separation membranes
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Desalination ◽  
2022 ◽  
Vol 526 ◽  
pp. 115519
Yang Xu ◽  
Huawen Peng ◽  
Hao Luo ◽  
Qi Zhang ◽  
Zhitian Liu ◽  

Membranes ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 87
Ruben Hammerstein ◽  
Tim Schubert ◽  
Gerd Braun ◽  
Tobias Wolf ◽  
Stéphan Barbe ◽  

In this work, supported cellulose acetate (CA) mixed matrix membranes (MMMs) were prepared and studied concerning their gas separation behaviors. The dispersion of carbon nanotube fillers were studied as a factor of polymer and filler concentrations using the mixing methods of the rotor–stator system (RS) and the three-roll-mill system (TRM). Compared to the dispersion quality achieved by RS, samples prepared using the TRM seem to have slightly bigger, but fewer and more homogenously distributed, agglomerates. The green γ-butyrolactone (GBL) was chosen as a polyimide (PI) polymer-solvent, whereas diacetone alcohol (DAA) was used for preparing the CA solutions. The coating of the thin CA separation layer was applied using a spin coater. For coating on the PP carriers, a short parameter study was conducted regarding the plasma treatment to affect the wettability, the coating speed, and the volume of dispersion that was applied to the carrier. As predicted by the parameter study, the amount of dispersion that remained on the carriers decreased with an increasing rotational speed during the spin coating process. The dry separation layer thickness was varied between about 1.4 and 4.7 μm. Electrically conductive additives in a non-conductive matrix showed a steeply increasing electrical conductivity after passing the so-called percolation threshold. This was used to evaluate the agglomeration behavior in suspension and in the applied layer. Gas permeation tests were performed using a constant volume apparatus at feed pressures of 5, 10, and 15 bar. The highest calculated CO2/N2 selectivity (ideal), 21, was achieved for the CA membrane and corresponded to a CO2 permeability of 49.6 Barrer.

2022 ◽  
Vol 8 (1) ◽  
Ohchan Kwon ◽  
Minsu Kim ◽  
Eunji Choi ◽  
Jun Hyuk Bae ◽  
Sungmi Yoo ◽  

CCS Chemistry ◽  
2022 ◽  
pp. 1-11
Mingxin Zhang ◽  
Haitao Yu ◽  
Qin Zou ◽  
Zi-Ang Li ◽  
Yuyan Lai ◽  

2022 ◽  
pp. 185-208
Asif Jamil ◽  
Muhammad Latif ◽  
Alamin Idris Abdulgadir ◽  
Danial Qadir ◽  
Hafiz Abdul Mannan

2022 ◽  
pp. 298-341
Won Jun Jo ◽  
Hongna Zhang ◽  
Georgios Katsoukis ◽  
Heinz Frei

2022 ◽  
Tieyi Lu ◽  
Wen Guo ◽  
Datar M. Prathamesh ◽  
Yue Xin ◽  
E. Neil G. Marsh ◽  

Protein adsorption on surfaces greatly impacts many applications such as biomedical materials, anti-biofouling coatings, bio-separation membranes, biosensors, and antibody protein drugs etc. For example, protein drug adsorption on widely used...

2021 ◽  
Vol 0 (0) ◽  
Grandprix T. M. Kadja ◽  
Nurul F. Himma ◽  
Nicholaus Prasetya ◽  
Afriyanti Sumboja ◽  
Martin Z. Bazant ◽  

Abstract The development of highly efficient separation membranes utilizing emerging materials with controllable pore size and minimized thickness could greatly enhance the broad applications of membrane-based technologies. Having this perspective, many studies on the incorporation of nanosheets in membrane fabrication have been conducted, and strong interest in this area has grown over the past decade. This article reviews the development of nanosheet membranes focusing on two-dimensional materials as a continuous phase, due to their promising properties, such as atomic or nanoscale thickness and large lateral dimensions, to achieve improved performance compared to their discontinuous counterparts. Material characteristics and strategies to process nanosheet materials into separation membranes are reviewed, followed by discussions on the membrane performances in diverse applications. The review concludes with a discussion of remaining challenges and future outlook for nanosheet membrane technologies.

2021 ◽  
Jason Yang ◽  
Lei Tao ◽  
Jinlong He ◽  
Jeffrey R. McCutcheon ◽  
Ying Li

Abstract Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research on membrane technologies, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine-learning (ML) implementation for the discovery of innovative polymers with ideal separation performance. Specifically, multitask ML models are trained on available experimental data to link polymer chemistry to gas permeabilities of He, H2, O2, N2, CO2, and CH4. We interpret the ML models and extract chemical heuristics for membrane design, through Shapley Additive exPlanations (SHAP) analysis. We then screen over nine million hypothetical polymers through our models and identify thousands of candidates that lie well above current performance upper bounds. Notably, we discover hundreds of never-before-seen ultrapermeable polymer membranes with O2 and CO2 permeability greater than 104 and 105 Barrer, respectively. These hypothetical polymers are capable of overcoming undesirable trade-off relationship between permeability and selectivity, thus significantly expanding the currently limited library of polymer membranes for highly efficient gas separations. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

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