Synthetic control of correlated disorder in UiO-66 frameworks

High-precision Helicobacter pylori infection diagnosis using a dual-element multimodal gas sensor array

Helicobacter pylori (H. pylori) is a globally widespread bacterial infection. Early diagnosis of this infection is vital for public and individual health. Prevalent diagnosis methods like the isotope 13C or 14C labelled urea breath test (UBT) are not convenient and may do harm to the human body. The use of cross-response gas sensor arrays (GSAs) is an alternative way for label-free detection of metabolite changes in exhaled breath (EB). However, conventional GSAs are complex to prepare, lack reliability, and fail to discriminate subtle changes in EB due to the use of numerous sensing elements and single dimensional signal. This work presents a dual-element multimodal GSA empowered with multimodal sensing signals including conductance (G), capacitance (C), and dissipation factor (DF) to improve the ability for gas recognition and H. pylori-infection diagnosis. Sensitized by poly(diallyldimethylammonium chloride) (PDDA) and the metal-organic framework material NH2-UiO66, the dual-element graphene oxide (GO)-composite GSAs exhibited a high specific surface area and abundant adsorption sites, resulting in high sensitivity, repeatability, and fast response/recovery speed in all three signals. The multimodal sensing signals with rich sensing features allowed the GSA to detect various physicochemical properties of gas analytes, such as charge transfer and polarization ability, enhancing the sensing capabilities for gas discrimination. The dual-element GSA could differentiate different typical standard gases and non-dehumidified EB samples, demonstrating the advantages in EB analysis. In a case-control clinical study on 52 clinical EB samples, the diagnosis model based on the multimodal GSA achieved an accuracy of 94.1%, a sensitivity of 100%, and a specificity of 90.9% for diagnosing H. pylori infection, offering a promising strategy for developing an accurate, non-invasive and label-free method for disease diagnosis.

Metal-Organic Frameworks for Dual Photo-Oxidation and Capture of Arsenic from Water

Despite rapid technological progress, heavy metal water pollution, and particularly arsenic contamination, remains a significant global challenge. In addition, the stabilization of trivalent arsenic as neutral arsenite (AsIII) species hinders its removal by conventional sorbents. While adsorption of anionic arsenate (AsV) species is in principle more feasible, there are only few adsorbents capable of adsorbing both forms of arsenic. In this work, we explore the potential of two well-known families of Metal-Organic Frameworks (MOFs), UiO-66 and MIL-125, to simultaneously adsorb and photo-oxidize arsenic species from water. Our results demonstrate that the formation of AsV ions upon light irradiation promotes the subsequent adsorption of AsIII species. Thus, we propose the combined utilization of photocatalysis and adsorption with Metal-Organic Framework photocatalysts for water remediation purposes.

Evaluating the Role of Functional Groups in the Selective Capture of Ag(I) onto UiO-66-Type Metal-Organic Frameworks

UiO-66-type metal-organic frameworks have been considered as promising adsorbents for capturing Ag(I) from wastewater. However, uncertainties persist regarding the specific absorptivity of individual functional groups to the UiO-66 framework structure. In this study, UiO-66-type metal-organic frameworks (UiO-66-X), featuring diverse functional groups (X = -(OH)2, -(COOH)2, -NO2, -NH2, -SO3H, -(SH)2), were synthesized in situ for Ag(I) capture. The findings revealed that functionalization significantly enhanced the adsorption capacity of Ag(I). Notably, quantitative analysis showed that 1 mol of -SH functional group onto the UiO-66 framework structure can adsorb 0.73 mol of Ag(I) ions, surpassing those of -COOH, -OH, -NH2, -SO3H, and -NO2 by 2.4-, 3.5-, 3.8-, 9.1-, and 24.3-fold, respectively. This represents the first assessment of the adsorption capacity of functionalized UiO-66 for Ag(I) based on each effective functional group, addressing limitations in traditional unit mass calculations. Further, the adsorption mechanism of UiO-66-X for selectively capturing Ag(I) was elucidated through experimental and theoretical analyses. Additionally, selectivity and practical applications confirm that UiO-66-(SH)2 exhibits strong anti-interference ability, whether in natural water bodies with complex compositions or in industrial wastewater under harsh conditions. We anticipate that this study will enhance our understanding of structure-performance dependencies of multivariate MOFs for designing novel adsorbents for Ag(I) capture.