Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
The continuous carbon dioxide (CO ) gas emissions associated with fossil fuel production, valorization, and utilization are serious challenges to the global environment. Therefore, several developments of CO capture, separation, transportation, storage, and valorization have been explored. Consequently, we documented a comprehensive review of the most advanced strategies adopted in metal-organic frameworks (MOFs) for CO capture and separation. The enhancements in CO capture and separation are generally achieved due to the chemistry of MOFs by controlling pore window, pore size, open-metal sites, acidity, chemical doping, post or pre-synthetic modifications. The chemistry of defects engineering, breathing in MOFs, functionalization in MOFs, hydrophobicity, and topology are the salient advanced strategies, recently reported in MOFs for CO capture and separation. Therefore, this review summarizes MOF materials' advancement explaining different strategies and their role in the CO mitigations. The study also provided useful insights into key areas for further investigations.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/tcr.202100230 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
HO and CO Sorption in Ion-Exchange Sorbents: Distinct Interactions in Amine Versus Quaternary Ammonium Materials.
ACS Appl Mater Interfaces
September 2025
The Steve Sanghi College of Engineering, Mechanical Engineering, Northern Arizona University, Flagstaff, Arizona 86011, United States.
This study investigates the HO and CO sorption behavior of two chemically distinct polystyrene-divinylbenzene-based ion exchange sorbents: a primary amine and a permanently charged strong base quaternary ammonium (QA) group with (bi)carbonate counter anions. We compare their distinct interactions with HO and CO through simultaneous thermal gravimetric, calorimetric, gas analysis, and molecular modeling approaches to evaluate their performance for dilute CO separations like direct air capture. Thermal and hybrid (heat + low-temperature hydration) desorption experiments demonstrate that the QA-based sorbent binds both water and CO more strongly than the amine counterparts but undergoes degradation at moderate temperatures, limiting its compatibility with thermal swing regeneration.
View Article and Find Full Text PDFDeep-learning-enabled high-throughput Screening of MXene photocatalysts for hydrogen production.
Nanoscale
September 2025
School of Materials Science and Engineering, Beihang University, Beijing 100191, China.
The challenge of photocatalytic hydrogen production has motivated a targeted search for MXenes as a promising class of materials for this transformation because of their high mobility and high light absorption. High-throughput screening has been widely used to discover new materials, but the relatively high cost limits the chemical space for searching MXenes. We developed a deep-learning-enabled high-throughput screening approach that identified 14 stable candidates with suitable band alignment for water splitting from 23 857 MXenes.
View Article and Find Full Text PDFRapid label-free identification of seven bacterial species using microfluidics, single-cell time-lapse phase-contrast microscopy, and deep learning-based image and video classification.
PLoS One
September 2025
Department of Information Technology, Uppsala University, Uppsala, Sweden.
For effective treatment of bacterial infections, it is essential to identify the species causing the infection as early as possible. Current methods typically require hours of overnight culturing of a bacterial sample and a larger quantity of cells to function effectively. This study uses one-hour phase-contrast time-lapses of single-cell bacterial growth collected from microfluidic chip traps, also known as a "mother machine".
View Article and Find Full Text PDFA Novel Entropy Metric for Unified Analysis of Temporal, Spatial, and Spectral EEG Properties.
IEEE Trans Biomed Eng
September 2025
Signal complexity analysis plays a crucial role in biomedical research, particularly in electroencephalography (EEG), for early disease diagnosis and cognitive monitoring. However, traditional entropy-based methods lack robustness, suffer from limitations such as sensitivity to noise, and fail to capture the multi-frequency structure of brain signals. To address these challenges, this study introduces Multivariate Multiscale Multi-Frequency Entropy (M3FrEn), a novel complexity metric that simultaneously incorporates multiscale dynamics, multichannel dependencies, and multi-frequency structure into a unified entropy-based framework.
View Article and Find Full Text PDFSimulations of Implanted Glutamate Sensor Performance in Three Spatial Dimensions and Time Inform Sensor Design and Data Interpretation.
ACS Chem Neurosci
September 2025
Chemical and Biomolecular Engineering Dept, University of California, Los Angeles, Los Angeles, California 90095, United States.
Simulations in three dimensions and time provide guidance on implantable, electroenzymatic glutamate sensor design; relative placement in planar sensor arrays; feasibility of sensing synaptic release events; and interpretation of sensor data. Electroenzymatic sensors based on the immobilization of oxidases on microelectrodes have proven valuable for the monitoring of neurotransmitter signaling in deep brain structures; however, the complex extracellular milieu featuring slow diffusive mass transport makes rational sensor design and data interpretation challenging. Simulations show that miniaturization of the disk-shaped device size below a radius of ∼25 μm improves sensitivity, spatial resolution, and the accuracy of glutamate concentration measurements based on calibration factors determined .
View Article and Find Full Text PDF