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At least 1,585 records · Page 88

Laser-Produced Coherent X-ray Sources. Final report

This is the final report for the DOE-AMO DE-FG02-05ER15663 grant. Using a high-peak-power laser system at the Extreme Light Laboratory of the University of Nebraska-Lincoln, we develop novel femtosecond radiation sources and use them to investigate ultrafast photo-induced processes. Pulses of high energy electrons and x-rays are generated when an optical pulse is focused to ultra-high intensity. The radiation is used to probe the evolution of matter under highly non-equilibrium conditions with atomic-scale temporal and spatial resolution. Moreover, the facility is small enough to fit in a university laboratory and is operated by graduate students and postdocs.

74 ATOMIC AND MOLECULAR PHYSICS↗

Seismic Spatial Gradients and Machine Learning-Based Classifiers for Explosion Monitoring (LDRD 218327)

This final report summarizes the work completed under the Laboratory Directed Research and Development (LDRD) project “Seismic Spatial Gradients as a Machine Learning-Based Classifier for Explosion Monitoring.” The overarching goal of the project was to explore the efficacy of using machine learning-based classification algorithms where the input data are the spatial gradient of the seismic wavefield collected at a single point on the Earth’s surface. The methods that I describe here are in direct contrast to conventional methods of seismic discrimination which typically rely on a spatially extended network of instruments and physics-based wavefield attributes such as, for example, the ratio between $\textit{P}$ and $\textit{S}$ waves. Rather, we use the spatial gradient of the seismic wavefield observed at a single point on the Earth’s surface and data processing approaches inspired by the machine learning community. We tested two algorithms, a neural network and a modified version of principal component analysis termed Spectrally Filtered Principal Component Analysis (SFPCA). To test these algorithms, we first conducted a series of numerical tests using synthetic data and then conducted a small-scale controlled field experiment. The tests using synthetic data showed that both algorithms had high success rates on gradiometric data, even when simulated noise was added to the signal. Furthermore, we found that using seismic spatial gradients increased the performance of our discrimination algorithms when compared to using just the traditional translational motion seismic data. The tests with field data also showed a high degree of discriminative success.

58 GEOSCIENCES↗

Understanding and Controlling Photoexcited Molecules in Complex Environments (Final Technical Report)

Predicting the outcome of a photochemical reaction is complicated by factors outside the scope of tradition theoretical chemistry. On such small scales, fluctuations of the environment render outcomes stochastic, nonadiabatic dynamics blur the separation between nuclear and electronic motion, and ultrafast relaxation renders typical assumptions of equilibrium inappropriate. This project aimed to elucidate and control nonadiabatic molecular dynamics in condensed phases. We developed accurate, efficient simulation tools to study irreversible molecular processes computational across a range of scales. We applied these methodological advances to study electron transfer under exotic conditions where spin and topology opened new pathways for reactivity. We also brought these ideas to bare on light harvesting systems, where energy and charge transport are coupled, and where long lifetimes can be deleterious to function. These advances helped to establish general principles for chemical efficiency and guide the design of nanoscale energy materials, molecular machines, and related technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Catastrophic disruption in the solar system - Asteroid collisional history, origin of Hirayama families and disruption of small satellites

The process of collisional catastrophic disruption has played a significantly role in structuring the solar system. Diverse populations of bodies such as the asteroid belt, small satellites of Jupiter and Saturn and perhaps even the rings of Saturn have been created or substantially changed by catastrophic distruption. Understanding the outcome of large scale impacts is essential to learning about the early history of the solar system in the asteroid zone and the reason why a planet failed to form there.

Davis, D. R.↗

Steady state flow/field model of solar wind interaction with Venus - Global implications of local effects

Physical and chemical processes in the Venus ionosphere driven by the interaction of the solar wind with the atmosphere of Venus are described, and a model describing the interrelationships of these processes in a self-consistent manner is formulated. It is shown that the magnetic field configuration of the ionosphere is a steady state global structure which results from a combination of a large-scale 'open' current system connecting through the ionopause to the postshock solar wind and two small-scale 'closed' current systems entirely confined within the ionosphere and generated by ionospheric flows and shears. A previously detected ionospheric layer in O2(+) near 170 km altitude is shown to be a new type of ionospheric layer resulting from transition of solar-wind-driven vertical flow to velocities approaching Mach 1.

Cloutier, P. A.↗

How well can regional fluxes be derived from smaller-scale estimates?

