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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 685 records · Page 38

Metal-to-Ligand Charge-Transfer Spectrum of a Ru-Bipyridine-Sensitized TiO 2 Cluster from Embedded Multiconfigurational Excited-State Theory

Understanding optical properties of the dye molecule in dye-sensitized solar cells (DSSCs) from first-principles quantum mechanics can contribute to improving the efficiency of such devices. While density functional theory (DFT) and time-dependent DFT have been pivotal in simulating optoelectronic properties of photoanodes used in DSSCs at the atomic scale, questions remain regarding DFT’s adequacy and accuracy to furnish critical information needed to understand the various excited-state processes involved. In this work, we simulate the absorption spectra of a dye-sensitized solar cell analogue, comprised of a Ru-bipyridine (Ru-bpy) dye molecule and a small TiO2 cluster via DFT and via an accurate embedded correlated wavefunction (CW) theory. We generated CW spectra for the adsorbed Ru-bpy dye via a recently introduced capped density functional embedding theory or capped-DFET (to generate the embedding potential that accounts for the interaction of the molecule and the TiO 2 cluster). We then combined capped-DFET with the accurate but expensive multiconfigurational complete active space second-order perturbation theory (CASPT2)—embedded CASPT2. Because the CW theory is conducted on only a portion of the total system in the presence of an embedding potential that describes that portion’s interaction with its environment, we efficiently obtain CW-quality predictions that reflect local properties of the entire system. Specifically, for example, with capped-DFET and embedded CW theory, we can simulate accurately a plethora of metal-to-ligand charge-transfer excited properties at a manageable computational cost. Here, we predict detailed electronic spectra within the visible region, featuring the lowest three singlet and triplet excited states, along with predictions of the singlets’ lifetimes. We illustrated these results using a Jablonski diagram that show the relative energy position of the singlet and longer-lived triplet excited states and analyzed and proposed relaxation paths for the excited state corresponding to the most intense but short-lived absorption (interconversion, intersystem crossing, fluorescence, and phosphorescence) that may lead to longer-lived excited states necessary for efficient charge separation required to generate current in solar cells.

14 SOLAR ENERGY↗

First-Principles Study of Alkoxides Adsorbed on Au(111) and Au(110) Surfaces: Assessing the Roles of Noncovalent Interactions and Molecular Structures in Catalysis

Microscopic understanding of molecular adsorption on catalytic surfaces is crucial for controlling the activity and selectivity of chemical reactions. However, for complex molecules, the adsorption process is very system-specific and there is a clear need to elaborate systematic understanding of important factors that determine catalytic functionality. In this study, we investigate the binding of eight molecules, including seven alkoxides and one carboxylate, on the Au(111) and Au(110) surfaces. Our density-functional theory calculations including long-range van der Waals interactions demonstrate the significant role of these “weak” noncovalent forces on the adsorption structures, energetics, and relative adsorbate stabilities. Interestingly, the binding energy trends are insensitive to the surface structure. Instead, the adsorption stability depends strongly on the structural and chemical characteristics of the molecules: linear vs branching configurations, number of unsaturated C–C bonds, bidentate adsorption, and the presence of electronegative atoms. Finally, our calculations help establish the influence of individual and collective chemical factors that determine the catalytic selectivity of alkoxides.

36 MATERIALS SCIENCE↗

Localizing Holes as Polarons and Predicting Band Gaps, Defect Levels, and Delithiation Energies of Solid-State Materials with a Local Exchange-Correlation Functional

