| 1. |
- Idris, Alamin, et al.
(författare)
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Effect of silane coupling agents on properties and performance of polycarbonate/silica MMMs
- 2019
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Ingår i: Polymer testing. - : Elsevier. - 0142-9418 .- 1873-2348. ; 73, s. 159-170
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Tidskriftsartikel (refereegranskat)abstract
- The choice of amine terminated silanes remain scarce although they have been used as coupling agents to enhance silica dispersion and interaction in polymer matrix. Functionalized silica particles were synthesized by co-condensing tetraethyl-orthosilicate with four types of silane agents in sol-gel process. These particles were characterized and incorporated into polycarbonate polymer matrix. The morphology, structure, thermal stability, mechanical strength and gas (N2, CH4, CO2) permeation properties of mixed matrix membranes (MMMs) were characterized by standard techniques. The functionalized silica particles were of various particle sizes and extent of functionalization. PC/Silica MMM produced by incorporating functionalized silica particles using (3-aminopropyl) trimethoxysilane exhibited better morphology. The corresponding MMM performance has improved (αCO2/N2 = 42.8 and αCO2/CH4 = 38) as compared to pure PC membrane (αCO2/N2 = 20.30 and αCO2/CH4 = 18.5) and other MMMs. Thus, low molecular weight single amine terminated silane agents are potential candidates for the development of PC/silica MMMs.
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| 2. |
- Idris, Alamin, et al.
(författare)
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Modified Bruggeman models for prediction of CO2 permeance in polycarbonate/silica nanocomposite membranes
- 2017
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Ingår i: The Canadian Journal of Chemical Engineering. - : John Wiley & Sons. - 0008-4034 .- 1939-019X. ; 95:12, s. 2398-2409
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Tidskriftsartikel (refereegranskat)abstract
- Abstract The polycarbonate membranes performances are improved by the incorporation of silica nanoparticles into the polymer matrix. Prepared PC/silica nanocomposite membranes with various silica content are considered and the experimental relative permeance of CO2 gas at 200 kPa (2 bar) feed pressure are used as reference in the predictions using the existing theoretical models such as Maxwell-Wagner-Sillar, Bruggeman, Lewis-Nielsen, Pal, and modified Pal models. TEM and BET analysis were used to characterize the silica nanoparticles; FESEM was used to characterize the morphology of the nanocomposite membranes. The TEM image of the silica nanoparticles reveals that the nanoparticles are mostly spherical. BET results reveal that the surface area and pore diameter of the silica nanoparticles are 618.8 m2/g and 0.28 nm, respectively. The existing models have resulted in poor predictions with errors AARE % of 26.52 to 28.02 %. Observation by FESEM image shows that the dispersed particles are surrounded by interfacial voids and rigidified polymer layer. Modified Bruggeman models that consider the interfacial volume show appreciable prediction with AARE 4.59 % being obtained with the pseudo-two-phase Bruggeman model. Moreover, when the model considered pseudo-three-phase morphology, the AARE % value reduced to 3.92 %. Thus, the contribution due to the interfacial rigidified layer was minimal.
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| 3. |
- Idris, Alamin, et al.
