Interference-Resilient Hydrogen Sensing for Sustainable Hydrogen Energy Systems: A Review of Material-, Algorithm-, and System-Level Strategies

Hydrogen gas sensors are essential for ensuring safety and efficient operation in the expanding hydrogen energy economy and its infrastructure. However, real-world sensor performance is frequently compromised by interference from coexisting gases, environmental fluctuations, and physical disturbances, leading to false alarms, missed detections, and increased recalibration or maintenance burden. This comprehensive review systematically summarizes recent advances in anti-interference technologies for hydrogen gas sensors across material-, signal-processing-, and system-level domains. At the material level, strategies such as noble-metal doping, nanostructure engineering, and selective membrane coatings improve selectivity and long-term stability. At the signal level, advanced noise reduction, dynamic calibration, drift compensation, and machine-learning-based pattern recognition enhance detection accuracy and robustness under varying conditions. At the system level, sensor arrays, optimized packaging, structural isolation, and adaptive redundancy mitigate interference in realistic deployments. By critically evaluating these multi-scale strategies, this review highlights progress, identifies key performance trade-offs, and outlines research directions toward interference-resilient sensing that supports scalable, low-maintenance, and energy-efficient hydrogen infrastructure.