Tuning Metal–Organic Frameworks with Open-Metal Sites and Its Origin for Enhancing CO₂ Affinity by Metal Substitution

Reducing anthropogenic carbon emission is a problem that requires immediate attention. Metal–organic frameworks (MOFs) have emerged as a promising new materials platform for carbon capture, of which Mg-MOF-74 offers chemospecific affinity toward CO₂ because of the open Mg sites. Here we tune the binding affinity of CO₂ for M-MOF-74 by metal substitution (M = Mg, Ca, and the first transition metal elements) and show that Ti- and V-MOF-74 can have an enhanced affinity compared to Mg-MOF-74 by 6–9 kJ/mol. Electronic structure calculations suggest that the origin of the major affinity trend is the local electric field effect of the open metal site that stabilizes CO₂, but forward donation from the lone-pair electrons of CO₂ to the empty d-levels of transition metals as in a weak coordination bond makes Ti and V have an even higher binding strength than Mg, Ca, and Sc

Correction and Addition to “Tuning Metal–Organic Frameworks with Open-Metal Sites and Its Origin for Enhancing CO₂ Affinity by Metal Substitution”

Correction and Addition to “Tuning Metal–Organic Frameworks with Open-Metal Sites and Its Origin for Enhancing CO₂ Affinity by Metal Substitution

Highly Efficient Catalytic Cyclic Carbonate Formation by Pyridyl Salicylimines

Cyclic carbonates as industrial commodities offer a viable nonredox carbon dioxide fixation, and suitable heterogeneous catalysts are vital for their widespread implementation. Here, we report a highly efficient heterogeneous catalyst for CO₂ addition to epoxides based on a newly identified active catalytic pocket consisting of pyridine, imine, and phenol moieties. The polymeric, metal-free catalyst derived from this active site converts less-reactive styrene oxide under atmospheric pressure in quantitative yield and selectivity to the corresponding carbonate. The catalyst does not need additives, solvents, metals, or co-catalysts, can be reused at least 10 cycles without the loss of activity, and scaled up easily to a kilogram scale. Density functional theory calculations reveal that the nucleophilicity of pyridine base gets stronger due to the conjugated imines and H-bonding from phenol accelerates the reaction forward by stabilizing the intermediate

Quantitative Proteomics Reveals Temporal Proteomic Changes in Signaling Pathways during BV2 Mouse Microglial Cell Activation

The development of systematic proteomic quantification techniques in systems biology research has enabled one to perform an in-depth analysis of cellular systems. We have developed a systematic proteomic approach that encompasses the spectrum from global to targeted analysis on a single platform. We have applied this technique to an activated microglia cell system to examine changes in the intracellular and extracellular proteomes. Microglia become activated when their homeostatic microenvironment is disrupted. There are varying degrees of microglial activation, and we chose to focus on the proinflammatory reactive state that is induced by exposure to such stimuli as lipopolysaccharide (LPS) and interferon-gamma (IFN-γ). Using an improved shotgun proteomics approach, we identified 5497 proteins in the whole-cell proteome and 4938 proteins in the secretome that were associated with the activation of BV2 mouse microglia by LPS or IFN-γ. Of the differentially expressed proteins in stimulated microglia, we classified pathways that were related to immune-inflammatory responses and metabolism. Our label-free parallel reaction monitoring (PRM) approach made it possible to comprehensively measure the hyper-multiplex quantitative value of each protein by high-resolution mass spectrometry. Over 450 peptides that corresponded to pathway proteins and direct or indirect interactors via the STRING database were quantified by label-free PRM in a single run. Moreover, we performed a longitudinal quantification of secreted proteins during microglial activation, in which neurotoxic molecules that mediate neuronal cell loss in the brain are released. These data suggest that latent pathways that are associated with neurodegenerative diseases can be discovered by constructing and analyzing a pathway network model of proteins. Furthermore, this systematic quantification platform has tremendous potential for applications in large-scale targeted analyses. The proteomics data for discovery and label-free PRM analysis have been deposited to the ProteomeXchange Consortium with identifiers and , respectively