Understanding and Overcoming Water-induced Interfacial Degradation in Si Modules
Sector: Chemical (Industrial) • Location: La Jolla, California, United States of America
Source: Department of Energy (DOE)
This project is developing a spatially-resolved characterization methodology to detect the location and amount of water present in photovoltaic (PV) modules and to model any predicted acceleration in performance degradation. The project team is examining the physical underpinnings of these effects by combining first-principles atomistic modeling of the segregation, diffusion, and chemical effects
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | Close |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | This project is developing a spatially-resolved characterization methodology to detect the location and amount of water present in photovoltaic (PV) modules and to model any predicted acceleration in performance degradation. The project team is examining the physical underpinnings of these effects by combining first-principles atomistic modeling of the segregation, diffusion, and chemical effects of interfacial water with continuum finite element method modeling of water distribution and its effects. Based on the resulting physical model of a module's water exposure over time and predicted changes in material properties and power output, the project team plans to develop statistical response surface models to predict a module′s hazard function. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
