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Bayesian optimization (BO) has been leveraged for guiding autonomous and high-throughput experiments in materials science. However, few have evaluated the efficiency of BO across a broad range of experimental materials domains. In this work, we quantify the performance of BO with a collection of surrogate model and acquisition function pairs across five diverse experimental materials systems. By defining acceleration and enhancement metrics for materials optimization objectives, we find that surrogate models such as Gaussian Process (GP) with anisotropic kernels and Random Forest (RF) have comparable performance in BO, and both outperform the commonly used GP with isotropic kernels. GP with anisotropic kernels has demonstrated the most robustness, yet RF is a close alternative and warrants more consideration because it is free from distribution assumptions, has smaller time complexity, and requires less effort in initial hyperparameter selection. We also raise awareness about the benefits of using GP with anisotropic kernels in future materials optimization campaigns.

 

This paper investigates the suitability of CdTe photovoltaic cells to be used as power sources for wireless sensors located in buildings. We fabricate and test a CdTe photovoltaic cell with a transparent conducting oxide front contact that provides for high photocurrents and low series resistance at low light intensities - and measure the photovoltaic response of this cell across five orders of magnitude of AM1.5G light intensity. Efficiencies of 10% and 17.1% are measured under ~1 W/m2 AM1.5G and LED irradiance respectively, the highest values for a CdTe device under ambient lighting measured to date. We use our results to assess the potential of CdTe for internet of things devices from an optoelectronic, as well as a techno-economic perspective, considering its established manufacturing know-how, potential for low-cost, proven long-term stability and issues around the use of cadmium. 

Perovskite solar cells (PSCs) have attracted much attention as efficiencies go beyond 22%. To achieve these impressive numbers, the PSC scientific community is working to improve both the perovskite optoelectronic properties, and, importantly, the interfacial properties of the adjacent electron selective contacts (ESLs). Improvements in both fronts have happened concurrently and are responsible for these rapid efficiency gains. Here, the authors review the recent advances in understanding the role of ESLs on performance improvements. ESLs can be prepared from either organic and inorganic semiconductors, or a combination of both, and their key characteristics are summarized in detail. Current state‐of‐the‐art PSCs employ fully inorganic ESLs made of a thin mesoporous TiO₂or a planar SnO₂, with reported certified efficiencies of 22.7 and 20.9%, respectively. While TiO₂shows excellent performance in the short term, it has also been shown to induce solar cell degradation due to its UV absorption properties. Understanding ESLs has been instrumental in the rapid development of PSCs; however, some challenges remain in terms of understanding the role of different ESLs on the long‐term stability of the devices.