Energy-consumption analysis of carbon-based material for CO2 capture process

Journal Pre-proof Energy-consumption analysis of carbon-based material for CO2 capture process Shanshan Wang, Zhibin Su, Xiaohua Lu PII:

S0378-3812(20)30050-9

DOI:

https://doi.org/10.1016/j.fluid.2020.112504

Reference:

FLUID 112504

To appear in:

Fluid Phase Equilibria

Received Date: 31 October 2019 Revised Date:

26 January 2020

Accepted Date: 29 January 2020

Please cite this article as: S. Wang, Z. Su, X. Lu, Energy-consumption analysis of carbon-based material for CO2 capture process, Fluid Phase Equilibria (2020), doi: https://doi.org/10.1016/j.fluid.2020.112504. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier B.V.

Shanshan Wang: Conceptualization, Writing-Original draft preparation, Reviewing and Editing, Zhibin Su: Data curation, Methodology, Software Xiaohua Lu: Writing- Reviewing and Editing

Energy-Consumption Analysis of Carbon-Based Material for CO2 Capture Process Shanshan Wang*, Zhibin Su, Xiaohua Lu State Key Laboratory of Material-Oriented Chemical Engineering, College of Chemical Engineering, Nanjing Tech University, Nanjing, P. R. China 211816

*Corresponding Author E-mail: [email protected] (Shanshan Wang).

ABSTRACT: Few studies have been reported on optimizing the energy consumption of the CO2 capture process. Thus neglecting that the scale of industrial application of adsorption technology depends on the energy consumption of the process. In this work, 98 different types of porous carbon materials were constructed. The quantitative relationship between the material properties and structure was established through analysis of the adsorption capacity, selectivity, and energy consumption by molecular simulation. In our work, we establish a set of evaluation criteria for carbon-based material for CO2 capture and storage by combining the adsorbent structure (pore properties and surface chemical properties) and operating conditions (temperature, pressure, and temperature and pressure coupling) with the evaluation criteria for the adsorption process (working capacity, selectivity, and energy consumption).

Keywords: energy consumption, CO2 capture, activated carbon, molecular simulation

1. Introduction Over the past several decades, research work on adsorption worldwide has mainly focused on the development of adsorbents and CO2 capture process optimization [1-3]. With the development of new highly efficient adsorbents and the optimization of separation technology, the cost of CO2 capture by adsorption can be reduced substantially, which is expected to make adsorption separation a very viable technology [4]. For the evaluation criteria of the adsorption process, much work to date has focused on improving the adsorption capacity of CO2 and adsorption selectivity of CO2/CH4 and CO2/N2, but few reports have been published on optimizing the energy consumption of the process. This neglects the dependence of the scale of industrial applications on the energy consumption of the process. The energy consumption of the adsorption process is mostly concentrated in the compressor and desorption tower. The energy consumption of the process includes the power consumed by the compressor to compress the gas mixture into the absorption tower, the sensible heat brought by the desorption tower in the process of adsorbent and CO2 heating, and the desorption energy needed to desorb CO2 from the pores of the adsorbent [5]. According to the thermodynamic model based on the Gibbs free-energy change, the lowest and highest theoretical energy consumption of the CO2 separation process from the flue gas, kiln gas, biogas, and biomass syngas were calculated [6]. There are two main factors affecting the energy consumption in the process. One is the performance of the adsorbent materials, and the other is the selection of the operation process. The influencing factors of adsorbent material performance mainly refer to the physical properties of the adsorbent itself, including its specific surface area, pore volume, pore size distribution, pore morphology, porosity, and the interaction between gas and adsorbent, such as the Henry coefficient and adsorption heat [7]. With the development of high-performance computers and the improvement in computing power [8, 9], compared with experiments, we can use theoretical calculation method to screen a large number of adsorbent materials in a shorter period of time, and determine the potential adsorbent materials [10-14].

