Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/16937
Title: Metal Organic Framework based Humidity Sensing: Stability, performance, and IoT Integration
Authors: Abbas, Zahir
Keywords: Iot-enabled Smart Agriculture;Ni/zn-mof Capacitive Sensors;Quick Response/recovery Time;Response-recovery Time;Soil Humidity
Issue Date: 2025
Publisher: Elsevier B.V.
Citation: Akram, W., Iqbal, S., Abbas, Z., Mansoor, S., Shah, I., Ullah, A., Xu, W., & Kim, W. (2025). Metal Organic Framework based Humidity Sensing: Stability, performance, and IoT Integration. Journal of Science: Advanced Materials and Devices. https://doi.org/10.1016/j.jsamd.2025.100972
Abstract: The incorporation of IoT technology with advanced sensing materials is converting smart agriculture by allowing precise control over environmental conditions and optimizing resource utilization for advanced agricultural productivity. This study examines the potential of metal-organic frameworks (MOFs) for soil moisture detection in plants, focusing on their application in IoT-enabled smart agriculture systems. Two MOFs, synthesized with nickel acetate and zinc acetate, were evaluated for their humidity-sensing capabilities. The nickel acetate-based MOF had a highly porous, rod-shaped morphology with homogeneous dendrites and high capacitance, in contrast to the Zn-MOF, which exhibited clustering and reduced effective humidity collecting sites, as confirmed by Raman and XRD investigations and SEM images. Ni-MOF outperformed Zn-MOF with a 7.5 times increase in capacitance between 10 % and 90 % relative humidity and a minimal hysteresis of 3.5 % at 70 % relative humidity. Additionally, Ni-MOF demonstrated exceptional response and recovery times of 1.6 s and 0.3 s, respectively. These attributes underscore Ni-MOF's suitability for reliable and efficient soil moisture sensing in agricultural applications. By integrating Ni-MOF sensors into wireless sensor networks and IoT frameworks, this research highlights their potential to fuse field-based sensor data with proximal sensing platforms, contributing to enhanced decision-making and optimization of agricultural operations. © 2025 Elsevier B.V., All rights reserved.
URI: https://dx.doi.org/10.1016/j.jsamd.2025.100972
https://dspace.iiti.ac.in:8080/jspui/handle/123456789/16937
ISSN: 24682179
24682284
Type of Material: Journal Article
Appears in Collections:Department of Chemistry

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