4 research outputs found

    In-situ Observation of AlN Formation from Ni-Al Solution Using an Electromagnetic Levitation Technique

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    Aluminum nitride is a promising substrate material for AlGaN-based UV-LED. In order to develop a robust growth processing route for AlN single crystals, fundamental studies of solution growth experiments using Ni-Al alloy melts as a new solution system were performed. Al can be stably kept in solution the Ni-Al liquid even at high temperature; in addition, the driving force of the AlN formation reaction from solution can be controlled by solution composition and temperature. To investigate AlN crystal growth behavior we developed an in situ observation system using an electromagnetic levitation technique. AlN formation behavior, including nucleation and growth, was quantitatively analyzed by an image processing pipeline. The nucleation rate of AlN decreased with increasing growth temperature and decreasing aluminum composition. In addition, hexagonal c-axis oriented AlN crystal successfully grew on the levitated Ni-40 mol%Al droplet reacted at low driving force (1960 K), on the other hand, AlN crystal with dendritic morphology appeared on the sample with higher driving force (Ni-50 mol%Al, 1960 K). Thus, the nucleation rate and crystal morphology were dominated by the driving force of the AlN formation reaction

    Insights into Metastability of Photovoltaic Materials at the Mesoscale Through Massive I–V Analytics

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    The authors demonstrate the feasibility of quantifying cell-level performance heterogeneity from module-level I–V curves by determining conditions of bypass diode turn-on. Analysis of these curves falls outside of typical diode-based models of photovoltaic (PV) performance. The authors show that this approach can leverage statistical and machine learning techniques for broad application to massive datasets, and combine those insights with simulations and laboratory-based experiments to provide useful information into the metastability of the interfaces of a PV cell. The authors find good agreement between the experimentally determined curves and the simulated curves, which guide the variable selection in the massive dataset collected from sites in Cleveland, OH, USA, the Negev Desert, Israel, Isla Gran Canaria, Spain, and Mount Zugspitze, Germany

    Modeling Degradation of Photovoltaic Modules using Machine Learning of Electroluminescent Images

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    El And I-V Correlation For Degradation Of Perc Vs. Al-Bsf Commercial Modules In Accelerated Exposures

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    Passivated emitter rear contact (PERC) cells offer increased power conversion efficiency but also present several degradation risks compared to the traditional aluminum back surface field (Al-BSF) cell, including instability of the passivation layer and increased light-induced degradation. Newer generations of bifacial PERC cells with localized back contacts (as opposed to full rear side metalization) introduce further vulnerabilities such as mechanical cracking and greater susceptibility to corrosion. In this work, we evaluate these degradation modes through accelerated exposures of full-size modules, using advanced characterization and analysis techniques. Damp-heat and thermal cycling are used to activate distinct degradation modes in Al-BSF, PERC, and bifacial PERC full-size modules. At stepwise intervals during exposure, the modules are measured by I -V curve tracing and electroluminescence (EL) imaging. EL images are standardized to allow for calculation of quantitative image parameters to be compared with standard I -V parameters. Correlation of parameters extracted from I -V and EL reveals statistical relationships between degradation mechanisms and performance, for module and accelerated exposure type. Bifacial PERC modules showed both the greatest power degradation in damp heat, and the most cell cracking in thermal cycling. The greater power degradation through damp heat exposure for modules with bifacial PERC cells is likely the result of both increased susceptibility of this cell type to corrosion, and instability of the rear-side encapsulant, white EVA
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