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Photovoltaic (PV) modules are subjected to environmental stressors (UV exposure, temperature, and humidity) that cause degradation within the encapsulant and its interfaces with adjacent glass and cell substrates. To save experimental time and to enable long‐term assessment with intensive degradation only taking place after many years, the development of predictive models is indispensable. Previous works have modeled the delamination of the ethylene vinyl acetate (EVA) encapsulant/glass and encapsulant/cell interfaces under field aging conditions with fundamental photochemical degradation reactions that lead to molecular scission and loss of interfacial adhesion, characterized by the fracture resistance, Gc. However, these models were fundamentally limited in that the following aspects were not incorporated: (i) molecular crosslinking in the field, (ii) synergistic autocatalytic interactions of degradation mechanisms, (iii) connection between degraded encapsulant structure and its mechanical properties, and (iv) rigorous treatment of the plasticity contribution to Gc with finite element models. Here, we present a time‐dependent multiscale model that addresses these limitations and is applicable to a wide range of encapsulants and interfaces. For the reference EVA encapsulant and its interfaces with the glass and cell, the presented model predicts an initial rise in Gc in the first 3 years of field aging from crosslinking, then a subsequent sharp decline from degradation mechanisms. We used nanoindentation to measure the changes in EVA mechanical properties over exposure time to tune the model parameters. The model predictions of Gc and mechanical properties match with experimental data and show an improvement compared to previous models. The model can even predict switches in failure interfaces, such as the observed EVA/cell to EVA/glass transition. We also conducted a sensitivity analysis study by varying the degradation and crosslinking kinetic parameters to demonstrate their effects on Gc. Model extensions to polyolefin elastomer‐ and silicone‐encapsulants and their interfaces are also demonstrated. [ABSTRACT FROM AUTHOR]

Kinetic Monte Carlo (kMC) modelling is ubiquitous to simulate the time evolution of (bio)chemical processes, specifically if populations are involved. A recurring task is the selection of the smallest control volume that leads to convergence, which means that the model outputs are accurate and sufficiently free from stochastic noise and do not significantly change upon further increasing this volume. Selecting a too high (safe) control volume leads to an excessive simulation time, while many small incremental control volume increases are inefficient. This work therefore presents an automated tool to determine the smallest control volume leading to convergence. The tool is illustrated for (intrinsic) free radical and nitroxide mediated polymerization (FRP/NMP), in which the chain length distribution (CLD) is a crucial output. The algorithm starts with a very low volume to then check if the desired (monomer) conversion can be reached, the number average chain length is accurate, and finally the signal‐to‐noise (SNR) ratio at the CLD level is below a threshold. The execution time of the algorithm is less than twice the time of running the converged simulation directly, hence, saving tremendous time in setting up a kMC simulation and facilitating benchmark studies even beyond polymer reaction engineering applications. [ABSTRACT FROM AUTHOR]

A challenge for high‐impact polystyrene (HIPS) production and design is the more accurate and low computational cost prediction of the phase separation and phase inversion conversion, the first conversion determining the onset of the two‐phase system and the second conversion defining the pathway toward a complex, for example, salami‐like morphology. In this work, a two‐phase deterministic method of moments (MoM) model running in several minutes is therefore developed in the intermediate styrene conversion range (up to around 30%), considering for simplicity only diffusional limitations on termination on an average basis. It is showcased that the phase separation conversion can be taken as 2 m%, and the phase inversion conversion should be calculated by algebraic means. Interestingly, the latter conversion varies with the initial reaction conditions either on a time basis (e.g., variation of initial radical concentration) or both a time and conversion basis (e.g., relative contribution of rubber and St partitioning coefficient). A comparison with the commonly used pseudo‐homogeneous MoM model reveals that by accounting for mass transfer in a more representative two‐phase model, the amount of monomer consumed is slightly reduced, the grafting efficiency decreases with increasing conversion instead of increasing, and the styrene composition in the graft copolymer decreases. The current work additionally puts forward two‐phase MoM data to facilitate future benchmarking with other (stochastic) modeling approaches and enables kinetic insights into heterogeneous grafting polymerization, further promoting the production of multiphase industrial polymer products. [ABSTRACT FROM AUTHOR]