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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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Local composition activity coefficient model for mixed-gas adsorption equilibria
Taking into consideration the adsorbate–adsorbent interactions, a novel activity coefficient model is derived from the non-random two-liquid theory for mixed-gas adsorption equilibria. In contrast with the conventional activity coefficient models developed for bulk liquids, the new model correctly predicts negative deviations from ideality for adsorbed phase mixtures including azeotropic behavior exhibited by selected gas-adsorbent systems. Here, the requiring a single binary interaction parameter per adsorbate–adsorbate pair, the model successfully correlates wide varieties of binary adsorption isotherm data and it should be a powerful engineering thermodynamic tool in correlating and predicting mixed-gas adsorption equilibria.
Impedance spectroscopy on copper phthalocyanine diodes with surface-induced molecular orientation
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Multiphonon relaxation slows singlet fission in crystalline hexacene
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Nanostructured Surfaces Frustrate Polymer Semiconductor Molecular Oreintation
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Investigation of combinatorial coevaporated thin film Cu{sub 2}ZnSnS{sub 4}. I. Temperature effect, crystalline phases, morphology, and photoluminescence
Cu{sub 2}ZnSnS{sub 4} is a promising low-cost, nontoxic, earth-abundant absorber material for thin-film solar cell applications. In this study, combinatorial coevaporation was used to synthesize individual thin-film samples spanning a wide range of compositions at low (325 °C) and high (475 °C) temperatures. Film composition, grain morphology, crystalline-phase and photo-excitation information have been characterized by x-ray fluorescence, scanning electron microscopy, x-ray diffraction, Raman spectroscopy, and photoluminescence imaging and mapping. Highly textured columnar grain morphology is observed for film compositions along the ZnS-Cu{sub 2}ZnSnS{sub 4}-Cu{sub 2}SnS{sub 3} tie line in the quasi-ternary Cu{sub 2}S-ZnS-SnS{sub 2} phase system, and this effect is attributed to structural similarity between the Cu{sub 2}ZnSnS{sub 4}, Cu{sub 2}SnS{sub 3}, and ZnS crystalline phases. At 475 °C growth temperature, Sn-S phases cannot condense because of their high vapor pressures. As a result, regions that received excess Sn flux during growth produced compositions falling along the ZnS-Cu{sub 2}ZnSnS{sub 4}-Cu{sub 2}SnS{sub 3} tie line. Room-temperature photoluminescence imaging reveals a strong correlation for these samples between film composition and photoluminescence intensity, where film regions with Cu/Sn ratios greater than ∼2 show strong photoluminescence intensity, in comparison with much weaker photoluminescence in regions that received excess Sn flux during growth or subsequent processing. The observed photoluminescence quenching in regions that received excess Sn flux is attributed to the effects of Sn-related native point defects in Cu{sub 2}ZnSnS{sub 4} on non-radiative recombination processes. Implications for processing and performance of Cu{sub 2}ZnSnS{sub 4} solar cells are discussed.
Ultra-high vacuum compatible optical chopper system for synchrotron x-ray scanning tunneling microscopy
High-speed beam choppers are a crucial part of time-resolved x-ray studies as well as a necessary component to enable elemental contrast in synchrotron x-ray scanning tunneling microscopy (SX-STM). However, many chopper systems are not capable of operation in vacuum, which restricts their application to x-ray studies with high photon energies, where air absorption does not present a significant problem. To overcome this limitation, we present a fully ultra-high vacuum (UHV) compatible chopper system capable of operating at variable chopping frequencies up to 4 kHz. The lightweight aluminum chopper disk is coated with Ti and Au films to provide the required beam attenuation for soft and hard x-rays with photon energies up to about 12 keV. The chopper is used for lock-in detection of x-ray enhanced signals in SX-STM.
Detecting element specific electrons from a single cobalt nanocluster with synchrotron x-ray scanning tunneling microscopy
Here, we use a nanofabricated scanning tunneling microscope tip as a detector to investigate local X-ray induced tunneling and electron emission from a single cobalt nanocluster on a Au(111) surface. The tip-detector is positioned a few angstroms above the nanocluster, and ramping the incident X-ray energy across the Co photoabsorption K-edge enables the detection of element specific electrons. Atomic-scale spatial dependent changes in the X-ray absorption cross section are directly measured by taking the X-ray induced current as a function of X-ray energy. From the measured sample and tip currents, element specific X-ray induced current components can be separated and thereby the corresponding yields for the X-ray induced processes of the single cobalt nanocluster can be determined. The detection of element specific synchrotron X-ray induced electrons of a single nanocluster opens a new avenue for materials characterization on a one particle at-a-time basis.
Amino Acid Encoding for Deep Learning Applications
Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.
Alkali-Metal-Intercalated Percolation Network Regulates Self-Assembled Electronic Aromatic Molecules
In the continuously growing field of correlated electronic molecular crystals, there is significant interest in addressing alkali-metal-intercalated aromatic hydrocarbons, in which the possibility of high-temperature superconductivity emerges. However, searching for superconducting aromatic molecular crystals remains elusive due to their small shielding fraction volume. To exploit this potential, a design principle for percolation networks of technologically important film geometry is indispensable. Here the effect of potassium-intercalation is shown on the percolation network in self-assembled aromatic molecular crystals. It is demonstrated that one-dimensional (1D) dipole pairs, induced by dipole interaction, regulate the conductivity, as well as the electronic and optical transitions, in alkalimetal-intercalated molecular electronic crystals. A solid-solution growth methodology of aromatic molecular films with a broad range of stability is developed to uncover electronic and optical transitions of technological importance. The light-induced electron interactions enhance the charge-carrier itinerancy, leading to a switchable metal-to-insulator transition. This discovery opens a route for the development of aromatic molecular electronic solids and long-term modulation of electronic efficacy in nano-technologically important thin films.
