The FeSe nematic phase has been the focus of recent research on iron-based superconductors (IBSs) due to its unusual properties, which are distinct from those of the pnictides. A series of theoretical/experimental studies were performed to determine the origin of the nematic phase. However, they yielded conflicting results and caused additional controversies. Here, we report the results of angle-resolved photoemission and X-ray absorption spectroscopy studies on FeSe detwinned by a piezo stack. We fully resolved band dispersions with orbital characters near the Brillouin zone (BZ) corner, and revealed an absence of any Fermi pocket at the Y point in the 1-Fe BZ. In addition, the occupation imbalance between d xz and d yz orbitals was the opposite of that of iron pnictides, consistent with the identified band characters. These results resolve issues associated with the FeSe nematic phase and shed light on the origin of the nematic phase in IBSs.

Using angle-resolved photoemission spectroscopy, we show direct evidence for charge transfer between adsorbed molecules and metal substrates, i.e., chemisorption of CO on Pt(111) and Pt–Sn/Pt(111) 2 × 2 surfaces. The observed band structures show a unique signature of charge transfer as CO atoms are adsorbed, revealing the roles of specific orbital characters participating in the chemisorption process. As the coverage of CO increases, the degree of charge transfer between CO and Pt shows a clear difference to that of Pt–Sn. With comparison to density functional theory calculation results, the observed distinct features in the band structure are interpreted as back-donation bonding states formed between the Pt molecular orbital and the 2π orbital of CO. Furthermore, the change in the surface charge concentration, measured from the Fermi surface area, shows that the Pt surface has a larger charge concentration change than the Pt–Sn surface upon CO adsorption. The differences between Pt and Pt–Sn surfaces are due to the effect of Pt–Sn intermetallic bonding on the interaction of CO with the surface.

<p>This study proposes a novel method for rainfall intensity estimation from acoustic and vibration data with low-cost sensors. At first, a precipitation measurement device was developed to collect sound and touch signals from raindrops, composed of Raspberry Pi, a condenser microphone, and an accelerometer with 6 degrees of freedom. To figure out whether rainfall occurred or not, a binary classification model with the XGBoost algorithm was considered to analyze long-term time series of vibration data. Then, high-resolution acoustic data was used to investigate the main characteristics of rainfall patterns at a frequency domain for the period when it was determined that rainfall occurred. As a result of the Short Time Fourier Transform (STFT), the highest frequency, mean and standard deviation of amplitudes were selected as representative values for minute data. Finally, different types of regression models were applied to develop the method for rainfall intensity estimation from comparative analysis with other precipitation measurement devices (e.g., PARSIVEL, etc.). It should be noted that the new device with the proposed method functions reliably under extreme environmental conditions when the estimated rainfall intensity was compared with measured data from ground-based precipitation devices. It shows that low-cost sensors with sound and touch signals from raindrops can be effectively used for rainfall intensity estimation with easy installation and maintenance, indicating a strong possibility of being considered in a wide range of areas for precipitation measurement with high resolution and accuracy</p><p><strong>Acknowledgement</strong></p><p>This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2022R1A4A3032838).</p>