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.

Thermal energy management in metal-organic frameworks (MOFs) is an important, yet often neglected, challenge for many adsorption-based applications such as gas storage and separations. Despite its importance, there is insufficient understanding of the structure-property relationships governing thermal transport in MOFs. To provide a data-driven perspective into these relationships, here we perform large-scale computational screening of thermal conductivity k in MOFs, leveraging classical molecular dynamics simulations and 10,194 hypothetical MOFs created using the ToBaCCo 3.0 code. We found that high thermal conductivity in MOFs is favored by high densities (> 1.0 g cm−3), small pores (< 10 Å), and four-connected metal nodes. We also found that 36 MOFs exhibit ultra-low thermal conductivity (< 0.02 W m−1 K−1), which is primarily due to having extremely large pores (~65 Å). Furthermore, we discovered six hypothetical MOFs with very high thermal conductivity (> 10 W m−1 K−1), the structures of which we describe in additional detail.

Thermal transport in metal–organic frameworks (MOFs) is an essential but frequently overlooked property.

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.

We quantified the impact of support interactions on the binding and interaction energies of CO and O adsorbed on Pt 13 nanoclusters supported on amorphous silica surfaces through the use of density functional theory calculations. We used an accurate model for amorphous silica having two different surface silanol concentrations, corresponding to low (200 °C) and high (715 °C) surface pretreatment temperatures. We compared CO and O adsorbed on supported and freestanding Pt 13 clusters. We found that Pt 13 is highly susceptible to both support-and adsorbate-induced reconstruction, depending on the relaxed structure of the Pt 13 cluster on the surface. Structure relaxation effects dominate over electronic effects of the support. We considered an ensemble of 50 different systems by varying the placement of the Pt 13 cluster on the surfaces and by exploring a range of different binding sites for CO and O on the Pt 13 cluster. In select cases, binding energy differences between supported and freestanding Pt 13 are as large as 2 eV. However, the mean absolute error between supported and freestanding clusters over all systems we studied is only a few tenths of an eV. Coverage effects on coadsorption of CO and O are significantly different on supported clusters compared with the Pt(111) surface. Our results can be used for predicting when support interactions may be important for any reaction catalyzed by small metal nanoclusters.