Here, we assess the performance of seven exchange–correlation functionals (some with and some without a Hubbard U correction) for their ability (i) to predict band gaps of silicon, diamond, and Li-ion battery cathode materials, (ii) to localize hole polarons and predict delithiation energies in Li-ion battery cathode materials, and (iii) to predict transition levels of charge carriers of doped silicon and diamond. Both local and hybrid exchange–correlation functionals were tested. The local functionals tend to underestimate band gaps and delocalize polarons. The hybrid functionals very often give a good description of both properties, but they may not be practical for calculations involving large unit cells, large ensembles, or dynamics, and therefore a local functional with a Hubbard U correction is often used (giving the method called DFT+U), where the value of a parameter U is adjusted according to the system and the property being investigated. Keeping in mind the importance of computational cost and the undesirability of having to adjust an empirical parameter for each system or property of interest, we recently developed a local functional, namely HLE17, to try to accurately predict band gaps and excitation energies, and we validated it using mostly main-group solids and molecules. Here we test the performance of HLE17 for its ability to predict band gaps and localize polarons in other solid-state materials, and we compare its performance to that of popular local functionals (PBE, PBEsol, and TPSS), a range-separated hybrid functional with screened exchange (HSE06), and DFT+U. We find that HLE17 predicts more accurate band gaps than other local functionals and can localize holes as polarons, which other local functionals usually fail to do, and for a number of cases it is comparable in performance quality to Hubbard-corrected functionals without the need for system-specific parametrization and to hybrid functionals without the high cost. Because HLE17 does not predict accurate lattice constants, we use the single-point method of quantum chemistry, where the geometry is optimized with one functional and the band gap is calculated with HLE17, or we perform calculations with the lattice constants obtained by TPSS and both the fractional intracell coordinates and the electronic structure obtained by HLE17 (a new method denoted HLE17\\TPSS). In particular, we performed calculations by HLE17//TPSS, HLE17//HSE06, HLE17//DFT+U, and HLE17\\TPSS, and these methods usually agree well with each other and give values similar to experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comment on “Localized and Delocalized States of a Diamine Cation: Resolution of a Controversy”

Since its appearance in and recent re-investigation in the dimethylpiperazine cation (DMP + ) has generated considerable discussion and controversy in the scientific literature over the existence of stable, local energy minima in this molecular system. Specifically, prior assumptions that the Rydberg state and radical cation of DMP are similar have led to significant confusion and debate regarding the accuracy of various quantum chemistry methods and the existence of stable configurations of DMP+ itself. The purpose of this Viewpoint is to highlight recent studies that call into question the main findings in the previously mentioned works as well as present new CCSDT (Coupled-Cluster with Single, Double, and Triple excitations) calculations to finally bring closure to this controversy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microscopic Theory of Long-Time Center-of-Mass Self-Diffusion and Anomalous Transport in Ring Polymer Liquids

We construct a microscopic theory at the level of segment-scale correlated space–time intermolecular forces for the long-time center-of-mass (CM) diffusion constant and intermediate-time non-Fickian transport in dense solutions and melts of ring polymers. The approach combines ideas of polymer, colloid, and liquid-state statistical mechanics to quantify how the multifractal intra-ring conformational structure and inter-ring packing correlations determine dynamic caging constraints and time-dependent friction. Breakdown of Rouse theory is predicted to occur due to length scale-dependent temporal correlation of forces exerted on pairs of tagged ring segments from surrounding polymers. At large enough degrees of polymerization (N), a stronger scaling of the CM diffusion constant (D ∝ N –2 ) is predicted, with a crossover N D proportional to the product of the system-specific macromolecular volume fraction and dimensionless compressibility. In analogy with caging effects in glass-forming fluids, the theory does appear to begin to fail at sufficiently high N/N D for the center-of-mass diffusivity, likely due to another crossover to an even slower activated transport regime. However, use of N/N D with the theoretically predicted N D , in conjunction with dynamic blob scaling ideas for local Rouse friction, collapses semidilute and concentrated solution simulation data onto a master curve. Based on the same physical ideas employed to predict the diffusion constant, a generalized Langevin equation description is formulated for intermediate-time CM transport. It predicts two subdiffusive regimes that emerge due to the self-similar nature of internal ring structure. Analytic and numerical predictions for the apparent non-Fickian exponent as a function of time, N/N D and dimensionless compressibility, the evolution of the maximum degree of subdiffusive motion with N/N D , and the time scale for recovering Fickian diffusion are made, all of which are in good accordance with melt simulations. Furthermore, the present work sets the stage to address activated dynamics and glass formation on the macromolecular scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Influence of Chain Architecture on the Transport Quantities of Polymer Electrolytes with Covalently Bonded Anions