There have been a few examples utilizing various theoretical methods to screen cost-effective materials for CO2 capture [15]. Lin et al. [16] generated a database of potential zeolite-like structures and calculated the parasitic energy for the materials (corresponding to the penalty imposed on a power plant) based on the Henry coefficient of CO2 in the adsorbents. Their screening showed a theoretical limit to the minimum parasitic energy obtainable with experimentally realized and hypothetical zeolite and zeolitic imidazolate framework (ZIF) materials [17], of which, many have lower parasitic energy than that of the current monoethanolamine (MEA) technology (1327 kJ/kg CO2). Although materials with a higher Henry coefficient yielded a high CO2 working capacity, they performed poorly due to the excessive energy consumption in the regeneration process, which illustrates the limitation of focusing on a single material property. Wilmer et al. [18] screened over 130,000 hypothetical MOFs and showed clear correlations between purely structural characteristics (e.g., pore size, surface area, and pore volume) and chemical characteristics (i.e., functional groups) with five adsorbent evaluation criteria taken from the engineering literature (i.e., CO2 uptake under adsorption conditions, working CO2 capacity, regenerability, selectivity under adsorption conditions, and sorbent selection parameter). Zhong et al. [19, 20] proposed a concept of adsorbility (AD), defined as the ratio of the isosteric heat of adsorption at infinite dilution (Q ) for an adsorbate and the porosity (φ). The concept of adsorbility combined the parameters describing the material structure (φ) and those describing the surface chemical properties of materials ( Q ). The evaluation criteria of the thermal regeneration energy, CO2 working capacity, adsorption

selectivity,

and

regenerability

were

adopted

to

explore

the

structure-property relationships for 151 MOFs. Further analysis of the top ten MOFs revealed that introducing strong adsorption sites for CO2 or slit-like pore space (pore width of 6.6 Å) formed by the adjacent parallel porphyrin rings can be regarded as effective strategies for improving the performance of CO2/CH4 separation. The nanoscrolls [21] made from various materials (graphene, graphite, boron nitride, and carbon nitride) possessed exceptional CO2 uptake capacity (greater than 7 mmol/g) and CO2/N2 selectivity (greater than 150) at 0.15 bar and 313 K, greater than those for

the benchmark material for post-combustion CO2 capture, Mg-MOF-74, which has a CO2 uptake capacity of 5.28 mmol/g and CO2/N2 selectivity of 122 under the same conditions [22]. The influence of operation process selection on energy consumption mainly depends on the different regeneration methods of adsorbents. According to the different regeneration methods, the operation process can be divided into pressure-swing adsorption (PSA) [23], temperature-swing adsorption (TSA) [22, 24], and temperature -pressure–swing adsorption (TPSA) [25]. Ishibashi et al. [26] developed a coupling technology of vacuum PSA and TSA. Zeolite was used as adsorbent to capture CO2 in the flue gas of a power plant. The effect was remarkable. The recovery rate of CO2 was over 90%, the purity of CO2 was over 99%, and the capture cost was reduced by 20%. The development of an industrial-scale CO2 adsorption system needs to combine materials and process development [27]. However, although much research has been performed on these two aspects separately [28], little has been introduced in combination. Hasan et al. [29] combined the material structure and process; selected the morphology of the pore structure, pore volume, adsorption selectivity; used the energy consumption and cost of the PSA process as screening criteria; and selected the optimum zeolite molecular sieve structure and corresponding process conditions to reduce the cost of CO2 capture from 194 zeolite molecular sieves. However, we still lack clear guidelines for the optimal carbon-based adsorbents for a given CO2 capture application. Carbon-based adsorbents mainly include carbon nanotubes [30], graphite slits [31], and activated carbons [32], and are still the preferred materials for industrial applications because of the rich source of raw materials, low price, and strong hydrothermal stability. In the latest research, the CO2 adsorption capacity of carbon materials has been greatly improved. Under the operation conditions of 0.15 bar and 313 K, the adsorption capacity of carbon dioxide in a carbon nanoscroll was 7 mmol/g, and the adsorption selectivity of CO2/N2 was 150, which was higher than that of Mg-MOF-74 under the same operation conditions (the adsorption capacity of carbon dioxide was 5.28 mmol/g and the selectivity of CO2/N2 was 122) [22]. Based on the advantages and the great potential of

carbon-based materials, it is imperative to screen them for CO2 capture and storage. Molecular simulation results show that the influence of the material structure and operating conditions on the adsorption capacity, selectivity, and energy consumption of the separation process, as well as the relationship between variables and performance, is investigated; these are the basis for process optimization and play an irreplaceable role in experiments. In this work, 98 different types of porous carbon materials were constructed. The quantitative relationship between the material properties and structure was established through analysis of the adsorption capacity and energy consumption. In our work, we establish a set of evaluation criteria for carbon material CO2 capture and storage, combining the adsorbent structure (pore properties, surface chemical properties), operating conditions (temperature, pressure, temperature and pressure coupling) with the evaluation criteria for the adsorption process (working capacity, energy consumption).

