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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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Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces
Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.
Neural Network Water Model Based on the MB-Pol Many-Body Potential
The MB-pol many-body potential accurately predicts many properties of water, including cluster, liquid phase, and vapor–liquid equilibrium properties, but its high computational cost can make applying it in large-scale simulations quite challenging. Here, in order to address this limitation, we developed a “deep potential” neural network (DPMD) model based on the MB-pol potential for water. We find that a DPMD model trained on mostly liquid configurations yields a good description of the bulk liquid phase but severely underpredicts vapor–liquid coexistence densities. By contrast, adding cluster configurations to the neural network training set leads to a good agreement for the vapor coexistence densities. Liquid phase densities under supercooled conditions are also represented well, even though they were not included in the training set. These results confirm that neural network models can combine accuracy and transferability if sufficient attention is given to the construction of a representative training set for the target system.
Development of Lipid-Coated Semiconductor Nanosensors for Recording of Membrane Potential in Neurons
In the past decade, optical imaging methods have significantly improved our understanding of the information processing principles in the brain. Although many promising tools have been designed, sensors of membrane potential are lagging behind the rest. Semiconductor nanoparticles are an attractive alternative to classical voltage indicators, such as voltage-sensitive dyes and proteins. Such nanoparticles exhibit high sensitivity to external electric fields via the quantum-confine Stark effect. Here we report the development of semiconductor voltage-sensitive nanorods (vsNRs) that self-insert into the neuronal membrane. To facilitate interaction of the nanorods with the membrane, we functionalized their surface with the lipid mixture derived from brain extract. We describe a workflow to detect and process the photoluminescent signal of vsNRs after widefield time-lapse recordings. We also present data indicating that vsNRs are feasible for sensing membrane potential in neurons at a single-particle level. This shows the potential of vsNRs for the detection of neuronal activity with unprecedentedly high spatial and temporal resolution.
Synthesis, Applications and Potential Photoluminescence Mechanism of Spectrally Tunable Carbon Dots
Due to the prominent characteristics of carbon-based luminescent nanostructures (known colloquially as carbon dots), such as inexpensive precursors, excellent hydrophilicity, low toxicity, and intrinsic fluorescence, these nanomaterials are regarded as potential candidates to replace traditional quantum dots in some applications. As such, research in the field of carbon dots has been increasing in recent years. In this mini-review, we summarize recent progress in studies of multicolor carbon dots focusing on potential photoluminescence mechanisms, strategies for effective syntheses, and applications in ion/molecule and temperature sensing, and high-resolution bioimaging techniques.
Universal scaling of potential energy functions describing intermolecular interactions. I. Foundations and scalable forms of new generalized Mie, Lennard-Jones, Morse, and Buckingham exponential-6 potentials
Based on the formulation of the analytical expression of the potential V(r) describing intermolecular interactions in terms of the dimensionless variables r*=r/rm and !*=V/!, where rm is the separation at the minimum and ! the well depth, we propose more generalized scalable forms for the commonly used Lennard-Jones, Mie, Morse and Buckingham exponential-6 potential energy functions (PEFs). These new generalized forms have an additional parameter from and revert to the original ones for some choice of that parameter. In this respect, the original forms can be considered as special cases of the more general forms that are introduced. We also propose a scalable, but nonrevertible to the original one, 4-parameter extended Morse potential.
Equation of motion coupled cluster methods for electron attachment and ionization potential in fullerenes C{sub 60} and C{sub 70}
In both molecular and periodic solid-state systems there is a need for the accurate determination of the ionization potential and the electron affinity for systems ranging from light harvesting polymers and photocatalytic compounds to semiconductors. The development of a Green's function approach based on the coupled cluster (CC) formalism would be a valuable tool for addressing many properties involving many-body interactions along with their associated correlation functions. As a first step in this direction, we have developed an accurate and parallel efficient approach based on the equation of motion-CC technique. To demonstrate the high degree of accuracy and numerical efficiency of our approach we calculate the ionization potential and electron affinity for C{sub 60} and C{sub 70}. Accurate predictions for these molecules are well beyond traditional molecular scale studies. We compare our results with experiments and both quantum Monte Carlo and GW calculations.
Derivative discontinuity and exchange-correlation potential of meta-GGAs in density-functional theory
We investigate fundamental properties of meta-generalized-gradient approximations (meta-GGAs) to the exchange-correlation energy functional, which have an implicit density dependence via the Kohn-Sham kinetic-energy density. To this purpose, we construct the most simple meta-GGA by expressing the local exchange-correlation energy per particle as a function of a fictitious density, which is obtained by inverting the Thomas-Fermi kinetic-energy functional. This simple functional considerably improves the total energy of atoms as compared to the standard local density approximation. The corresponding exchange-correlation potentials are then determined exactly through a solution of the optimized effective potential equation. These potentials support an additional bound state and exhibit a derivative discontinuity at integer particle numbers. We further demonstrate that through the kinetic-energy density any meta-GGA incorporates a derivative discontinuity. However, we also find that for commonly used meta-GGAs the discontinuity is largely underestimated and in some cases even negative.
