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At least 253 records · Page 14

Shock-Wave/Boundary-Layer Interaction (SWBLI) Experiments in the Presence of Transition-to-Turbulence on a Flat Plate Model in the NASA LaRC 31-Inch Mach 10 Air Tunnel

Historically, there have been a limited number of studies involving Transitional Shock-Wave/Boundary-Layer Interactions (XSWBLI) in hypersonic flows, the majority of which have been performed at Mach Numbers of 7.5 and below. Additionally, there have been even fewer such experiments which incorporate non-intrusive and optical diagnostics. NASA Langley Research Center (NASA LaRC), in collaboration with The University of Texas at San Antonio (UTSA) and The University of Tennessee Space Institute (UTSI), is currently planning and preparing for a series of experimental aerodynamic tests using the NASA LaRC 31-inch Mach 10 Air Tunnel. The experiments will primarily focus on studying the dynamics of Shock-Wave/Boundary-Layer Interactions (SWBLI) in the presence of transition (XSWBLI) and turbulence (SWTBLI) on a large, flat plate model at a freestream Mach number of 10. Besides continued interest in understanding the flow at high Mach numbers, executing such tests at Mach 10 avoids some known concerns and will aid in solving new problems. XSWBLI are a highly unsteady phenomena and the generation of XSWBLI at lower Mach numbers can prove to be a significant challenge. This concern will be somewhat mitigated in the Mach 10 flow, as boundary layers become increasingly stabilized, but some difficulty in achieving transition is still expected. Modelling SWBLI in the presence of transitional and turbulent boundary layers has also proven to be difficult, so a high-Mach number experiment which applies non-intrusive and optical diagnostics will aid in solving a unique problem as well as advancing the understanding and characterization of an aerodynamic surface at Mach 10.The NASA LaRC 31-inch Wind Tunnel incorporates a test section having a cross-section of 31-inches × 31-inches and provides optical access to the test section via three (3) ultra-violet (UV) transmitting windows on the top, side, and bottom. The Mach 10 operating conditions will consist of pressures (P0) ranging from 2.4 to 10MPa (348 to 1,450 psi) at a temperature (T0) of 1,000 K (1,800 °R). The NASA LaRC 31-inch wind tunnel will deliver 1-minute blow-down runs, of which 30-45 seconds will be consumed to reach the aforementioned test conditions. The pump down time between runs will be approximately 45-60 minutes, which will provide for 6-10 test runs per day over the course of a weeklong entry. The proposed flat plate model will be constructed of stainless steel with geometry consisting of a10-inch × 30-inch upper surface and a 2-inch thickness. The model will be designed to support multiple leading-edge inserts in order to examine blunt, round, and sharp leading edges at Mach 10. Adjustments will be made to manage boundary layer thickness as well as the strength and size of the shock interaction region for each test. Measurements and diagnostics will be performed though high-speed Schlieren, on-body high-speed pressure transducers, IR thermography, and oil flow visualization. Hypersonic vehicle applications have and will continue to emerge at the forefront of aerospace. The NASA-UTSA-UTSI team realizes the value of characterizing SWBLI, XSWBLI, and SWTBLI behaviors well beyond single-digit hypersonic Mach numbers. As hypersonic vehicle speed capabilities continue to increase, measurement and diagnostic methods for Mach numbers of 10 and beyond will provide the foundation for a firm understanding of flow field behavior which will directly influence the advancement of technologies towards the design and manufacturing of high-speed aerodynamic surfaces, controls, thermal protection systems, acoustic treatments, and structural components. The use of non-intrusive and optical diagnostic methods in such experimentation is pivotal in developing the visualization and empirical data necessary to advance the aforementioned technology areas.