Here, we use a combination of experiments and coarse-grained molecular dynamics simulations to elucidate the structure–property relationships in polymer electrolytes obtained by the copolymerization of poly(vinyl ethylene carbonate─lithium styrene bis(trifluoromethanesulfonyl)imide) or p(VEC-LiSTFSI). Experiments show that the conductivity reduces with increasing anion (i.e., STFSI) fraction on the chain, and the cation transference number (t + ) is found to be dependent on the anion fraction. Furthermore, a significant fraction of unpolymerized VEC monomers are observed. Since it is inherently difficult to experimentally control the chain architecture and the amount of unpolymerized VEC in these systems, we perform coarse-grained molecular dynamics simulations on model polymer systems with different chain architectures to mimic the plausible experimental systems. Specifically, we look at the differences in transference numbers arising from (i) a random copolymer of VEC and STFSI monomers; (ii) a blend of VEC-STFSI copolymer with VEC monomers; and (iii) a ternary blend of the VEC homopolymer, STFSI homopolymers, and VEC monomers. The ternary blend model demonstrates the closest resemblance with the experimental transference numbers and diffusivities. The lithium diffusivity obtained from the coarse-grained models with VEC monomers (plasticizers) is about 1.5 times that of the model without VEC monomers, showing that the plasticizing effect of VEC monomers is modest. We rationalize the experimental observations based on aggregate and cluster analyses obtained from molecular simulations. This work reveals that polymer electrolyte chain architecture and plasticizers can critically influence the transport properties, and these parameters should be considered when designing single ion conducting polymeric electrolytes.

cluster distribution↗

Challenges and Roadmap for Solar-Thermal Desalination

Decarbonizing desalination systems requires combining renewable energy technologies with desalination systems. Solar thermal desalination, which combines a thermal desalination system (e.g., distillation, multistage flash, etc.) with a concentrated solar system is attractive in geographic regions with an abundance of saline water and solar energy. However, the high economic cost and low efficiency limits its adoption. This review provides an overview of the techno-economic, materials, and performance challenges that need to be overcome to realize solar-desalination. The review describes the four most prominent pathways for overcoming thermodynamic and cost limitations present in current systems. Specifically, methodologies and approaches such as direct solar evaporation structures, low-cost thermal energy storage, solar cogeneration schemes for power and desalination, and solar hybrid desalination are discussed. Furthermore, these strategies can enable solar thermal desalination technologies that are resilient to intermittent solar energy.

14 SOLAR ENERGY↗

Design of High-Performance Photon-Number-Resolving Photodetectors Based on Coherently Interacting Nanoscale Elements

A number of applications in basic science and technology would benefit from high-fidelity photon-number-resolving photodetectors. While some recent experimental progress has been made in this direction, the requirements for true photon number resolution are stringent, and no design currently exists that achieves this goal. Here we employ techniques from fundamental quantum optics to demonstrate that detectors composed of subwavelength elements interacting collectively with the photon field can achieve high-performance photon number resolution. We propose a new design that simultaneously achieves photon number resolution, high efficiency, low jitter, low dark counts, and high count rate. Finally, we discuss specific systems that satisfy the design requirements, pointing to the important role of nanoscale device elements.

47 OTHER INSTRUMENTATION↗

Implications of Local Cathode Structure in Solid-State Batteries

Solid-state batteries (SSBs) are promising candidates for energy storage systems—specifically for automotive applications—owing to their higher energy density and supreme safety. SSBs currently must improve area-specific cathode loadings as well as the electro-chemo-mechanical stability at high voltages. Composite cathodes in SSBs are comprised of active material, ion and electronic conductors, binders, and electronic conducting materials. In addition to experimental limitations with engineering thick cathode architectures, low utilization and chemomechanical degradation of the cathodes limit the performance of composite cathodes. Composite cathodes must optimize several parameters simultaneously to achieve high performances that include loading, electrochemically active surface area, mechanical resilience, and porosity. This chapter summarizes the current state-of-the-art applications with regard to composite cathodes for SSBs and provides insights into cathode architectures using geometric packing models. Tailoring ion and electron transport pathways within the electrode while mitigating operational stresses is crucial for achieving energy-dense cathode structres for SSBs.

