFDataExtractor outputs information in JSON and plain text, including the metadata of a PDF file, such as paper title, authors, affiliation, email, abstract, keywords, journal, year, document object identifier (DOI), reference, and issue number. With a self-created evaluation article set, PDFDataExtractor achieved promising precision for all key assessed metadata areas of the document text.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