Emerging mxene–polymer hybrid nanocomposites for high-performance ammonia sensing and monitoring Article

Chaudhary, V, Gautam, A, Mishra, YK et al. (2021). Emerging mxene–polymer hybrid nanocomposites for high-performance ammonia sensing and monitoring . 11(10), 10.3390/nano11102496

cited authors

  • Chaudhary, V; Gautam, A; Mishra, YK; Kaushik, A

authors

abstract

  • Ammonia (NH3) is a vital compound in diversified fields, including agriculture, automo-tive, chemical, food processing, hydrogen production and storage, and biomedical applications. Its extensive industrial use and emission have emerged hazardous to the ecosystem and have raised global public health concerns for monitoring NH3 emissions and implementing proper safety strat-egies. These facts created emergent demand for translational and sustainable approaches to design efficient, affordable, and high-performance compact NH3 sensors. Commercially available NH3 sensors possess three major bottlenecks: poor selectivity, low concentration detection, and room-tem-perature operation. State-of-the-art NH3 sensors are scaling up using advanced nano-systems possessing rapid, selective, efficient, and enhanced detection to overcome these challenges. MXene– polymer nanocomposites (MXP-NCs) are emerging as advanced nanomaterials of choice for NH3 sensing owing to their affordability, excellent conductivity, mechanical flexibility, scalable produc-tion, rich surface functionalities, and tunable morphology. The MXP-NCs have demonstrated high performance to develop next-generation intelligent NH3 sensors in agricultural, industrial, and bi-omedical applications. However, their excellent NH3-sensing features are not articulated in the form of a review. This comprehensive review summarizes state-of-the-art MXP-NCs fabrication tech-niques, optimization of desired properties, enhanced sensing characteristics, and applications to detect airborne NH3. Furthermore, an overview of challenges, possible solutions, and prospects as-sociated with MXP-NCs is discussed.

publication date

  • October 1, 2021

Digital Object Identifier (DOI)

volume

  • 11

issue

  • 10