Decoupling the Effects of Self-Assembled Monolayers on Gold, Silver, and Copper Organic Transistor Contacts
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2D Ionic Liquid-Like State of Charged Rare-Earth Clusters on a Metal Surface
Rare-earth complexes are vital for separation chemistry and useful in many advanced applications including emission and energy upconversion. Here, 2D rare-earth clusters having net charges are formed on a metal surface, enabling investigations of their structural and electronic properties on a one-cluster-at-a-time basis using scanning tunneling microscopy. While these ionic complexes are highly mobile on the surface at ≈100 K, their mobility is greatly reduced at 5 K and reveals stable and self-limiting clusters. In each cluster, a pair of charged rare-earth complexes formed by electrostatic and dispersive interactions act as a basic unit, and the clusters are chiral. Unlike other non-ionic molecular clusters formed on the surfaces, these rare-earth clusters show mechanical stability. Moreover, their high mobility on the surface suggests that they are in a 2D liquid-like state.
Lattice Symmetry-Guided Charge Transport in 2D Supramolecular Polymers Promotes Triplet Formation
Singlet-to-triplet intersystem crossing (ISC) in organic molecules is intimately connected with their geometries: by modifying the molecular shape, symmetry selection rules pertaining to spin-orbit coupling can be partially relieved, leading to extra matrix elements for increased ISC. As an analog to this molecular design concept, the study finds that the lattice symmetry of supramolecular polymers also defines their triplet formation efficiencies. A supramolecular polymer self-assembled from weakly interacting molecules is considered. Its 2D oblique unit cell effectively renders it as a coplanar array of 1D molecular columns weakly bound to each other. Using momentum-resolved photoluminescence imaging in combination with Monte Carlo simulations, the study found that photogenerated charge carriers in the supramolecular polymer predominantly recombine as spin-uncorrelated carrier pairs through inter-column charge transfer states. This lattice-defined recombination pathway leads to a substantial triplet formation efficiency (≈60%) in the supramolecular polymer. These findings suggest that lattice symmetry of micro-/macroscopic structures relying on intermolecular interactions can be strategized for controlled triplet formation.
From Langmuir isotherm to Brunauer–Emmett–Teller isotherm
Abstract Developed for multilayer adsorption, the Brunauer–Emmett–Teller ( BET) isotherm considers the adsorption of the first layer as an equilibrium chemical reaction between adsorbate molecules and adsorption sites and the adsorption of the second and subsequent layers as a condensation–evaporation process. Following the recent development of an activity‐based formulation for the Langmuir isotherm for monolayer adsorption, we present an activity‐based formulation for the BET isotherm in which species concentrations are replaced with species activities. Capturing the adsorbent surface heterogeneity for the adsorption of the first layer, the resulting thermodynamic BET isotherm is shown to accurately represent pure component adsorption isotherms over the relative pressure range of zero to unity or prior to the onset of capillary condensation. The thermodynamic BET isotherm should facilitate accurate estimation of monolayer adsorption capacity and the corresponding adsorbent surface area.
Generalization of thermodynamic Langmuir isotherm for mixed‐gas adsorption equilibria
Abstract This work presents a comprehensive thermodynamic model for both pure component isotherms and mixed‐gas adsorption equilibria. A generalization of thermodynamic Langmuir isotherm, the proposed model assumes competitive adsorption of multiple adsorbates on adsorbent surface for mixed‐gas adsorption equilibria, and it applies an area‐based adsorption nonrandom two‐liquid activity coefficient model in the activity coefficient calculations for the adsorbate phase. The resulting generalized Langmuir isotherm properly captures both surface loading dependence and adsorbate phase composition dependence for mixed‐gas adsorption equilibria. The model is validated with accurate representations of gas adsorption equilibrium data for varieties of unary, binary, and ternary gas systems. The model results are further compared with those calculated from extended Langmuir isotherm and Ideal Adsorbed Solution Theory.
An activity-based formulation for Langmuir adsorption isotherm
This work presents an activity-based formulation for Langmuir adsorption isotherm. Treating adsorption as a chemical reaction between the gas molecule and the adsorption vacant site, the classical Langmuir isotherm model expresses the reaction in terms of the species concentrations. Designed to capture the surface heterogeneity, the proposed thermodynamic Langmuir isotherm model substitutes the species concentrations with the species activities and calculates the species activity coefficients with the adsorption non-random two-liquid activity coefficient model. Here, the resulting isotherm model accurately represents pure component adsorption isotherms for gases with wide varieties of adsorbents including silica gels, activated carbons, zeolites and metal organic frameworks at various temperatures. With three physically meaningful parameters, the model outperforms the classical Langmuir isotherm model for the 98 isotherms of 33 systems examined.