The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Two-dimensional membrane and three-dimensional bulk aerogel materials via top-down wood nanotechnology for multibehavioral and reusable oil/water separation
Abstract
Abstract Traditional oil/water separation materials can be divided into two types on the basis of their separation behavior: filtration materials (e.g., meshes, textiles, membranes, etc.) and absorption materials (e.g., sponges, foams, and aerogels). Both types of materials have advantages and disadvantages. Combining the filtration and absorption functions into one and the same material for oil/water separation applications presents a challenge. Prompted by the highly oriented porous structures and anisotropic architectures of wood and its hygro-responsive characteristic, two-dimensional (2D) membrane and three-dimensional (3D) bulk aerogel materials with water-responsive shape memory function, anisotropy, robustness, and superhydrophobicity are prepared using top-down wood nanotechnology for multibehavioral (absorption and filtration) and reusable oil/water separation. Wood aerogel is obtained by partially removing hemicellulose and lignin. Further, it is superhydrophobically treated using a polydimethylsiloxane (PDMS)/curing agent system. As-prepared wood aerogel/PDMS bulk materials possess high oil absorption capacity (about 20 g/g) and can be reused because of their fast water-responsive shape memory function. The prepared wood aerogel/PDMS membrane materials can efficiently separate oil/water mixtures with high separation efficiency (99.5%) and flux (around 2.25 × 104 L/m2·h) by only the driving force of gravity. Top-down wood nanotechnology is low-cost, facile, scalable, green, and efficient, exhibiting potential for application in multibehavioral oil/water separation and ability to handle industrial oily wastewater and oil spillage accidents.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Bioinspired Surfaces with Superwettability: New Insight on Theory, Design, and Applications
Wang, S., Liu, K., Yao, X., & Jiang, L. (2015) · Chemical Reviews · doi:10.1021/cr400083y · Cited by 1,646
Wood-based nanotechnologies toward sustainability
Jiang, F., Li, T., Li, Y., Zhang, Y., Gong, A., Dai, J., Hitz, E., Luo, W., & Hu, L. (2018) · Advanced Materials · doi:10.1002/adma.201703453 · Cited by 599
Bioinspired wood nanotechnology for functional materials
Berglund, L. A., & Burgert, I. (2018) · Advanced Materials · doi:10.1002/adma.201704285 · Cited by 518
Rapidly switchable water-sensitive shape-memory cellulose/elastomer nano-composites
Zhu, Y., Hu, J., Luo, H., Young, R. J., Deng, L., Zhang, S., Fan, Y., & Ye, G. (2012) · Soft Matter · doi:10.1039/c2sm07035a · Cited by 208
Self-citationLu, H., Liu, Y., Leng, J., & Du, S. (2009) · Smart Materials and Structures · doi:10.1088/0964-1726/18/8/085003 · Cited by 98
Chen, S., Mo, F., Stadler, F. J., Chen, S., Ge, Z., & Zhuo, H. (2015) · Journal of Materials Chemistry B · doi:10.1039/c5tb01075f · Cited by 56
Metadata
- Authors
- Wang, K., Liu, X., Tan, Y., Zhang, W., Zhang, S., & Li, J.
- Venue
- Chemical Engineering Journal
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 371
- Pages
- 769-780
- ISSN
- 1385-8947 (ISSN-L)
- OpenAlex
- W2940223880
- Cited by
- 238
- References
- 6
- FWCI
- 7.55
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Two-dimensional membrane and three-dimensional bulk aerogel materials via top-down wood nanotechnology for multibehavioral and reusable oil/water separation. https://app.cochat.ai/papers/10.1016/j.cej.2019.04.108
- The paper
- Wang, K., Liu, X., Tan, Y., Zhang, W., Zhang, S., & Li, J. (2019). Two-dimensional membrane and three-dimensional bulk aerogel materials via top-down wood nanotechnology for multibehavioral and reusable oil/water separation. Chemical Engineering Journal. https://doi.org/10.1016/j.cej.2019.04.108
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
