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- Li, Xiaoting, et al.
(författare)
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"Mix-Then-On-Demand-Complex" : In Situ Cascade Anionization and Complexation of Graphene Oxide for High-Performance Nanofiltration Membranes
- 2021
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Ingår i: ACS Nano. - : American Chemical Society (ACS). - 1936-0851 .- 1936-086X. ; 15:3, s. 4440-4449
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Tidskriftsartikel (refereegranskat)abstract
- Assembling two-dimensional (2D) materials by polyelectrolyte often suffers from inhomogeneous microstructures due to the conventional mixing-and-simultaneous-complexation procedure (mix-and-complex) in aqueous solution. Herein a mix-then-on-demand-complex concept via on-demand in situ cascade anionization and ionic complexation of 2D materials is raised that drastically improves structural order in 2D assemblies, as exemplified by classical graphene oxide (GO)-based ultrathin membranes. Specifically, in dimethyl sulfoxide, the carboxylic acid-functionalized GO sheets (COOH-GOs) were mixed evenly with a cationic poly(ionic liquid) (PIL) and upon filtration formed a well-ordered layered composite membrane with homogeneous distribution of PIL chains in it; next, whenever needed, it was alkali-treated to convert COOH-GO in situ into its anionized state COO--GO that immediately complexed ionically with the surrounding cationic PIL chains. This mix-then-on-demand-complex concept separates the ionic complexation of GO and polyelectrolytes from their mixing step. By synergistically combining the PIL-induced hydrophobic confinement effect and supramolecular interactions, the as-fabricated nanofiltration membranes carry interface transport nanochannels between GO and PIL, reaching a high water permeability of 96.38 L m(-2) h(-1) bar(-1) at a maintained excellent dye rejection 99.79% for 150 h, exceeding the state-of-the-art GO-based hybrid membranes. The molecular dynamics simulations support the experimental data, confirming the interface spacing between GO and PIL as the water transport channels.
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| 2. |
- Song, Zhaoliang, et al.
(författare)
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High potential of stable carbon sequestration in phytoliths of China's grasslands
- 2022
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Ingår i: Global Change Biology. - : John Wiley & Sons. - 1354-1013 .- 1365-2486. ; 28:8, s. 2736-2750
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Tidskriftsartikel (refereegranskat)abstract
- Phytolith carbon (C) sequestration plays a key role in mitigating global climate change at a centennial to millennial time scale. However, previous estimates of phytolith-occluded carbon (PhytOC) storage and potential in China's grasslands have large uncertainties mainly due to multiple data sources. This contributes to the uncertainty in predicting long-term C sequestration in terrestrial ecosystems using Earth System Models. In this study, we carried out an intensive field investigation (79 sites, 237 soil profiles [0-100 cm], and 61 vegetation assessments) to quantify PhytOC storage in China's grasslands and to better explore the biogeographical patterns and influencing factors. Generally, PhytOC production flux and soil PhytOC density in both the Tibetan Plateau and the Inner Mongolian Plateau had a decreasing trend from the Northeast to the Southwest. The aboveground PhytOC production rate in China's grassland was 0.48 x 10(6) t CO2 a(-1), and the soil PhytOC storage was 383 x 10(6) t CO2. About 45% of soil PhytOC was stored in the deep soil layers (50-100 cm), highlighting the importance of deep soil layers for C stock assessments. Importantly, the Tibetan Plateau had the greatest contribution (more than 70%) to the PhytOC storage in China's grasslands. The results of multiple regression analysis indicated that altitude and soil texture significantly influenced the spatial distribution of soil PhytOC, explaining 78.1% of the total variation. Soil phytolith turnover time in China's grasslands was mainly controlled by climatic conditions, with the turnover time on the Tibetan Plateau being significantly longer than that on the Inner Mongolian Plateau. Our results offer more accurate estimates of the potential for phytolith C sequestration from ecological restoration projects in degraded grassland ecosystems. These estimates are essential to parameterizing and validating global C models.
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