Jacob Clenney, Erick M Loran, G. von Gastrow, D. Fenning, R. Meier, M. Bertoni
{"title":"Insights into Na+ Diffusion in Silicon Modules under Operating Conditions: Measuring Low Concentrations by D-SIMS","authors":"Jacob Clenney, Erick M Loran, G. von Gastrow, D. Fenning, R. Meier, M. Bertoni","doi":"10.1109/PVSC45281.2020.9300773","DOIUrl":null,"url":null,"abstract":"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 [1] 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) [1]. 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 D0,EVA = 0.09 ± 0.14 cm2/s and an activation energy EA,EVA = 0.85 ± .04 eV for Na in EVA and diffusivities higher than extrapolated literature values in silicon (D0,Si = (3.03 ± 2.42)x10−5 cm2/s, and EA,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 mudle stack and the diffusion of Na+ through each material. This tool can be used for process optimization as well as material selection significantly reducing the cost and time to validate a technology.","PeriodicalId":6773,"journal":{"name":"2020 47th IEEE Photovoltaic Specialists Conference (PVSC)","volume":"3 1","pages":"0863-0867"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 47th IEEE Photovoltaic Specialists Conference (PVSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PVSC45281.2020.9300773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
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 [1] 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) [1]. 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 D0,EVA = 0.09 ± 0.14 cm2/s and an activation energy EA,EVA = 0.85 ± .04 eV for Na in EVA and diffusivities higher than extrapolated literature values in silicon (D0,Si = (3.03 ± 2.42)x10−5 cm2/s, and EA,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 mudle stack and the diffusion of Na+ through each material. This tool can be used for process optimization as well as material selection significantly reducing the cost and time to validate a technology.