Development of tandem cells consisting of GaAs single crystal and CuInSe2/CdZnS polycrystalline thin films

The tandem cells consisting of GaAs single crystal and CuInSe2 polycrystalline thin films are being developed under the joint program of the Boeing Co. and Kopin Corp. to meet the increasing power needs for future spacecraft. The updated status of this program is presented along with experimental results such as cell performance, and radiation resistance. Other cell characteristics including the specific power of and the interconnect options for this tandem cell approach are also discussed

GaAs (AlGaAs)/CuInSe2 tandem solar cells. Technology status and future directions

Mechanically stacked, high efficiency, lightweight, and radiation resistant photovoltaic cells based on a GaAs thin film top and CuInSe2 thin film bottom cells were developed, and are considered one of the most promising devices for planar solar array applications. The highest efficiency demonstrated so far using the 4 sq cm design is 23.1 pct. AM0, one sun efficiency when measured in four-terminal configuration. The current status of the GaAs(AlGaAs)/CuInSe2 tandem cell program is presented and future directions that will lead to cell efficiencies higher than 26 pct. Air Mass Zero (AM0). A new 8 sq cm cell design developed for a two terminal and voltage matched configuration to minimize wiring complexity is discussed. Optimization of the GaAs structure for a higher end-of-life performance and further improvement of tandem cells by utilizing AlGaAs as an top absorber are described. Results of environmental tests conducted with these thin film GaAs/CuInSe2 tandem cells are also summarized

An Assessment of Small Unmanned Aerial Systems in Support of Sustainable Forestry Management Initiatives

Sustainable forest management practices are receiving renewed attention in the growing effort to make efficient long-term use of natural resources. Sustainable management approaches require accurate and timely measurement of the world’s forests to monitor volume, biomass, and changes in sequestered carbon. It is in this context that remote sensing technologies, which possess the capability to rapidly capture structural data of entire forests, have become a key research area. Laser scanning systems, also known as lidar (light detection and ranging), have reached a maturity level where they may be considered a standard data source for structural measurements of forests; however, airborne lidar mounted on manned aircraft can be cost-prohibitive. The increasing performance capabilities and reduction of cost associated with small unmanned aerial systems (sUAS), coupled with the decreasing size and mass of lidar sensors, provide the potential for a cost-effective alternative. Our objectives for this study were to assess the extensibility of established airborne lidar algorithms to sUAS data and to evaluate the use of more cost-effective structure-from-motion (SfM) point cloud generation techniques from imagery obtained by the sUAS. A data collection was completed by both manned and sUAS lidar and imaging systems in Lebanon, VA and Asheville, NC. Both systems produced adequately dense point clouds with the manned system exceeding 30 pts/m^2 and the sUAS exceeding 400 pts/m^2. A cost analysis, two carbon models and a harvest detection algorithm were explored to test performance. It was found that the sUAS performed similarly on one of the two biomass models, while being competitive at a cost of $8.12/acre, compared to the manned aircraft’s cost of$8.09/acre, excluding mobilization costs of the manned system. On the biomass modeling front, the sUAS effort did not include enough data for training the second model or classifier, due to a lack of samples from data corruption. However, a proxy data set was generated from the manned aircraft, with similar results to the full resolution data, which then was compared to the sUAS data from four overlapping plots. This comparison showed good agreement between the systems when ingested into the trained airborne platform’s data model (RMSE = 1.77 Mg/ha). Producer’s accuracy, User’s accuracy, and the Kappa statistic for detection of harvested plots were 94.1%, 92.2% and 89.8%, respectively. A leave-one-out and holdout cross validation scheme was used to train and test the classifier, using 1000 iterations, with the mean values over all trials presented in this study. In the context of an investigative study, this classifier showed that the detection of harvested and non-harvested forest is possible with simple metrics derived from the vertical structure of the forest. Due to the closed nature of the forest canopy, the SfM data did not contain many ground returns, and thus, was not able to match the airborne lidar’s performance. It did, however, provide fine detail of the forest canopy from the sUAS platform. Overall, we concluded that sUAS is a viable alternative to airborne manned sensing platforms for fine-scale, local forest assessments, but there is a level of system maturity that needs to be attained for larger area applications

Network sensitivity to geographical configuration

Gravitational wave astronomy will require the coordinated analysis of data from the global network of gravitational wave observatories. Questions of how to optimally configure the global network arise in this context. We have elsewhere proposed a formalism which is employed here to compare different configurations of the network, using both the coincident network analysis method and the coherent network analysis method. We have constructed a network model to compute a figure-of-merit based on the detection rate for a population of standard-candle binary inspirals. We find that this measure of network quality is very sensitive to the geographic location of component detectors under a coincident network analysis, but comparatively insensitive under a coherent network analysis.Comment: 7 pages, 4 figures, accepted for proceedings of the 4th Edoardo Amaldi conference, incorporated referees' suggestions and corrected diagra

