Related papers: Physics-based material parameters extraction from …
Halide perovskites make efficient solar cells due to their exceptional optoelectronic properties, but suffer from several stability issues. The characterization of the degradation processes is challenging because of the limitations in the…
We report the machine learning (ML)-based approach allowing thermoelectric generator (TEG) efficiency evaluation directly from 5 parameters: 2 physical properties - carriers density and energy gap, and 3 engineering parameters - external…
Cosmological experiments often employ Bayesian workflows to derive constraints on cosmological and astrophysical parameters from their data. It has been shown that these constraints can be combined across different probes such as Planck and…
Cosmological probes pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters which characterize the underlying physical system -- our Universe. Modern…
Cesium based halide perovskites, such as CsPbI3 and CsSnI3, have emerged as exceptional candidates for next generation photovoltaic and optoelectronic technologies, but their practical application is limited by temperature dependent phase…
The effect of 14 organic cations on the optical properties of the lead iodine perovskite is analyzed. The electronic and optical properties are obtained using first principles. The absorption coefficients are split into inter-atomic species…
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 internal luminescence quantum efficiency ($Q_\mathrm{i}^\mathrm{lum}$) provides an excellent assessment of the optoelectronic quality of semiconductors. To determine $Q_\mathrm{i}^\mathrm{lum}$ of perovskite films from the…
While transient photoluminescence measurements are a very popular tool to monitor the charge-carrier dynamics in the field of halide perovskite photovoltaics, interpretation of data obtained on multilayer samples is highly challenging due…
This work introduces ParAMS -- a versatile Python package that aims to make parameterization workflows in computational chemistry and physics more accessible, transparent and reproducible. We demonstrate how ParAMS facilitates the parameter…
Automated chemical synthesis, materials fabrication, and spectroscopic physical measurements often bring forth the challenge of process trajectory optimization, i.e., discovering the time dependence of temperature, electric field, or…
Bayesian optimization works effectively optimizing parameters in black-box problems. However, this method did not work for high-dimensional parameters in limited trials. Parameters can be efficiently explored by nonlinearly embedding them…
The partially observable constrained optimization problems (POCOPs) impede data-driven optimization techniques since an infeasible solution of POCOPs can provide little information about the objective as well as the constraints. We endeavor…
Perovskite solar cells have drawn much attention in recent years, owing to its world-record setting photovoltaic performances. Despite its promising use in tandem applications and flexible devices, its practicality is still limited by its…
Metal halide perovskites (MHPs) are low-temperature processable hybrid semiconductor materials with exceptional performances that are revolutionizing the field of optoelectronic devices. Despite their great potential, commercial deployment…
Chalcogenide perovskites, such as BaZrS$_3$, are emerging semiconductors with potential for high photovoltaic power conversion efficiency. The role of defects in the efficiency of the generation and collection of photo-excited carriers has…
Synthetic perovskites with photovoltaic properties open a new era in solar photovoltaics. Due to high optical absorption perovskite-based thin-film solar cells are usually considered as fully absorbing solar radiation on condition of ideal…
Organic-inorganic hybrid perovskites are considered to be most promising photovoltaic materials. Highest efficiencies of perovskite solar cells have been achieved by using appropriate cation and anion mixtures. Mixed perovskite solar cells…
The high performance of hybrid perovskite based devices is attributed to its excellent bulk-transport properties. However, carrier dynamics, especially at the metal-perovskite interface, and its influence on device operation are not widely…
We introduce a statistical measure of the effective model complexity, called the Bayesian complexity. We demonstrate that the Bayesian complexity can be used to assess how many effective parameters a set of data can support and that it is a…