Regional surface fluxes are essential lower boundary conditions for large scale numerical weather and climate models and are the elements of global budgets of important trace gases. Surface properties affecting the exchange of heat, moisture, momentum and trace gases vary with length scales from one meter to hundreds of km. A classical difficulty is that fluxes have been measured directly only at points or along lines. The process of scaling up observations limited in space and/or time to represent larger areas was done by assigning properties to surface classes and combining estimated or calculated fluxes using an area weighted average. It is not clear that a simple area weighted average is sufficient to produce the large scale from the small scale, chiefly due to the effect of internal boundary layers, nor is it known how important the uncertainty is to large scale model outcomes. Simultaneous aircraft and tower data obtained in the relatively simple terrain of the western Alaska tundra were used to determine the extent to which surface type variation can be related to fluxes of heat, moisture, and other properties. Surface type was classified as lake or land with aircraft borne infrared thermometer, and flight level heat and moisture fluxes were related to surface type. The magnitude and variety of sampling errors inherent in eddy correlation flux estimation place limits on how well any flux can be known even in simple geometries.

Moore, Kathleen E.↗

How well can regional fluxes be derived from smaller-scale estimates?

Regional surface fluxes are essential lower boundary conditions for large scale numerical weather and climate models and are the elements of global budgets of important trace gases. Surface properties affecting the exchange of heat, moisture, momentum and trace gases vary with length scales from one meter to hundreds of km. A classical difficulty is that fluxes have been measured directly only at points or along lines. The process of scaling up observations limited in space and/or time to represent larger areas was done by assigning properties to surface classes and combining estimated or calculated fluxes using an area weighted average. It is not clear that a simple area weighted average is sufficient to produce the large scale from the small scale, chiefly due to the effect of internal boundary layers, nor is it known how important the uncertainty is to large scale model outcomes. Simultaneous aircraft and tower data obtained in the relatively simple terrain of the western Alaska tundra were used to determine the extent to which surface type variation can be related to fluxes of heat, moisture, and other properties. Surface type was classified as lake or land with aircraft borne infrared thermometer, and flight level heat and moisture fluxes were related to surface type. The magnitude and variety of sampling errors inherent in eddy correlation flux estimation place limits on how well any flux can be known even in simple geometries.

Moore, Kathleen E.↗

The electron diffusion region and its relation to the larger-scale environment

The electron diffusion region forms the inner core of the magnetic reconnection machine. In this region, physical processes act to sustain a reconnection electric field, they accelerate to provide current density, and the heat to provide particle pressure in the current layer. The relative roles of these processes depend on whether the overall geometry is anti-parallel or asymmetric, and whether a guide field is present of not, but the overall concept applies in each case. The EDR is embedded in successively larger regions, starting with the ion diffusion region to even larger scales, where the plasma increasingly behaves like an anisotropic MHD plasma. With our new understanding of how the EDR works, it is of great interest to study how EDR processes couple to the larger scale environment. The ultimate efficacy of the magnetic reconnection is shaped by this interesting example of micro-macro coupling. In this presentation, we present some thoughts pertaining to this topic. In particular, we will discuss how information transport between scales is mediated, and how the very small scales can reach balance with the larger, overall system. We will review any pertinent research and present a set of questions inviting future research.

Michael Hesse↗

Lunar and Planetary Science XXXV: Mars Polar Processes: Land and Sky

The titles in this section include: 1) Morphological Evidence for the Large-scale Evolution of Martian North Polar Troughs? 2) New Views of the Martian Polar Regions: The Latest Results from the Mars Odyssey THEMIS Investigation; 3) Observations at the Chasma Australe Re-Entrant, South Polar Region, Mars; 4) Stratigraphic Details of Uppermost Units within South Polar Layered Deposits on Mars; 5) Detailed Geologic Analysis of Part of the South Polar Layered Deposits, Planum Australe, Mars: Part II; 6) SHARAD: Radar Volume Scattering and the Polar Layered Terrains on Mars; 7) Arabia and Memnonia Equatorial Regions with High Content of Water: Data from HEND/Odyssey; 8) Alaskan Permafrost Analogs of Martian Small Valley Networks, Thermokarst, Terrain Softening, Terraces, and Volcanic Craters; 9) Periglacial Processes in the Southern Hemisphere of Mars; 10) Thermal Modeling of Possible Surface Water Ice Deposits in Juventae Chasma; 11) Modeling Depth to Ground Ice on Mars; 12) Ground Ice at the Phoenix Landing Site: A Preflight Assessment; 13) Possible Temperature-related Differences in Slope Angle between the North and South Walls of Coprates Chasma, Mars; 14) Seasonal Variations within Korolev Crater, Mars; 15) South Polar Ar Enhancement as a Tracer for Southern Winter Horizontal Meridional Mixing; 16) An Investigation of the Correlation of Water-Ice and Dust Retrievals via the MGS TES Data Set; 17) Observations of Plasma Waves near Mars and Their Implications for Atmospheric Loss.

