energy efficient hybrid gas separation with ionic liquid
TRANSCRIPT
Presenter: Xinyan Liua,b
Supervisor: Xiaodong Lianga; Georgios Kontogeorgisa; Rafiqul Gania
Xiangping Zhangb; Suojiang Zhangb
a Department of Chemical and Biochemical Engineering, DTU, Lyngby, Denmark b State Key Laboratory of Multiphase Complex System, Beijing Key Laboratory of Ionic Liquids Clean
Process, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China
Energy Efficient Hybrid Gas Separation with Ionic Liquid
1
• Background – Gas separation processes – Overview of traditional separation technologies – Solution proposal & objective
• Framework – Three-stage methodology – Multi-scale concept
• Database & model library • Case study • Conclusion and future work
Outline
2
Background
3
Petroleum C5+ C4 C3 C2 CH4…
Purification
Chemical Production
Gas
Separation
Processes
Decarbonization Desulfuration Denitrification …
Biomass Gasification Methanol to Olefin …
Gas Separation Processes
4
Find alternative technology
Novel solvent for absorption
Distillation ✘High energy consumption
Non-volatile
Stability
Designable
Adjustable
Large capacity
Good recycle
Low energy
Widely application
Advantages Feature
Ionic Liquid
Membrane ✘Lower purity of product, low flow
Solvent absorption
✘Chemical: High energy, toxicity
✘Physical: Lower recovery
Gas separation with ionic liquid is a new way to be energy efficient and environmentally friendly.
Overview of traditional separation technologies
5
Natural gas Light hydrocarbon gas mixture
Method Application Advantages and disadvantages
Acid gas removal (CO2,H2S…)
Synthesis gas separation (H2…) Acid gas removal
✔Flexible and high purity
✔Economical, energy-saving
✔Mature, widely used
Adsorption
• Propose a systematic method for ILs screening for various kinds of raw gas, then develop the most efficient hybrid gas separation process.
• High solubility • High selectivity • Low viscosity, easy for industrialization
Problem: 1. How to find out the promising IL
2. How to separate any gas from gas mixtures for high energy efficiency, low environmental impact and increased profit.
Objective:
6
Solution proposal & objective For gas mixtures (>2) separation system
Hybrid gas separation processes (use technologies where they are most efficient)
IL-based absorption Traditional technologies: distillation or membrane
Combine with
Framework
7
Objective
Research
Application
Establish IL-based hybrid gas separation processes for various kinds of gas mixtures (Natural gas or shale gas…)
Stage 1:ILs screening Problem definition Screen ILs based on solubility and selectivity. Gas mixture analysis Screen IILs based on physical properties
Stage 2:Process design
Generate all possible flowsheets. Preliminary evaluation. Select flowsheet.
Apply a screening method to determine an environmentally friendly and economical hybrid gas separation scheme with low energy consumption
Stage 3:Process simulation and evaluation
Rigorous IL-based hybrid gas separation process simulation. Energy consumption and economical cost evaluation of the process. Compare this IL-based gas separation with conventional process.
8
Three-stage methodology
Objective
Research
Application
Establish IL-based hybrid gas separation process for various kinds of gas mixtures (Natural gas or shale gas…)
Stage 1:ILs screening Problem definition Screen ILs based on solubility and selectivity. Gas mixture analysis Screen IILs based on physical properties
Stage 2:Process design
Generate all possible flowsheets. Preliminary evaluation. Select flowsheet.
Apply a screening method to determine an environmentally friendly and economical hybrid gas separation scheme with low energy consumption
Stage 3:Process simulation and evaluation
Rigorous IL-based hybrid gas separation process simulation. Energy consumption and economical cost evaluation of the process. Compare this IL-based gas separation with conventional process.
