Top-Down Approaches for 10 nm-Scale Nanochannel: Toward Exceptional HS Detection.

Metal oxide semiconductors (MOS) have proven to be most powerful sensing materials to detect hydrogen sulfide (HS), achieving part per billion (ppb) level sensitivity and selectivity. However, there has not been a way of extending this approach to the top-down HS sensor fabrication process, completely limiting their commercial-level productions. In this study, we developed a top-down lithographic process of a 10 nm-scale SnO nanochannel for HS sensor production.

Finding Hidden Signals in Chemical Sensors Using Deep Learning.

Achieving high signal-to-noise ratio in chemical and biological sensors enables accurate detection of target analytes. Unfortunately, below the limit of detection (LOD), it becomes difficult to detect the presence of small amounts of analytes and extract useful information via any of the conventional methods. In this work, we examine the possibility of extracting "hidden signals" using deep neural network to enhance gas sensing below the LOD region.