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DOE OSTI2025

A Gigaparsec-scale Hydrodynamic Volume Reconstructed with Deep Learning

The next generation of spectroscopic surveys will map the large-scale structure of the Universe at high redshifts (2 ≤ z ≤ 5) using millions of quasar spectra, enabling major advances in constraining both the standard cosmological model and its extensions. Robust cosmological analyses of these data sets require numerical simulations that both cover gigaparsec volumes and resolve features on ∼10 kpc scales and smaller. However, running such large-volume, high-resolution hydrodynamic simulations is computationally prohibitive. We present a generative deep learning model that enhances a low-resolution, gigaparsec-scale (960 h −1 Mpc) hydrodynamic simulation using a smaller (80 h −1 Mpc) high-resolution input hydrodynamic simulation as training data. The resulting enhanced simulation reproduces the line-of-sight power spectrum to within ∼10% and the three-dimensional power spectrum at the ∼20% level at intermediate to small scales (k ≲ 2 h Mpc −1 ). Our method shows strong promise for producing realistic simulations for cosmological analyses with current surveys such as the Dark Energy Spectroscopic Instrument and upcoming next-generation experiments, but further improvements are needed to accurately recover the large-scale modes. We publicly release the enhanced hydrodynamic simulation, along with a halo catalog from a companion N-body dark matter simulation to support the calibration of data analysis pipelines for these large-scale surveys.

Convolutional neural networks↗

NASA NTRS2010

Proposed Objective Odor Control Test Methodology for Waste Containment

The Orion Cockpit Working Group has requested that an odor control testing methodology be proposed to evaluate the odor containment effectiveness of waste disposal bags to be flown on the Orion Crew Exploration Vehicle. As a standardized "odor containment" test does not appear to be a matter of record for the project, a new test method is being proposed. This method is based on existing test methods used in industrial hygiene for the evaluation of respirator fit in occupational settings, and takes into consideration peer reviewed documentation of human odor thresholds for standardized contaminates, industry stardnard atmostpheric testing methodologies, and established criteria for laboratory analysis. The proposed methodology is quantitative, though it can readily be complimented with a qualitative subjective assessment. Isoamyl acetate (IAA - also known at isopentyl acetate) is commonly used in respirator fit testing, and there are documented methodologies for both measuring its quantitative airborne concentrations. IAA is a clear, colorless liquid with a banana-like odor, documented detectable smell threshold for humans of 0.025 PPM, and a 15 PPB level of quantation limit.

Vos, Gordon↗

NASA NTRS2018

SLS Navigation Model-Based Design Approach

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and management of design requirements to the development of usable models, model requirements, and model verification and validation efforts. The models themselves are represented in C/C++ code and accompanying data files. Under the idealized process, potential ambiguity in specification is reduced because the model must be implementable versus a requirement which is not necessarily subject to this constraint. Further, the models are shown to emulate the hardware during validation. For models developed by the Navigation Team, a common interface/standalone environment was developed. The common environment allows for easy implementation in design and analysis tools. Mechanisms such as unit test cases ensure implementation as the developer intended. The model verification and validation process provides a very high level of component design insight. The origin and implementation of the SLS variant of Model-based Design is described from the perspective of the SLS Navigation Team. The format of the models and the requirements are described. The Model-based Design approach has many benefits but is not without potential complications. Key lessons learned associated with the implementation of the Model Based Design approach and process from infancy to verification and certification are discussed

Oliver, T. Emerson↗

NASA NTRS2024

Filament Wound Composite Analysis Using the NASA Multiscale Analysis Tool (NASMAT) and Finite Element Analysis