Shockwave/Boundary-Layer Interactions↗

Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Space flight

Control of vehicles and other complex systems is a high-level integrative function of the central nervous system (CNS). It requires well-functioning subsystem performance, including good visual acuity, eye-hand coordination, spatial and geographic orientation perception, and cognitive function. Evidence from space flight research demonstrates that the function of each of these subsystems is altered by removing gravity, a fundamental orientation reference, which is sensed by vestibular, proprioceptive, and haptic receptors and used by the CNS for spatial orientation, posture, navigation, and coordination of movements. The available evidence also shows that the degree of alteration of each subsystem depends on a number of crew- and mission-related factors. There is only limited operational evidence that these alterations cause functional impacts on mission-critical vehicle (or complex system) control capabilities. Furthermore, while much of the operational performance data collected during space flight has not been available for independent analysis, those that have been reviewed are somewhat equivocal owing to uncontrolled (and/or unmeasured) environmental and/or engineering factors. Whether this can be improved by further analysis of previously inaccessible operational data or by development of new operational research protocols remains to be seen. The true operational risks will be estimable only after we have filled the knowledge gaps and when we can accurately assess integrated performance in off-nominal operational settings (Paloski et al. 2008). Thus, our current understanding of the Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Space flight is limited primarily to extrapolation of scientific research findings, and, since there are limited ground-based analogs of the sensorimotor and vestibular changes associated with space flight, observation of their functional impacts is limited to studies performed in the space flight environment. Fortunately, many sensorimotor and vestibular experiments have been performed during and/or after space flight missions since 1959 (Reschke et al. 2007). While not all of these experiments were directly relevant to the question of vehicle/complex system control, most provide insight into changes in aspects of sensorimotor control that might bear on the physiological subsystems underlying this high-level integrated function.

Bloomberg, Jacob J.↗

Direct Visualization and Manipulation of Tunable Quantum Well State in Semiconducting Nb 2 SiTe 4

We report quantum well states (QWSs) can form at the surface or interfaces of materials with confinement potential. They have broad applications in electronic and optical devices such as high mobility electron transistor, photodetector, and quantum well laser. The properties of the QWSs are usually the key factors for the performance of the devices. However, direct visualization and manipulation of such states are, in general, challenging. In this work, by using angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy/spectroscopy (STM/STS), we directly probe the QWSs generated on the vacuum interface of a narrow band gap semiconductor Nb 2 SiTe 4 . Interestingly, the position and splitting of QWSs could be easily manipulated via potassium (K) dosage onto the sample surface. Our results suggest Nb 2 SiTe 4 to be an intriguing semiconductor system to study and engineer the QWSs, which has great potential in device applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Feasibility study of vortex interaction control on a chine forebody/delta wing configuration at high angles of attack

The feasibility of controlling vortex interactions or merger on a blended chine forebody and delta wing configuration was experimentally investigated. Low-speed wind tunnel diagnostics using smoke visualizations and wing upper-surface pressure measurements were performed on a generic 60 deg delta and chine forebody model, to assess chine modifications and leading edge flaps. Both techniques were shown to promote uncoupled vortex flows at high angles of attack and sideslip, with significant influence on the wing flow field, indicating potential for alleviating adverse high-alpha characteristics of blended chine swept wing configurations.

Rao, Dhanvada M.↗

Use of Linear Perspective Scene Cues in a Simulated Height Regulation Task

As part of a long-term effort to quantify the effects of visual scene cuing and non-visual motion cuing in flight simulators, an experimental study of the pilot's use of linear perspective cues in a simulated height-regulation task was conducted. Six test subjects performed a fixed-base tracking task with a visual display consisting of a simulated horizon and a perspective view of a straight, infinitely-long roadway of constant width. Experimental parameters were (1) the central angle formed by the roadway perspective and (2) the display gain. The subject controlled only the pitch/height axis; airspeed, bank angle, and lateral track were fixed in the simulation. The average RMS height error score for the least effective display configuration was about 25% greater than the score for the most effective configuration. Overall, larger and more highly significant effects were observed for the pitch and control scores. Model analysis was performed with the optimal control pilot model to characterize the pilot's use of visual scene cues, with the goal of obtaining a consistent set of independent model parameters to account for display effects.

