The development of porous metal−organic framework (MOF) solids displaying efficient separation and purification of acetylene is of cardinal significance but challenging in the chemical industry. Among the reported MOFs for such a purpose, there usually exists an issue associated with trade-off between the uptake capacity and adsorption selectivity. In this work, we employed an N-oxide-functionalized dicarboxylate ligand to successfully construct under suitable solvothermal conditions a dicopper paddlewheel-based MOF featuring two different types of nanocages and rich open oxygen atoms on the channel surface. These structural features endow the material with the promising potential for C 2 H 2 recovery from CO 2 and CH 4 at ambient conditions with impressive adsorption selectivity of C 2 H 2 over CO 2 and CH 4 as well as considerable C 2 H 2 capture capacity, which have been validated by isotherm measurements, ideal adsorbed solution theory calculations, and breakthrough experiments. Furthermore, molecular modeling studies revealed the vital role that the oxygen atoms coming from both N-oxide moieties and carboxylate groups play in selectively recognizing C 2 H 2 over CO 2 and CH 4 . KEYWORDS: metal−organic frameworks, C 2 H 2 separation and purification, C 2 H 2 /CO 2 separation, gas separation, N-oxide
Two NbO-type MOFs with N-oxide functionality immobilized in the pore surface display significantly enhanced C2H2/CH4 and CO2/CH4 separation performance.
An aromatic-rich chloride-embedded nanocage-based MOF displayed an unusual adsorption relationship towards C2 hydrocarbons, with the potential for C2H4 separation and purification application.
An NbO-type MOF based on an aminopyridine-heterobifunctionalized diisophthalate linker was synthesized, displaying markedly enhanced C2H2 and CO2 adsorption over CH4 compared to its parent compound.
Solvothermal assembly of copper(II)
cations and 5-(pyridine-3-yl)isophthalate
linkers bearing different position-substituted methyl groups afforded
four ligand-induced metal–organic framework (MOF) isomers as
a platform for investigating diverse selective gas adsorption properties
and understanding the positional effect of methyl functionality. Single-crystal
X-ray diffraction (SCXRD) analyses showed that, when the methyl substituent
is at the para position with respect to the pyridinic
N atom, the resultant framework compound ZJNU-27 features
an
eea
-type topology, while the other
three solids possess an isoreticular structure with an
rtl
-type topology when the methyl group is situated
at the other positions. As revealed by N2 physi-adsorption
measurements at 77 K, they exhibit moderate specific surface areas
ranging from 584 to 1182 m2 g–1 and distinct
degrees of framework flexibility, which are heavily dependent on the
methyl position. Comprehensive gas adsorption studies show that they
are capable of effectively separating three pairs of binary gas mixtures
including C2H2–CH4, CO2–CH4, and CO2–N2 couples. Moreover, their uptake capacities and adsorption selectivities
can be tailored by altering the methyl position. In addition, their
framework hydro-stability is also influenced by the methyl position.
Compared to ZJNU-27 and ZJNU-28, ZJNU-26 and ZJNU-29 exhibit poorer stability against H2O, although the methyl group is more close to inorganic secondary
building units (SBUs), which are believed to originate from the steric
effect of the methyl group. Overall, the four MOFs display the methyl
position-dependent network architectures, framework flexibilities,
and selective gas adsorption properties as well as hydrostabilities.
The findings observed in this work not only demonstrate the importance
of the positional effect of the functional group but also highlight
that engineering the substituent position is a potential strategy
for achieving the modulation of MOF structures and properties.
A substituent-induced ligand conformation regulation strategy was employed to tailor the structures and gas adsorption properties of copper-bent diisophthalate frameworks.
Lung cancer remains the leading cause of cancer death globally, with lung adenocarcinoma (LUAD) being its most prevalent subtype. Due to the heterogeneity of LUAD, patients given the same treatment regimen may have different responses and clinical outcomes. Therefore, identifying new subtypes of LUAD is important for predicting prognosis and providing personalized treatment for patients. Pyroptosis-related genes play an essential role in anticancer, but there is limited research investigating pyroptosis in LUAD. In this study, 33 pyroptosis gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. By bioinformatics and machine learning analyses, we identified novel subtypes of LUAD based on 10 pyroptosis-related genes and further validated them in the GEO dataset, with machine learning models performing up to an AUC of 1 for classifying in GEO. A web-based tool was established for clinicians to use our clustering model (http://www.aimedicallab.com/tool/aiml-subphe-luad.html). LUAD patients were clustered into 3 subtypes (A, B, and C), and survival analysis showed that B had the best survival outcome and C had the worst survival outcome. The relationships between pyroptosis gene expression and clinical characteristics were further analyzed in the three molecular subtypes. Immune profiling revealed significant differences in immune cell infiltration among the three molecular subtypes. GO enrichment and KEGG pathway analyses were performed based on the differential genes of the three subtypes, indicating that differentially expressed genes (DEGs) were involved in multiple cellular and biological functions, including RNA catabolic process, mRNA catabolic process, and pathways of neurodegeneration-multiple diseases. Finally, we developed an 8-gene prognostic model that accurately predicted 1-, 3-, and 5-year overall survival. In conclusion, pyroptosis-related genes may play a critical role in LUAD, and provide new insights into the underlying mechanisms of LUAD.
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