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At least 937 records · Page 52

The Multiple Use Plug Hybrid for NanoSats (MUPHyN) Miniature Thruster

The Multiple Use Plug Hybrid (for) Nanosats is a prototype thruster is being developed to fill a niche application for NanoSat-scale spacecraft propulsion. When fully developed, the MUPHyN thruster will provide an effective and low-risk propulsive capability that could enable multiple NanoSats to be independently re-positioned after deployment from a parent launch vehicle. Because the environmentally benign, chemically-stable propellants are mixed only within the combustion chamber after ignition and the flow rate of the fuel is determined by a pyrolysis mechanism that is nearly independent of pressure or fuel grain defects, the system is inherently safe and can be piggy-backed near a secondary payload with little or no overall mission risk increase to the primary payload. The MUPHyN thruster uses safe-handling and inexpensive nitrous oxide (N2O) and acrylonitrile-butadiene-styrene (ABS) as propellants. Fused Deposition Modeling (FDM), a direct digital manufacturing process, is used to fabricate short-form-factor solid fuel grains with multiple helical combustion ports from ABS thermoplastic. This manufacturing process allows for the rapid development and manufacture of complex fuel grain geometries that are not possible to extrude or cast using conventional methods. This technology enables the construction of fuel grains with length-to-diameter ratios appropriate for incorporation into CubeSats while maintaining high surface areas and regression rates that allow the system to maintain a near optimal oxidizer to fuel ratio. The MUPHyN system provides attitude control torques by using secondary-injection thrust vectoring on a truncated aerospike nozzle. This configuration allows large impulse delta V burns and small impulse attitude control firings to be performed with the same system. To ensure survivability during extend duration burns, the MUPHyN incorporates a novel regenerative cooling design where the N2O oxidizer flows through a cooling path embedded in the aerospike nozzle before being injected into the combustion chamber near the nozzle base.

Eilers, Shannon D.↗

Missing Data and Multiple Imputation: An Unbiased Approach

The default method of dealing with missing data in statistical analyses is to only use the complete observations (complete case analysis), which can lead to unexpected bias when data do not meet the assumption of missing completely at random (MCAR). For the assumption of MCAR to be met, missingness cannot be related to either the observed or unobserved variables. A less stringent assumption, missing at random (MAR), requires that missingness not be associated with the value of the missing variable itself, but can be associated with the other observed variables. When data are truly MAR as opposed to MCAR, the default complete case analysis method can lead to biased results. There are statistical options available to adjust for data that are MAR, including multiple imputation (MI) which is consistent and efficient at estimating effects. Multiple imputation uses informing variables to determine statistical distributions for each piece of missing data. Then multiple datasets are created by randomly drawing on the distributions for each piece of missing data. Since MI is efficient, only a limited number, usually less than 20, of imputed datasets are required to get stable estimates. Each imputed dataset is analyzed using standard statistical techniques, and then results are combined to get overall estimates of effect. A simulation study will be demonstrated to show the results of using the default complete case analysis, and MI in a linear regression of MCAR and MAR simulated data. Further, MI was successfully applied to the association study of CO2 levels and headaches when initial analysis showed there may be an underlying association between missing CO2 levels and reported headaches. Through MI, we were able to show that there is a strong association between average CO2 levels and the risk of headaches. Each unit increase in CO2 (mmHg) resulted in a doubling in the odds of reported headaches.

Foy, M.↗

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

Modeling↗

Multiple-Instance Regression with Structured Data

We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.