Fiber reinforced composite materials, owing to their tailorable thermomechanical and functional properties, allow one to produce a structure that is stronger, stiffer, and lighter than its metal counterpart while performing the same function, yielding a more efficient structure. This not only allows for the improvement of current technologies like aircraft structures, but also enables new technologies like gaseous hydrogen storage for mobility applications, which are otherwise impractical when manufactured using traditional metals due to weight and space restrictions or material embrittlement. However, the use of composites imposes greater design and manufacturing challenges on an engineer, since they are heterogenous, having a distinct structure across multiple length scale, behave generally anisotropically at the structural level and require complex manufacturing and processing methods. Capturing this complex behavior requires detailed numerical simulations, including the modeling of microstructural features like undulations, voids, and fiber alignment. In this paper, multiple repeating unit cells (RUCs), representing filament wound composites, are developed (via a script provided in the Appendix) and analyzed. The refinement of these RUCs is varied, and the analyses are performed using both the Abaqus finite element software and the NASA Multiscale Analysis Tool (NASMAT). A study is undertaken to compare the predicted effective elastic properties of the wound RUC to a laminate representation of the wound RUC, which neglects the undulations. Additionally, two different sets of periodic boundary conditions (PBCs) have been examined. One approximates the real boundary conditions using a standard approach and the other represents the PBCs exactly through the use of an offset. Lastly, a comparison of the local elastic stress fields is made among the models and approaches. Since wound structures are often approximated as laminated structures, it is important to understand the degree to which this assumption is valid, namely by first comparing the elastic constants and local elastic fields. This will provide, on the one hand, information concerning the bulk mechanical behavior and, on the other hand, insights concerning local load distributions and likely damage initiation sites.

Composites↗

NASA NTRS2004

Two-Finger EKG Method of Detecting Evasive Responses

A system based on acquisition and processing of electrocardiographic (EKG) signals from two fingers has been proposed as a means of determining whether a person is answering questions evasively. The system -- in effect, a "lie detector" of sorts, would be used to gauge prospective passengers responses to questions at airport security checkpoints. The person to be interrogated would be required to put one finger from each hand onto two metal strips on a counter and would be instructed to relax and wait for the system to indicate that it is ready. Then a security person would ask the passenger a set of standard security questions. EKG signals acquired through contact with the fingers would be processed by an algorithm that would extract a single-value measure of the level of stress in the interrogated person. This measure would be used to determine whether the system should display a green or a red light to signify that the person is or is not, respectively, telling the truth. It has also been conjectured that the system may be useful for communicating with a person who is in a coma and, hence, unable to speak.

Oldham, Daniel↗

DOE OSTI2016

SU-F-I-76: Fluoroscopic X-Ray Beam Profiles for Spectra Incorporating Copper Filtration

Purpose: The purpose of this investigation is to characterize and quantify X-ray beam profiles for fluoroscopic x-ray beam spectra incorporating spectral (copper) filtration. Methods: A PTW (Freiburg, Germany) type 60016 silicon diode detector and PTW MP3 water tank were used to measure X-ray beam profiles for 60, 80, 100 and 120 kVp x-ray beams at five different copper filtration thicknesses ranging from 0–0.9 mm at 22 and 42 cm fields of view and depths of 1, 5, and 10 cm in both the anode-cathode axis (inplane) and cross-plane directions. All measurements were acquired on a Siemens (Erlangen, Germany) Artis ZeeGo fluoroscope inverted from the typical orientation providing an x-ray beam originating from above the water surface with the water level set at 60 cm from the focal spot. Results: X-ray beam profiles for beam spectra without copper filtration compared well to previously published data by Fetterly et al. [Med Phys, 28, 205 (2001)]. Our data collection benefited from the geometric orientation of the fluoroscope, providing a beam perpendicular to the tank water surface, rather than through a thin side wall as did the previously mentioned study. Profiles for beams with copper filtration were obtained which have not been previously investigated and published. Beam profiles in the anode-cathode axis near the surface and at lower x-ray energy exhibited substantial heel effect, which became less pronounced at greater depth. At higher energy with copper filtration in the beam, the dose falloff out-of-field became less pronounced, as would be anticipated given higher scatter photon energy. Conclusion: The x-ray beam profile data for the fluoroscopic x-ray beams incorporating copper filtration are intended for use as reference data for estimating doses to organs or soft tissue, including fetal dose, involving similar beam qualities or for comparison with mathematical models.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗

DOE OSTI2021

Molecular Mechanisms of Nanomaterial-Bacterial Interactions Revealed by Omics—The Role of Nanomaterial Effect Level