Levison, W. H.↗

Heavy ion irradiation effects on GaN/AlGaN high electron mobility transistor failure at off-state

We investigate the effects of ion irradiation on AlGaN/GaN high electron mobility electron transistors using in-situ transmission electron microscopy. The experiments are performed inside the microscope to visualize the defects, microstructure and interfaces of ion irradiated transistors during operation and failure. Here, experimental results indicate that heavy ions such as Au 4+ can create a significant number of defects such as vacancies, interstitials and dislocations in the device layer. It is hypothesized that these defects act as charge traps in the device layer and the resulting charge accumulation lowers the breakdown voltage. Sequential energy dispersive X-ray spectroscopy mapping allows us to track individual chemical elements during the experiment, and the results suggest that the electrical degradation in the device layer may originate from oxygen and nitrogen vacancies.

36 MATERIALS SCIENCE↗

Drought adaptation index (DAI) based on BLUP as a selection approach for drought-resilient switchgrass germplasm

This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.

BLUP↗

A Model of Manual Control with Perspective Scene Viewing

A model of manual control during perspective scene viewing is presented, which combines the Crossover Model with a simpli ed model of perspective-scene viewing and visual- cue selection. The model is developed for a particular example task: an idealized constant- altitude task in which the operator controls longitudinal position in the presence of both longitudinal and pitch disturbances. An experiment is performed to develop and vali- date the model. The model corresponds closely with the experimental measurements, and identi ed model parameters are highly consistent with the visual cues available in the perspective scene. The modeling results indicate that operators used one visual cue for position control, and another visual cue for velocity control (lead generation). Additionally, operators responded more quickly to rotation (pitch) than translation (longitudinal).

pilot modeling↗

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗

Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

Abstract Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

Sehnal, David↗

Networks for image acquisition, processing and display

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

Ahumada, Albert J., Jr.↗

Homogenized halides and alkali cation segregation in alloyed organic-inorganic perovskites

The role of the alkali metal cations in halide perovskite solar cells is not well understood. Using synchrotron-based nano–x-ray fluorescence and complementary measurements, we found that the halide distribution becomes homogenized upon addition of cesium iodide, either alone or with rubidium iodide, for substoichiometric, stoichiometric, and overstoichiometric preparations, where the lead halide is varied with respect to organic halide precursors. Halide homogenization coincides with long-lived charge carrier decays, spatially homogeneous carrier dynamics (as visualized by ultrafast microscopy), and improved photovoltaic device performance. We found that rubidium and potassium phase-segregate in highly concentrated clusters. Alkali metals are beneficial at low concentrations, where they homogenize the halide distribution, but at higher concentrations, they form recombination-active second-phase clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plant density and enhanced plant vigor estimation for high-resolution images v1

The package contains algorithms for the estimation of sprout/plant density and the corresponding enhanced plant vigor from remotely sensed (RS) images. These algorithms aim to improve the plant characterization and monitoring in the early season when the soil component is significant compared to the plant spatial coverage. In such a scenario, the identification of sprouts (or plants) and the estimation of plant vegetation indexes can be performed only using UAV-acquired images. Additionally, because of the extremely high resolution, gridding becomes necessary to improve visualization and provide more informative maps. However, to capture the real range of values of the VIs, it is important to avoid the inclusion of those pixels belonging to the soil component. The sprout/plant density estimation algorithm takes in input a classification map and uses the vegetation class to estimates the plant density within a user-defined grid using a floating window. Similarly, the enhanced plant vigor algorithm takes in input the vegetation index and the classification map. The enhanced vegetation index is computed for each pixel as the average value among those pixels that belong to the vegetation class within a floating window. The software is developed for the MATLAB environment.

