The Evolution of Gas Sensors Into Neuromorphic Systems

ABSTRACT Gas sensors are essential in applications ranging from environmental monitoring and industrial safety to healthcare diagnostics and consumer devices, where reliable and selective detection is critical. With growing demands for sensitivity, selectivity, and energy efficiency, sensor technology has evolved significantly. Historically, the field advanced from sentinel organisms and gas lamps to a range of sophisticated mechanisms. Yet, conventional sensors remain limited to passive detection, relying on separate units for memory and processing, which leads to higher power consumption, slower response, and reduced adaptability in dynamic environments. Neuromorphic sensing provides a compelling alternative by integrating sensing, memory, and computation in a single device, enabling compact, energy‐efficient, and adaptive gas detection inspired by biological olfactory systems. This review begins with a concise overview of traditional semiconductor metal oxide gas sensors, providing a baseline for introducing memristor‐based gas sensors, or “gasistors.” These devices represent a transformative shift, offering improved efficiency, reliability, and versatility in gas sensing electronics. We then highlight the neuromorphic in‐memory gas sensing paradigm, with examples including electronic noses, bio‐inspired olfactory systems, and spike‐based computational frameworks. Finally, we discuss progress in materials, device architectures, and algorithms, and outline opportunities and challenges for realizing the full potential of neuromorphic gas sensing.