Mean Inner Potential of Liquid Water
Improving our experimental and theoretical knowledge of electric potentials at liquid-solid boundaries is essential to achieve a deeper understanding of the driving forces behind interfacial processes. Electron holography has proved successful in probing solid-solid interfaces but requires knowledge of the materials’ mean inner potential (MIP, V0), which is a fundamental bulk material property. Combining off-axis electron holography with liquid phase transmission electron microscopy (LPTEM), we provide the first quantitative MIP determination of liquid water V0=+4.48±0.19 V. This value is larger than most theoretical predictions, and to explain the disagreement we assess the dominant factors needed in quantum simulations of liquid water. A precise MIP lays the foundations for nanoscale holographic potential measurements in liquids and provides a benchmark to improve quantum mechanical descriptions of aqueous systems and their interfaces in e.g. electrochemistry, solvation processes and spectroscopy.
Errors in retarding potential analyzers caused by nonuniformity of the grid-plane potential.
One aspect of the degradation in performance of retarding potential analyzers caused by potential depressions in the retarding grid is quantitatively estimated from laboratory measurements and theoretical calculations. A simple expression is obtained that permits the use of laboratory measurements of grid properties to make first-order corrections to flight data. Systematic positive errors in ion temperature of approximately 16% for the Ogo 4 instrument and 3% for the Ogo 6 instrument are deduced. The effects of the transverse electric fields arising from the grid potential depressions are not treated.
An Investigation of Applications for Thermodynamic Work Potential Methods: Working Tables and Charts for Estimation of Thermodynamic Work Potential in Equilibrium Mixtures of Jet-A and Air
The objective of this report is to provide a tool to facilitate the application of thermodynamic work potential methods to aircraft and engine analysis. This starts with a discussion of the theoretical background underlying these methods, which is then used to derive various equations useful for thermodynamic analysis of aircraft engines. The work potential analysis method is implemented in the form of a set of working charts and tables that can be used to graphically evaluate work potential stored in high-enthalpy gas. The range of validity for these tables is 300 to 36,000 R, pressures between between 0.01 atm and 100 atm, and fuel-air ratios from zero to stoichiometric. The derivations and charts assume mixtures of Jet-A and air as the working fluid. The thermodynamic properties presented in these charts were calculated based upon standard thermodynamic curve fits.
Review of Potential–Induced Degradation in Bifacial Photovoltaic Modules
Bifacial modules are increasingly deployed in the field and are expected to represent half of the market share within 10 years. Their rear structure differs from monofacial modules to allow additional light absorption. However, it brings new reliability challenges to address. In particular, the risk of potential-induced degradation (PID) is increased as both module sides are impacted. Different PID processes have been identified in the literature: shunting type (PID-s), polarization type (PID-p), Na penetration type, and corrosion type (PID-c). Their occurrence depends on the photovoltaic system configuration as well as the module's materials. Apart from PID-s, PID processes are not well understood and extensive research is needed to elucidate the PID scenario and underlying mechanisms. Herein, current knowledge about PID processes and their impact on the main bifacial modules in the market are gathered with the aim to guide future research. Bifacial module technologies and leakage current paths leading to PID are described. Indoor and outdoor PID testing methods are detailed. For each bifacial module technology, the PID processes are investigated with their indicators, mechanism and recovery process. Furthermore, PID-impacting factors and limitation solutions are finally reported and a state of the art on PID modeling is presented.
Accelerating ab initio path integral molecular dynamics with multilevel sampling of potential surface
A multilevel approach to sample the potential energy surface in a path integral formalism is proposed. The purpose is to reduce the required number of ab initio evaluations of energy and forces in ab initio path integral molecular dynamics (AI-PIMD) simulation, without compromising the overall accuracy. To validate the method, the internal energy and free energy of an Einstein crystal are calculated and compared with the analytical solutions. As a preliminary application, we assess the performance of the method in a realistic model—the FCC phase of dense atomic hydrogen, in which the calculated result shows that the acceleration rate is about 3 to 4-fold for a two-level implementation, and can be increased up to 10 times if extrapolation is used. With only 16 beads used for the ab initio potential sampling, this method gives a well converged internal energy. The residual error in pressure is just about 3 GPa, whereas it is about 20 GPa for a plain AI-PIMD calculation with the same number of beads. The vibrational free energy of the FCC phase of dense hydrogen at 300 K is also calculated with an AI-PIMD thermodynamic integration method, which gives a result of about 0.51 eV/proton at a density of r{sub s}=0.912.
New XDM-corrected potential energy surfaces for Ar–NO(X{sup 2}Π): A comparison with CCSD(T) calculations and experiments
We report new potential energy surfaces for the ground state Ar–NO(X{sup 2}Π) van der Waals system calculated using the unrestricted Hartree-Fock (UHF) method with the addition of the Becke-Roussel correlation functional and exchange-hole dipole moment dispersion correction (XDM). We compare UHFBR-XDM surfaces and those previously reported by Alexander from coupled cluster CCSD(T) calculations [J. Chem. Phys. 111, 7426 (1999)]. The bound states of Ar–NO have been investigated with these new UHFBR-XDM surfaces, including relative energy-level spacing, adiabatic bender states and wave functions, and spectroscopic data. These results have been found to be in good agreement with calculations based on the CCSD(T) PESs. These new PESs are used to investigate the inelastic scattering of NO(X) by Ar. Full close-coupling integral cross sections at collision energies of 442 cm{sup −1}, 1774 cm{sup −1} and differential cross sections at collision energy of 530 cm{sup −1} were determined for transitions out of the lowest NO(X) rotational level (j = ω = 1/2,f). These cross sections are in good agreement with those calculated with CCSD(T) and accordingly in good agreement with the most recent initial and final state resolved experimental data. The UHFBR-XDM scheme yields high-quality potential surfaces with computational cost comparable to the Hartree-Fock method and our results may serve as a benchmark for application of this scheme to collisions between larger molecules.