Falco, Nicola↗

MetaboDirect: an analytical pipeline for the processing of FT-ICR MS-based metabolomic data

Background: Microbiomes are now recognized as the main drivers of ecosystem function ranging from the oceans and soils to humans and bioreactors. However, a grand challenge in microbiome science is to characterize and quantify the chemical currencies of organic matter (i.e., metabolites) that microbes respond to and alter. Critical to this has been the development of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), which has drastically increased molecular characterization of complex organic matter samples, but challenges users with hundreds of millions of data points where readily available, user-friendly, and customizable software tools are lacking. Results: Here, we build on years of analytical experience with diverse sample types to develop MetaboDirect, an open-source, command-line-based pipeline for the analysis (e.g., chemodiversity analysis, multivariate statistics), visualization (e.g., Van Krevelen diagrams, elemental and molecular class composition plots), and presentation of direct injection high-resolution FT-ICR MS data sets after molecular formula assignment has been performed. When compared to other available FT-ICR MS software, MetaboDirect is superior in that it requires a single line of code to launch a fully automated framework for the generation and visualization of a wide range of plots, with minimal coding experience required. Among the tools evaluated, MetaboDirect is also uniquely able to automatically generate biochemical transformation networks (ab initio) based on mass differences (mass difference network-based approach) that provide an experimental assessment of metabolite connections within a given sample or a complex metabolic system, thereby providing important information about the nature of the samples and the set of microbial reactions or pathways that gave rise to them. Finally, for more experienced users, MetaboDirect allows users to customize plots, outputs, and analyses. Conclusion: Application of MetaboDirect to FT-ICR MS-based metabolomic data sets from a marine phage-bacterial infection experiment and a Sphagnum leachate microbiome incubation experiment showcase the exploration capabilities of the pipeline that will enable the research community to evaluate and interpret their data in greater depth and in less time. It will further advance our knowledge of how microbial communities influence and are influenced by the chemical makeup of the surrounding system. The source code and User’s guide of MetaboDirect are freely available through (https://github.com/Coayala/MetaboDirect) and (https://metabodirect.readthedocs.io/en/latest/), respectively.

54 ENVIRONMENTAL SCIENCES↗

Autonomous Coupler Alignment Using Position-Based Visual Servoing in a ROS 2 Framework

As robotic arms are becoming increasingly common alongside humans as collaborative robots, their high precision in motion enables tasks to be performed at significantly higher speeds with reduced disruption in the environment. The Fermi National Accelerator Laboratory is exploring this application by incorporating a UR16e from Universal Robots in a cleanroom setting during assembly of couplers to superconducting radio frequency cavities as part of the PIP-II project. The goal of the robotic assembly process is to precisely position the UR16e robot so that the coupler flange, mounted on the robot’s end-effector, is accurately aligned with and pressed against the cavity flange, requiring only final fastening by a lab technician. This thesis builds upon an initial system in which the robotic process was limited to the alignment phase using position-based visual servoing with an eye-in-hand camera to only align the coupler to the cavity with an offset distance. The objective of this thesis is to further advance autonomous robotic assembly by extending the process. To this end, the entire software framework was reconstructed, as the previous development environment posed significant challenges in modifying the software and adapting to hardware changes. The main contributions of this thesis are as follows: (i) a modular and scalable software framework based on ROS~2 was developed to facilitate performance expansion and interchangeability of software and hardware components; (ii) the desired alignment position for position-based visual servoing was parameterized to enable flexible configuration; and (iii) a methodology was developed to close the offset distance between the coupler and cavity utilizing the internal force-torque sensing capability of the UR16e, as visual feedback is not available during the offset-closing phase. The proposed autonomous robotic assembly reduces assembly time and technician involvement, thereby minimizing the risk of airborne particulate contamination, which is essential in the cleanroom setting. Moreover, the ROS~2-based framework provides a foundation for further expansion and continued advancement of robotic automation in Fermilab.