Source record↗

Exploration Architecture with Quantum Inertial Gravimetry and In-Situ ChipSat Sensors

The Dual Exploration Architecture is a mission concept that combines remote sensing and in-situ observations into a single mission to answer planetary science questions that can only be answered with both types of data. Adoption of dual exploration architectures may short circuit the long, slow cycle of missions to inaccessible bodies by eliminating the need for separate precursor and follow-up missions. Additionally, the dual architecture possesses inherent flexibility that enables the design of adaptive, event-driven missions that are very different from traditional, largely pre-planned missions. Five key observations about the state and trends of planetary science exploration lead us to the dual architecture: increasing complexity of observations; scarcity of future mission opportunities; desire to capture transitory events; continued miniaturization of spacecraft components; and the Mars exploration cycle. Our goal in this study is to explore missions that can only happen using the dual architecture concept and find technology development needs that must be filled for those missions to compete. A survey of historical and current missions finds that opportunities for exploration are becoming less frequent, causing the flexibility and dual-nature elements of each mission to become more common. The dual exploration architecture takes these trends to their far conclusion, attempting to eliminate precursor and follow-up missions while still returning more scientific payoff. A study of the future of planetary science goals through the decadal survey reveals broad applicability of dual missions to solve mysteries that cannot be answered with a traditional mission architecture. These missions fall into three broad classes: choosing a local target from a global survey; dynamic/reactive science; and global in-situ networks. Two example missions of each class are notionally described. A deeper look at these dual architecture classes reveals four technology development needs that must be addressed for wide adoption of dual missions: passive landers; guided atmospheric probes; robust sensing packages; and small, precise orbital instruments. This study pursues a specific focus on two examples of such enabling technologies: the ChipSat and cold atom gravimetry. The ChipSat is a fully functional spacecraft-on-a-chip system that has broad versatility in the dual architecture mission space. Initial studies show that ChipSats could survive as passive impactor landers on bodies up to the size of Europa. Furthermore, COTS (Commercial Off-The-Shelf) components could provide an in-situ sensor suite that readily answers a number of pressing planetary science questions. Cold atom gravimetry uses inertial sensors based on light-pulse atom interferometry in a small form factor to map the gravity field of a body to precision equaling what would normally require two full spacecraft to achieve. The cold atom gravimeter provides an example of how advanced remote sensing capability can enable dual missions by providing greater returns in a significantly smaller package. Using the above two technologies, we study an example dual-architecture mission to both characterize and sample the subsurface oceans at Europa. The greatest scientific return in terms of detecting extraterrestrial life is in those regions where Europa’s ice crust is thin. The identification of regions with thin ice should therefore precede the selection of surface targets and dispatch of probes to those targets. This two-step process, if accomplished by separate flagship-scale missions, might take decades. As a result, a combined mission to both identify thin areas of Europa’s ice and follow up with surface observations at those regions is a good candidate for the dual-exploration architecture. This example mission consists of an orbiter spacecraft carrying a cold atom gravimeter capable of sensing or inferring the ice thickness on regional to local scales, along with a number of ChipSat probes capable of landing on the moon. The small size and weight of the ChipSats allows large numbers of them to be carried, ensuring that enough can be dropped to ensure survival of a minimum number of probes and potentially allowing for the in-situ sampling of multiple locations on the moon. The example missions and Europa case study show that amazing scientific return can obtained from dual-exploration architecture missions with a single launch by breaking the long timescales of planetary exploration and providing the flexibility to capturing transitory events and collect data across the local, regional, and global scales.