learning↗

AgMIP Training in Multiple Crop Models and Tools

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

farm crops↗

Coilgun Acceleration Model Containing Interactions Between Multiple Coils

Electromagnetic (EM) accelerators have the potential to fill a performance range not currently being met by conventional chemical and electric propulsion systems by providing a specific impulse of 600-1000 seconds and a thrust-to-power ratio greater than 200 mN/kW. A propulsion system based on EM acceleration of small projectiles has the traditional advantages of using a pulsed system, including precise control over a range of thrust and power levels as well as rapid response and repetition rates. Furthermore, EM accelerators have lower power requirements than conventional electric propulsion systems since no plasma creation is necessary. A coilgun is a specific type of EM device where a high-current pulse through a coil of wire interacts with a conductive projectile via an induced magnetic field to accelerate the projectile. There are no physical or electrical connections to the projectile, which leads to less system degradation and a longer life expectancy. Multi-staging a coilgun by adding multiple turns on a single coil or on the projectile increases the inductance, thus permitting acceleration of the projectile to higher velocities. Previously, a simplified problem of modeling an inductively-coupled, single-coil coilgun using a circuit-based analysis coupled to the one-dimensional momentum equation through Lenz's law was solved; however, the analysis was only conducted on uncoupled coils. The problem is significantly more complicated when multiple, independently-powered coils simultaneously operate and interact with each other and the projectile through induced magnetic fields. This paper presents a multi-coil model developed with the magnetostatic finite element solver QuickField. In the model, mutual inductance values between pairs of conductors were found by first computing the magnetic field energy for different cases where individual coils or multiple coils carry current, then integrating over the entire finite element domain for each case, and finally using the definition of inductive energy storage to solve for the self and mutual inductance. The electric circuit model is coupled to the projectile through Lenz's law, with the coils coupled through mutual inductance but able to be independently triggered at different times to optimize the acceleration profile. This initial model to predict the behavior of a projectile's acceleration through a coupled, multi-coil coilgun increases the potential of building a highly efficient coilgun thruster with key advantages over other EM thruster systems, thus making it a promising candidate for satellite main propulsion or attitude control thrusters.

Liu, Connie↗

Kepler Data Validation II–Transit Model Fitting and Multiple-Planet Search

This paper discusses the transit model-fitting and multiple-planet search algorithms and performance of the Kepler Science Data Processing Pipeline, developed by the Kepler Science Operations Center (SOC). Threshold crossing events (TCEs), which are transit candidate events, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the data validation (DV) component. The transit model is used in DV to fit TCEs to characterize planetary candidates and to derive parameters that are used in various diagnostic tests to classify them. After the signature associated with the TCE is removed from the light curve of the target star, the residual light curve goes through TPS again to search for additional TCEs. The iterative process of transit model fitting and multiple-planet search continues until no TCE is generated from the residual light curve or an upper limit is reached. The transit model-fitting and multiple-planet search performance of the final release (9.3, 2016January) of the pipeline is demonstrated with the results of the processing of four years (17 quarters) of flight data from the primary Kepler Mission. The transit model-fitting results are accessible from the NASA Exoplanet Archive. The final version of the SOC codebase is available through GitHub.