Giffen, Nickolas [Northern Illinois U.]↗

Active Control of Separation from the Slat Shoulder of a Supercritical Airfoil

Active flow control in the form of zero-mass-flux excitation was applied at the slat shoulder of a simplified high-lift airfoil to delay flow separation. The NASA Energy Efficient Transport (EET) supercritical airfoil was equipped with a 15% chord simply hinged leading edge slat and a 25% chord simply hinged trailing edge flap. The cruise configuration data was successfully reproduced, repeating previous experiments. The effects of flap and slat deflection angles on the performance of the airfoil integral parameters were quantified. Detailed flow features were measured as well, in an attempt to identify optimal actuator placement. The measurements included: steady and unsteady model and tunnel wall pressures, wake surveys, arrays of surface hot-films, flow visualization and Particle Image Velocimetry (PIV). High frequency periodic excitation was applied to delay the occurrence of slat stall and improve the maximum lift by 10 to 15%. Low frequency amplitude modulation was used to reduce the oscillatory momentum coefficient by roughly 50% with similar aerodynamic performance.

Pack, LaTunia G.↗

Role of nanocellulose in tailoring electroanalytical performance of hybrid nanocellulose/multiwalled carbon nanotube electrodes

Abstract Nanocellulose has emerged as a promising green dispersant for carbon nanotubes (CNTs), and there is an increasing trend in developing nanocellulose/CNT hybrid materials for electrochemical detection of various small molecules. However, there have been very few comprehensive studies investigating the role of nanocellulosic material properties upon the electroanalytical performance of the resultant hybrid electrodes. In this work, we demonstrate the influence of both nanocellulose functionalization and geometry, utilizing sulfated cellulose nanocrystals, sulfated cellulose nanofibers, and TEMPO-oxidized cellulose nanofibers. Transmission electron microscopy tomography enables direct visualization of the effect of nanocellulosic materials on the hybrid architectures. High resolution X-ray absorption spectroscopy verifies that the chemical nature of CNTs in the different hybrids is unmodified. Electroanalytical performances of the different nanocellulose/CNT hybrid electrodes are critically evaluated using physiologically relevant biomolecules with different charge such as, dopamine (cationic), paracetamol (neutral), and uric acid (anionic). The hybrid electrode containing fibrillar nanocellulose geometry with a high degree of sulfate group functionalization provides the highest electroanalytical sensitivity and strongest enrichment towards all studied analytes. These results clearly demonstrate for the first time, the extent of tailorability upon the electroanalytical response of nanocellulose/CNT hybrid electrodes towards different biomolecules, offered simply by the choice of nanocellulosic materials.

Durairaj, Vasuki↗

A Comprehensive Methodology to Evaluate Losses and Process Variations in Silicon Solar Cell Manufacturing

Novel, high-throughput metrology methods are used in this paper for detailed performance loss analysis of approximately 400 industrial crystalline silicon solar cells, all coming from the same production line. The characterization sequence combines traditional global cell measurements (e.g., current-voltage, Suns-VOC) with camera-based cell imaging of voltage distribution and power dissipation from photoluminescence and lock-in thermography, respectively. Spatial variations in current collection are visualized using a high-speed external quantum efficiency and reflectance measurement technique. A nondestructive transfer length method (TLM) measurement technique is also implemented, featuring circular TLM structures hidden within the busbars of the cells. The variance of individual loss parameters and their impact on cell performance are quantified for this large group of cells. Based on correlations performed across parameters, recombination losses in the bulk and rear surface of the cell are shown to be the primary limiting factor for the cell efficiency. The nature of these distributions and correlations provide important insights about loss mechanisms in industrial solar cells, helping to prioritize efforts for optimizing the performance of the production line. Additionally, many of the parameters extracted from these techniques can be tied back to incoming material quality issues (e.g., poor bulk carrier lifetime, nonuniform wafer doping) and to individual unit processes (e.g., texturing, phosphorus diffusion, silicon nitride deposition, metallization), allowing the data to be used directly for process control in manufacturing. All of the datasets are made available for download.

14 SOLAR ENERGY↗