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.

Implementation of a Core-Shell Design Approach for Constructing MOFs for CO2 Capture.

Adsorption-based capture of CO2 from flue gas and from air requires materials that have a high affinity for CO2 and can resist water molecules that competitively bind to adsorption sites. Here, we present a core-shell metal-organic framework (MOF) design strategy where the core MOF is designed to selectively adsorb CO2, and the shell MOF is designed to block H2O diffusion into the core. To implement and test this strategy, we used the zirconium (Zr)-based UiO MOF platform because of its relative structural rigidity and chemical stability. Previously reported computational screening results were used to select optimal core and shell MOF compositions from a basis set of possible building blocks, and the target core-shell MOFs were prepared. Their compositions and structures were characterized using scanning electron microscopy, transmission electron microscopy, and powder X-ray diffraction. Multigas (CO2, N2, and H2O) sorption data were collected both for the core-shell MOFs and for the core and shell MOFs individually. These data were compared to determine whether the core-shell MOF architecture improved the CO2 capture performance under humid conditions. The combination of experimental and computational results demonstrated that adding a shell layer with high CO2/H2O diffusion selectivity can significantly reduce the effect of water on CO2 uptake.

In silico identification and synthesis of a multi-drug loaded MOF for treating tuberculosis.

Conventional drug delivery systems have been applied to a myriad of active ingredients but may be difficult to tailor for a given drug. Herein, we put forth a new strategy, which designs and selects the drug delivery material by considering the properties of encapsulated drugs (even multiple drugs, simultaneously). Specifically, through an in-silico screening process of 5109 MOFs using grand canonical Monte Carlo simulations, a customized MOF (referred as BIO-MOF-100) was selected and experimentally verified to be biologically stable, and capable of loading 3 anti-Tuberculosis drugs Rifampicin+Isoniazid+Pyrazinamide at 10% + 28% + 23% wt/wt (total > 50% by weight). Notably, the customized BIO-MOF-100 delivery system cleared naturally Pyrazinamide-resistant Bacillus Calmette-Guérin, reduced growth of virulent Erdman infection in macaque macrophages 10-100-fold compared to soluble drugs in vitro and was also significantly reduced Erdman growth in mice. These data suggest that the methodology of identifying-synthesizing materials can be used to generate solutions for challenging applications such as simultaneous delivery of multiple, small hydrophilic and hydrophobic molecules in the same molecular framework.

Designing optimal core-shell MOFs for direct air capture.

Metal-organic frameworks (MOFs), along with other novel adsorbents, are frequently proposed as candidate materials to selectively adsorb CO2 for carbon capture processes. However, adsorbents designed to strongly bind CO2 nearly always bind H2O strongly (sometimes even more so). Given that water is present in significant quantities in the inlet streams of most carbon capture processes, a method that avoids H2O competition for the CO2 binding sites would be technologically valuable. In this paper, we consider a novel core-shell MOF design strategy, where a high-CO2-capacity MOF "core" is protected from competitive H2O-binding via a MOF "shell" that has very slow water diffusion. We consider a high-frequency adsorption/desorption cycle that regenerates the adsorbents before water can pass through the shell and enter the core. To identify optimal core-shell MOF pairs, we use a combination of experimental measurements, computational modeling, and multiphysics modeling. Our library of MOFs is created from two starting MOFs-UiO-66 and UiO-67-augmented with 30 possible functional group variations, yielding 1740 possible core-shell MOF pairs. After defining a performance score to rank these pairs, we identified 10 core-shell MOF candidates that significantly outperform any of the MOFs functioning alone.

VOC Mixture Sensing with a MOF Film Sensor Array: Detection and Discrimination of Xylene Isomers and Their Ternary Blends.

Detection and recognition of volatile organic compounds (VOCs) are crucial in many applications. While pure VOCs can be detected by various sensors, the discrimination of VOCs in mixtures, especially of similar molecules, is hindered by cross-sensitivities. Isomer identification in mixtures is even harder. Metal-organic frameworks (MOFs) with their well-defined, nanoporous, and versatile structures have the potential to improve the VOC sensing performance by tailoring the adsorption affinities. Here, we detect and identify ternary xylene isomer mixtures by using an array of six gravimetric, quartz crystal microbalance (QCM)-based sensors coated with selected MOF films with different isomer affinities. We use classical molecular simulations to provide insights into the sensing mechanism. In addition to the attractive interaction between the analytes and the MOF film, the isomer discrimination is caused by the rigid crystalline framework sterically controlling the access of the isomers to different adsorption sites in the MOFs. The sensor array has a very low limit of detection of 1 ppm for each pure isomer and allows the isomer discrimination in mixtures. At 100 ppm, 16 different ternary o-p-m-xylene mixtures were identified with high classification accuracy (96.5%). This work shows the unprecedented performance of MOF-sensor arrays, also referred to as MOF-electronic nose (MOF-e-nose), for sensing VOC mixtures. Based on the study, guidelines for detecting and discriminating complex mixtures of volatile molecules are also provided.

