Exceptional Electrical Detection of Trace NO 2 via Mixed Metal MOF-on-MOF Film-Based Sensors
The tunability of metal–organic frameworks (MOFs) makes them exceptional materials for the development of highly selective, low-power sensors for toxic gas detection. Herein, we demonstrate enhanced detection of NO 2 gas by a MOF-based electrical impedance sensor made using a unique mixed metal MOF-on-MOF synthesis. For this work, a combined experimental and computational study was performed using the exemplar Ni x Mg 1–x -MOF-74 to understand the fundamental structure–property relationships behind metal mixing and MOF film synthesis methods on sensor performance. Density functional theory results indicated that the presence of Ni in Mg-MOF-74 increased framework stability and increased the electron density of states at lower energies near the HOMO, as well as enhanced the NO 2 –Mg adsorption interaction. Impedance data of the Ni x Mg 1–x -MOF-74 films with larger Ni contents showed greater impedance change after exposure to 1 ppm of NO 2 gas. Furthermore, when synthesized through either a drop-cast or direct solvothermal film growth approach, the monometallic Ni-based sensors had the best performance. However, the mixed metal Ni x Mg 1–x -MOF-74 sensors synthesized through a MOF-on-MOF approach resulted in the highest impedance change, outperforming all monometallic Ni-based sensors. In particular, the mixed metal Ni-on-Mg-MOF-74 film was the best-performing sensor with an impedance change of 309 upon trace NO 2 exposure. Change in impedance response after NO 2 exposure was improved by 52% compared to the best monometallic Ni-on-Ni-MOF-74 sensor. Structural analysis of the Ni-on-Mg film showed that the first Mg-MOF-74 layer acts as a structural template controlling the structural features of the final film after metal exchange with Ni. This led to improved film quality, evidenced by the greater crystallinity and larger MOF grain sizes, and resulted in enhanced sensor performance which was not achievable through other metal mixing methods. Altogether, this study identifies structure–property relationships and synthetic templating methods that inform MOF-based sensor design, allowing for improved detection of toxic compounds.