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  1. ABSTRACT We present the discovery and characterization of six short-period, transiting giant planets from NASA’s Transiting Exoplanet Survey Satellite (TESS) -- TOI-1811 (TIC 376524552), TOI-2025 (TIC 394050135), TOI-2145 (TIC 88992642), TOI-2152 (TIC 395393265), TOI-2154 (TIC 428787891), and TOI-2497 (TIC 97568467). All six planets orbit bright host stars (8.9 <G < 11.8, 7.7 <K < 10.1). Using a combination of time-series photometric and spectroscopic follow-up observations from the TESS Follow-up Observing Program Working Group, we have determined that the planets are Jovian-sized (RP  = 0.99--1.45 RJ), have masses ranging from 0.92 to 5.26 MJ, and orbit F, G, and K stars (4766 ≤ Teff ≤ 7360 K). We detect a significant orbital eccentricity for the three longest-period systems in our sample: TOI-2025 b (P  = 8.872 d, 0.394$^{+0.035}_{-0.038}$), TOI-2145 b (P  = 10.261 d, e  = $0.208^{+0.034}_{-0.047}$), and TOI-2497 b (P  = 10.656 d, e  = $0.195^{+0.043}_{-0.040}$). TOI-2145 b and TOI-2497 b both orbit subgiant host stars (3.8 < log  g <4.0), but these planets show no sign of inflation despite very high levels of irradiation. The lack of inflation may be explained by the high mass of the planets; $5.26^{+0.38}_{-0.37}$ MJ (TOI-2145 b) and 4.82 ± 0.41 MJ (TOI-2497 b). These six new discoveries contribute to the larger community effort to use TESS to create a magnitude-complete, self-consistent sample of giant planets with well-determined parameters for future detailed studies. 
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  2. Abstract

    The optimal synthesis of advanced nanomaterials with numerous reaction parameters, stages, and routes, poses one of the most complex challenges of modern colloidal science, and current strategies often fail to meet the demands of these combinatorially large systems. In response, an Artificial Chemist is presented: the integration of machine‐learning‐based experiment selection and high‐efficiency autonomous flow chemistry. With the self‐driving Artificial Chemist, made‐to‐measure inorganic perovskite quantum dots (QDs) in flow are autonomously synthesized, and their quantum yield and composition polydispersity at target bandgaps, spanning 1.9 to 2.9 eV, are simultaneously tuned. Utilizing the Artificial Chemist, eleven precision‐tailored QD synthesis compositions are obtained without any prior knowledge, within 30 h, using less than 210 mL of total starting QD solutions, and without user selection of experiments. Using the knowledge generated from these studies, the Artificial Chemist is pre‐trained to use a new batch of precursors and further accelerate the synthetic path discovery of QD compositions, by at least twofold. The knowledge‐transfer strategy further enhances the optoelectronic properties of the in‐flow synthesized QDs (within the same resources as the no‐prior‐knowledge experiments) and mitigates the issues of batch‐to‐batch precursor variability, resulting in QDs averaging within 1 meV from their target peak emission energy.

     
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