2. Models and Computational Details 2.1 Porous carbon-based material. To build a database of carbon-based materials and provide data support for the synthesis of carbon-based materials, we synthetically consider various factors of structure, arrange, and combine pore morphology, pore size, surface properties, and other structural properties and construct a series of carbon-based materials. The partial structure of the material series is shown in Fig. 1. Three kinds of carbon-based materials, carbon nanotubes with one-dimensional channel, graphite slits with two-dimensional channels, and porous three-dimensional activated carbon materials, were constructed. The oxidation of carbon materials has been reported experimentally [33, 34], so it is feasible to use porous carbon materials to modify the hydroxyl groups. The hydroxyl groups were modified in the three kinds of materials by connecting hydroxyl groups with carbon atoms inside the carbon tubes, as shown in Fig. 1. In order to obtain different structures, we constructed 98 kinds of porous carbon materials with different structures. In carbon nanotubes, we adjusted the diameter, the roughness of the tube wall and numbers of surface functional groups; In graphite slits,

we adjusted the width of slit, the roughness of the slit wall and numbers of surface functional groups; In activated carbon, we adjusted the size, the roughness and surface functional groups numbers of the basic structural units, which were randomly arranged

to construct the activated carbons. And by adjusting numbers of the basic

structural units, activated carbons with different surface area and pore size distribution were built. We described this in detail in our previous work. [35] The textural properties of those models were characterized by various computational methods: (a) the surface area was defined geometrically as the area of the surface created by a probe corresponding to a spherical molecule with a diameter of 3.8 Å (the kinetic diameter of CH4), rolled along the atoms of carbon-based materials; and (b) the pore-size distribution was calculated using the method proposed by Gelb and Gubbins [36], which defines the pore size at a given point in the simulation cell based on the diameter of the largest sphere that can encompass the point without overlapping with the carbon-based models.

Fig. 1. Structures of the carbon nanotube, graphite slit, activated carbon, and modified materials

2.2 Simulation details. In this study, for a carbon-based, atomic-force Lennard–Jones (L–J) parameters are taken from the universal force field (UFF), which has been successfully employed for metal complexes and organic molecules [37]; this model has been successfully employed by numerous authors for previous simulations using similar systems [38] and in our previous work [35]. The hydroxyl groups were described as 2-center models, and the C atoms of carbon-based models connected with groups were

assigned as partial charges. All of the models were considered to be rigid. The CH4 model is a rigid regular tetrahedron with five charged L–J interaction sites, and the L–J potential parameters are taken from the TraPPE model [39]. For CO2 molecules, to consider the quadrupole effect and linear geometry, the EPM2 model [40] is used. The interactions between gas molecules and carbon absorbents were described by the L–J 12-6 potential and the Coulomb potential, as in Eq. (1). U ( ri j ) = 4ε i j [(

σ ij rij

)12 − (

σ ij rij

)6 ] +

qi q j rij

2

(1)

where rij denotes the distance between atoms i and j; qi denotes the quantity of charges of atom i, and εij and σij denote energy and size parameters, respectively. The L–J parameters and atomic partial charges used in this study are listed in Table 1. The L–J parameters between different atom types are from the Lorentz–Berthelot mixing rule. All interactions were truncated and shifted at 12.8 Å. Table 1. Lennard–Jones parameters and atomic partial charges atom

ε (k)

σ (nm)

q (e)

C(CH4)

55.05

0.340

-0.612

H(CH4)

7.90

0.265

0.153

C(CO2)

28.13

0.2757

0.6512

O(CO2)

80.51

0.3033

−0.3256

C(Carbon-based models)

29.13

0.340

0.00

C(Carbon-based models–OH)

29.13

0.340

0.20

O(–OH)

34.72

0.312

−0.644

H(–OH)

22.12

0.257

0.44

Music 4.0 code was employed for grand canonical Monte Carlo (GCMC) calculations [41], with the temperature, chemical potential, and pore volume specified in advance and held constant throughout the simulation. In each simulation, the adsorbent was treated as rigid, with Monte Carlo (MC) moves attempted randomly with a 50% probability of translation, rotation, and creation/deletion of CH4 molecules. Periodic boundary conditions were imposed in

all three directions. For each studied condition, 2 × 107 configurations were generated, where the first 107 configurations were discarded to guarantee equilibration, and the second 107 configurations were employed for ensemble properties. 2.3 Calculation of energy consumption. In the adsorption/desorption process, there are the PSA, TSA, and TPSA processes. The energy consumption of different materials in the three processes is analyzed in this work. The diagrams of the three processes are shown in Fig. 2.