Nanotechnology is employed across a wide range of antibacterial applications in clinical settings, food, pharmaceutical and textile industries, water treatment and consumer goods. Depending on type and concentration, engineered nanomaterials (ENMs) can also benefit bacteria in myriad contexts including within the human body, in biotechnology, environmental bioremediation, wastewater treatment, and agriculture. However, to realize the full potential of nanotechnology across broad applications, it is necessary to understand conditions and mechanisms of detrimental or beneficial effects of ENMs to bacteria. To study ENM effects, bacterial population growth or viability are commonly assessed. However, such endpoints alone may be insufficiently sensitive to fully probe ENM effects on bacterial physiology. To reveal more thoroughly how bacteria respond to ENMs, molecular-level omics methods such as transcriptomics, proteomics, and metabolomics are required. Because omics methods are increasingly utilized, a body of literature exists from which to synthesize state-of-the-art knowledge. Here we review relevant literature regarding ENM impacts on bacterial cellular pathways obtained by transcriptomic, proteomic, and metabolomic analyses across three growth and viability effect levels: inhibitory, sub-inhibitory or stimulatory. As indicated by our analysis, a wider range of pathways are affected in bacteria at sub-inhibitory vs. inhibitory ENM effect levels, underscoring the importance of ENM exposure concentration in elucidating ENM mechanisms of action and interpreting omics results. In addition, challenges and future research directions of applying omics approaches in studying bacterial-ENM interactions are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Spurious Correlations between Galaxies and Multiepoch Image Stacks in the DESI Legacy Surveys

A nonnegligible source of systematic bias in cosmological analyses of galaxy surveys is the on-sky modulation that is caused by foregrounds and variable image characteristics, such as observing conditions. Standard mitigation techniques perform a regression between the observed galaxy density field and sky maps of the potential contaminants. Such maps are ad hoc lossy summaries of the heterogeneous sets of coadded exposures that contribute to the survey. We present a methodology for addressing this limitation, and we extract spurious correlations between the observed distributions of galaxies and arbitrary stacks of single-epoch exposures. We study four types of galaxies (luminous red galaxies, emission-line galaxies, quasars, and Lyman-break galaxies) in the three regions of the DESI Legacy Surveys (North, South, and Dark Energy Survey), resulting in 12 samples with varying levels and types of contamination. We find that the new technique outperforms the traditional ones in all cases, and is able to remove higher levels of contamination. This paves the way for new methods that extract more information from multiepoch galaxy survey data and mitigate large-scale biases more effectively.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1992

The Global Ocean Observing System

A Global Ocean Observing System (GOOS) should be established now with international coordination (1) to address issues of global change, (2) to implement operational ENSO forecasts, (3) to provide the data required to apply global ocean circulation models, and (4) to extract the greatest value from the one billion dollar investment over the next ten years in ocean remote sensing by the world's space agencies. The objectives of GOOS will focus on climatic and oceanic predictions, on assessing coastal pollution, and in determining the sustainability of living marine resources and ecosystems. GOOS will be a complete system including satellite observations, in situ observations, numerical modeling of ocean processes, and data exchange and management. A series of practical and economic benefits will be derived from the information generated by GOOS. In addition to the marine science community, these benefits will be realized by the energy industries of the world, and by the world's fisheries. The basic oceanic variables that are required to meet the oceanic and predictability objectives of GOOS include wind velocity over the ocean, sea surface temperature and salinity, oceanic profiles of temperature and salinity, surface current, sea level, the extent and thickness of sea ice, the partial pressure of CO2 in surface waters, and the chlorophyll concentration of surface waters. Ocean circulation models and coupled ocean-atmosphere models can be used to evaluate observing system design, to assimilate diverse data sets from in situ and remotely sensed observations, and ultimately to predict future states of the system. The volume of ocean data will increase enormously over the next decade as new satellite systems are launched and as complementary in situ measuring systems are deployed. These data must be transmitted, quality controlled, exchanged, analyzed, and archived with the best state-of-the-art computational methods.

Kester, Dana↗

NASA NTRS1995

Measuring forest landscape patterns in the Cascade Range of Oregon, USA

This paper describes the use of a set of spatial statistics to quantify the landscape pattern caused by the patchwork of clearcuts made over a 15-year period in the western Cascades of Oregon. Fifteen areas were selected at random to represent a diversity of landscape fragmentation patterns. Managed forest stands (patches) were digitized and analyzed to produce both tabular and mapped information describing patch size, shape, abundance and spacing, and matrix characteristics of a given area. In addition, a GIS fragmentation index was developed which was found to be sensitive to patch abundance and to the spatial distribution of patches. Use of the GIS-derived index provides an automated method of determining the level of forest fragmentation and can be used to facilitate spatial analysis of the landscape for later coordination with field and remotely sensed data. A comparison of the spatial statistics calculated for the two years indicates an increase in forest fragmentation as characterized by an increase in mean patch abundance and a decrease in interpatch distance, amount of interior natural forest habitat, and the GIS fragmentation index. Such statistics capable of quantifying patch shape and spatial distribution may prove important in the evaluation of the changing character of interior and edge habitats for wildlife.