Hybridization from Guest-Host Interactions Reduces the Thermal Conductivity of Metal-Organic Frameworks.

We experimentally and theoretically investigate the thermal conductivity and mechanical properties of polycrystalline HKUST-1 metal-organic frameworks (MOFs) infiltrated with three guest molecules: tetracyanoquinodimethane (TCNQ), 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4-TCNQ), and (cyclohexane-1,4-diylidene)dimalononitrile (H4-TCNQ). This allows for modification of the interaction strength between the guest and host, presenting an opportunity to study the fundamental atomic scale mechanisms of how guest molecules impact the thermal conductivity of large unit cell porous crystals. The thermal conductivities of the guest@MOF systems decrease significantly, by on average a factor of 4, for all infiltrated samples as compared to the uninfiltrated, pristine HKUST-1. This reduction in thermal conductivity goes in tandem with an increase in density of 38% and corresponding increase in heat capacity of ∼48%, defying conventional effective medium scaling of thermal properties of porous materials. We explore the origin of this reduction by experimentally investigating the guest molecules' effects on the mechanical properties of the MOF and performing atomistic simulations to elucidate the roles of the mass and bonding environments on thermal conductivity. The reduction in thermal conductivity can be ascribed to an increase in vibrational scattering introduced by extrinsic guest-MOF collisions as well as guest molecule-induced modifications to the intrinsic vibrational structure of the MOF in the form of hybridization of low frequency modes that is concomitant with an enhanced population of localized modes. The concentration of localized modes and resulting reduction in thermal conductivity do not seem to be significantly affected by the mass or bonding strength of the guest species.

Computational Design of MOF-Based Electronic Noses for Dilute Gas Species Detection: Application to Kidney Disease Detection.

The diverse chemical composition of exhaled human breath contains a vast amount of information about the health of the body, and yet this is seldom taken advantage of for diagnostic purposes due to the lack of appropriate gas-sensing technologies. In this work, we apply computational methods to design mass-based gas sensor arrays, often called electronic noses, that are optimized for detecting kidney disease from breath, for which ammonia is a known biomarker. We define combined linear adsorption coefficients (CLACs), which are closely related to Henry's law coefficients, for calculating gas adsorption in metal-organic frameworks (MOFs) of gases commonly found in breath (i.e., carbon dioxide, argon, and ammonia). These CLACs were determined computationally using classical atomistic molecular simulation techniques and subsequently used to design and evaluate gas sensor arrays. We also describe a novel numerical algorithm for determining the composition of a breath sample given a set of sensor outputs and a library of CLACs. After identifying an optimal array of five MOFs, we screened a set of 100 simplified computer-generated, water-free breath samples for kidney disease and were able to successfully quantify the amount of ammonia in all samples within the tolerances needed to classify them as either healthy or diseased, demonstrating the promise of such devices for disease detection applications.

Toward comprehensive exploration of the physisorption space in porous pseudomaterials using an iterative mutation search algorithm.

We describe an updated algorithm for efficiently exploring structure-property spaces relating to physisorption of gases in porous materials. This algorithm uses previously described "pseudomaterials," which are crystals of randomly arranged and parameterized Lennard-Jones spheres, and combines it with a new iterative mutation exploration method. This algorithm is significantly more efficient at sampling the structure-property space than previously reported methods. For the sake of benchmarking to prior work, we apply this method to exploring methane adsorption at 35 bars (298 K) and void fraction as the main structure-property combination. We demonstrate the effect and importance of the changes that were required to increase efficiency over prior methods. The most important changes were (1) using "discrete" mutations less often, (2) decreasing degrees of freedom, and (3) removing biasing from mutations on bounded parameters.

Size Discrimination of Carbohydrates via Conductive Carbon Nanotube@Metal Organic Framework Composites.

Traditional chemical sensing methodologies have typically relied on the specific chemistry of the analyte for detection. Modifications to the local environment surrounding the sensor represent an alternative pathway to impart selective differentiation. Here, we present the hybridization of a 2-D metal organic framework (Cu3(HHTP)2) with single-walled carbon nanotubes (SWCNTs) as a methodology for size discrimination of carbohydrates. Synthesis and the resulting conductive performance are modulated by both mass loading of SWCNTs and their relative oxidation. Liquid gated field-effect transistor (FET) devices demonstrate improved on/off characteristics and differentiation of carbohydrates based on molecular size. Glucose molecule detection is limited to the single micromolar concentration range. Molecular Dynamics (MD) calculations on model systems revealed decreases in ion diffusivity in the presence of different sugars as well as packing differences based on the size of a given carbohydrate molecule. The proposed sensing mechanism is a reduction in gate capacitance initiated by the filling of the pores with carbohydrate molecules. Restricting diffusion around a sensor in combination with FET measurements represents a new type of sensing mechanism for chemically similar analytes.

