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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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We review recent results on discoveries of new magnetic compounds by combining experiments, adaptive genetic algorithm searches, and advanced electronic-structure computational methods.
The photophysical and photochemical properties of two Pt(IV)Re(I) conjugates were studied via both experimental and computational methods. Additionally, both conjugates exhibit modest photocytotoxicity against ovarian cancer cells. X-ray fluorescence microscopy showed that Pt and Re colocalize in cells whether they had been irradiated or not. This work demonstrates the potential of photoactivated multilimetallic agents for combating cancer.
The ubiquity of metal–organic frameworks in recent scientific literature underscores their highly versatile nature. MOFs have been developed for use in a wide array of applications, including: sensors, catalysis, separations, drug delivery, and electrochemical processes. Often overlooked in the discussion of MOF-based materials is the mass transport of guest molecules within the pores and channels. Given the wide distribution of pore sizes, linker functionalization, and crystal sizes, molecular diffusion within MOFs can be highly dependent on the MOF-guest system. In this paper, we discuss the major factors that govern the mass transport of molecules through MOFs at both the intracrystalline and intercrystalline scale; provide an overview of the experimental and computational methods used to measure guest diffusivity within MOFs; and highlight the relevance of mass transfer in the applications of MOFs in electrochemical systems, separations, and heterogeneous catalysis.
The factors that control the diverse reactivity of the μ-η 2 :η 2 -peroxo dicopper(II) oxy-intermediates in the coupled binuclear copper proteins remain elusive. In this study, spectroscopic and computational methods reveal H-bonding interactions between active-site waters and the μ-η 2 :η2-peroxide of oxy-tyrosinase, and define their effects on the Cu(II) 2 O 2 electronic structure and O 2 activation.
Understanding the physical and chemical processes occurring in concentrated electrolyte solutions is required to achieve redox flow batteries with high energy density. Highly concentrated electrolyte solutions are often studied in which collective crowded interactions between molecules and ions become predominant. In this work, experimental and computational methods were used to examine non-aqueous electrolyte solutions in two different states of charge as a function of redoxmer concentration. As the latter increases and the ionic association strengthens, the electric conductivity passes through a maximum and the solution increasingly gels, which is seen through a rapid non-linear increase in viscosity. We establish that the structural rigidity of ionic networks is closely connected with this loss of fluidity and show that charging generally yields softer ionic assemblies with weaker attractive forces and improved dynamical properties.
Supramolecular interactions are well recognized and many of them have been extensively studied in chemistry. The formation of supramolecular complexes that rely on weak force interactions are less well studied in bilayer membranes. Herein, a supported bilayer membrane is used to probe the penetration of a complex between tetracycline and a macrocyclic polyether. In a number of bacterial systems, the presence of the macrocycle has been found to significantly enhance the potency of the antimicrobial in vitro. The crown·tetracycline complex has been characterized in solution, neutron reflectometry has probed complex penetration, and the phenomena have been modeled by computational methods.
We synthesize air-stable, p-type CaCuP thin films with high hole concentration and high hole mobility as potential p-type transparent conductors. We study their optoelectronic properties in detail by advanced experimental and computational methods.
The design of organic light emitting diode (OLED) materials with the potential for exhibiting thermally-activated delayed fluorescence (TADF) is reported. Using computational methods (DFT/TD-DFT) as a guiding tool, six materials with a benzobisoxazole (BBO) core and donor–acceptor–donor architectures were designed by changing the conjugation position of carbazole-substituted phenyl substituents and the type of BBO isomer (cis- vs. trans-). Experimental steady-state and transient absorption spectroscopic techniques were utilized to probe the TADF activity of these molecules. Each material was then used in host–guest OLED devices as either near-UV dopants or host with low singlet-triplet energy differences. The electroluminescent properties show that when used as dopants these materials provide near-UV emission (CIE y < 0.06 and CIE x = 0.16), whereas when used as hosts, these materials show reduced operating voltages and increased performance efficiencies when compared to commercial materials.
Surface characterization at the atomic scale is essential for understanding the catalytic properties of supported metal nanoparticles. Secondary electron (SE) imaging in scanning transmission electron microscopy (STEM) provides three-dimensional surface topographic information, enabling the characterization of the size, morphology, and distribution of supported nanoparticles. Furthermore, real-time observation of catalyst materials in a gaseous environment would enhance the understanding of catalyst dynamics under operational conditions. Ongoing technical developments in SE-STEM and advancements in computational methods are expected to facilitate atomic-scale surface observations and enable more quantitative and statistical analyses. This progress will not only elucidate fundamental mechanisms at the atomic level but also provide comprehensive and universal insights into catalyst performances. Here, this minireview showcases the recent advancements and research findings in surface-sensitive SE imaging in STEM for the characterization of active catalyst materials.
