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Morphological–Electrical Property Relation in Cu(In,Ga)(S,Se) 2 Solar Cells: Significance of Crystal Grain Growth and Band Grading by Potassium Treatment
Abstract Solution‐processed Cu(In,Ga)(S,Se) 2 (CIGS) has a great potential for the production of large‐area photovoltaic devices at low cost. However, CIGS solar cells processed from solution exhibit relatively lower performance compared to vacuum‐processed devices because of a lack of proper composition distribution, which is mainly instigated by the limited Se uptake during chalcogenization. In this work, a unique potassium treatment method is utilized to improve the selenium uptake judiciously, enhancing grain sizes and forming a wider bandgap minimum region. Careful engineering of the bandgap grading structure also results in an enlarged space charge region, which is favorable for electron–hole separation and efficient charge carrier collection. Besides, this device processing approach has led to a linearly increasing electron diffusion length and carrier lifetime with increasing the grain size of the CIGS film, which is a critical achievement for enhancing photocurrent yield. Overall, 15% of power conversion efficiency is achieved in solar cells processed from environmentally benign solutions. This approach offers critical insights for precise device design and processing rules for solution‐processed CIGS solar cells.
Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images
Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.
Improved CO 2 Capture Performance of Electrochemically Mediated Amine Regeneration Processes with Ionic Surfactant Additives
For the effective reduction of global CO 2 emissions, it is essential to develop and deploy efficient and cost-effective technologies for CO 2 capture, especially from large point sources. We recently developed an electrochemically mediated amine regeneration (EMAR) system to replace traditional thermal desorption for the capture of CO 2 from post-combustion flue gases. Despite EMAR effectiveness on a laboratory scale, concerns regarding the high gas-to-liquid ratio in the electrochemical cell and long-term instability of the electrodes need to be addressed before further scale-up of the process to a pilot plant and beyond can be entertained. Accordingly, we investigated the effect of using sodium dodecyl sulfate (SDS) as an anionic surfactant and dodecyltrimethylammonium bromide (DTAB) as a cationic surfactant on the process operation. It was found that it is advantageous to use an anionic surfactant for a system such as EMAR that contains hydrophilic electrodes and a positively charged electrochemically active species. The overall cell resistance was notably reduced when SDS anionic surfactant was used. The precipitation of copper particles observed in the anode outlet when no surfactant was used was effectively avoided when SDS was added to the electrolyte, resulting in electrode stability. In addition, smaller gas bubbles were produced in the presence of the SDS surfactant, which resulted in less blockage of the electrode by the gas with a resultant lower cell potential under constant current conditions, driving more efficient CO 2 desorption. This led to an ~25% reduction in the electrochemical energy requirement, the lowest ever achieved experimentally for the EMAR process. Altogether, the addition of a very low concentration of SDS resulted in the successful circumvention of the important problems faced by the EMAR system regarding further scale-up.
Solution-processable 2D semiconductors for high-performance large-area electronics
Not provided.
Pagosa Performance Analysis: Fortran Array-Syntax Restructuring and Code Vectorizability [PowerPoint]
Topics covered in the presentation include: Primary causes of current performance on KNL/Haswell processers; compiler discussion; array-syntax; compiler-option/code modifications; and, performance results.
Radioiodine sorbent selection criteria
Methods for preventing radioiodine from entering the environment are needed in processes related to nuclear energy and medical isotope production. The development and performance of many different types of sorbents to capture iodine have been reported on for decades; however, there is yet to be a concise overview on the important parameters that should be considered when selecting a material for chemically capturing radioiodine. This paper summarizes several criteria that should be considered when selecting candidate sorbents for implementation into real-world systems. The list of selection criteria discussed are 1) optimal capture performance, 2) kinetics of adsorption, 3) performance under relevant process conditions, 4) properties of the substrate that supports the getter, and 5) environmental stability and disposition pathways for iodine-loaded materials.