Exploration↗

Development of Nanocrystalline Graphite from Lignin Sources

Carbon composites are attractive to a variety of high-impact applications, such as carbon fibers, batteries, and vehicle parts, due to their multifunctional properties. The properties of carbon are highly dependent on the allotrope the carbon takes and the functionality, impurities, and defects contained within the structure. The increase in demand for sustainable carbon sources in energy storage devices motivates interest in understanding synthesis parameters of lignin value-added products. Also, as the dependence on oil for fuel decreases, alternative sources for carbon in many applications will be needed. In this work, the thermochemical conversion of lignin powders from different feedstocks was evaluated via small and wide-angle X-ray scattering techniques to resolve the amorphous, disordered, and crystalline domains present in the lignin carbons. Scattering analyses indicated an evolution of hierarchical structures along with an increase in ordered domains as a function of carbonization temperature. Qualitative and quantitative methods were used to describe isotropic scattering intensity profiles at multiple length scales. The use of power law models in the mesoscopic region served as the basis to describe morphological changes related to structural features, for example, graphene stacking, degree of roughness, and surface fractals. Kraft softwood and switchgrass produced carbon powder with the most crystalline domains and the least surface roughness. Softwoods reached the highest degree of crystallinity followed by switchgrass samples and had less variability in particle sizes. These results suggest lignin carbons extracted from softwoods and switchgrass are viable substitutes for graphite. Interpretation of X-ray scattering data from lignin carbon powders elucidates feedstock- and processing-dependent morphological features across multiple length scales providing a straightforward framework to evaluate the feasibility of leveraging lignin carbons for producing tunable application-specific materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data Summarization and Inference at Scale

This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.

97 MATHEMATICS AND COMPUTING↗

SPITZER SPECTROSCOPY OF INFRARED-LUMINOUS GALAXIES: DIAGNOSTICS OF ACTIVE GALACTIC NUCLEI AND STAR FORMATION AND CONTRIBUTION TO TOTAL INFRARED LUMINOSITY

We use mid-infrared (MIR) spectroscopy from the Spitzer Infrared Spectrograph to study the nature of star-formation and supermassive black hole accretion for a sample of 65 IR-luminous galaxies at 0.02 < z < 0.6 with F(24 {mu}m) > 1.2 mJy. The MIR spectra cover wavelengths 5-38 {mu}m, spanning the polycyclic aromatic hydrocarbon (PAH) features and important atomic diagnostic lines. Our sample of galaxies corresponds to a range of total IR luminosity, L{sub IR} = L(8-1000 {mu}m) = 10{sup 10}-10{sup 12} L{sub Sun} (median L{sub IR} of 3.0 Multiplication-Sign 10{sup 11} L{sub Sun }). We divide our sample into a subsample of galaxies with Spitzer Infrared Array Camera 3.6-8.0 {mu}m colors indicative of warm dust heated by an active galactic nucleus (AGN; IRAGN) and those galaxies whose colors indicate star-formation processes (non-IRAGN). Compared to the non-IRAGN, the IRAGN show smaller PAH emission equivalent widths, which we attribute to an increase in mid-IR continuum from the AGN. We find that in both the IRAGN and star-forming samples, the luminosity in the PAH features correlates strongly with [Ne II] {lambda}12.8 {mu}m emission line, from which we conclude that the PAH luminosity directly traces the instantaneous star-formation rate (SFR) in both the IRAGN and star-forming galaxies. We compare the ratio of PAH luminosity to the total IR luminosity, and we show that for most IRAGN star-formation accounts for 10%-50% of the total IR luminosity. We also find no measurable difference between the PAH luminosity ratios of L{sub 11.3}/L{sub 7.7} and L{sub 6.2}/L{sub 7.7} for the IRAGN and non-IRAGN, suggesting that AGN do not significantly excite or destroy PAH molecules on galaxy-wide scales. Interestingly, a small subset of galaxies (8 of 65 galaxies) show a strong excess of [O IV] {lambda}25.9 {mu}m emission compared to their PAH emission, which indicates the presence of heavily-obscured AGN, including 3 galaxies that are not otherwise selected as IRAGN. The low PAH emission and low [Ne II] emission of the IRAGN and [O IV]-excess objects imply the IR luminosity of these objects is dominated by processes associated with the AGN. Because these galaxies lie in the ''green valley'' of the optical color-magnitude relation and have low implied SFRs, we argue their hosts have declining SFRs and these objects will transition to the red sequence unless some process restarts their star-formation.