9
Three-stage methodology
Multi-scale
Macro scale
Model
Process Design
Model data (COSMO-RS)
Experimental data Gas solubility data in ILs Henry constant of gas in ILs Gas selectivity data in ILs Property data of pure ILs
Henry constant data prediction
IL property data prediction Density Viscosity Surface tension Vapor pressure
IL-based absorption
Distillation
Membrane separation
Absorption …
Combine to hybrid gas separation process
10
Multi-scale concept
Database
11
Database & Model library
CO2 CO CH4 H2 C2H6 C2H4
C3H8 C4H10
N2 O2
N2O C4H8 C3H6
C2H2 NH3
NO2 SO2
COS H2S
12
Database establishment Gas component Measured solubility database
Number of gas
Number of ILs
Number of data
16 260 13875
CO2 CO CH4 H2 C2H6 C2H4
C3H8 C4H10
N2 O2
N2O C4H8 C3H6
C2H2 NH3
NO2 SO2
COS H2S
13
Database establishment Gas component Measured solubility database
Number of gas
Number of ILs
Number of data
16 260 13875
Number of gas
Number of ILs
Number of data
11 110 516
Measured Henry constant database
CO2 CO CH4 H2 C2H6 C2H4
C3H8 C4H10
N2 O2
N2O C4H8 C3H6
C2H2 NH3
NO2 SO2
COS H2S
14
Database establishment Gas component Measured solubility database
Number of gas
Number of ILs
Number of data
16 260 13875
Number of gas
Number of ILs
Number of data
11 110 516
Measured Henry constant database
Number of gas
Number of ILs
16 13585
Predicted Henry constant database (COSMO-RS)
CO2 CO CH4 H2 C2H6 C2H4
C3H8 C4H10
N2 O2
N2O C4H8 C3H6
C2H2 NH3
NO2 SO2
COS H2S
15
Database establishment Gas component Measured solubility database
Number of gas
Number of ILs
Number of data
16 260 13875
Number of gas
Number of ILs
Number of data
11 110 516
Measured Henry constant database
Number of gas
Number of ILs
16 13585
Predicted Henry constant database (COSMO-RS)
Merge into
Database
CO2 CO CH4 H2 C2H6 C2H4
C3H8 C4H10
N2 O2
N2O C4H8 C3H6
C2H2 NH3
NO2 SO2
COS H2S
16
Database establishment Gas component Measured solubility database
Number of gas
Number of ILs
Number of data
16 260 13875
Number of gas
Number of ILs
Number of data
11 110 516
Measured Henry constant database
Number of gas
Number of ILs
16 13585
Predicted Henry constant database (COSMO-RS)
Merge into
Database
209 cations
65 anions
19 gases
17
Database establishment Sufficient data can be retrieved from COSMO-RS.
Need a correction for CH4 , the same situation occurs for C2H4, C3H8.
(Take the common gases such as CO2 and light hydrocarbon gases as example)
the comparison between experiment and COSMO-RS
CO2 CH4
18
Model library establishment (Quantitative model)
Engineering model for Henry’s constant of CO2
The temperature dependence of the Henry’s constants was described by the following equation:
H exp[ / ]a b T= +
Based on sufficient experimental data, a model for Henry’s constant of CO2 in imidazolium-based ILs with three kinds of anions is established. The value of a and b can be fitted with carbon atom number on the alkyl chain: (a and b are calculated from group contribution method)
Eq.(1)
Model
[Cnmim][Tf2N] Eq.(2)
[Cnmim][BF4]
Eq.(3)
[Cnmim][PF6]
Eq.(4)
1373.335 149.075exp[8.835 0.273 ]CnH CnT
− −= + +
3082.425+180.795exp[14.977 0.733 ]CnH CnT
−= − +
2064.244+85.694exp[11.108 0.352 ]CnH CnT
−= − +
Comparison result for Henry’s constant of CO2 (Quantitative)
The AARD for predicted Henry’s constant of CO2 in imidazolium-based ILs with [Tf2N], [BF4] and [PF6] is 7.12%. Therefore, the predicted data is in good agreement with experiments as shown in Figures.
19
Model library establishment (Quantitative model)
Case study
20
Stage 2 Process Design
21
Framework: Workflow & Dataflow
Problem: gas mixtures need to be separated Available: solubility, selectivity, viscosity …. Find: potential IL solvent
Stage 1 ILs screening is highlighted together with the collected data and developed models in this presentation.
Step 1: Problem definition (gas mixture, product)
START Workflow
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Stage 1: Screening
Gas A H2
B CH4
C C2H4
D C2H6
E CO2
Shale gas model 5 gas product separate
Step 1: Problem definition (gas mixture:A,B,C,D; product)
START Workflow
Step 2: ILs screening based on solubility
Tool Dataflow
2.1 Retrieve Henry constant data of each gas in ILs
2.2 List suitable ILs for each gas (Hn< Ho)
A(H2) B(CH4) C(C2H4) D(C2H6) E(CO2) IL1 ✘ ✔ ✘ ✔ ✔ IL2 ✘ ✘ ✔ ✘ ✔ … … … … … … ILn ✘ ✘ ✔ ✔ ✘
Database Literature
Henry constant
Objective: Find feasible ILs for each gas
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Stage 1: Screening
START Workflow Tool Dataflow
Step 3: ILs screening based on selectivity
Objective: Narrow down the ILs through further considering the selectivity
…
Feasible IL: 𝑆𝑆 =
𝐻𝐻𝑚𝑚𝑚𝑚𝑚𝑚𝐻𝐻𝑚𝑚𝑚𝑚𝑚𝑚
> 𝑆𝑆𝑜𝑜 𝐸𝐸𝐸𝐸. (5)
Database Literature Henry constant
For five gases (ABCDE) separation problem, list 30 possible cases as below, for each case, the corresponding feasible ILs (from step 2) can be chosen :
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Stage 1: Screening
Where 𝐻𝐻𝑚𝑚𝑚𝑚𝑚𝑚 is the minimum H of the unabsorbed gas; 𝐻𝐻𝑚𝑚𝑚𝑚𝑚𝑚 is the maxmum H of the absorbed gas.
