Relative humidity (RH) and temperature responsive nanofilms have been developed as colorimetric sensors based on light interference, with the sensors providing rapid and easy detection, high accuracy, good mobility, wearability, and power-free sensing ability. However, current studies on RH and temperature-sensitive colorimetric films focus only on the effect of either temperature or RH on the sensing ability. With an inherent relationship between temperature and RH, this constraint leads to significant limitations for the use of thin film sensors in practical applications. In this work, we address these limitations by examining the correlation between structural color (thickness), temperature, and RH using nanolayered polyelectrolyte films made from chitosan (CHI) and carboxymethyl cellulose (CMC). We propose a novel 3-dimensional (3D) non-linear regression model to describe the correlation between the normalized thickness, temperature, and RH; with the thickness prediction showing high agreement with experimental results. Furthermore, photoreactive carboxymethyl cellulose-azido derivative (CMC-N3) was used to build CHI/CMC-N3 films that can be covalently crosslinked upon UV irradiation. By taking advantage of different swelling behaviors of CHI/CMC-N3 films before and after UV treatment, a variety of colors and crosslinked patterns are hidden/displayed at selected RHs and temperatures. This enables a tunable multimodal display of the pattern-encoded information. Remarkably, in temperature ranges from 2 °C to 55 °C, uniform colors covering the entire visible spectra were observed, while in the low temperature (2–10 °C) and high RH (∼80%) regimes, the film demonstrated vivid color changes with 1 °C resolution. We expect the film to provide a versatile platform for potential applications in environmental sensing, anticounterfeiting, food storage, and quality control in drug transport.
Contributions
Publication Authors:
Md Nayeem Hasan Kashem, Karl Gardner, Moriom Rojy Momota, Bashir I. Morshed, Wei Li
Publication Acknowledgements:
W.L. thanks New Faculty Startup Funds from Texas Tech University (TTU) and funding support from Global Laboratory for Energy Asset Management and Manufacturing (GLEAMM) at TTU.