Size-Based Norfentanyl Detection with SWCNT@UiO-MOF Composites.

Single-walled carbon nanotube (SWCNT)@metal-organic framework (MOF) field-effect transistor (FET) sensors generate a signal through analytes restricting ion diffusion around the SWCNT surface. Four composites made up of SWCNTs and UiO-66, UiO-66-NH2, UiO-67, and UiO-67-CH3 were synthesized to explore the detection of norfentanyl (NF) using SWCNT@MOF FET sensors with different pore sizes. Liquid-gated FET devices of SWCNT@UiO-67 showed the highest sensing response toward NF, whereas SWCNT@UiO-66 and SWCNT@UiO-66-NH2 devices showed no sensitivity improvement compared to bare SWCNT. Comparing SWCNT@UiO-67 and SWCNT@UiO-67-CH3 indicated that the sensing response is modulated by not only the size-matching between NF and MOF channel but also NF diffusion within the MOF channel. Additionally, other drug metabolites, including norhydrocodone (NH), benzoylecgonine (BZ), and normorphine (NM) were tested with the SWCNT@UiO-67 sensor. The sensor was not responding toward NH and or BZ but a similar sensing result toward NM because NM has a similar size to NF. The SWCNT@MOF FET sensor can avoid interference from bigger molecules but sensor arrays with different pore sizes and chemistries are needed to improve the specificity.

Correlated missing linker defects increase thermal conductivity in metal-organic framework UiO-66.

Thermal transport in metal-organic frameworks (MOFs) is an essential but frequently overlooked property. Among the small number of existing studies on thermal transport in MOFs, even fewer have considered explicitly the influence of defects. However, defects naturally exist in MOF crystals and are known to influence many of their material properties. In this work, we investigate the influence of both randomly and symmetrically distributed defects on the thermal conductivity of the MOF UiO-66. Two types of defects were examined: missing linker and missing cluster defects. For symmetrically distributed (i.e., spatially correlated) defects, we considered three experimentally resolved defect nanodomains of UiO-66 with underlying topologies of bcu, reo, and scu. We observed that both randomly distributed missing linker and missing cluster defects typically decrease thermal conductivity, as expected. However, we found that the spatial arrangement of defects can significantly impact thermal conductivity. In particular, the spatially correlated missing linker defect nanodomain (bcu topology) displayed an intriguing anisotropy, with the thermal conductivity along a particular direction being higher than that of the defect-free UiO-66. We attribute this unusual defect-induced increase in thermal conductivity to the removal of the linkers perpendicular to the primary direction of heat transport. These perpendicular linkers act as phonon scattering sources such that removing them increases thermal conductivity in that direction. Moreover, we also observed an increase in phonon group velocity, which might also contribute to the unusual increase. Overall, we show that structural defects could be an additional lever to tune the thermal conductivity of MOFs.

Influence of Missing Linker Defects on the Thermal Conductivity of Metal-Organic Framework HKUST-1.

Although metal-organic frameworks (MOFs) are promising materials for gas storage and separation applications, the heat released during the exothermic adsorption process can potentially negatively impact their practical utility. Thermal transport in MOFs has not been widely studied, and among the relatively few reports on the topic, MOFs have either been assumed to be defect free or the presence of defects was not discussed. However, defects naturally exist in MOFs and can also be introduced intentionally. Here, we investigate the effect of missing linker defects on the thermal conductivity of HKUST-1 using molecular dynamics (MDs) simulation and the Green-Kubo method. We found that missing linker defects, even at low concentrations, substantially reduce the thermal conductivity of HKUST-1. If not taken into account, the presence of defects could lead to significant discrepancies between experimentally measured and computationally predicted thermal conductivities.

CFD Modeling of Chamber Filling in a Micro-Biosensor for Protein Detection.

Tuberculosis (TB) remains one of the main causes of human death around the globe. The mortality rate for patients infected with active TB goes beyond 50% when not diagnosed. Rapid and accurate diagnostics coupled with further prompt treatment of the disease is the cornerstone for controlling TB outbreaks. To reduce this burden, the existing gap between detection and treatment must be addressed, and dedicated diagnostic tools such as biosensors should be developed. A biosensor is a sensing micro-device that consists of a biological sensing element and a transducer part to produce signals in proportion to quantitative information about the binding event. The micro-biosensor cell considered in this investigation is designed to operate based on aptamers as recognition elements against Mycobacterium tuberculosis secreted protein MPT64, combined in a microfluidic-chamber with inlet and outlet connections. The microfluidic cell is a miniaturized platform with valuable advantages such as low cost of analysis with low reagent consumption, reduced sample volume, and shortened processing time with enhanced analytical capability. The main purpose of this study is to assess the flooding characteristics of the encapsulated microfluidic cell of an existing micro-biosensor using Computational Fluid Dynamics (CFD) techniques. The main challenge in the design of the microfluidic cell lies in the extraction of entrained air bubbles, which may remain after the filling process is completed, dramatically affecting the performance of the sensing element. In this work, a CFD model was developed on the platform ANSYS-CFX using the finite volume method to discretize the domain and solving the Navier-Stokes equations for both air and water in a Eulerian framework. Second-order space discretization scheme and second-order Euler Backward time discretization were used in the numerical treatment of the equations. For a given inlet-outlet diameter and dimensions of an in-house built cell chamber, different inlet liquid flow rates were explored to determine an appropriate flow condition to guarantee an effective venting of the air while filling the chamber. The numerical model depicted free surface waves as promoters of air entrainment that ultimately may explain the significant amount of air content in the chamber observed in preliminary tests after the filling process is completed. Results demonstrated that for the present design, against the intuition, the chamber must be filled with liquid at a modest flow rate to minimize free surface waviness during the flooding stage of the chamber.