Threshold crossing events (TCEs↗

Simulation and Analysis of Opportunistic MSPA for Multiple Cubesat Deployments

We describe a software approach for simultaneous demodulation and decoding of multiple frequency- multiplexed spacecraft across multiple ground stations. The approach involves the use of a single ground antenna with wide enough aperture to receive multiple angularly adjacent spacecraft simultaneously. This technique uses a wide-band RF signal digitizer coupled with easily and cheaply duplicated software-receiver modules to independently process the frequency-channelized downlink signals from the spacecraft. This approach relaxes the need for realizable modems at each antenna, for example in the Deep-SpaceNetwork (DSN), and can also function as a delayed data retrieval method for cubesat missions with routine science data return. Thus, we hope that this solution can enable more efficient utilization of DSN assets. We concentrate on a simulation similar to the proposed Exploration Mission 1 (EM-1) mission from a geometric perspective. To that end, the simulated scenario involves ten secondary cubesats deployed and tracked for a span of four days (the modeled motion over the first four days of the mission does not include any Trajectory Correction Maneuvers (TCMs) that may be necessary as the cubesats approach the moon). Transmissions from the cubesats may be received through a combination of DSN ground sites based on visibility. The cubesats are assumed to utilize typical cubesat transmit powers and a waveform similar to that of the Iris radio. One cubesat is chosen as the “target” and is considered tracked by all ground-stations throughout the simulation (i.e., it is consistently at the center of the main lobe of each ground station antenna when the ground station is in view of the cubesat in terms of elevation angle). The simulation effort involves synthesizing a wideband signal that includes the ten cubesats across a large bandwidth due to each cubesat having its own center-frequency in X-band, near 8.4 GHz. Each signal is characterized by its own Doppler-frequency shift and free-space path-loss computed through the underlying geometry of the simulation as well as the cubesat transmit power. Finally, each cubesat signal experiences a unique antenna gain at each ground station due to the underlying antenna pattern and spacecraft-ground station geometry. We establish two interesting findings: First, the link-budget for the EM-1-like scenario is almost completely limited by the angle between the center of the antenna main beam and the cubesat, which means that the signal-to-noise ratio is wholly adequate for demodulation and decoding at the simulated bitrates unless the cubesat exits the main beam. Secondly, and fortunately due to the use of a software radio architecture, we show that it is possible to successfully receive signals from most cubesats for the entire 4-day simulation. Due to the signal-to-noise ratio being sufficient for demodulation even after the side-lobe’s 17dB reduction in SNR, the software radio can still demodulate such cubesats as long as the radio is capable of re-establishing carrier lock as the cubesats leave the main beam and enter the side-lobe. Considering that the target application utilizes offline processing, a loss of lock can be detected and lock can be re-established by iterating over the data. Extensive simulations demonstrate these results.

Abraham, Douglas S.↗

Multiple Scattering Effects of Trees on L-band Microwave Using a Hybrid Method

The multiple scattering of electromagnetic waves in forests is studied using a two-step hybrid method. First, the T-matrix of a single tree is calculated based on its far-field computed with the full-wave simulations of the FEKO software. The T-matrix captures the multiple scattering caused by the tree structure. Second, the the interactions among different trees are considered using the T-matrices of the individual trees and the Foldy-Lax equations. The result of the two-step hybrid method is validated with FEKO by solving scattering from two trees directly. The multiple scattering effects are illustrated by the field solutions.

Yueh, Simon↗

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗

Deep Interacting Multiple Model Filtering

In this paper, a deep learning-based multiple model estimation framework is presented for the state estimation of hybrid dynamical systems from high dimensional observations such as camera images. A low dimensional vector which represents the measurement of the latent dynamical system and its corresponding variance are learned using a deep encoder neural network. An Interacting Multiple Model (IMM) filter is used to generate the latent state estimates and covariances using multiple dynamical models, which can be learned using backpropagation through time. The state estimates of the dynamical system and the corresponding covariance matrix are generated from the latent state estimates and covariance using a deep decoder neural network. The whole network is trained in an end-to-end manner using a loss function which minimizes the negative log-likelihood of the neural network parameters. Simulation results are presented using a 2D bouncing ball example and estimation error statistics are computed which demonstrates the accuracy and consistency of the estimation.

Ghananeel Rotithor↗

Multiple Subscale Magnetic Reconnection Embedded inside a Heliospheric Current Sheet Reconnection Exhaust: Evidence for Flux Rope Merging

We report observations of multiple subscale reconnecting current sheets embedded inside a large-scale heliospheric current sheet (HCS) reconnection exhaust. The discovery was made possible by the unusual skimming trajectory of Parker Solar Probe through a sunward-directed HCS exhaust, sampling structures convecting with the exhaust outflows for more than 3 hr during Encounter 14, at a radial distance of ∼17 solar radii. A large number of subscale current sheets (SCSs) were detected inside the HCS exhaust. Remarkably, five SCSs showed direct evidence for reconnection, displaying near-Alfvénic outflow jets and bifurcated current sheets. The reconnecting SCSs all had small magnetic shears (27°–81°), i.e., strong guide fields. The thickness of the subscale reconnecting current sheets ranged from ∼60 km to ∼5000 km (∼20–2000 ion inertial lengths). The SCS exhausts were directed predominantly in the normal or out-of-plane direction of the HCS, i.e., nearly orthogonal to the HCS exhaust direction. The presence of multiple low-magnetic-shear reconnecting current sheets inside a large-scale exhaust could be associated with coalescence of multiple large flux ropes inside the HCS exhaust. The orientation of some SCS exhausts was partly in the ecliptic plane of the HCS, which may indicate that the coalescence process is highly three-dimensional. Since the coalescence process is likely short-lived, the detection of five such events inside a single HCS crossing could imply the common occurrence of flux rope coalescence in large-scale HCS reconnection exhausts.

