Progress in Modeling of Silica-Based Membranes and Membrane Reactors for Hydrogen Production and Purification
Abstract
:1. Introduction
- Cost-effective hydrogen generation in a carbon constrained global energy system: the challenges in this area involve hydrogen production from fossil fuels combined to carbon sequestration, in parallel with an increase in renewable sources exploitation.
- Hydrogen purification and storage technologies able to separate and purify hydrogen streams to the requirements of the end-users: efficient hydrogen separation and storage devices will have to match the United States—Department of Energy (US DOE) targets, such as hydrogen permeability and permselectivity (2015, last up-date), recognized worldwide as reference values for any hydrogen permselective membrane worthy of interest for its potential utilization in industrial applications.
- An efficient, widely available, and well-managed hydrogen delivery and distribution infrastructure.
- Efficient fuel cells and other energy conversion technologies fueled by hydrogen.
2. Silica Membranes
2.1. Silica Structure
2.2. Transport Mechanism in Microporous Silica Membrane
3. Membrane Reactor Technology
- catalytic membrane reactors (CMR);
- packed bed membrane reactors (PBMR);
- catalytic non-permselective membrane reactors (CNMR),
- non-permselective membrane reactors (NMR);
- reactant-selective packed bed reactors (RSPBR).
4. Application of Silica Membranes in MR Systems
Modeling of Silica MRs
- the simple model represents a useful tool for a preliminary evaluation of the WGS-MR performance.
- The CFD-based model can be adopted for designing the WGS-MR and for optimising the silica MR performance.
- The desired MR performance can be provided with a high perm-selective silica membrane.
5. Conclusions and Future Trends
Funding
Conflicts of Interest
List of Acronyms
ANN | Artificial Neural Network |
CCS | Carbon capture and storage |
CFD | Computational fluid dynamics |
CMR | Catalytic membrane reactor |
CNMR | Catalytic non perm-selective membrane reactors |
FBR | Fixed bed reactor |
MD | Molecular dynamics |
MR | Membrane reactor |
NMR | Non perm-selective membrane reactors |
PBMR | Packed bed membrane reactors |
PEMFC | Proton exchange membrane fuel cell |
RSPBR | Reactant-selective packed bed reactors |
TR | Traditional reactor |
WGS | Water gas shift |
List of Symbols
D0 | mean intrinsic diffusion coefficient for micropore diffusion (m2·s−1) |
K0 | intrinsic Henry constant (-) |
ε | membrane porosity (-) |
L | membrane thickness (m) |
bulk density (Kg/m3) | |
qst | isosteric heat adsorption (J/mol) |
Ei | activation energy for gas species (KJ/mol) |
R | universal gas constant (J/mol·K) |
T | temperature (K) |
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Microporous (<2 nm) | Mesopores | Macropores | |
---|---|---|---|
Ultramicropores | Supermicropores | ||
<0.7 nm | >0.7 nm | 2–50 nm | >50 nm |
Type of Membrane | Transport Mechanism | Perm-Selectivity |
---|---|---|
Macroporous > 50 nm | Viscous flow Molecular diffusion | 1 |
1 | ||
Mesoporous, 2–50 nm | Knudsen diffusion Surface diffusion Capillary Condensation, pore filling | |
More than Knudsen value | ||
Much more than Knudsen value | ||
Microporous, <2 nm | Micropore diffusion | Much more than Knudsen value |
Silica MRs Advantages | Silica MRs Disadvantages |
---|---|
|
|
|
|
|
|
Model Type | Theoretical Assumptions | Reaction Process | Primary Target | References |
---|---|---|---|---|
Mass balance and CFD | 2-D Non-Isothermal (CFD model) Isothermal (simple model) | WGS reaction | Simulation of silica MR performance by two types of mathematical models | Kouku et al. [36] |
Mass balance | 1-D Isothermal | Methane dry reforming | Comparison between silica MR and other kinds of reactors | Prabhu et al. [37] |