79 ASTRONOMY AND ASTROPHYSICS↗

Toward Real Time Neural Net Flight Controllers

NASA Ames Research Center has an ongoing program in neural network control technology targeted toward real time flight demonstrations using a modified F-15 which permits direct inner loop control of actuators, rapid switching between alternative control designs, and substitutable processors. An important part of this program is the ACTIVE flight project which is examining the feasibility of using neural networks in the design, control, and system identification of new aircraft prototypes. This paper discusses two research applications initiated with this objective in mind: utilization of neural networks for wind tunnel aircraft model identification and rapid learning algorithms for on line reconfiguration and control. The first application involves the identification of aerodynamic flight characteristics from analysis of wind tunnel test data. This identification is important in the early stages of aircraft design because complete specification of control architecture's may not be possible even though concept models at varying scales are available for aerodynamic wind tunnel testing. Testing of this type is often a long and expensive process involving measurement of aircraft lift, drag, and moment of inertia at varying angles of attack and control surface configurations. This information in turn can be used in the design of the flight control systems by applying the derived lookup tables to generate piece wise linearized controllers. Thus, reduced costs in tunnel test times and the rapid transfer of wind tunnel insights into prototype controllers becomes an important factor in more efficient generation and testing of new flight systems. NASA Ames Research Center is successfully applying modular neural networks as one way of anticipating small scale aircraft model performances prior to testing, thus reducing the number of in tunnel test hours and potentially, the number of intermediate scaled models required for estimation of surface flow effects.

Jorgensen, C. C.↗

Economic viability of multiple algal biorefining pathways and the impact of public policies

This study presents an extensive systems-level multi-pathway sustainability assessment of algae biofuel production that demonstrates the necessity of high-value co-products, examines the impact of public policy scenarios, and identifies improvements and pathway directions required for economic viability. Engineering process models for several fuel and co-product pathways were leveraged to perform high fidelity techno-economic analysis. These pathways included: baseline hydrothermal liquefaction; protein extraction followed by hydro-thermal liquefaction; fractionation into high-value chemicals with fermentation followed by hydrothermal liquefaction for fuels; and a small-scale first-of-a-kind plant coupled with a wastewater treatment facility. From these models, it was shown that hydrothermal liquefaction as a fuel-only pathway is not economically viable. Likewise, the benefits of coupling with wastewater water treatment are insignificant compared to the impact ofreduced facility size resulting in increased capital costs. These models were also used to examine public policy scenarios, uniquely presenting their impact on the breakeven cost of fuel production and sensitivity to scenario assumptions. Specifically, depreciation type was shown to be irrelevant for write offs faster than 10 years. Due to discounting, short-term subsidies were found to capture 50% of the subsidy value in 6 years with an additional24 years required for full subsidy valuation. Integration of a carbon economy was shown to decrease biofuel production costs, particularly for the protein pathway due to the co-product accounting. Finally, a metric of normalized costs was used to compare algal biorefineries to corn and cellulosic ethanol production, showing that algal systems are uniquely different due to significantly higher capital costs, though operational costs are comparable. Overall, this work demonstrates that, to reach economic viability, algal biofuel production must either utilize higher value non-fuel co-products or achieve drastic reductions in capital costs.

09 BIOMASS FUELS↗

Experiments and CFD simulation of mass transfer and hydrodynamics in a cylindrical bubble column

Flow visualization, Particle Image Velocimetry (PIV) and dissolved oxygen charging experiments are carried out in a small-scale cylindrical air-water bubble column at different superficial gas velocities. Void fraction profile, total gas holdup, liquid phase velocity field and volumetric mass transfer coefficient are obtained. Details of each experiment are given, with a new procedure for obtaining a 2D void fraction profile from flow visualization by image processing and time averaging which could provide useful information for CFD model validation. The experimental results are analyzed and compared with simulations where good agreement is found for both local and global flow patterns. The averaged governing equations and constitutive relations used in the simulation are discussed briefly, with emphasis on the proper comparison between simulations and experiments based on the derivation of the two-fluid model. Finally, by conducting three sets of experiments related to phase distribution, velocity field and mass transfer in the same apparatus, a validated CFD model for multiphase mass transfer is established and can be used in the future design of a multi-phase reactor.

42 ENGINEERING↗

Jacobian-based model diagnostics and application to equation oriented modeling of a carbon capture system

It can be difficult to identify the specific variables or equations responsible for convergence issues in large mathematical programming models. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms. A singular value decomposition is then performed to identify degenerate sets of equations and remaining scaling issues. Here, this work presents a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. This work takes the reader through the entire process of model diagnostics and reformulation, from a basic introduction to the mathematics behind these model diagnostics to the reformulations necessary to make the model numerically robust, including a significantly modified enhancement factor model.

IDAES↗

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↗