This work integrates experiments and computational methods to quantify how the cis/trans ratio of the OSDA used in SSZ-39 synthesis impacts the crystallization kinetics, material properties, and final product composition. The crystallization kinetics increase by 30% when increasing the trans isomer content from 14% to 80%. Per prior work, in all cases based on the synthesis gel composition and product yield aluminum is the limiting reagent, and the absence of any amorphous material detected in the time resolved PXRD studies leads us to conclude that FAU dissolution is the rate limiting step in the formation of SSZ-39 in this synthesis protocol. The TGA and NMR results suggest that the trans isomer of OSDA is selectively incorporated into the product. The NMR binding studies, and corresponding DFT-based results show that the trans isomer binds to FAU more strongly than the cis isomer, providing one possible explanation for this enhancement in kinetics and preferential uptake of the trans isomer. The EDS analysis indicates that the Si/Al ratios are between 7.7 and 8.6 at low and high trans OSDA content, indicating zeolite composition is mildly sensitive to the trans isomer content. EDS results show this decrease in aluminum content leads to a corresponding decrease in sodium uptake. DFT-based calculations confirm OSDA–sodium interactions cannot explain any decrease in sodium uptake, reinforcing lower aluminum content as the cause of lower sodium uptake. Preliminary cobalt titration experiments show a surprisingly low cobalt uptake but also show a clear dependence of the cobalt uptake on the solution pH.
A data-driven computational method is introduced to extract chemical reaction mechanisms from time series chemical concentration data. It is realized through the use of dynamic symbolic regression in which a sparse analytical form for a dynamical system is discoverable from the underlying data. We specifically develop the stoichiometrically-informed symbolic regression (SISR) method to address a standing challenge in complex chemical reaction networks: given a time-series dataset of concentrations of several components, what is the mechanism and the associated rate constants? SISR finds the optimal mechanism, kinetic equations and rate constants by combining differential optimization with a genetic optimization approach that searches a symbolic space of possible reaction mechanisms. Use of SISR in several paradigmatic examples spanning linear and nonlinear reaction schemes results in excellent agreement between true and predicted mechanisms, including when the method is applied to noisy data. The advantages of a stoichiometrically-informed approach such as SISR to address reaction discovery is illustrated through comparison with the use of generic state-of-the-art data-driven approaches.
We report on a new water-soluble cobalt( II ) complex capable of water splitting bifunctionality, i.e., water reduction and water oxidation. The species [Co II (L Qpy )H 2 O]ClO 4 (1), where L Qpy is the deprotonated form of the new tripodal ligand N 1 ,N 1 -bis(pyridin-2-ylmethyl)-N 2 -(quinolin-8-yl)benzene-1,2-diamine, HL Qpy , was developed aiming to replace an oxidation prone methylene group by a sturdy and redox stable quinoline. The molecular and electronic structures of 1 were evaluated by multiple spectroscopic, spectrometric, electrochemical and computational methods, and detailed pre- and post-catalytic studies were conducted to ascertain the molecular nature of the conversions. Complex 1 performs water reduction at a low onset overpotential (η) of 0.65 V at pH 7, reaching TON 3h 2900 (TOF 970 h −1 ) and TON 18h 12 100 (TOF 672 h −1 ) with up to 98% faradaic efficiency (FE). Species 1 also promotes water oxidation at η = 0.34 V under pH 8, achieving TON 3h 193 (TOF 64 h −1 ) at 84% FE. Experimental and DFT results enabled us to propose reaction intermediates and mechanisms.
We report the first monomeric formally M I transition metal salen complex without ion pairing. A combination of spectroscopy, crystallography, and computations indicates that reduction of an Fe II salen complex gives substantial reduced ligand character. We also present a computational method for accurately predicting 57 Fe Mössbauer parameters of Fe salen complexes.