Process-microstructure relationship of laser processed thermoelectric material Bi2Te3
Additive manufacturing allows fabrication of custom-shaped thermoelectric materials while minimizing waste, reducing processing steps, and maximizing integration compared to conventional methods. Establishing the process-structure-property relationship of laser additive manufactured thermoelectric materials facilitates enhanced process control and thermoelectric performance. This research focuses on laser processing of bismuth telluride (Bi 2 Te 3 ), a well-established thermoelectric material for low temperature applications. Single melt tracks under various parameters (laser power, scan speed and number of scans) were processed on Bi 2 Te 3 powder compacts. A detailed analysis of the transition in the melting mode, grain growth, balling formation, and elemental composition is provided. Rapid melting and solidification of Bi 2 Te 3 resulted in fine-grained microstructure with preferential grain growth along the direction of the temperature gradient. Experimental results were corroborated with simulations for melt pool dimensions as well as grain morphology transitions resulting from the relationship between temperature gradient and solidification rate. Samples processed at 25 W, 350 mm/s with 5 scans resulted in minimized balling and porosity, along with columnar grains having a high density of dislocations.
Modeling and analysis of Power Processing Systems
The paper deals with a NASA-sponsored, computer-based program Modeling and Analysis of Power Processing Systems (MAPPS). Three major MAPPS subprograms, Design Optimization, Control Design, and Performance Analysis are considered. The program makes it possible to reduce the design, analysis, and development time, and thus the cost, in achieving the required performance for power processing equipment and systems.
Availability of Seasat synthetic aperture radar imagery
One of the sensors of the Seasat satellite was a synthetic aperture radar (SAR), which was operated over both oceanic and land areas. The Seasat SAR was an active imaging microwave system which transmitted and received horizontally polarized radiation at L-band frequency (1.275 GHz, 23-cm wavelength). Extensive coverage was obtained over North America, Europe, the Eastern Pacific Ocean, the Western and Northern Atlantic Ocean, and the Beaufort Sea. Surface coverage was also acquired over limited portions of Central America, the Gulf of Mexico, and the Caribbean Sea. The majority of the data has been optically processed in a so-called survey mode. Each optically processed Seasat pass has a swath width of 100 km at a scale of 1:500,000. A subset of the SAR data has been digitally processed in a so-called high-resolution mode. Digital processing has been performed upon selected scenes with dimensions of 100 x 100 km. Digitally processed imagery has a nominal ground resolution of 25 m.
Multi-crop area estimation and mapping on a microprocessor/mainframe network
The data processing system is outlined for a 1985 test aimed at determining the performance characteristics of area estimation and mapping procedures connected with the California Cooperative Remote Sensing Project. The project is a joint effort of the USDA Statistical Reporting Service-Remote Sensing Branch, the California Department of Water Resources, NASA-Ames Research Center, and the University of California Remote Sensing Research Program. One objective of the program was to study performance when data processing is done on a microprocessor/mainframe network under operational conditions. The 1985 test covered the hardware, software, and network specifications and the integration of these three components. Plans for the year - including planned completion of PEDITOR software, testing of software on MIDAS, and accomplishment of data processing on the MIDAS-VAX-CRAY network - are discussed briefly.
Magellan SAR processing algorithm and H/W design
The SAR (synthetic-aperture radar) data-processing algorithm to be used for the Magellan mission is described. Radar system design, SAR data characteristics, and hardware (H/W) constraints, which are critical to the processing algorithm design, are highlighted. Data flow and the H/W architecture are given to show the real-time data processing capability. Simulation results obtained from processing the synthetic point-target echos are presented to demonstrate the performance of the processing algorithm.
Photon detection with parallel asynchronous processing
An approach to photon detection with a parallel asynchronous signal processor is described. The visible or IR photon-detection capability of the silicon p(+)-n-n(+) detectors and the parallel asynchronous processing are addressed separately. This approach would permit an independent analog processing channel to be dedicated to every pixel. A laminar architecture consisting of a stack of planar arrays of the devices would form a 2D array processor with a 2D array of inputs located directly behind a focal-plane detector array. A 2D image data stream would propagate in neuronlike asynchronous pulse-coded form through the laminar processor. Such systems can integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The possibility of multispectral image processing is addressed.
