Finite Element Simulation of Potential-Induced Degradation Kinetics in p-Type Silicon Solar Modules
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Energy & Fuels↗
Engineering topics
Clenney, Jacob
Publications and source records attributed to Clenney, Jacob.
A Poisson–Nernst–Planck Model of Ion Transport and Interface Segregation in Metal–Insulator–Semiconductor Structures and Solar Cells
A numerical model that describes the transport of mobile ionic species in metal–insulator–semiconductor (MIS) and photovoltaic (PV) devices subject to temperature and voltage stress is presented. The finite element method (FEM) is used to solve the Nernst–Planck equation while imposing Poisson's equation self-consistently as a restriction for the electrostatic potential. This allows the contribution of the ionic species to the potential to be taken into account. Using a variational formulation eases the implementation of diverse boundary conditions, including the incorporation of segregation kinetics at the device interfaces. Segregation across the dielectric–semiconductor interface is relevant to modeling the electronic device degradation in systems where contamination reaches the semiconductor. The model in closed systems with no-flux boundary conditions is validated first. In the limiting case of low contamination levels with respect to the gate bias, the FEM solution matches analytically derived approximations. Then, the implementation is broadened to include an open boundary at the dielectric–semiconductor interface to account for leakage of ions. The predicted time dependence of the flatband voltage in Na-contaminated MIS test structures agrees well with measurements. This model successfully captures the role of long-range ion transport at concentrations of relevance to electronic and PV device instability and neuromorphic computing.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Modeling Time to Failure in Potential-Induced Degradation of Silicon Solar Modules based on Quantitative Sodium Kinetics
We present a physics-based simulation environment for the prediction of potential-induced-degradation (PID) failure time in silicon solar modules. Our model is based on experimental sodium migration kinetics obtained from our recently developed trap-corrected bias-stress-temperature method and from secondary ion mass spectrometry measurements. Furthermore, we model sodium migration to stacking faults and subsequent formation of conductive pathways through the p-n junction, which causes a decrease of the shunt resistance and loss of efficiency.
42 ENGINEERING↗
Insights into Na + Diffusion in Silicon Modules under Operating Conditions: Measuring Low Concentrations by D-SIMS
Sodium induced shunting under an electric field is a challenging reliability issue in crystalline Si solar modules. The source of this Potential-Induced Degradation of the Shunting type (PID-s) is well understood and its influence on power loss has been intensively studied based on phenomenological models on cell or module level relating the experimental power-loss to stressing parameters (time, temperature, voltage). However, little is known about the Na ion migration kinetics, responsible for PID on a microscopic level, and its quantitative relation to the efficiency degradation. In this paper we present our investigations of sodium ion migration in Ethylene-Vinyl Acetate (EVA) and silicon through Dynamic Secondary Ion Mass Spectroscopy (D-SIMS). Each sample was annealed at field relevant temperatures from 60-90 °C to address typical migration mechanisms of common PV installations. Analysis of the SIMS migration profiles revealed a diffusivity constant D 0,EVA = 0.09 ± 0.14 cm 2 /s and an activation energy E A,EVA = 0.85 ± .04 eV for Na in EVA and diffusivities higher than extrapolated literature values in silicon (D 0,Si = (3.03 ± 2.42)x10 -5 cm 2 /s, and E A,Si = 0.98 ± 0.02 eV). The new insight will be included in a drift-diffusion based degradation model accounting for the partition coefficient across all relevant interfaces. This model can assist in predicting PID-failure in the field based on the given model stack and the diffusion of Na + through each material. Furthermore, this tool can be used for process optimization as well as material selection significantly reducing the cost and time to validate a technology.
14 SOLAR ENERGY↗