Dixit, Marm↗

Characteristics of ice nucleating particles in and around California winter storms

A major component of California’s yearly precipitation comes from wintertime atmospheric river (AR) events which bring large amounts of moisture from the tropics up to the midlatitudes. Understanding these systems, specifically the effects of aerosol particles on precipitation associated with these storms, was a major focus of the 2015 Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), which was part of the wintertime CalWater 2015 campaign. The measurement campaign provided sampling platforms on four aircraft, including the ARM Aerial Facility G-1, as well as the NOAA Ronald H. Brown research vessel and at a ground station in Bodega Bay, CA. Measurements of ice nucleating particles (INPs) were made with the Colorado State University (CSU) Continuous Flow Diffusion Chamber (CFDC) aboard the G-1, and aerosol filters were collected on the G-1, at the Bodega Bay site and on the Ronald H. Brown for post-processing via immersion freezing in the CSU Ice Spectrometer. Aerosol composition was measured aboard the G-1 with the Aerosol Time-of-Flight Mass Spectrometer (ATOFMS). Here we present INP concentrations and aerosol chemical compositions during the course of the aircraft campaign. During the AR event we found that marine aerosol was the dominant aerosol type and that marine INPs were dominant at cloud activation temperatures, which is in stark contrast to the dominance of dust INPs during the AR events in the CalWater 2011 campaign.

Levin, Ezra↗

High-harmonic generation from an epsilon-near-zero material

High-harmonic generation (HHG) is a signature optical phenomenon of strongly driven, nonlinear optical systems. Specifically, the understanding of the HHG process in rare gases has played a key role in the development of attosecond science. Recently, HHG has also been reported in solids, providing novel opportunities such as controlling strong-field and attosecond processes in dense optical media down to the nanoscale. Here, we report HHG from a low-loss, indium-doped cadmium oxide thin film by leveraging the epsilon-near-zero (ENZ) effect, whereby the real part of the material’s permittivity in certain spectral ranges vanishes, as well as the associated large resonant enhancement of the driving laser field. We find that ENZ-assisted harmonics exhibit a pronounced spectral redshift as well as linewidth broadening, resulting from the photo induced electron heating and the consequent time-dependent ENZ wavelength of the material. Furthermore, our results provide a new platform to study strong-field and ultrafast electron dynamics in ENZ materials, reveal new degrees of freedom for spectral and temporal control of HHG, and open up the possibilities of compact solid-state attosecond light sources.

36 MATERIALS SCIENCE↗

Detecting and characterizing special nuclear material for nuclear nonproliferation applications

Abstract There is an urgent need for new, better instrumentation and techniques for detecting and characterizing special nuclear material (SNM), i.e., highly enriched uranium and plutonium. The development of improved instruments and techniques requires experiments performed with the SNM itself, which is of limited availability. This paper describes the findings of experiments performed at the National Criticality Experiments Research Center conducted using new instruments and techniques on unclassified, kg-quantity SNM objects. These experiments, performed in the framework of the Department of Energy, National Nuclear Security Administration Consortium for Monitoring, Technology, and Verification, focused on detecting, characterizing, and localizing SNM samples with masses ranging from 3.3 to 13.8 kg, including plutonium and highly enriched uranium using prototype detectors and techniques. The work demonstrates SNM detection and characterization using recently-developed prototype detection systems. Specifically, we present new results in passive detection and imaging of plutonium and uranium objects using gamma-ray and dual particle (fast neutron and gamma-ray) imaging. We also present a new analysis of the delayed neutron emissions during active interrogation of uranium using a neutron generator.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗

Protein search for multiple targets on DNA

Protein-DNA interactions are crucial for all biological processes. One of the most important fundamental aspects of these interactions is the process of protein searching and recognizing specific binding sites on DNA. A large number of experimental and theoretical investigations have been devoted to uncovering the molecular description of these phenomena, but many aspects of the mechanisms of protein search for the targets on DNA remain not well understood. One of the most intriguing problems is the role of multiple targets in protein search dynamics. Using a recently developed theoretical framework we analyze this question in detail. Our method is based on a discrete-state stochastic approach that takes into account most relevant physical-chemical processes and leads to fully analytical description of all dynamic properties. Specifically, systems with two and three targets have been explicitly investigated. It is found that multiple targets in most cases accelerate the search in comparison with a single target situation. However, the acceleration is not always proportional to the number of targets. Surprisingly, there are even situations when it takes longer to find one of the multiple targets in comparison with the single target. It depends on the spatial position of the targets, distances between them, average scanning lengths of protein molecules on DNA, and the total DNA lengths. Physical-chemical explanations of observed results are presented. Our predictions are compared with experimental observations as well as with results from a continuum theory for the protein search. Extensive Monte Carlo computer simulations fully support our theoretical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mimicking Martian dust: An in-vacuum dust deposition system for testing the ultraviolet sensors on the Curiosity rover