Fig. 2. Diagrams of the PSA, TSA, and TPSA processes

The CO2 separation process includes the compressor, adsorption tower, heat exchanger, desorption tower, and reboiler. Assuming that the heat exchange in the heat exchanger can be neglected, the energy consumption is mainly concentrated in the desorption tower, and the energy consumption includes the sensible heat needed to heat solid adsorbents from T1 to T2, the heat required to remove CO2 from the solid adsorbents, and the compression work required for the increase in pressure from P2 to pressure P1. For the TSA process, the energy consumption WTSA equals to the sum of sensible heat Eheat needed for heating the adsorbents and heat Edes needed for desorbing CO2 [42, 43], as shown in Eq. (2). ∆

∆

∆

∆

∆

,

(2)

where Cp denotes the specific heat capacity, kJ/(kg·K); and the heat capacity of the carbon-based materials is listed in Table 2. ∆T is the difference between the adsorption and desorption temperatures, K. Cp·T represents the energy required to heat the adsorbents. mCO2 is the working adsorption capacity of CO2, (kg CO2)/(kg C),

which denotes the difference between the CO2 adsorption capacity in the adsorption state and that in the desorption state. Hi (I = CO2, CH4) is expressed as the energy contributed to overcome the desorption process of CO2 and CH4, respectively, which is related to the heat of adsorption and can be calculated by Eq. (3). Δ

!

',,

"#$, ('

,'

) )*

−!

',,

"#$, ('

,'

) )*,

(3)

where Qst,i denotes the heat of adsorption and is a function of the adsorption capacity.

Table 2. Specific heat capacity of some carbon-based materials Carbon-based materials

Specific heat capacity J/(kg·K)

Activated carbon [44]

840

Graphite slits [45]

710

Carbon nanotubes [46]

690

For the PSA process, the energy consumption equals the sum of the compression work WPSA required by the compressed gas and the heat Edes required to desorb CO2 from the solid material. Assuming that the compression process of the feed gas mixture is an isothermal compression process, the compression work of feed gas mixture can be expressed as Eq. (4), and the total energy consumption Wpressure of the PSA process can be expressed as Eq. (5). -. /

4

∑9@:; 1!4 2)36 5

/AB##CAB

-. /

9

∑97:; 1!7:; + EFB#

78 4

-. /

4

∑97:; 1<=>?< 6 (4) 4

)36 +

∆

5

∆

∆

(5)

It should be noted that for a binary system, the compression work of the two gases should be calculated and added separately. Therefore, it should be noted that P1 and P2 are the partial pressures of the gases in the mixture before and after compression, respectively.

3. Results and Discussions 3.1 Energy Consumption of the PSA Process. Assuming that CO2 is adsorbed at 298 K, 5 bar and desorbed at 298 K, 1 bar, the

total energy consumption includes the compression power and desorption energy consumption, which can be calculated by Eq. (5). We assume that this PSA process is accomplished by one-stage compression. The effects of the surface area (Sm) and porosity on the energy consumption in the PSA process are shown in Fig. 3. We can see that there is no obvious correlation between Sm and porosity with the process energy consumption, which proves that it is not enough to quantify by analyzing only one physical property of the adsorbents. 1.2

(a) 1.0

0.8

0.6

0.4

Etotal(PSA), MJ/kgCO2

Etotal(PSA), MJ/kgCO2

1.2

(b)

1.0

0.8

0.6

0.4 0

1500

3000

4500

Sm, m2/g

6000

0.00

0.15

0.30

0.45

Porosity

Fig. 3. Relationship between energy consumption with (a) surface area (Sm), (b) porosity at adsorption conditions of 298 K, 5 bar and desorption conditions of 298 K, 1 bar

Smit et al. screened the adsorbents with the lowest energy consumption by using the Henry coefficient of CO2 as the comparative factor [5]. Subsequently, the authors concluded that in addition to the Henry coefficient of CO2, the pore structures of the adsorbents also affected the energy consumption. Considering the Henry coefficient (which is related to the heat of adsorption of CO2) and the structural properties of the materials, Zhong et al. proposed the concept of adsorbility [20]. We studied the relationship between the difference in adsorbility of CO2/CH4 in the adsorbents and the energy consumption, as shown in Fig. 4. Compared with the structure and properties of the three kinds of carbon-based materials, there is a significant correlation between the difference in adsorbility of CO2/CH4 and the process energy consumption. We can see that carbon nanotubes have a higher process energy consumption, whereas the process energy consumption in activated carbon is lower.

