Hydrochromic NiI2/(CH3)4NI derived humidity self-adaptive nano-electronic for precisely tracking gastric cancer-related volatile markers under humid condition

Abstract Continuously monitoring the variation of gastric cancer (GC)-related volatile markers that derived from human breath could be a promising approach to timely pre-warn gastric cancer, thus, offers the opportunity of decreasing future GC patients’ mortalities. Nevertheless, effective eliminating the negative impact derived from oral moisture remains a challenging issue when implementing the volatolomics-based non-invasive med-tech. Here, concept of humidity self-adaptability is created via developing a hydrochromic-type optical modulator that based on the newly reported hybridized NiI2/(CH3)4NI. Particularly, a humidity self-adaptive intelligent nano-electronic that integrated with the hydrochromic-type optical modulator was specifically designed to serve as a powerful sensing platform for high performance tracking GC-relevant volatiles markers under high humidity condition. Impressively, the fast hydrochromic speed (less than4 s, from dry to wet) and desirable humidity depended transmittance of the presented hybridized NiI2/(CH3)4NI enabled the proposed humidity self-adaptability to be successfully realized for the intelligent nano-electronic within the relative humidity (R.H.) range of 0–53.2% by indirectly tailoring the gas molecular reactivity, resulting in the frequently encountered adverse humidity impact being eliminated. Notably, desirable specificity (>81%), sensitivity and low detection of limit (parts per billion level) is further confirmed for the designed nano-electronic that comprised of 11 kinds of various ligands functionalized Au@ZnO nanoarray-based nanosensors when constantly monitoring 9 kinds of GC-relevant volatiles markers, even at high humidity condition. Conclusively, these impressive pilot results suggest a bright future for precisely tracking the volatile markers derived from humidified breath sample, allowing GC to be timely pre-warned.