We have designed and developed an in-vacuum dust deposition system specifically conceived to simulate and study the effect of accumulation of Martian dust on the electronic instruments of scientific planetary exploration missions. We have used this device to characterize the dust effect on the UV sensor of the Rover Environmental Monitoring Station in the Mars science Laboratory mission of NASA in similar conditions to those found on Mars surface. The UV sensor includes six photodiodes for measuring the radiation in all UV wavelengths (direct incidence and reflected); it is placed on the body of Curiosity rover and it is severely affected by the dust deposited on it. Our experimental setup can help to estimate the duration of reliable reading of this instrument during operation. We have used an analogous of the Martian dust in chemical composition (magnetic species), color, and density, which has been characterized by X-ray spectroscopy. To ensure a Brownian motion of the dust during its fall and a homogeneous coverage on the instrumentation, the operating conditions of the vacuum vessel, determined by partial pressures and temperature, have to be modified to account for the different gravities of Mars with respect to Earth. We propose that our designed device and operational protocol can be of interest to test optoelectronic instrumentation affected by the opacity of dust, as can be the degradation of UV photodiodes in planetary exploration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

CAMELOT: A machine learning approach for coarse-grained simulations of aggregation of block-copolymeric protein sequences

We report the development and deployment of a coarse-graining method that is well suited for computer simulations of aggregation and phase separation of protein sequences with block-copolymeric architectures. Our algorithm, named CAMELOT for Coarse-grained simulations Aided by MachinE Learning Optimization and Training, leverages information from converged all atom simulations that is used to determine a suitable resolution and parameterize the coarse-grained model. To parameterize a system-specific coarse-grained model, we use a combination of Boltzmann inversion, non-linear regression, and a Gaussian process Bayesian optimization approach. The accuracy of the coarse-grained model is demonstrated through direct comparisons to results from all atom simulations. We demonstrate the utility of our coarse-graining approach using the block-copolymeric sequence from the exon 1 encoded sequence of the huntingtin protein. This sequence comprises of 17 residues from the N-terminal end of huntingtin (N17) followed by a polyglutamine (polyQ) tract. Simulations based on the CAMELOT approach are used to show that the adsorption and unfolding of the wild type N17 and its sequence variants on the surface of polyQ tracts engender a patchy colloid like architecture that promotes the formation of linear aggregates. These results provide a plausible explanation for experimental observations, which show that N17 accelerates the formation of linear aggregates in block-copolymeric N17-polyQ sequences. The CAMELOT approach is versatile and is generalizable for simulating the aggregation and phase behavior of a range of block-copolymeric protein sequences.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Comparison of the Marcus and Pekar partitions in the context of non-equilibrium, polarizable-continuum solvation models

The Marcus and Pekar partitions are common, alternative models to describe the non-equilibrium dielectric polarization response that accompanies instantaneous perturbation of a solute embedded in a dielectric continuum. Examples of such a perturbation include vertical electronic excitation and vertical ionization of a solution-phase molecule. Here, we provide a general derivation of the accompanying polarization response, for a quantum-mechanical solute described within the framework of a polarizable continuum model (PCM) of electrostatic solvation. Although the non-equilibrium free energy is formally equivalent within the two partitions, albeit partitioned differently into “fast” versus “slow” polarization contributions, discretization of the PCM integral equations fails to preserve certain symmetries contained in these equations (except in the case of the conductor-like models or when the solute cavity is spherical), leading to alternative, non-equivalent matrix equations. Unlike the total equilibrium solvation energy, however, which can differ dramatically between different formulations, we demonstrate that the equivalence of the Marcus and Pekar partitions for the non-equilibrium solvation correction is preserved to high accuracy. Differences in vertical excitation and ionization energies are <0.2 eV (and often <0.01 eV), even for systems specifically selected to afford a large polarization response. Numerical results therefore support the interchangeability of the Marcus and Pekar partitions, but also caution against relying too much on the fast PCM charges for interpretive value, as these charges differ greatly between the two partitions, especially in polar solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