ILa one gas absorbed ILs:
two gas absorbed ILs:
three gas absorbed ILs:
four gas absorbed ILs:
ILb ILc ILd ILe
ILab ILac ILad ILae ILbc ILbd ILbe ILcd ILce ILde
ILabc ILabd ILade ILbcd ILbce ILcde ILabe ILacd ILbcd ILbde
ILabcd ILabce ILabde ILacde ILbcde
START Workflow
Step 4: Gas mixture analysis
…
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Stage 1: Screening
Objective: Narrow down the ILs through considering the economical aspect
4.1 Composition analysis
80%
3% 7% 3% 7%
Shale gas
CH4H2CO2C2H4C2H6
Shale Gas Percent
A H2 3%
B CH4 80%
C C2H4 3%
D C2H6 7%
E CO2 7%
Database Literature
Tool
Shale Gas Percent B.P/oC
A H2 3% -252.8
B CH4 80% -161.4
C C2H4 3% -103.7
D C2H6 7% -88.6
E CO2 7% -78.5
START Workflow
Step 4: Gas mixture analysis
…
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Stage 1: Screening
4.1 Composition analysis
4.2 Remove the undesired ILs
Objective: Narrow down the ILs through considering the economical aspect
Remove the solvents (ILs) for the compound in the largest amount (B) together with the gas which has a
lower B.P. than B.
Screening rule:
Optimal solvent: the ILs which don’t like CH4 and H2.
Organize the gas w.r.t boiling point.
Increased
Database Literature
Tool
Shale Gas Percent B.P/oC
A H2 3% -252.8
B CH4 80% -161.4
C C2H4 3% -103.7
D C2H6 7% -88.6
E CO2 7% -78.5
START Workflow
Step 4: Gas mixture analysis
…
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Stage 1: Screening
4.1 Composition analysis
4.2 Remove the undesired ILs
Objective: Narrow down the ILs through considering the economical aspect
Database tool: experimental data
Henry’s constant of 5 gases in [emim][Tf2N]-left and [bmim][BF4]-right
Tool
Database Literature
Shale Gas Percent B.P/oC
A H2 3% -252.8
B CH4 80% -161.4
C C2H4 3% -103.7
D C2H6 7% -88.6
E CO2 7% -78.5
START Workflow
Step 4: Gas mixture analysis
…
28
Stage 1: Screening
4.1 Composition analysis
4.2 Remove the undesired ILs
Objective: Narrow down the ILs through considering the economical aspect
Database tool: experimental data
Henry’s constant of 5 gases in [emim][Tf2N]-left and [bmim][BF4]-right
Tool
Database Literature
CH4 and H2 have lower solubility in ILs
Shale Gas Percent B.P/oC
A H2 3% -252.8
B CH4 80% -161.4
C C2H4 3% -103.7
D C2H6 7% -88.6
E CO2 7% -78.5
START Workflow
Step 4: Gas mixture analysis
…
29
Stage 1: Screening
4.1 Composition analysis
4.2 Remove the undesired ILs
Objective: Narrow down the ILs through considering the economical aspect
Database tool: experimental data
Henry’s constant of 5 gases in [emim][Tf2N]-left and [bmim][BF4]-right
Tool
Database Literature
It is possible to find solvent which don’t like both CH4 and H2 in database.
START Workflow
Step 4: Gas mixture analysis
…
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Stage 1: Screening Tool Dataflow
Step 5: ILs screening based on physical properties
Objective: Find the promising IL w.r.t. absorber parameters
5.1 Retrieve the physical property data of the selected IL Viscosity, density….
Database for IL pure property
5.2 Ranking the candidate based on optimal properties of selected IL
[emim][Tf2N] In this case study:
Stage 2 Process Design
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Stage 2: Process Design
Design: hybrid gas separation process scheme. Select: the process for high energy efficiency.
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Stage 2: Process Design STAR
T Workflow Tools & methods
…
Step 7: Preliminarily evaluate the flowsheets Flowsheet
energy method
Step 8: Select the most efficient process design scheme for hybrid gas
separation processes
Step 6: Generate all possible flowsheets Knowledge
based method for Separation
techniques
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Step 6: Generate all possible flowsheets
ABCDE
Knowledge based method for Separation
techniques
*Where d means distillation, m means membrane separation
Tools & methods
The promising IL which don’t like both A and B.
