Integration Of Robotic Platforms Research Articles

Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells

AbstractSimultaneously optimizing the processing parameters of functional thin films remains a challenge. The design and utilization of a fully automated platform called SPINBOT is presented for the engineering of solution‐processed functional thin films. The SPINBOT is capable of performing experiments with high sampling variability through the unsupervised processing of hundreds of substrates with exceptional experimental control. Through the iterative optimization process enabled by the Bayesian optimization (BO) algorithm, the SPINBOT explores an intricate parameter space, continuously improving the quality and reproducibility of the produced thin films. This machine learning (ML)‐guided reliable SPINBOT platform enables the acceleration of the optimization process of perovskite solar cells via a simple photoluminescence characterization of films. As a result, this study arrives at an optimal film that, when processed into a solar cell in an ambient atmosphere, immediately yields a champion power conversion efficiency (PCE) of 21.6% with satisfactory performance reproducibility. The unsealed devices retain 90% of their initial efficiency after 1100 h of continuous operation at 60–65 °C under metal‐halide lamps. It is anticipated that the integration of robotic platforms with the intelligent algorithm will facilitate the widespread adoption of effective autonomous experimentation to address the evolving needs and constraints within the materials science research community.

3D imaging applications for robotic urologic surgery: an ESUT YAUWP review.

Despite the current era of precision surgery in robotics, an unmet need still remains for optimal surgical planning and navigation for most genitourinary diseases. 3D virtual reconstruction of 2D cross-sectional imaging has been increasingly adopted to help surgeons better understand the surgical anatomy. To provide a short overview of the most recent evidence on current applications of 3D imaging in robotic urologic surgery. A non-systematic review of the literature was performed. Medline, PubMed, the Cochrane Database and Embase were screened for studies regarding the use of 3D models in robotic urology. 3D reconstruction technology creates 3D virtual and printed models that first appeared in urology to aid surgical planning and intraoperative navigation, especially in the treatment of oncological diseases of the prostate and kidneys. The latest revolution in the field involves models overlapping onto the real anatomy and performing augmented reality procedures. 3D virtual/printing technology has entered daily practice in some tertiary centres, especially for the management of urological tumours. The 3D models can be virtual or printed, and can help the surgeon in surgical planning, physician education and training, and patient counselling. Moreover, integration of robotic platforms with the 3D models and the possibility of performing augmented reality surgeries increase the surgeon's confidence with the pathology, with potential benefits in precision and tailoring of the procedures.