T D Phan↗

A Workflow to Rapidly Interrogate Multiscale Model Simulation Results Across Multiple Length Scales

Many tools can be used to visualize field and state variables for a single scale analysis so that the influence of relevant mechanisms can be evaluated. Finite element software is often utilized to simulate a unit cell of a material and visualize results at that scale. Material properties can be homogenized from individual constituents and local deformation, damage, and failure mechanisms can be evaluated within the unit cell due to globally applied boundary conditions. Such solutions can produce satisfactory results if a user is only interested in analyzing a single scale. But materials in general contain features across multiple length scales, and assumptions must be made when attempting to account for lower length scale phenomena within a higher length scale model. Multiscale modeling is an attractive means to model materials because detailed material responses can be tracked across multiple disparate length scales while reducing the amount of required assumptions. However, as the complexity of these models increases, a large amount of data can be produced, and data traceability can become increasingly more difficult. Field and state variables, which are naturally dependent on spatial position, may themselves be calculated from one or more lower length scale unit cell models each with their own appropriate field and state variables. The NASA Multiscale Analysis Tool (NASMAT) is one software that can be used to perform a multiscale analysis efficiently and output requested data at all length scales in the analysis. A companion open-source Python software, NASMAT PrePost, can be used to visualize NASMAT model results and rapidly interrogate multiscale data across multiple length scales. This presentation will demonstrate some of the key features of NASMAT PrePost on two multiscale problems by quickly displaying and demonstrating connectivity among multiscale results from large datasets.

Python↗

Rotating dipole and quadrupole field for a multiple cathode system

A multiple cathode system has been designed to provide the high average current polarized electron bunches for the future electron-ion collider eRHIC [1]. One of the key research topics in this design is the technique to generate a combined dipole and quadrupole rotating field at high frequency (700 kHz). This type of field is necessary for combining bunches from different cathodes to the same axis with minimum emittance growth. Our simulations and the prototype test results to achieve this will be presented. The future eRHIC project, next upgrade of EHIC, will be the first electron-heavy ion collider in the world. For polarized-electron and polarized proton collisions, it requires a polarized electron source with high average current ({approx}50 mA), short bunch ({approx}3 mm), emittance of about 20 {micro}m and energy spread of {approx}1% at 10 MeV. The state-of-art polarized electron cathode can generate average current of about more than 1 mA, but much less than 50 mA. The current is limited by the quantum efficiency, lifetime, space charge and ultra-high vacuum requirement of the polarized cathode. A possible approach to achieve the 50 mA beam is to employ multiple cathodes, such as 20 cathodes, and combine the multiple bunched beams from cathodes to the same axis. We name it as 'Gatling gun' because its operations bear similarity to a multi-barrel Gatling gun. The electron spin direction is not affected by electric field but will follow to the direction of the magnetic bending. This requires that, to preserve the spin polarization from cathode, the fixed bending field after the solenoid and the rotating bending field in combiner must be either a pair of electric bendings or a pair of magnetic bendings. We choose the scheme with a pair of magnetic bendings because it is much easier than the scheme with a pair of electric bendings at our 200 keV electron energy level.

43 PARTICLE ACCELERATORS↗

Organic light emitting device having multiple separate emissive layers

An organic light emitting device having multiple separate emissive layers is provided. Each emissive layer may define an exciton formation region, allowing exciton formation to occur across the entire emissive region. By aligning the energy levels of each emissive layer with the adjacent emissive layers, exciton formation in each layer may be improved. Devices incorporating multiple emissive layers with multiple exciton formation regions may exhibit improved performance, including internal quantum efficiencies of up to 100%.

