Related papers: PeroMAS: A Multi-agent System of Perovskite Materi…
A contactless effective series resistance imaging method for large area perovskite solar cells that is based on photoluminescence imaging with non-uniform illumination is introduced and demonstrated experimentally. The proposed technique is…
Materials discovery driven by statistical property models is an iterative decision process, during which an initial data collection is extended with new data proposed by a model-informed acquisition function--with the goal to maximize a…
Recent developments highlighting the promise of two-dimensional perovskites have vastly increased the compositional search space in the perovskite family. This presents a great opportunity for the realization of highly performant devices,…
Alloy-based perovskite solar cells offer tunable properties and improved stability, but their complexity has impeded accurate modeling, hindering development. We present a machine-learning (ML) accelerated atomistic modeling approach for…
Fully-textured perovskite/silicon tandem solar cells have emerged as promising candidates for next-generation photovoltaics. The optical functions of full texturing, however, are not yet fully understood. A key challenge is the requirement…
Perovskite solar cells (PSCs) with superior performance have been recognized as a potential candidate in photovoltaic technologies. However, the defects in active perovskite layer induce non-radiative recombination which restricts the…
The large-scale search for high-performing candidate 2D materials is limited to calculating a few simple descriptors, usually with first-principles density functional theory calculations. In this work, we alleviate this issue by extending…
Complex chemical space and limited knowledge scope with biases holds immense challenge for human scientists, yet in automated materials discovery. Existing intelligent methods relies more on numerical computation, leading to inefficient…
Perovskite solar cells (PSCs) without a hole transport layer (HTL) offer a cost-effective and stable alternative to conventional architectures, utilizing only an absorber layer and an electron transport layer (ETL). This study presents a…
The integration of Artificial Intelligence (AI) with High-Performance Computing (HPC) is transforming scientific workflows from human-directed pipelines into adaptive systems capable of autonomous decision-making. Large language models…
Owing to their high energy-conversion efficiency and inexpensive fabrication routes, solar cells based on metal-organic halide perovskites have rapidly gained prominence as a disruptive technology. An attractive feature of perovskite…
With the rapid advancement of photovoltaic science, there has been an increasing focus on the development of environment-friendly and structurally advanced perovskite solar cells (PSCs). In this context, this study investigates an…
Perovskite solar cells (PSCs) represent a breakthrough in photovoltaic technology, combining high power conversion efficiencies (PCEs), ease of fabrication, and tunable optoelectronic properties. However, their commercial viability is…
In general, perovskite solar cells (PSC) with a sensitized or thin film architecture absorb light from a single illumination. This paper reported a PSC architecture with a semitransparent Au/ITO counter electrode, which allows light to pass…
Interpreting the impedance response of perovskite solar cells (PSC) is significantly more challenging than for most other photovoltaics. This is for a variety of reasons, of which the most significant are the mixed ionic-electronic…
Ferroelectric perovskites have been ubiquitously applied in piezoelectric devices for decades, among which, eco-friendly lead-free (K,Na)NbO3-based materials have been recently demonstrated to be an excellent candidate for sustainable…
Perovskite solar cells (PSCs) have emerged as a promising photovoltaic technology, already achieving efficiencies surpassing 25%. However, effects such as hysteresis are commonly observed due to the interplay of ionic and electronic…
Artificial intelligence (AI)-assisted workflows have transformed materials discovery, enabling rapid exploration of chemical spaces of functional materials. Endowed with extraordinary optoelectronic properties, two-dimensional (2D) hybrid…
Rapid identification of candidate materials with target properties has become a key task in materials science. Machine learning has emerged as an alternative to physics-based simulation, offering a faster and cheaper way to filter materials…
Implementation of resonant colloidal nanoparticles for improving performance of organometal halide perovskites solar cells is highly prospective approach, because it is compatible with the solution processing techniques used for any organic…