Mass balance | One-dimensional Isothermal | HI decomposition reaction | Evaluation of silica MR performance | Hwang and Onuki [38] |
Mass balance | 1-D Isothermal and pseudo-homogeneous | Methane steam reforming | Evaluation of silica MR performance | Yu et al. [39] |
Mass balance | 1-D 2-D | Methane steam reforming | silica MR performance comparison between 1-D and 2-D models | Oyama and Hacarlioglu [40] |
Mass balance | 1-D Isothermal | Methane steam reforming | Permselectivity variation effects on silica MR performance | Tsuru et al. [41] |
Mass balance | 1-D Isothermal | WGS reaction | Evaluation of silica MR performance | Tsuru et al. [41] |
Mass balance and economic analysis | 1-D | Propane and ethylbenzene dehydrogenations | Economic evaluation between silica and Pd-based MRs | Moparthi et al. [42] |
Mass balance | 1-D 2-D | Methanol steam reforming and WGS | Evaluation of silica MR performance | Ghasemzadeh et al. [43,44,45,46] |
K2 | Mole Fraction | |||||
---|---|---|---|---|---|---|
Experimental | Theoretical | H2O | H2 | CO | CO2 | CH4 |
Fixed-bed Reactor | ||||||
0.37 | 0.37 | 0.03 | 0.2 | 0.26 | 0.11 | 0.14 |
Vycor MR | ||||||
0.45 | 0.37 | 0.03 | 0.18 | 0.24 | 0.09 | 0.12 |
Nanosil MR | ||||||
0.38 | 0.37 | 0.03 | 0.19 | 0.27 | 0.1 | 0.13 |
T (K) | P (bar) | H2 yield × 10−6 (Experimental) | CO yield × 10−6 (Experimental) | CO2 yield × 10−6 (Experimental) | H2 yield × 10−6 (Theoretical) | CO yield × 10−6 (Theoretical) | CO2 yield × 10−6 (Theoretical) | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PBR | MR | PBR | MR | PBR | MR | PBR | MR | PBR | MR | PBR | MR | ||
873 | 1 | 7.4 | 10.4 | 0.9 | 0.9 | 1.6 | 1.8 | 9 | 11.5 | 0.9 | 0.9 | 1.6 | 1.9 |
5 | 24.4 | 34.1 | 1.6 | 1.9 | 5.3 | 7.0 | 27.2 | 38.0 | 1.8 | 2.0 | 5.8 | 7.6 | |
10 | 38.6 | 53.1 | 1.7 | 2.3 | 7.9 | 11.5 | 41.2 | 57.9 | 1.9 | 2.5 | 8.7 | 12.9 | |
15 | 48.1 | 67.1 | 1.8 | 2.5 | 9.6 | 14.8 | 52.2 | 73.1 | 2 | 2.8 | 11.8 | 16.9 | |
20 | 55.6 | 77.7 | 1.8 | 2.7 | 10.9 | 17.5 | 60.4 | 85.7 | 2.2 | 3.1 | 13.2 | 20.4 | |
923 | 1 | 7.9 | 11.5 | 1.5 | 1.4 | 1.5 | 1.8 | 9.8 | 12.3 | 1.5 | 1.3 | 1.5 | 1.8 |
5 | 31.2 | 42.8 | 3.3 | 3.8 | 6.1 | 7.8 | 34.4 | 46.1 | 2.6 | 3.8 | 6.4 | 8.2 | |
10 | 50.1 | 68.9 | 3.7 | 4.9 | 9.7 | 13.5 | 53.9 | 76.1 | 3.1 | 5.1 | 10.2 | 14.5 | |
15 | 62.4 | 88.7 | 3.9 | 5.4 | 12.0 | 18.0 | 66.7 | 95.3 | 4.2 | 5.8 | 14.2 | 20.0 | |
20 | 73.1 | 104.7 | 4.0 | 5.7 | 13.8 | 21.8 | 79.2 | 112.7 | 4.6 | 6.0 | 16.7 | 25.0 |
Silica MR | Dense Pd-Ag MR | ||||
---|---|---|---|---|---|
H2/N2 = 14 | H2/N2 = 60 | H2/N2 = 600 | H2/N2 = 6000 | H2/N2 = ∞ | |
Methanol conversion [%] | 59.33 | 70.21 | 75.41 | 76.11 | 80.95 |
Hydrogen Recovery [%] | 30.97 | 58.29 | 67.03 | 67.29 | 52.07 |
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Ghasemzadeh, K.; Basile, A.; Iulianelli, A. Progress in Modeling of Silica-Based Membranes and Membrane Reactors for Hydrogen Production and Purification. ChemEngineering 2019, 3, 2. https://doi.org/10.3390/chemengineering3010002
Ghasemzadeh K, Basile A, Iulianelli A. Progress in Modeling of Silica-Based Membranes and Membrane Reactors for Hydrogen Production and Purification. ChemEngineering. 2019; 3(1):2. https://doi.org/10.3390/chemengineering3010002
Chicago/Turabian StyleGhasemzadeh, Kamran, Angelo Basile, and Adolfo Iulianelli. 2019. "Progress in Modeling of Silica-Based Membranes and Membrane Reactors for Hydrogen Production and Purification" ChemEngineering 3, no. 1: 2. https://doi.org/10.3390/chemengineering3010002
APA StyleGhasemzadeh, K., Basile, A., & Iulianelli, A. (2019). Progress in Modeling of Silica-Based Membranes and Membrane Reactors for Hydrogen Production and Purification. ChemEngineering, 3(1), 2. https://doi.org/10.3390/chemengineering3010002