(författare)
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Polycarbonate/silica nanocomposite membranes : Fabrication, characterization, and performance evaluation
- 2017
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Ingår i: Journal of Applied Polymer Science. - : John Wiley & Sons. - 0021-8995 .- 1097-4628. ; 134:38, s. 1-18
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Tidskriftsartikel (refereegranskat)abstract
- ABSTRACT Polycarbonate/silica nanocomposite membranes at low silica loading were fabricated by solution blending and solvent evaporation technique. The functionalized silica nanoparticles used were synthesized by co-condensing hydrolyzed tetraethylorthosilicate with 3-aminopropyl trimethoxysilane in the sol–gel process. The membranes morphology, composition, surface, structure, thermal and mechanical properties were analyzed by the standard characterization techniques. The gas permeation tests were conducted in four-channel permeation cells. Field emission scanning electron microscopy results reveal that membranes above 3 wt % silica content formed distinguishable voids and agglomerates. Fair distribution of silica nanoparticles and absence of residual solvents were observed by energy dispersive X-ray and thermogravimetric analysis. Fourier transform infrared spectroscopy spectra confirmed the presence of new functional groups (NH) and (OH) bonds. The X-ray diffraction pattern revealed the polymer-particle interactions, the formation of rigidified polymer chain, and nanostructured silicon crystals. Further, the thermogravimetric analysis results revealed thermal stability enhancement while differential scanning calorimetry results of increased glass transition temperatures confirmed the presence of rigidified polymer chain. Furthermore, enhancements in mechanical strength of the membranes were observed. Moreover, at all feed pressures, increased CO2, N2, and CH4 gas permeation was observed. At 6 bar feed pressure, the CO2/N2 and CO2/CH4 ideal selectivities of PC membranes with 3 wt % silica loading have increased from 19.2 to 38.0 and 29.2, respectively. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45310.
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| 4. |
- Nawaz, Muhammad, et al.
(författare)
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Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework
- 2021
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Ingår i: Chinese Journal of Chemical Engineering. - : Elsevier. - 1004-9541 .- 2210-321X. ; 29:1, s. 253-265
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Tidskriftsartikel (refereegranskat)abstract
- Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety. Small or incipient irregularities may lead to severe degradation in complex chemical processes, and the conventional process monitoring techniques cannot detect these irregularities. In this study to improve the performance of monitoring, an online multiscale fault detection approach is proposed by integrating multiscale principal component analysis (MSPCA) with cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts. The new Hotelling’s T2 and square prediction error (SPE) based fault detection indices are proposed to detect the incipient irregularities in the process data. The performance of the proposed fault detection methods was tested for simulated data obtained from the CSTR system and compared to that of conventional PCA and MSPCA based methods. The results demonstrate that the proposed EWMA based MSPCA fault detection method was successful in detecting the faults. Moreover, a comparative study shows that the SPE-EWMA monitoring index exhibits a better performance with lower values of missed detections ranging from 0 - 0.80% and false alarms ranging from 0 - 21.20%.
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| 5. |
- Taqvi, Syed Ali Ammar, et al.
(författare)
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Simultaneous fault diagnosis based on multiple kernel support vector machine in nonlinear dynamic distillation column
- 2022
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Ingår i: Energy Science & Engineering. - : John Wiley & Sons. - 2050-0505. ; 10:3, s. 814-839
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Tidskriftsartikel (refereegranskat)abstract
- Although numerous works have been done, most of the studies in fault diagnosis are limited to single fault type at a time. Majority of the works reported in the literature do not extend the diagnosis of the root cause of the fault for simultaneous faults specifically in the distillation column. However, an industrial system is susceptible to more than one fault at a time, which may or may not be interrelated. These faults not only reduce the diagnosis performance but also increase the computational complexity of the diagnosis algorithm. In this work, therefore, a multiple kernel support vector machine (MK-SVM) algorithm is proposed to diagnose simultaneous faults in the distillation column. In the developed MK-SVM algorithm, multilabel approach based on various kernel functions has been utilized for the classification of simultaneous faults. Dynamic simulation of a pilot-scale distillation column using Aspen Plus(R) is used for generating data in normal and faulty operation. Eight different fault types are considered, including valve sticking at reflux and reboiler, tray upsets, loss of feed flow, feed composition, and feed temperature changes. In the classification of simultaneous faults, a combination of two, three, and four faults is introduced for the performance evaluation of the proposed MK-SVM algorithm. The result showed that the proposed MK-SVM has a high fault detection rate (FDR) of 99.51% and a very low misclassification rate (MR) of 0.49%. The MK-SVM-based classification is better with the F1 score of >97% for all combinations of faults. Moreover, it is observed that the proposed MK-SVM shows better fault diagnosis for single, multiple, and simultaneous faults as compared to other established machine-learning algorithms.
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