Work

Organometallic Precursor‐Induced Gradient Architecture on Multilayer Nanoporous Graphene Membranes for Precise Organic Solvent Nanofiltration

Year: 2025
Type: article
Abstract: Tuning the pore and interlayer structure of multilayer graphene is crucial for achieving precise molecular separation in organic solvent nanofiltration (OSN). Here, an advanced organometallic precursor‐driven deposition strategy is presented that enables gradient‐controlled surface modification of multilayer nanoporous graphene membranes, resulting in finely tuned selectivity and structure. Highly porous and crystalline graphene is first prepared through thermal activation, followed by microwave‐assisted reduction. However, this process generated non‐selective defects and expanded interlayer spacing under solvated conditions, resulting in a high molecular weight cut‐off (MWCO). Subsequently, the growth of the alumina layer narrowed surface pores and cross‐linked top graphene layers, forming a nanoscopic gradient coating from the top surface. This alumina deposition reduced the MWCO from 800 to 640 Da while retaining high ethanol permeance (136.5 LMH bar −1 ), surpassing the performance upper bound of previously reported 2D‐material‐based OSN membranes. Additionally, concentration‐dependent separation is observed in binary mixtures: selective rejection occurred even below the MWCO at dilute concentrations, whereas solute–solute interactions dominated at higher concentrations. This work offers a scalable and precise approach to tailoring 2D membranes for high‐performance OSN applications.
Institution: Yonsei University
Language: English
Open Access status: hybrid
Estimated APC paid: $5,790
OpenAlex ID: W4416536693
FWCI: 0.255
Cites: 44
Cited by: 1
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