A unified process for systems identification based on performance assessment
Many modern spacecraft are complex multi-body dynamic systems where the bodies are connected by several active control systems for pointing and isolation. Mission requirements indicate that many structural modes and possibly some nonlinear effects will require characterization. Thus, even characterization at the subsystem level will become more difficult than usual. System level characterization difficulties will be compounded by the fact that only limited ground testing will be possible on the full up system, and flight testing will be restricted by an extremely limited measurements set. The object of the present discussion is the application of matrix majorant theory to the problem of assessing dynamic system performance when knowledge of the system is uncertain. We show how majorants provide an effective tool to relate required performance output to system identification test quality in terms of residual uncertainty in input-output relations, parameter values, nonlinearities, and interactions. The underlying machinery consists of the block-norm matrix which is a nonnegative matrix each of whose elements is the norm of a block of a suitably partitioned matrix. A matrix which bounds the block-norm matrix in the sense of nonnegative matrices, i.e., element by element is known as a majorant.
Design of a mixer for the thrust-vectoring system on the high-alpha research vehicle
One of the advanced control concepts being investigated on the High-Alpha Research Vehicle (HARV) is multi-axis thrust vectoring using an experimental thrust-vectoring (TV) system consisting of three hydraulically actuated vanes per engine. A mixer is used to translate the pitch-, roll-, and yaw-TV commands into the appropriate TV-vane commands for distribution to the vane actuators. A computer-aided optimization process was developed to perform the inversion of the thrust-vectoring effectiveness data for use by the mixer in performing this command translation. Using this process a new mixer was designed for the HARV and evaluated in simulation and flight. An important element of the Mixer is the priority logic, which determines priority among the pitch-, roll-, and yaw-TV commands.
Smagglce: Surface Modeling and Grid Generation for Iced Airfoils: Phase 1 Results
SmaggIce (Surface Modeling and Grid Generation for Iced Airfoils) is a software toolkit used in the process of aerodynamic performance prediction of iced airfoils with grid-based Computational Fluid Dynamics (CFD). It includes tools for data probing, boundary smoothing, domain decomposition, and structured grid generation and refinement. SmaggIce provides the underlying computations to perform these functions, a GUI (Graphical User Interface) to control and interact with those functions, and graphical displays of results, it is being developed at NASA Glenn Research Center. This paper discusses the overall design of SmaggIce as well as what has been implemented in Phase 1. Phase 1 results provide two types of software tools: interactive ice shape probing and interactive ice shape control. The ice shape probing tools will provide aircraft icing engineers and scientists with an interactive means to measure the physical characteristics of ice shapes. On the other hand, the ice shape control features of SmaggIce will allow engineers to examine input geometry data, correct or modify any deficiencies in the geometry, and perform controlled systematic smoothing to a level that will make the CFD process manageable.
Accelerating Demand Paging for Local and Remote Out-of-Core Visualization
This paper describes a new algorithm that improves the performance of application-controlled demand paging for the out-of-core visualization of data sets that are on either local disks or disks on remote servers. The performance improvements come from better overlapping the computation with the page reading process, and by performing multiple page reads in parallel. The new algorithm can be applied to many different visualization algorithms since application-controlled demand paging is not specific to any visualization algorithm. The paper includes measurements that show that the new multi-threaded paging algorithm decreases the time needed to compute visualizations by one third when using one processor and reading data from local disk. The time needed when using one processor and reading data from remote disk decreased by up to 60%. Visualization runs using data from remote disk ran about as fast as ones using data from local disk because the remote runs were able to make use of the remote server's high performance disk array.
Identification of High Performance, Low Environmental Impact Materials and Processes Using Systematic Substitution (SyS)
Process analysis can identify opportunities for efficiency improvement including cost reduction, increased safety, improved quality, and decreased environmental impact. A thorough, systematic approach to materials and process selection is valuable in any analysis. New operations and facilities design offer the best opportunities for proactive cost reduction and environmental improvement, but existing operations and facilities can also benefit greatly. Materials and processes that have been used for many years may be sources of excessive resource use, waste generation, pollution, and cost burden that should be replaced. Operational and purchasing personnel may not recognize some materials and processes as problems. Reasons for materials or process replacement may include quality and efficiency improvements, excessive resource use and waste generation, materials and operational costs, safety (flammability or toxicity), pollution prevention, compatibility with new processes or materials, and new or anticipated regulations.