Bimetallic Two‐Dimensional Metal–Organic Frameworks for the Chemiresistive Detection of Carbon Monoxide

Aykanat, Aylin; Meng, Zheng; Stolz, Robert M.; Morrell, Colin T.; Mirica, Katherine A.

doi:10.1002/ange.202113665

Cited by 7 publications

(2 citation statements)

References 80 publications

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“…Common examples of recognition elements are metal oxides [11], polymers [12], carbon nanotubes [13], and metalorganic frameworks [14]. The analyte adsorbs onto the recognition element and, through either physical or chemical interactions, alters some property of it (e.g., mass [15], electrical resistance [16], or color [17]). This change in property of the recognition element is converted by a transducer (e.g., a quartz crystal microbalance [18] in the case of a gravimetric sensor) into an electrical signal that is subsequently used to infer the concentration of the analyte in the gas.…”

Section: Introductionmentioning

confidence: 99%

A toy model of a catalytic filter in series with a gas sensor

Fabusola

Noh

Simon

2022

Preprint

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The cross-sensitivity of a gas sensor can be mitigated by installing a catalytic filter upstream. The objective of the filter is to convert interferents into species that interact weakly with the recognition element of the sensor. Mathematical models may be useful for optimizing the design parameters of the catalytic filter. Particularly, if the catalyst is not perfectly selective for the interferent over the analyte, we hypothesize the existence of an optimal residence time of the gas in the filter. Short residence times allow too much interferent to reach the sensor and corrupt its response, while long residence times degrade too much of the analyte, diminishing the signal-to-noise ratio. Herein, we develop a toy mathematical and probabilistic model of a catalytic filter and gas sensor in series. We model (a) the catalytic filter as an isothermal, packed-bed reactor that decomposes the interferent and analyte with first-order kinetics and reactant-selectivity for the interferent and (b) the cross-sensitive gas sensor as gravimetric, producing a response with contributions from the analyte and interferent, governed by the competitive Langmuir adsorption model. Under distributions of (a) concentrations of interferent and analyte in the sensing environment and (b) measurement noise corrupting the response of the sensor, we simulate deployment of the model catalytic filter-gas sensor, where the objective is to accurately predict the concentration of the analyte in the gas phase from the response of the sensor. The performance of the catalytic filter-gas sensor is measured by the expected error in the predicted concentration of the analyte. Indeed, our toy model shows an optimal residence time of gas in the catalytic filter, which depends on the reactant-selectivity of the catalyst. While just a caricature of a catalytic filter-gas sensor, our toy model illustrates the utility of mathematical and probabilistic models for optimizing their design parameters.

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Section: Introductionmentioning

confidence: 99%

A toy model of a catalytic filter in series with a gas sensor

Fabusola

Noh

Simon

2022

Preprint

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“…T he development model of the fossil-energy economy in today's world has led to the uncontrolled emission of large amounts of gaseous pollutants such as nitrides, sulfides, carbides, and volatile organic compounds, resulting in serious environmental pollution problems. 1 Among them, nitrogen dioxide, as a major contributor to photochemical smog and acid rain, poses significant threats to the ecological environment. Moreover, it can lead to respiratory system disorders in humans, such as bronchitis, pulmonary edema, and asthma.…”

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confidence: 99%

Metalloporphyrin-Based Metal–Organic Frameworks for the Ultrasensitive Chemiresistive Detection of NO₂: Effect of the Central Metal on Tuning the Sensing Performance

Zhang,

Liu,

Sun

et al. 2023

ACS Sens.

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The highly sensitive and selective detection of trace hazardous gases at room temperature is very promising for health protection and environmental safety. Herein, chemiresistive sensors for NO 2 were fabricated based on self-assembled films of the four metalloporphyrin (MPor)-based metal−organic frameworks PCN-222-M (M = Cu, Ni, Co, Fe) by the quasi-Langmuir−Shafer method. It is found that the relative responses of the four PCN-222-M films are linearly related to the NO 2 concentration, and the PCN-222-Cu possessed an unprecedented high response to NO 2 with a sensitivity of 2209% ppm −1 in the 4−20 ppb range and a low limit of detection (LOD) of 0.93 ppb, achieving the best performance reported so far for NO 2 detection at room temperature. Meanwhile, PCN-222-Ni showed the fastest recovery among the four PCN-222-M films, which can be used for the rapid detection of NO 2 . Excellent reproducibility, stability, selectivity, and moisture resistance are shown for both Combining the experimental study and density functional theory (DFT) calculation, the essential roles of MPor units and the MPor/Zr 6 cluster hybrid material in tuning the Fermi level and the electron transfer between PCN-222-M and NO 2 were further proved. These were less considered topics in previous studies on MOFs. This work explores the application of MPor-based MOFs in gas sensing by selecting appropriate MPor units, thus providing guidance for the development of MOF-based chemiresistive sensors.

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ChemFET Anion Sensor Based on MOF Nanoparticles

Banning,

Davenport,

Lakanen

et al. 2024

ChemPlusChem

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Nanoparticles of metal‐organic frameworks (nanoMOFs) possess the unusual combination of both internal and external surfaces. While internal surfaces have been the focus of fundamental and applications‐based MOF studies, the chemistry of the external surfaces remains scarcely understood. Herein we report that specific ion interactions with nanoparticles of Cu(1,2,3‐triazolate)2 (Cu(TA)2) resemble the Hofmeister behavior of proteins and the supramolecular chemistry of synthetic macromolecules. Inspired by these anion‐selective interactions, we tested the performance of Cu(TA)2 nanoparticles as chemical field effect transistor (ChemFET) anion sensors. Rather than size‐based selectivity, the detection limits of the devices exhibit a Hofmeister trend, with the greatest sensitivity towards anions perchlorate, iodide, and nitrate. These results highlight the importance of the pore‐based supramolecular interactions, rather than localized donor‐acceptor pairs, in designing MOF‐based technologies.

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Bimetallic Two‐Dimensional Metal–Organic Frameworks for the Chemiresistive Detection of Carbon Monoxide

Cited by 7 publications

References 80 publications

A toy model of a catalytic filter in series with a gas sensor

A toy model of a catalytic filter in series with a gas sensor

Metalloporphyrin-Based Metal–Organic Frameworks for the Ultrasensitive Chemiresistive Detection of NO₂: Effect of the Central Metal on Tuning the Sensing Performance

ChemFET Anion Sensor Based on MOF Nanoparticles

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Bimetallic Two‐Dimensional Metal–Organic Frameworks for the Chemiresistive Detection of Carbon Monoxide

Cited by 7 publications

References 80 publications

A toy model of a catalytic filter in series with a gas sensor

A toy model of a catalytic filter in series with a gas sensor

Metalloporphyrin-Based Metal–Organic Frameworks for the Ultrasensitive Chemiresistive Detection of NO2: Effect of the Central Metal on Tuning the Sensing Performance

ChemFET Anion Sensor Based on MOF Nanoparticles

Contact Info

Product

Resources

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Metalloporphyrin-Based Metal–Organic Frameworks for the Ultrasensitive Chemiresistive Detection of NO₂: Effect of the Central Metal on Tuning the Sensing Performance