ILcde-AB/CDE
d or m or ILb-A/B
d or ILc or ILde-C/DE
ILd or ILce-D/CE
d or ILd or ILe-D/E
AB part
CDE part
Ex.
The first operation unit: absorber
34
Step 8-Select flowsheet (case study)
17% of total gas
Evaporation of the gases: 13.5 KJ/mol gas
Preliminary energy balance
100 kmol/h
170 kmol/h
No energy required compared to distillation
Stage 2 Process Design
Simulate: IL-based absorption hybrid process Analyze: energy consumption and economy. Compare: traditional process and IL-based process.
35
Stage 3: Process Simulation & Evaluation
• The objective of Stage 3 is to simulate and evaluate the IL-based hybrid gas separation process by comparing the energy consumption and economical cost with conventional process.
36
Stage 3: Process Simulation & Evaluation START Workflow
Step 9: Rigorous IL-based hybrid gas separation process simulation
…
Step 10: Energy consumption and economical cost evaluation of the process
Step 11:Compare the IL-based gas separation with conventional process
Final process design
I. Databases and model library – Databases store many experimental data of gas solubility
and Henry’s constant. – Models used for property prediction play an important role in
gas separation problems.
II. IL-based gas separation process – A framework for the ILs screening, gas separation process
design and evaluation is proposed. – An IL-based hybrid separation scheme for shale gas model
has been introduced and the potential energy-saving highlighted through a conceptual example.
37
Conclusion
– Further work is necessary to fine-tune the IL screening tool (database, model, search engine).
– More detailed analysis is necessary to account for all possible performance criteria to establish the hybrid gas separation scheme.
– Different gas separation case studies will be developed.
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Future work
39
Thank you very much
40
Case study- Feed gas analysis
CO2
C2H4
CH4
C2H6
H2
Shale gas
Traditional technology Boiling point (℃)
-252.8
-161.4
-103.7
-88.6
-78.5
Large energy consumption Find alternative hybrid separation process
Database & Model library
Database
Model library
Solubility, Henry constant
Pure IL property
Henry constant predicted model
Pure IL property model (Quantitative model)
Qualitative model
Quantitative model
Measured data Predicted data
41
Database and model library
Measured solubility database Gas ILs number Data dots
CO2 137 8827
CH4 11 510
H2S 15 722
NH3 7 225
SO2 16 303
CO 5 198
N2 10 208
O2 12 728
H2 12 552
N2O 12 577
C2H6 14 614
C3H8 3 95
C4H10 1 16
C2H4 3 268
C3H6 1 16
C4H8 1 16
42
Database establishment
Measured solubility database Gas ILs number Data dots
CO2 137 8827
CH4 11 510
H2S 15 722
NH3 7 225
SO2 16 303
CO 5 198
N2 10 208
O2 12 728
H2 12 552
N2O 12 577
C2H6 14 614
C3H8 3 95
C4H10 1 16
C2H4 3 268
C3H6 1 16
C4H8 1 16
43
Database establishment
Gas number :16
ILs number: 260
Data dots: 13875
Measured Henry constant database
44
Database establishment
Gas ILs number Data dots
CO2 34 165
CH4 22 130
C2H4 14 38
C2H6 10 41
C3H8 6 12
C4H10 1 7
N2O 6 21
N2 9 46
H2 4 28
O2 3 19
CO 1 9
Measured Henry constant database
45
Database establishment
Gas ILs number Data dots
CO2 34 165
CH4 22 130
C2H4 14 38
C2H6 10 41
C3H8 6 12
C4H10 1 7
N2O 6 21
N2 9 46
H2 4 28
O2 3 19
CO 1 9
Gas number :11
ILs number: 110
Data dots: 516
All of these measured data can be used for quantitative model to be applied to correction for predicted data and rigorous simulation.
Predicted Henry constant database (COSMO-RS)
46
Database establishment
Predicted Henry constant database (COSMO-RS)
47
Database establishment
CO2 CH4 C2H2 C2H4
C2H6 CO N2 NH3
O2 SO2 COS H2S H2
13 Gases
Predicted Henry constant database (COSMO-RS)
48
Database establishment
209 kinds of cations
Imidazole Pyridine Pyrrole Phosphonium Ammonium ……
Predicted Henry constant database (COSMO-RS)
49
Database establishment
209 kinds of cations 65 kinds of anions
Imidazole Pyridine Pyrrole Phosphonium Ammonium ……
Predicted Henry constant database (COSMO-RS)
50
Database establishment
209 kinds of cations 65 kinds of anions
Imidazole Pyridine Pyrrole Phosphonium Ammonium ……
ILs number: 13585