In Situ Nuclear Magnetic Resonance Investigation of Molecular Adsorption and Kinetics in Metal-Organic Framework UiO-66.

Thermodynamic and kinetic properties of molecular adsorption and transport in metal-organic frameworks (MOFs) are crucially important for many applications, including gas adsorption, filtration, and remediation of harmful chemicals. Using the in situ 1H nuclear magnetic resonance (NMR) isotherm technique, we measured macroscopic thermodynamic and kinetic properties such as isotherms and rates of mass transfer while simultaneously obtaining microscopic information revealed by adsorbed molecules via NMR. Upon investigating isopropyl alcohol adsorption in MOF UiO-66 by in situ NMR, we obtained separate isotherms for molecules adsorbed at distinct environments exhibiting distinct NMR characteristics. A mechanistic view of the adsorption process is obtained by correlating such resolved isotherms with the cage structure effect on the nucleus-independent chemical shift, molecular dynamics such as the crowding effect at high loading levels, and the loading level dependence of the mass transfer rate as measured by NMR and elucidated by classical Monte Carlo simulations.

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.

Enhanced Thermal Conductivity in a Diamine-Appended Metal-Organic Framework as a Result of Cooperative CO2 Adsorption.

Diamine-appended variants of the metal-organic framework M2(dobpdc) (M = Mg, Mn, Fe, Co, Zn; dobpdc4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) exhibit exceptional CO2 capture properties owing to a unique cooperative adsorption mechanism, and thus hold promise for use in the development of energy- and cost-efficient CO2 separations. Understanding the nature of thermal transport in these materials is essential for such practical applications, however, as temperature rises resulting from exothermic CO2 uptake could potentially offset the energy savings offered by such cooperative adsorbents. Here, molecular dynamics (MD) simulations are employed in investigating thermal transport in bare and e-2-appended Zn2(dobpdc) (e-2 = N-ethylethylenediamine), both with and without CO2 as a guest. In the absence of CO2, the appended diamines function to enhance thermal conductivity in the ab-plane of e-2-Zn2(dobpdc) relative to the bare framework, as a result of noncovalent interactions between adjacent diamines that provide additional heat transfer pathways across the pore channel. Upon introduction of CO2, the thermal conductivity along the pore channel (the c-axis) increases due to the cooperative formation of metal-bound ammonium carbamates, which serve to create additional heat transfer pathways. In contrast, the thermal conductivity of the bare framework remains unchanged in the presence of zinc-bound CO2 but decreases in the presence of additional adsorbed CO2.

Observation of reduced thermal conductivity in a metal-organic framework due to the presence of adsorbates.

Whether the presence of adsorbates increases or decreases thermal conductivity in metal-organic frameworks (MOFs) has been an open question. Here we report observations of thermal transport in the metal-organic framework HKUST-1 in the presence of various liquid adsorbates: water, methanol, and ethanol. Experimental thermoreflectance measurements were performed on single crystals and thin films, and theoretical predictions were made using molecular dynamics simulations. We find that the thermal conductivity of HKUST-1 decreases by 40 - 80% depending on the adsorbate, a result that cannot be explained by effective medium approximations. Our findings demonstrate that adsorbates introduce additional phonon scattering in HKUST-1, which particularly shortens the lifetimes of low-frequency phonon modes. As a result, the system thermal conductivity is lowered to a greater extent than the increase expected by the creation of additional heat transfer channels. Finally, we show that thermal diffusivity is even more greatly reduced than thermal conductivity by adsorption.

Genetic Algorithm Design of MOF-based Gas Sensor Arrays for CO2-in-Air Sensing.

Gas sensor arrays, also known as electronic noses, leverage a diverse set of materials to identify the components of complex gas mixtures. Metal-organic frameworks (MOFs) have emerged as promising materials for electronic noses due to their high-surface areas and chemical as well as structural tunability. Using our recently reported genetic algorithm design approach, we examined a set of 50 MOFs and searched through over 1.125 × 1015 unique array combinations to identify optimal arrays for the detection of CO2 in air. We found that despite individual MOFs having lower selectivity for O2 or N2 relative to CO2, intelligently selecting the right combinations of MOFs enables accurate prediction of the concentrations of all components in the mixture (i.e., CO2, O2, N2). We also analyzed the physical properties of the elements in the arrays to develop an intuition for improving array design. Notably, we found that an array whose MOFs have diversity in their volumetric surface areas has improved sensing. Consistent with this observation, we found that the best arrays consistently had greater structural diversity (e.g., pore sizes, void fractions, and surface areas) than the worst arrays.