47 OTHER INSTRUMENTATION↗

Approaches to Future Generation Photovoltaics and Solar Fuels: Multiple Exciton Generation in Quantum Dots, Quantum Dot Arrays, Molecular Singlet Fission, and Quantum Dot Solar Cells

One potential, long-term approach to more efficient future generation solar cells is to utilize the unique properties of quantum dots (QDs) and unique molecular chromophores to control the relaxation pathways of excited states to produce enhanced conversion efficiency through efficient multiple electron-hole pair generation from single photons . We have observed efficient multiple exciton generation (MEG) in PbSe, PbS, PbTe, and Si QDs and efficient singlet fission (SF) in molecules that satisfy specific requirements for their excited state energy level structure to achieve carrier multiplication. We have studied MEG in close-packed QD arrays where the QDs are electronically coupled in the films and thus exhibit good transport while still maintaining quantization and MEG. We have developed simple, all-inorganic QD solar cells that produce large short-circuit photocurrents and power conversion efficiencies in the 3-5% range via both nanocrystalline Schottky junctions and nanocrystalline p-n junctions. These solar cells also show QYs for photocurrent that exceed 100% in the photon energy regions where MEG is possible; the photocurrent MEG QYs as a function of photon energy match those determined via time-resolved spectroscopy. We have also observed very efficient SF in thin films of molecular crystals of 1,3 diphenylisobenzofuran with quantum yields of 200% at the optimum SF threshold of 2Eg (HOMO-LUMO for S{sub 0}-S{sub 1}), reflecting the creation of two excited triplet states from the first excited singlet state. Various possible configurations for novel solar cells based on MEG in QDs and SF in molecules that could produce high conversion efficiencies will be presented, along with progress in developing such new types of solar cells. Recent analyses of the effect of MEG or SF combined with solar concentration on the conversion efficiency of solar cells will be discussed.

14 SOLAR ENERGY↗

Highly Efficient and Reversible SO(2) Capture by Tunable Azole-Based Ionic Liquids through Multiple-Site Chemical Absorption

A novel strategy for SO{sub 2} capture through multiple-site absorption in the anion of several azole-based ionic liquids is reported. An extremely high capacity of SO{sub 2} (>3.5 mol/mol) and excellent reversibility (28 recycles) were achieved by tuning the interaction between the basic anion and acidic SO{sub 2}. Spectroscopic investigations and quantum-mechanical calculations showed that such high SO{sub 2} capacity originates from the multiple sites of interaction between the anion and SO{sub 2}. These tunable azole-based ionic liquids with multiple sites offer significant improvements over commonly used absorbents, indicating the promise for industrial applications in acid gas separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiple Exciton Generation in PbSe Quantum Dots and Quantum Dot Solar Cells

Multiple exciton generation in quantum dots (QDs) has been intensively studied as a way to enhance solar energy conversion by channeling the excess photon energy (energy greater than the bandgap) to produce multiple electron-hole pairs. Among other useful properties, quantum confinement can both increase Coulomb interactions that drive the MEG process and decrease the electron-phonon coupling that cools hot-excitons in bulk semiconductors. We have demonstrated that MEG in PbSe QDs is about two times as efficient at producing multiple electron-hole pairs than bulk PbSe. I will discuss our recent results investigating MEG in PbSe, PbS and PbSxSe1-x, which exhibits an interesting size-dependence of the MEG efficiency. Thin films of electronically coupled PbSe QDs have shown promise in simple photon-to-electron conversion architectures with power conversion efficiencies above 5%. We recently reported an enhancement in the photocurrent resulting from MEG in PbSe QD-based solar cells. We find that the external quantum efficiency (spectrally resolved ratio of collected charge carriers to incident photons) peaked at 114% in the best devices measured, with an internal quantum efficiency of 130%. These results demonstrate that MEG charge carriers can be collected in suitably designed QD solar cells. We compare our results to transient absorption measurements and find reasonable agreement.

14 SOLAR ENERGY↗