Ripple, William J.↗

NASA NTRS1996

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Duong, Tuan A.↗

DOE OSTI2017

System and method for preventing stator permanent magnet demagnetization during vacuum pressure impregnation

A permanent magnet electrical machine includes a stator having conductive windings wound thereon and one or more permanent magnets embedded in the stator. A magnetic keeper element is positioned on the stator so as to form a magnetic flux path with the permanent magnets, with the magnetic keeper element closing the magnetic flux path of the permanent magnets by providing a low reluctance flux path to magnetic flux generated by the permanent magnets. A vacuum pressure impregnation (VPI) process is performed on the stator to increase a thermal conductivity of the windings, with the VPI process including a curing step that is performed at a selected temperature. The magnetic keeper element sets an operating point of the permanent magnets to an internal flux density level above a demagnetization threshold associated with the selected temperature at which the curing step is performed.

42 ENGINEERING↗

NASA NTRS2018

Impacts of Snow and Cloud Covers on Satellite-Derived PM 2.5 Levels

Satellite aerosol optical depth (AOD) has been widely employed to evaluate ground fine particle (PM 2.5 ) levels, whereas snow/cloud covers often lead to a large proportion of non-random missing AOD. As a result, the fully covered and unbiased PM 2.5 estimates will be hard to generate. Among the current approaches to deal with the data gap issue, few have considered the cloud-AOD relationship and none of them have considered the snow-AOD relationship. This study examined the impacts of snow and cloud covers on AOD and PM 2.5 and made full-coverage PM 2.5 predictions with the consideration of these impacts. To estimate the missing AOD, daily gap-filling models with snow/cloud fractions and meteorological covariates were developed using the random forest algorithm. By using these models in New York State, a daily AOD data set with a 1-km resolution was generated with a complete coverage. The“out-of-bag” R 2 of the gap-filling models averaged 0.93 with an interquartile range from 0.90 to 0.95. Subsequently, a random forest-based PM 2.5 prediction model with the gap-filled AOD and covariates was built to predict fully covered PM 2.5 estimates. A ten-fold cross-validation for the prediction model showed a good performance with an R 2 of 0.82. In the gap-filling models, the snow fraction was of higher significance in the snow season compared with the rest of the year. The prediction models fitted with/without the snow fraction also suggested the discernible changes in PM 2.5 patterns, further confirming the significance of this parameter. Compared with the methods without considering snow and cloud covers, our PM 2.5 prediction surfaces showed more spatial details and reflected small-scale terrain-driven PM 2.5 patterns. The proposed methods can be generalized to the areas with extensive snow/cloud covers and large proportions of missing satellite AOD for predicting PM 2.5 levels with high resolutions and complete coverage.

AOD↗

DOE OSTI2016

Anharmonic modeling of the conformation-specific IR spectra of ethyl, n-propyl, and n-butylbenzene

In this paper, conformation-specific UV-IR double resonance spectra are presented for ethyl, n-propyl, and n-butylbenzene. With the aid of a local mode Hamiltonian that includes the effects of stretch-scissor Fermi resonance, the spectra can be accurately modeled for specific conformers. These molecules allow for further development of a first principles method for calculating alkyl stretch spectra. Across all chain lengths, certain dihedral patterns impart particular spectral motifs at the quadratic level. However, the anharmonic contributions are consistent from molecule to molecule and conformer to conformer. This transferability of anharmonicities allows for the Hamiltonian to be constructed from only a harmonic frequency calculation, reducing the cost of the model. Finally, the phenyl ring alters the frequencies of the CH 2 stretches by about 15 cm -1 compared to their n-alkane counterparts in trans configurations. Conformational changes in the chain can lead to shifts in frequency of up to 30 cm -1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