Silver Nanofilament Formation Dynamics in a Polymer-Ionic Liquid Thin Film by Direct-Write.

Silver nanofilament formation dynamics are reported for an ionic liquid (IL)-filled solid polymer electrolyte prepared by a direct-write process using a conductive atomic force microscope (C-AFM). Filaments are electrochemically formed at hundreds of xy locations on a ~40 nm thick polymer electrolyte, polyethylene glycol diacrylate (PEGDA)/[BMIM]PF6. Although the formation time generally decreases with increasing bias from 0.7 to 3.0 V, an unexpected non-monotonic maximum is observed ~ 2.0 V. At voltages approaching this region of inverted kinetics, IL electric double layers (EDLs) becomes detectable; thus, the increased nanofilament formation time can be attributed to electric field screening which hinders silver electro-migration and deposition. Scanning electron microscopy confirms that nanofilaments formed in this inverted region have significantly more lateral and diffuse features. Time-dependent formation currents reveal two types of nanofilament growth dynamics: abrupt, where the resistance decreases sharply over as little as a few ms, and gradual where it decreases more slowly over hundreds of ms. Whether the resistance change is abrupt or gradual depends on the extent to which the EDL screens the electric field. Tuning the formation time and growth dynamics using an IL opens the range of accessible resistance states, which is useful for neuromorphic applications.

The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation.

Metal-organic frameworks (MOFs) are highly tuneable, extended-network, crystalline, nanoporous materials with applications in gas storage, separations, and sensing. We review how molecular models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chemical warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable molecular simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.

Heat Flux for Many-Body Interactions: Corrections to LAMMPS.

The virial stress tensor-based instantaneous heat flux, which is used by LAMMPS, is only valid for the small subset of simulations that contain only pairwise interactions. For systems that contain many-body interactions using 3- or 4-body potentials, a more complete derivation is required. We have created a software patch to LAMMPS that implements the correct heat flux calculation approach for 3- and 4-body potentials, based on the derivation by Torii et al. ( J. Chem. Phys. 2008 , 128 , 044504 ) Using two example systems, the error in the uncorrected code for many-body potential heat flux is shown to be significant and reaches nearly 100% of the many-body potential heat flux for the systems we studied; hence, the error of the total heat flux calculation is proportional to the fraction of the total heat flux transferred through the many-body potentials. This error may have consequences for thermal conductivities calculated using the Green-Kubo method or any NEMD method that uses the instantaneous heat flux. We recommend that all researchers using LAMMPS for heat flux calculations where significant heat is transferred via the many-body potentials adopt the corrected code.

Intelligent Selection of Metal-Organic Framework Arrays for Methane Sensing via Genetic Algorithms.

Gas sensor arrays, also called electronic noses, use many chemically diverse materials to adsorb and subsequently identify gas species in complex mixture environments. Ideally these materials should have maximally complementary adsorption profiles to achieve the best sensing performance, but in practice they are selected by trial-and-error. Thus current electronic noses do not achieve optimal detection. In this work, we employ metal-organic frameworks (MOFs) as sensing materials and leverage a genetic algorithm to identify optimal combinations of them for detecting methane leaks in air. We build on our previously reported computational design methodology, which ranked MOF arrays by their Kullback-Liebler divergence (KLD) values for probabilistically describing the concentrations of each gas species in an unknown mixture. We ran the genetic algorithm to find optimal MOF arrays of various sizes when selecting from a library of 50 different MOF materials. The genetic algorithm was able to accurately predict the best arrays of any desired size when compared to brute-force screening. Thus, this search optimization can be integrated into the efficient design of MOF-based electronic noses.

High-Pressure Methane Adsorption in Porous Lennard-Jones Crystals.

Decades of research have yet to yield porous adsorbents that meet the U.S. Department of Energy's methane storage targets. To better understand why, we calculated high-pressure methane adsorption in 600 000 randomly generated porous crystals, or "pseudomaterials," using atomistic grand canonical Monte Carlo (GCMC) simulations. These pseudomaterials were periodic configurations of Lennard-Jones spheres whose coordinates in space, along with corresponding well depths and radii, were all chosen at random. GCMC simulations were performed for pressures of 35 and 65 bar at a temperature of 298 K. Methane adsorption was compared for all materials against a range of other properties: average well depths and radii, number density, helium void fraction, and volumetric surface area. The results reveal structure-property relationships that resemble those previously observed for metal-organic frameworks and other porous materials. We contend that our computational methodology can be useful for discovering useful structure-property relationships related to gas adsorption without requiring experimentally accessible structural data.