Due to the usually complicated and anisotropic nature of the fast-ion distribution function, diagnostic velocity-space weight functions, which indicate the sensitivity of a diagnostic to different fast-ion velocities, are used to facilitate the analysis of experimental data. Additionally, when velocity-space weight functions are discretized, a linear equation relating the fast-ion density and the expected diagnostic signal is formed. In a technique known as velocity-space tomography, many measurements can be combined to create an ill-conditioned system of linear equations that can be solved using various computational methods. However, when velocity-space weight functions (which by definition ignore spatial dependencies) are used, velocity-space tomography is restricted, both by the accuracy of its forward model and also by the availability of spatially overlapping diagnostic measurements. In this work, we extend velocity-space weight functions to a full 6D generalized coordinate system and then show how to reduce them to a 3D orbit-space without loss of generality using an action-angle formulation. Moreover, we show how diagnostic orbit-weight functions can be used to infer the full fast-ion distribution function, i.e., orbit tomography. In depth derivations of orbit weight functions for the neutron, neutral particle analyzer, and fast-ion D-α diagnostics are also shown
We explore the adsorption of pyridine on Cu, Ag, Au, and Pt(110) surfaces using density functional theory. To account for the van der Waals interaction, we use the optB86b-vdW, optB88-vdW, optPBE-vdW, revPBE-vdW, and rPW86-vdW2 functionals. For comparison, we also run calculations using the generalized gradient approximation-PBE (Perdew–Burke–Ernzerhof) functional. We find the most stable adsorption site to depend on both metal and functional, with two energetically favorable adsorption sites, namely, a vertically oriented site and a flat pyridine site. We calculate that every functional predicts pyridine to lie in the vertical configuration on the coinage metals at a low coverage. On Pt(110), by contrast, we calculate all the functionals—except rPW86-vdW2—to predict pyridine to lie flat at a low coverage. By analyzing these differences for these adsorption configurations, along with various geometric and electronic properties of the adsorbate/substrate system, we access in detail the performance of the 6 functionals we use. We also characterize the nature of the bonding of pyridine on the coinage metals from weak to strong physisorption, depending on the functional used. On Pt(110), we characterize the nature of the bonding of pyridine as ranging from strong physisorption to strong chemisorption depending again on the functional used, illustrating both the importance of the van der Waals interaction to this system and that this system can make a stringent test for computational methods.
Coupling of the Peierls-Boltzmann equation with density functional theory paved the way for predictive thermal materials discovery and a variety of new physical insights into vibrational transport behaviors. Here, rapid theoretical and numerical developments have generated a wealth of thermal conductivity data and understanding of a wide variety of materials—1D, 2D, and bulk—for thermoelectric and thermal management applications. Nonetheless, modern ab initio descriptions of phonon thermal transport face challenges regarding the effects of defects, disorder, structural complexity, strong anharmonicity, quasiparticle couplings, and time and spatially varying perturbations. Highlighting recent research on these issues, this perspective explores opportunities to expand current ab initio phonon transport techniques beyond the paradigm of weakly perturbed crystals, to the wider variety of materials possible. Recent developments in phonon-defect interactions, complexity, disorder and anharmonicity, hydrodynamic transport, and the rising roles of molecular dynamics simulations, high throughput, and machine learning tools are included in this perspective. Lastly, as more sophisticated theoretical and computational methods continue to advance thermal transport predictions, novel vibrational physics and thermally functional materials will be discovered for improved energy technologies.
In this work, linear simulations of toroidal Alfvén eigenmodes (TAEs) driven by energetic particles (EPs) on EAST (Experimental Advanced Superconducting Tokamak) are performed using the hybrid-kinetic MHD model implemented in NIMROD code. Furthermore, the EAST equilibrium is reconstructed using the EFIT code based on the experimental measurement. The “slowing down” distribution is adopted for modeling the equilibrium distribution of the energetic ions from the deuterium neutral beam injection on EAST. The frequency, the dominant poloidal mode number, the radial location and the detailed 2D mode structure of the TAE/RSAE (Reverse Shear Alfvén Eigenmode)/EPM (energetic particle mode) modes are consistent between the eigenvalue analysis and the NIMROD simulation. As the β fraction of EP increases, a transition between even and odd TAEs occurs, along with that between the ballooning and antiballooning mode structures. It is demonstrated that when the β fraction of EP is close to the transition threshold, both types of TAEs coexist.
Autoencoder techniques find increasingly common use in reduced order modeling as a means to create a latent space. This reduced order representation offers a modular data-driven modeling approach for nonlinear dynamical systems when integrated with a time series predictive model. In this Letter, we put forth a nonlinear proper orthogonal decomposition (POD) framework, which is an end-to-end Galerkin-free model combining autoencoders with long short-term memory networks for dynamics. By eliminating the projection error due to the truncation of Galerkin models, a key enabler of the proposed nonintrusive approach is the kinematic construction of a nonlinear mapping between the full-rank expansion of the POD coefficients and the latent space where the dynamics evolve. We test our framework for model reduction of a convection-dominated system, which is generally challenging for reduced order models. Our approach not only improves the accuracy, but also significantly reduces the computational cost of training and testing.