arXiv subjects

Yasin Ameslon

Publications and source records attributed to Yasin Ameslon.

4 recordsLinked to original sources

arXiv2026

Predicting Organic Solar Cell Performance and Stability from Fast, Morphology-aware Current-Voltage Modeling

Understanding the relationship between morphology and performance in organic solar cells is essential for developing devices that are both high performing and resilient to aging. This work introduces a unique method capable of calculating the current-voltage (JV) curve of complex heterojunction morphologies containing up to five phases (donor amorphous, donor crystalline, acceptor amorphous, acceptor crystalline, mixed amorphous) with a very low computation time using morphology-aware descriptors of light absorption, exciton dissociation, non-geminate recombination and free charge carrier mobilities. The method is validated against Monte Carlo and 3D drift-diffusion simulations and applied to P3HT:PCBM and PM6:Y6 systems, shedding light on the physical compromises encountered to optimize device performance and lifetime. Finally, we show that the morphology-performance relationship is dependent on the materials system studied.

cond-mat.mtrl-sci↗

arXiv2025

Towards a fully differentiable digital twin for solar cells

Maximizing energy yield (EY) - the total electric energy generated by a solar cell within a year at a specific location - is crucial in photovoltaics (PV), especially for emerging technologies. Computational methods provide the necessary insights and guidance for future research. However, existing simulations typically focus on only isolated aspects of solar cells. This lack of consistency highlights the need for a framework unifying all computational levels, from material to cell properties, for accurate prediction and optimization of EY prediction. To address this challenge, a differentiable digital twin, Sol(Di)$^2$T, is introduced to enable comprehensive end-to-end optimization of solar cells. The workflow starts with material properties and morphological processing parameters, followed by optical and electrical simulations. Finally, climatic conditions and geographic location are incorporated to predict the EY. Each step is either intrinsically differentiable or replaced with a machine-learned surrogate model, enabling not only accurate EY prediction but also gradient-based optimization with respect to input parameters. Consequently, Sol(Di)$^2$T extends EY predictions to previously unexplored conditions. Demonstrated for an organic solar cell, the proposed framework marks a significant step towards tailoring solar cells for specific applications while ensuring maximal performance.

physics.comp-ph↗

arXiv2025

Taxonomy of amorphous ternary phase diagrams: the importance of interaction parameters

Understanding phase diagrams is essential for material selection and design, as they provide a comprehensive representation of the thermodynamics of mixtures. This work delivers a broad and systematic overview of possible ternary phase diagrams for amorphous systems representative of polymers, small organic molecules, and solvents. Thanks to computationally efficient methods, an unprecedented library of $>$80,000 ternary phase diagrams is generated based on a systematic screening of interaction parameters. Twenty-one phase diagram types, including unreported ones, are identified. They are classified according to simple rules related to the number of immiscible material pairs, of miscibility gaps, and of three-phase regions. They are mapped onto the three-dimensional interaction parameters space, providing a clear picture of their likelihood and existence conditions. Four well-known phase-diagram types with 0, 1, 2, or 3 immiscible pairs are found to be the most likely. The numerous uncommon phase diagrams are mostly observed within a small parameter window around the critical interaction parameter values. For the most common phase diagram types, we show that the size of the processability window becomes sensitive to interaction parameter variations close to critical values. The sensitivity decreases for materials with increasing molar size. Finally, successful comparisons of simulated and experimental phase diagrams showcase the real-world relevance of this theoretical analysis. The presented results lay a robust foundation for rational design of solution processing conditions and for blend morphology control. Immediate applications include organic thin films and the identification of green solvents for sustainable processing.

cond-mat.mtrl-sci↗

arXiv2024

Phase field simulations of thermal annealing for all-small molecule organic solar cells

Interest in organic solar cells (OSCs) is constantly rising in the field of photovoltaic devices. The device performance relies on the bulk heterojunction (BHJ) nanomorphology, which develops during the drying process and additional post-treatment. This work studies the effect of thermal annealing (TA) on an all-small molecule DRCN5T: PC71 BM blend with phase field simulations. The objective is to determine the physical phenomena driving the evolution of the BHJ morphology for a better understanding of the posttreatment/morphology relationship. Phase-field simulation results are used to investigate the impact on the final BHJ morphology of the DRCN5T crystallization-related mechanisms, including nucleation, growth, crystal stability, impingement, grain coarsening, and Ostwald ripening, of the amorphous-amorphous phase separation (AAPS), and of diffusion limitations. The comparison of simulation results with experimental data shows that the morphological evolution of the BHJ under TA is dominated by dissolution of the smallest, unstable DRCN5T crystals and anisotropic growth of the largest crystals.

cond-mat.mtrl-sci↗