In this work, a series of Ni/Co-TCPP (tetrakis(4-carboxyphenyl)phosphonium porphyrin) MOFs (metalloporphyrinic metxal-organic framework) were controllably synthesized by adjusting the ratio of Ni/Co and solvent volume. The results showed that the morphologies of sheet-like, film-like, flower-like and rod-like morphologies of Ni/Co-TCPP MOFs were successfully synthesized. The obtained Ni/Co-TCPP MOFs-1 were used as electrochemical sensors for glucose detection. The sensor showed a high sensitivity of 2.8 mA mM ⁻¹ cm ⁻² , fast response time (about 5 s), a low detection limit of 0.3 μ M (S/N = 3), and wide linear range of 1.0 μ M to 3.8 mM. It shows that the obtained Ni/Co-TCPP MOFs may be expected to be used to develop effective non-enzymatic glucose sensors.

Crosslevel is defined as the difference in elevation between the top surface of two railroad tracks. Severe changes in crosslevel, for example, due to earthquakes, ground settlement, or crushed ballasts, affect track geometry and can cause train derailment. Therefore, the objective of this study was to monitoring railroad crosslevel by using electrical time domain reflectometry (ETDR) to simultaneously interrogate multiple capacitive tilt sensor prototypes connected in a transmission line. ETDR works by propagating an electrical pulse signal from one end of the transmission line and then monitoring the characteristics of each reflected pulse, which is affected by the capacitance (or tilt) of the sensors. This study begins with a discussion of the capacitive tilt sensor’s design. These 3D-printed sensors were tested to characterize their tilt sensing performance. Then, multiple tilt sensors were connected in a transmission line and interrogated by ETDR. The ability to use ETDR to multiplex and interrogate sensors subjected to different angles of tilt was validated.

Strain measurements are vital for monitoring the load-bearing capacity and safety of structures. A common approach is to affix strain gages onto structural surfaces. On the other hand, most aerospace, automotive, civil, and mechanical structures are painted and coated, often with many layers, prior to their deployment. There is an opportunity to design smart and multifunctional paints that can be directly pre-applied onto structural surfaces to serve as a sensing layer among their other layers of functional paints. Therefore, the objective of this study was to design a strain-sensitive paint that can be used for structural monitoring. Carbon nanotubes (CNT) were dispersed in paint by high-speed shear mixing, while paint thinner was employed for adjusting the formulation’s viscosity and nanomaterial concentration. The study started with the design and fabrication of the CNT-based paint. Then, the nanocomposite paint’s electromechanical properties and its sensitivity to applied strains were characterized. Third, the nanocomposite paint was spray-coated onto patterned substrates to form “Sensing Meshes” for distributed strain monitoring. An electrical resistance tomography (ERT) measurement strategy and algorithm were utilized for reconstructing the conductivity distribution of the Sensing Meshes, where the magnitude of conductivity (or resistivity) corresponded to the magnitude of strain, while strain directionality was determined based on the strut direction in the mesh.

Contact pressure mapping is commonly used in many automotive, healthcare, industrial, and robotics applications. This study used electrical impedance tomography (EIT) for mapping pressure using a commercial Smartfoam. The sensitivity of the Smartfoam was enhanced by depositing a piezoresistive carbon nanotube-based thin film. Controlled pressure mapping tests were performed by placing different weights of varying contact areas on different locations (or positions) of the resulting Nanocomposite Smartfoam. The EIT results confirmed that the Nanocomposite Smartfoam could resolve pressure hotspots at different locations, as well as different magnitudes of contact pressure applied.