https://www.selleckchem.com/products/dapansutrile.html Tunable terahertz (THz)-wave absorption spectroscopy is a promising technique to detect trace gases suspended in ambient air owing to their strong absorption fingerprints in the THz-wave spectral region. Here, we present a THz-wave spectroscopic gas detection platform based on a frequency-tunable injection-seeded THz-wave parametric generator and compact multipass gas absorption cells. Using a 1.8-m-path-length multipass cell, we detected gas-phase methanol (CH3OH) down to a trace concentration of 0.2 ppm at the 1.48-THz transparent atmospheric window. We also developed a transportable walk-through screening prototype using a 6-m-path-length multipass cell to identify suspicious subjects. Our results demonstrate the potential of the proposed system for security screening applications.The phase of electromagnetic waves can be manipulated and tailored by artificial metasurfaces, which can lead to ultra-compact, high-performance metalens, holographic and imaging devices etc. Usually, nanostructured metasurfaces are associated with a large number of geometric parameters, and the multi-parameter optimization for phase design cannot be possibly achieved by conventional time-consuming simulations. Deep learning tools capable of acquiring the relationship between complex nanostructure geometry and electromagnetic responses are best suited for such challenging task. In this work, by innovations in the training methods, we demonstrate that deep neural network can handle six geometric parameters for accurately predicting the phase value, and for the first time, perform direct inverse design of metasurfaces for on-demand phase requirement. In order to satisfy the achromatic metalens design requirements, we also demonstrate simultaneous phase and group delay prediction for near-zero group delay dispersion. Our results suggest significantly improved design capability of complex metasurfaces with the aid of deep learning tools