The Influence of Perceived Celebrity Endorser Credibility in Advertising on Purchase Intention of Thai Consumers

Thai advertisers have used the celebrity strategies widely to promote products while the number of studies on celebrity credibility is still limited. The aim of this research is to develop the comprehensive celebrity credibility measurement model for aiding celebrity selection in Thailand. This model was tested using the structural equation modeling approach. The sample consisted of 420 Thai consumers living in Bangkok Metropolitan area. Furthermore, in order to bridge the methodological gap regarding the celebrity and product match-up in the previous studies (Till & Busler, 1998, 2000), the present research allowed the respondents to self-select the celebrity and product in order to better reflect the true perceptions of Thai consumers. The results showed the modified celebrity credibility measurement model was validated with Thai consumers. However, only perceived attractiveness and perceived expertise were significantly related to the purchase intention. The revised model, therefore, provides advertisers and marketers with practical guidelines to select an appropriate celebrity endorser in order to enhance the effectiveness of advertising and the resulting campaigns

Progress in GaAs/CuInSe2 tandem junction solar cells

Much more power is required for spacecraft of the future than current vehicles. To meet this increased demand for power while simultaneously meeting other requirements for launch, deployment, and maneuverability, the development of higher-efficiency, lighter-weight, and more radiation resistant photovoltaic cells is essential. Mechanically stacked tandem junction solar cells based on (AlGaAs)GaAs thin film CLEFT (Cleavage of Lateral Epitaxial Film for Transfer) top cells and CuInSe2(CIS) thin film bottom cells are being developed to meet these power needs. The mechanically stacked tandem configuration is chosen due to its interconnect flexibility allowing more efficient array level performance. It also eliminates cell fabrication processing constraints associated with monolithically integrated multi-junction approaches, thus producing higher cell fabrication yields. The GaAs cell is used as the top cell due to its demonstrated high efficiency, and good radiation resistance. Furthermore, it offers a future potential for bandgap tuning using AlGaAs as the absorber to maximize cell performance. The CuInSe2 cell is used as the bottom cell due to superb radiation resistance, stability, and optimal bandgap value in combination with an AlGaAs top cell. Since both cells are incorporated as thin films, this approach provides a potential for very high specific power. This high specific power (W/kg), combined with high power density (W/sq m) resulting from the high efficiency of this approach, makes these cells ideally suited for various space applications

Narrow-line magneto-optical cooling and trapping of strongly magnetic atoms

Laser cooling on weak transitions is a useful technique for reaching ultracold temperatures in atoms with multiple valence electrons. However, for strongly magnetic atoms a conventional narrow-line magneto-optical trap (MOT) is destabilized by competition between optical and magnetic forces. We overcome this difficulty in Er by developing an unusual narrow-line MOT that balances optical and magnetic forces using laser light tuned to the blue side of a narrow (8 kHz) transition. The trap population is spin-polarized with temperatures reaching below 2 microkelvin. Our results constitute an alternative method for laser cooling on weak transitions, applicable to rare-earth-metal and metastable alkaline earth elements.Comment: To appear in Phys. Rev. Lett. 4 pages, 5 figure

Manned Aircraft Versus Small Unmanned Aerial System—Forestry Remote Sensing Comparison Utilizing Lidar and Structure-From-Motion for Forest Carbon Modeling and Disturbance Detection

Sustainable forest management relies on the acquisition of timely (change detection) and accurate structural information of forest landscapes. Light detection and ranging (lidar) remote sensing platforms enable rapid, three-dimensional (3-D), structural data collection with a high spatial resolution. This study explores a functional carbon model applied to a dense, closed deciduous forest. Data are collected by manned airborne systems and unmanned aerial system, producing both lidar and structure-from-motion (SfM) 3-D mapping. A hybrid approach combining cost-effective SfM-generated data with lidar-derived digital elevation models also is explored, since the SfM fails to produce adequate terrain returns. Carbon modeling results are comparable to those achieved by the initial developers (r2 ¼ 0.64 versus r2 ¼ 0.72), despite the challenging uneven-aged forest environment. Vertical profiles, mapped utilizing a volumetric point density from the manned airborne lidar, are leveraged to train a binary classifier for disturbance detection. Producer’s accuracy, user’s accuracy, and Kappa statistic for disturbance detection are 94.1%, 92.2%, and 89.8%, respectively, showing a high likelihood of detecting disturbances (harvesting). The results bode well for the use of unmanned aerial system (UAS) systems, and either lidar or SfM, to assess forest stocking. Although disturbance detection is successful, further study is required to validate the use of UAS, and especially SfM, for this task