Etotal(PSA), MJ/kgCO2

1.2

1.0

CNT slitpore Activated carbon

0.8

0.6

0.4 0.00

0.05

0.10

0.15

1/∆ ∆AD

Fig. 4. Relationship between the energy consumption and the difference in adsorbility of CO2/CH4 in the PSA process. ∆AD means difference in adsorbility of CO2 and CH4. To determine more intuitively which kinds of materials are conducive to energy saving, we mark carbon nanotubes, graphite slits, and activated carbon with different colors.

Energy consumption is an evaluation criterion for the economy of an adsorption process, but it is also important that we pay attention to the working capacity. We compared the relationship between the CO2 working capacity and process energy consumption in the PSA process, as shown in Fig. 5. It was found that carbon nanotubes had high energy consumption and low working capacity in the PSA

CO2 capacity, mol/kg

process, so they were not suitable as adsorbent materials for the PSA process.

CNT slitpore

2.5

Activated carbon 2.0 1.5 1.0 0.5 0.0 0.6

0.8

1.0

1.2

Etotal(PSA), MJ/kgCO2

Fig. 5. Relationship between CO2 working capacity and energy consumption in the PSA process

3.2 Energy Consumption of the TSA Process. In the TSA process, assuming that CO2 is adsorbed at 298 K, 5 bar and desorbed at

373 K, 5 bar, the energy consumption of regeneration includes desorption energy consumption and sensible heat brought by increasing the temperature, which can be calculated by Eq. (2). CO2 capacity adsorbed is directly obtained from the adsorption isotherm. The effects of surface area (Sm) and porosity on energy consumption in the TSA process are studied, same as the energy consumption in the PSA process. The results are shown in Fig. 6. Similar to the PSA process, we have not seen a very significant correlation between specific surface area and porosity. 8

(a) 6

4

2

0

1500

3000

4500

Sm, m2/g

6000

Etotal(PSA), MJ/kgCO2

Etotal(PSA), MJ/kgCO2

8

(b) 6

4

2

0.00

0.15

0.30

0.45

0.60

Porosity

Fig. 6. Relationship between energy consumption with (a) specific surface area (Sm) (b) porosity at adsorption conditions of 298 K, 5 bar and desorption conditions of 373 K, 5 bar

Based on the above analysis, we studied the relationship between the difference in the adsorbility of CO2/CH4 and the process energy consumption in the TSA process (Fig. 7). Obviously, there is a significant correlation between the difference in adsorbility and the process energy consumption. We can see that carbon nanotubes have a higher process energy consumption, whereas the process energy consumption in activated carbon is lower. Compared CO2 working capacity and process energy consumption in the TSA process in Fig. 8, it can be seen that the graphite slit structure is more advantageous to the TSA process. Under TSA process, the energy consumption was relatively low while the high capacity was guaranteed in the graphite slit structures.

Etotal(PSA), MJ/kgCO2

8

6

CNT Slitpore Activated carbon

4

2

0.00

0.05

0.10

0.15

1/∆ ∆AD

Fig. 7. Relationship between the energy consumption and the difference in adsorbility of CO2 and CH4 in the TSA process. Same as Fig. 4, ∆AD means difference in adsorbility of CO2 and CH4 and

CO2 capacity, mol/kg

different types of nanoporous porous carbon materials are maked with different colors CNT Slitpore Activated carbon

2.5 2.0 1.5 1.0 0.5 0.0 2

4

6

8

Etotal(PSA), MJ/kgCO2

Fig. 8. Relationship between CO2 working capacity and energy consumption in the TSA process

Compared with Fig. 5 and Fig. 8, the energy consumption of the TSA process is higher than that of the PSA process to obtain the same amount of CO2 adsorption capacity. For example, when the working capacity of CO2 is around 2.5 mol/kg, the energy required for PSA process is about 0.62 MJ/mol CO2, while the energy required for TSA process is about 1.5 MJ/mol CO2.

