Among the current CO2 capture technologies, membrane gas separation has many inherent advantages over other conventional techniques. However, fabricating gas separation membranes with both high CO2 permeance and high CO2/N2 selectivity, especially under wet conditions, is a challenge. In this study, sub-20-nm thick, layered graphene oxide (GO)-based hollow fiber membranes with grafted, brush-like CO2-philic agent alternating between GO layers are prepared by a facile coating process for highly efficient CO2/N2 separation under wet conditions. Piperazine, as an effective CO2-philic agent, is introduced as a carrier-brush into the GO nanochannels with chemical bonding. The membrane exhibits excellent separation performance under simulated flue gas conditions with CO2 permeance of 1,020 GPU and CO2/N2 selectivity as high as 680, demonstrating its potential for CO2 capture from flue gas. We expect this GO-based membrane structure combined with the facile coating process to facilitate the development of ultrathin GO-based membranes for CO2 capture.

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Extracellular antibiotic resistance genes (eARGs) are widespread in the environment and can genetically transform bacteria. This work examined the role of environmentally relevant nanoparticles (NPs) in regulating eARG bioavailability. eARGs extracted from antibiotic-resistant B. subtilis were incubated with nonresistant recipient B. subtilis cells. In the mixture, particle type (either humic acid coated nanoparticles (HASNPs) or their micron-sized counterpart (HASPs)), DNase I concentration, and eARG type were systematically varied. Transformants were counted on selective media. Particles decreased bacterial growth and eARG bioavailability in systems without nuclease. When DNase I was present (≥5 μg/mL), particles increased transformation via chromosomal (but not plasmid-borne) eARGs. HASNPs increased transformation more than HASPs, indicating that the smaller nanoparticle with greater surface area per volume is more effective in increasing eARG bioavailability. These results were also modeled via particle aggregation theory, which represented eARG–bacteria interactions as transport leading to collision, followed by attachment. Using attachment efficiency as a fitting factor, the model predicted transformant concentrations within 35% of experimental data. These results confirm the ability of NPs to increase eARG bioavailability and suggest that particle aggregation theory may be a simplified and suitable framework to broadly predict eARG uptake.

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