X-ray-line coincidence photopumping in a potassium-chlorine mixed plasma

Exploiting the multiple long pulse capability and suite of x-ray diagnostics of the Orion laser, we have set out to explore line coincidence photopuming—the enhancement in population of an atomic level brought on by resonant absorption of x rays from a different emitting ion. Unlike previous work, the two ions are in the same plasma and so the experiment is an x-ray analog of the well-known Bowen resonance fluorescence mechanism that operates in astrophysical situations in the optical region. Herein, our measurements have shown enhanced fluorescence in a chlorine plasma, attributable to line coincident photopumping from co-mixed potassium ions. To detect this relatively low signal-to-noise phenomenon, the data from multiple shots are combined, and the statistical method of bootstrapping is used to assign a confidence value to the measured enhancement, resulting in an estimate of the enhancement of 39 ± 18 16 % compared to the null case, where no pumping occurs. The experimental results have been compared to coupled radiation-transport and radiation hydrodynamics simulations using the CRETIN code together with the NYM radiation hydrodynamics model and agreement has been found, with the simulations also predicting modest enhancement.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

Electronic and Spectral Properties of RRhSn (R = Gd, Tb) Intermetallic Compounds

The investigations of electronic structure and optical properties of GdRhSn and TbRhSn were carried out. The calculations of band spectrum, taking into account the spin polarization, were performed in a local electron density approximation with a correction for strong correlation effects in 4f shell of rare earth metal (LSDA + U method). The optical studies were done by ellipsometry in a wide range of wavelengths, and the set of spectral and electronic characteristics was determined. It was shown that optical absorption in a region of interband transitions has a satisfactory explanation within a scope of calculations of density of electronic states carried out.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Quantum Mechanical Simulations of Complex Nanostructures for Photovoltaic Applications

A quantitative understanding of the electronic excitations in nanostructures, especially complex nanostructures, is crucial for making new-generation photovoltaic (PV) cells based on nanotechnology, which have high efficiency and low cost. Yet current quantum mechanical simulation methods are either computationally too expensive or not accurate and reliable enough, hindering the rational design of the nanoscale PV cells. The PI seeks to develop new methodologies to overcome the challenges in this very difficult and long-lasting problem, pushing the field forward so that electronic excitations can be accurately predicted for systems involving thousands of atoms. The primary objective of this project is to develop new approaches for electronic excitation calculations that are more accurate than traditional density functional theory (DFT) and are applicable to systems larger than what current beyond-DFT methods can treat. In this proposal, the PI will first address the excited-state problem within the DFT framework to obtain quasiparticle energies from both Kohn-Sham (KS) eigenvalues and orbitals; and the electron-hole binding energy will be computed based on screened Coulomb interaction of corresponding DFT orbitals. The accuracy of these approaches will be examined against many-body methods of GW/BSE and quantum Monte Carlo (QMC). The PI will also work on improving the accuracy and efficiency of the GW/BSE and QMC methods in electronic excitation computations by using better KS orbitals obtained from orbital-dependent DFT as inputs. Then an extended QMC database of ground- and excited-state properties will be developed, and this will be spot checked and supplemented with data from GW/BSE calculations. The investigation will subsequently focus on the development of an improved exchange-correlation (XC) density functional beyond the current generalized gradient approximation (GGA) level of parameterization, with parameters fitted to the QMC database. This will allow the ground-state properties of focus systems to be more precisely predicted using DFT. These new developments will then be applied to investigate a chosen set of complex nanostructures that have great potential for opening new routes in designing materials with improved transport, electronic, and optical properties for PV and other optoelectronic usages: (1) Hybrid interfaces between materials with distinct electronic and optical properties, such as organic molecules (conjugated polymers, e.g. P3HT) and inorganic semiconducting materials (Si and ZnO). Complicated interface structures, including interface bonding configurations, compositional and geometrical blending patterns, interfacial defects, and various sizes and shapes of inorganic nanomaterials, will be considered for the purpose of understanding the working mechanisms of present organic/nano PV systems and designing optimum interface structures for fast charge separation and injection. (2) Complex-structured semiconducting nanomaterials that could induce charge separation without pn- or hetero-junctions. The new methodology will allow the PI to investigate the performance of realistic semiconducting nanomaterials of internal (impurities, defects, etc.) and external (uneven surface, mechanical twisting and bending, surface chemistry, etc.) complexities on optical absorption and charge transport against charge trapping and recombination. Of particular interest is whether such structural complexity in a single material could even be beneficial for PV usage, for example, charge separation through morphology control. Successful completion of the proposed DFT methodology would have a far-reaching impact on our ability to study and exploit the nature of electronic excitations in complex materials, advancing the design of next-generation electronic and optoelectronic devices in all facets of renewable energy conversion and storage, including photovoltaics, thermoelectricity, photochemistry, etc.

14 SOLAR ENERGY↗