3.3 Energy Consumption of the TPSA Process. For the TPSA process, the calculation of energy consumption can be divided into two steps, as shown in Fig. 9. The first is to calculate sensible heat and desorption energy consumption in the TSA process; the second is to calculate sensible heat and desorption energy consumption in the PSA process; the total energy consumption of

the TPSA process is the sum of the four items. Similarly, we calculated the relationship between energy consumption and the surface area (Sm) and the porosity, and obtained the relationship between the energy consumption and the capacity.

Fig. 9. Schematic diagram of energy consumption calculation of the TPSA process

The effects of specific surface area and porosity on the energy consumption of the TPSA process are shown in Fig. 10. Similar to the PSA and TSA processes, we did not see a very significant correlation between specific surface area and porosity with the energy consumption. Fig. 11 shows the relationship between the difference in the adsorbility of CO2/CH4 and the process energy consumption in the TPSA process. From Fig. 11, it can be concluded that carbon nanotubes are more advantageous to the TPSA process. In the TPSA process, the energy consumption is relatively low while the high capacity is guaranteed in carbon nanotubes. 15

(a)

Etotal(PSA), MJ/kgCO2

Etotal(PSA), MJ/kgCO2

15

12

9

6

3

0

1500

3000

4500

Sm, m2/g

6000

(b) 12

9

6

3

0.00

0.15

0.30

0.45

Porosity

Fig. 10. Relationship between energy consumption with (a) surface area and (b) porosity at adsorption conditions of 298 K, 5 bar and desorption conditions of 373 K, 1 bar

15

(a)

Etotal(PSA), MJ/kgCO2

Etotal(PSA), MJ/kgCO2

15

12

9

6

3

0.00

0.05

0.10

0.15

(b) 12

9

6

CNT Slitpore Activated carbon

3

0.00

0.05

1/∆ ∆Ω

0.10

0.15

1/∆ ∆Ω

Fig. 11. Relationship between the energy consumption and the difference in adsorbility of CO2 and CH4 in the TPSA process

Compared with Fig. 5, Fig. 8 and Fig. 12, we can see that when the working capacity of CO2 is about 2.5 mol/kg, the energy required for PSA process is about 0.62 MJ/mol CO2, the energy required for TSA process is about 1.5 MJ/mol CO2, and the energy required for the TPSA process is about 1.2 MJ/mol CO2. CO2 capacity, mol/kg

5

CNT Slitpore Activated carbon

4 3

2 1

0 3

6

9

12

15

Etotal(PSA), MJ/kgCO2

Fig. 12. Relationship between CO2 working capacity and energy consumption in the TPSA process

4. Conclusion The quantitative relationship between the adsorption capacity and energy consumption of CO2/CH4 adsorbed on 98 porous carbon-based materials is discussed by using the GCMC method. The specific surface area and porosity were used to control the structural properties of materials. It was noted that there was no strong correlation between the change in a single factor and the energy consumption, which proved the limitation of the single-factor control method. By introducing the difference in the adsorbility of CO2/CH4, energy consumption has a strong correlation and can be used as a criterion for material screening.

For the selection of the CO2/CH4 adsorption process, we found that the energy consumption of the TSA process is the highest and that of the PSA process is the lowest. Energy consumption of the TPSA process is slightly higher than that of the PSA process. For example, when the working capacity of CO2 is about 2.5 mol/kg, the energy required for PSA process is about 0.62 MJ/mol CO2, the energy consumption for TSA process is about 1.5 MJ/mol CO2, and the energy consumption for TPSA process is about 1.2 MJ/mol CO2. By analyzing the energy consumption in different processes, we screened out the best types of adsorbents suitable for different adsorption processes. Considering the high adsorption capacity and low desorption energy consumption, we found that the three-dimensional activated carbons have high adsorption capacity and low desorption energy consumption in the PSA process, whereas the two-dimensional graphite slits are more advantageous to the TSA process, with high adsorption capacity and low desorption energy consumption. In the TPSA process, one-dimensional carbon nanotubes are more advantageous. This study provides a theoretical basis for selecting different adsorbent structures for different processes.

Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant Nos. 91934302, 21838004), the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 21921006) and the computational resources are generously provided by the High Performance Computing Center of Nanjing Tech University.

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Declaration of interests

√The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: