Process Simulation of an Integrated Dimethyl Ether Production and Purification Process from CO₂/CH₄ Rich Feedstock

1. Introduction

The global imperative to reduce atmospheric carbon dioxide concentrations has accelerated interest in technologies that convert CO₂ from an environmental liability into a chemical feedstock. Among the emerging pathways for CO₂ valorization, the production of oxygenated fuels and chemical intermediates represents one of the more commercially tractable routes, combining environmental benefit with economic value [1,2]. Dimethyl ether (DME, CH₃OCH₃) has attracted substantial attention in this context. It is the simplest ether and carries physical properties remarkably similar to liquefied petroleum gas (LPG), including a boiling point of −24.8°C at atmospheric pressure and a vapour pressure of approximately 5.1 bar at 20°C. These make it efficient within existing LPG infrastructure without modification, which confers an advantage over many other alternative fuels that demand entirely new distribution networks [3]. DME has a cetane number of 55–60, significantly higher than diesel fuel (40–55), making it an effective diesel substitute in compression-ignition engines with near-zero particulate emissions owing to its oxygen content and absence of carbon-carbon bonds [4]. Its calorific value, at approximately 28.4 MJ kg⁻¹, is lower than diesel on a mass basis but competitive when the cleaner combustion is taken into account. DME also serves as a methylating agent in chemical synthesis, a propellant in aerosol products, and a refrigerant, while its potential as a hydrogen carrier for fuel cell applications has also been explored [5].

The conventional industrial route to DME is the two-step process, which follows that methanol is first synthesized from syngas (Eq.1) at 250–280°C and 50–80 bar over a Cu/ZnO/Al₂O₃ catalyst and subsequently dehydrated over solid acid catalysts such as γ-alumina (Eq.2) at 250–350°C [6]. Syngas itself is predominantly derived from steam methane reforming (SMR) of natural gas, a process that is net carbon positive. The growing availability of CO₂ captures from power generation, and industrial processes has prompted investigation of CO₂-containing feeds as alternatives. Dry reforming of methane (Eq.3) offers the singular advantage of consuming two greenhouse gases simultaneously, producing a syngas with a H₂:CO ratio of unity, which is particularly suitable for subsequent downstream processing [7,8].

CO + 2H₂ → CH₃OH

(1)

2CH₃OH → CH₃OCH₃ + H₂O

(2)

$$\mathit{CH}₄+{\mathit{CO}}_2\rightleftharpoons 2\mathit{CO}+2H₂({\Delta H}_{298}^{°}=+247\mathit{kJ}{\mathit{mol}}^{-1})$$

(3)

Despite the thermodynamic attractiveness of DRM, industrial implementation remains challenging. The reaction is highly endothermic, requiring temperatures of 800–950°C, and the resulting syngas H₂:CO ratio of approximately 1 is lower than the 2:1 stoichiometric ratio required for methanol synthesis. This requires either a water-gas shift (WGS) adjustment step or the acceptance of a CO-rich syngas entering the methanol reactor, with implications for conversion efficiency and selectivity [9]. An alternative is the integration of CO₂ co-hydrogenation reactions within the methanol synthesis reactor itself, exploiting both CO and CO₂ hydrogenation pathways. Published simulation studies have demonstrated that such integrated approaches are technically feasible, though economic viability is strongly sensitive to natural gas and electricity prices, catalyst costs, and the valuation assigned to CO₂ [10,11].

Process simulation is an indispensable tool in the early-stage evaluation of such routes. It allows rigorous material and energy balances to be established before experimental campaigns and permits rapid sensitivity analysis across a wide parameter space. Several simulation platforms have been applied to DME-related processes. E-Moghaddam et al. [12] analyzed different synthesis routes for CH₃OH and DME from syngas utilizing Aspen Plus. The authors deployed kinetic models for both methanol and DME production while assessing the efficiency of the downstream processes. Similarly, Dieterich et al. [13] compared four renewable DME production pathways from CO₂ and H₂ using Aspen Plus and process heat integration. They found considerable differences in energy and economic performance between direct and indirect configurations. Fedeli et al. [14] developed a rigorous Aspen Plus flowsheet integrating reforming, DME synthesis and downstream purification and further optimized the separation section using technical, economic and sustainability indicators.

ChemCAD (Chemstations Inc.) is a rigorous steady-state process simulator with proven capabilities for petroleum, gas processing, and chemical plant design. Its NRTL thermodynamic package is well-established for polar component systems involving methanol, water, and ethers. The platform’s kinetic reactor module (KREA) supports user-defined reaction kinetics with axial temperature profiles, making it suitable for simulating the non-isothermal behaviour of both the methanol synthesis and dehydration reactors. To the best of the authors’ knowledge, no published study has reported a complete three-stage DRM-methanol-DME process simulation in ChemCAD incorporating all process units from feed mixing through to distillation product recovery.

The present work addresses this gap. We report a steady-state ChemCAD simulation of a complete process chain encompassing: (i) dry reforming of methane, modelled as an equilibrium reactor; (ii) methanol synthesis from the resulting syngas, modelled with kinetic equations from the Vanden Bussche and Froment [15] mechanism; (iii) methanol dehydration to DME over γ-Al₂O₃, modelled with the kinetics of Bercic and Levec [13]; and (iv) product separation and purification via flash separation and two distillation columns. Mass and energy balances are presented for all unit operations, and the results are benchmarked against published experimental and simulation data. The study culminates in a preliminary techno-economic discussion that identifies the key cost drivers for this process configuration and outlines priority areas for optimization.

2. Materials and Methods

2.1. Overall Process Concept

The process evaluated in this study consists of three chemically distinct reaction stages connected by heat integration and separation equipment. Figure 1 shows the ChemCAD process flowsheet as developed for this simulation. Carbon dioxide and methane are fed to a mixing unit at a CO₂:CH₄ molar ratio of 1:1, consistent with the stoichiometry of the DRM reaction. The mixed feed enters a fired equilibrium reactor (the DRM reactor, R-101-DRM) operating at thermodynamic equilibrium at elevated temperature. The hot syngas product is then cooled in a heat exchanger train before entering the CH₃OH synthesis reactor (R-102-MeOH), a kinetic plug-flow reactor. The methanol-containing reactor effluent proceeds through further cooling, compression, and a primary flash separation to recover condensable products. The liquid phase, containing methanol, water, residual CO₂, and dissolved gases, is fed to the dehydration reactor (R-103-DRM dehydration), where MeOH is conventionally converted over solid acid catalyst to DME. The crude DME mixture then passes through a two-column distillation sequence to recover DME at the required purity and separate methanol for recycling. The process is intended as a once-through conversion with unconverted syngas exiting the top of the first flash separator (V-101) as a gas-phase stream rich in H₂, CO, CH₄, and CO₂. As annotated on the flowsheet, this stream is designated for future recycle optimization, representing a significant lever for improving overall carbon utilisation efficiency. The thermodynamic specifications were calibrated as presented in Table 1.

2.2. Dry Reforming of Methane

The feed consisted of methane and carbon dioxide mixed at the specified design ratio before entering the dry reforming reactor. Reactor 1 (R-101-DRM) represented the dry reforming of methane over a Ni/Al₂O₃ catalyst to generate synthesis gas. The reformate entered Reactor 2 (R-102-MeOH) where methanol was synthesised over a Cu/ZnO/Al₂O₃ catalyst using a kinetic plug-flow reactor. The methanol-rich stream was subsequently fed to Reactor 3 (R-103-DRM dehydration) where methanol dehydration over γ-Al₂O₃ produced dimethyl ether and water. Reactor effluent was cooled and routed through two flash separation stages. The first flash removed condensed liquid while the vapour was compressed and chilled to enhance DME condensation before a second flash separator. The combined liquid stream entered a rigorous distillation column for DME purification, followed by a second distillation column for methanol recovery and recycle [16]. The equilibrium calculation in ChemCAD minimises the Gibbs free energy of the system simultaneously across all possible reactions, including the primary DRM reaction, the reverse water-gas shift (Eq.4), and the Boudouard reaction (Eq.5). No solid carbon phase was included in the phase equilibrium, which is a common modelling simplification acceptable when operating above the carbon deposition boundary [17].

RWGS: CO₂ + H₂ ⇌ CO + H₂O

(4)

2CO ⇌ CO₂ + C

(5)

2.3. Methanol Synthesis

Methanol synthesis was modelled using the ChemCAD KREA (kinetic reactor 2) unit. The reactor operates as a plug-flow reactor (PFR) and employs the kinetic rate expressions of Vanden Bussche and Froment [15], which account for three parallel reactions (Eq.6 to 8) on the Cu/ZnO/Al₂O₃ catalyst surface:

R1: CO₂ + 3H₂⇌ CH₃OH + H₂O ΔH° = −49.5 kJ mol⁻¹

(6)

R2: CO₂ + H₂⇌ CO + H₂O ΔH° = +41.2 kJ mol⁻¹ (RWGS)

(7)

R3:CO + 2H₂⇌ CH₃OH ΔH° = −90.7 kJ mol⁻¹

(8)

The extracted simulation data indicate an inlet temperature of approximately 227°C (500 K) with reactor pressure of 44 bar, consistent with published operating windows for methanol synthesis (220–280°C, 30–50 bar) [10].

2.4. Separation System

The reactor effluent was first cooled using cooling water before entering the primary flash separator. Vapour leaving the separator was compressed and further cooled using chilled water to increase DME condensation before a secondary flash separator (V-102). A rigorous staged distillation column (T-101) recovered DME as the overhead product while methanol and water were withdrawn as bottoms. A second distillation (T-102) column recovered methanol as an overhead recycle stream and produced a water-rich bottoms stream suitable for purge. Material and energy balances were evaluated for each unit operation. Product distribution, DME recovery, methanol recovery, utility demand and separation performance were obtained from the converged simulation and used for subsequent techno-economic assessment.

3. Simulation Methodology

3.1. Software and Thermodynamic Framework

The NRTL (Non-Random Two-Liquid) activity coefficient model was selected for the liquid-phase fugacity calculation, with the Redlich-Kwong equation of state applied to the vapour phase. The NRTL model is well-established for the methanol-water-DME ternary system, and ChemCAD 8 binary interaction parameters for this system are taken from the built-in databank, which has been validated against published VLE data [18]. Enthalpy was computed using the latent heat method (latent heat of vaporization from the ChemCAD library), which is appropriate for streams where vaporization and condensation dominate the thermal load, as is the case in the distillation and flash sections. For the high-temperature DRM reactor section, a local thermodynamic override to the Soave-Redlich-Kwong (SRK) equation of state was applied to better represent the H₂-CO₂-CH₄ gas phase at elevated temperature and moderate to high pressure. The simulation convergence criterion applied a tolerance of 0.001 on temperature, pressure, vapour fraction, enthalpy, and flow rate simultaneously across all recycle streams and unit operations. The maximum number of iterations for the outer recycle loop was set to 80, consistent with the default ChemCAD configuration. The simulation was confirmed to have achieved convergence at the reported conditions. The overall system is as presented in Figure 1.

Figure 1. Flow diagram of the DME synthesis process.

Figure 1. Flow diagram of the DME synthesis process.

3.2. Feed Specification and Basis

The simulation basis is 1,000 kmol/h of combined CO₂ and CH₄ feed, fed in equimolar proportions (500 kmol/h each) at 25°C and 1 bar. This basis corresponds to approximately 88 t h^-1 of raw feed. A nitrogen purge stream is included to maintain the simulation’s convergence stability and to represent inert trace components that would be present in a real CO₂ capture stream. The CO₂ feed and CH₄ feed are mixed in a single mixer before preheating to the DRM reactor inlet temperature. No Sulphur species or higher hydrocarbons are included in the feed, which is equivalent to assuming a pre-treated and purified feed gas.

3.3. Reactor Modelling

Table 2 summarizes the reactor types, model approaches, and key operating conditions employed in the simulation. The DRM reactor (R-101-DRM) was modelled using a kinetic plug flow reactor (PFR) rather than an equilibrium (Gibbs) reactor. A kinetic reactor was selected because the DRM reaction is strongly influenced by catalyst activity, reaction kinetics and residence time, making an equilibrium-based approach less representative of practical industrial operation. The PFR model enables the incorporation of experimentally derived kinetic parameters and provides a more realistic prediction of methane and carbon dioxide conversion over a fixed-bed catalytic reactor. The reactor was simulated under steady-state conditions at 800 °C and 3 atm, employing a Ni/Al₂O₃ catalyst represented through an Arrhenius-type kinetic expression. Temperature was held constant by the fired heater unit, which calculated the required fuel duty to maintain the set-point.

The methanol synthesis reactor was modelled as a kinetic plug flow reactor (PFR) using the intrinsic kinetic model developed by Vanden Bussche and Froment. Unlike equilibrium-based reactor models, the kinetic PFR accounts for finite reaction rates, catalyst activity, residence time and adsorption phenomena, thereby providing a more representative description of industrial fixed-bed methanol synthesis reactors. The Vanden Bussche–Froment model remains one of the most extensively applied kinetic formulations for methanol synthesis and has been adopted in numerous process simulation and reactor design studies because of its ability to accurately predict methanol formation over a broad range of operating conditions [19]. The kinetic model simultaneously considers carbon dioxide hydrogenation, carbon monoxide hydrogenation and the reverse water-gas shift (RWGS) reaction using Langmuir–Hinshelwood–Hougen–Watson (LHHW) rate expressions. The reaction rates implemented are expressed as in Eq.9.

$$r_1=k_1{f}_{{\mathit{CO}}_2}{f}_{H_2}{\displaystyle \frac{\left(1-{\eta }_1\right)}{{\mathit{Den}}^3}}$$

(9)

The CO₂ hydrogenation follows Eq. 10,

$$r_2=k_2{f}_{{\mathit{CO}}_2}{f}_{H_2}{\displaystyle \frac{\left(1-{\eta }_2\right)}{\mathit{Den}}}$$

(10)

For RWGS,

$$r_3=k_3{f}_{{\mathit{CO}}_2}{f}_{H_2}^2{\displaystyle \frac{\left(1-{\eta }_3\right)}{{\mathit{Den}}^3}}$$

(11)

where r_i represents the intrinsic reaction rate, k_i is the Arrhenius temperature-dependent rate constant, f_idenotes the fugacity of the reacting species, η_i is the approach-to-equilibrium factor for each reaction, and Den represents the adsorption denominator accounting for competitive adsorption of reactants and products on the catalyst surface. The adsorption term incorporates the inhibiting effects of strongly adsorbed species and enables accurate prediction of catalyst behaviour under varying temperatures, pressures and reactant compositions.

The methanol dehydration reactor was similarly modelled as a kinetic plug flow reactor to simulate the catalytic conversion of methanol into dimethyl ether (DME) over a γ-Al₂O₃ catalyst. A kinetic reactor was selected because methanol dehydration is governed by catalyst-controlled reaction kinetics and competitive adsorption rather than thermodynamic equilibrium alone. Consequently, the kinetic approach provides a more realistic representation of industrial fixed-bed dehydration reactors and enables prediction of catalyst utilization, reaction rates and temperature profiles along the reactor length.

The dehydration reaction was represented using the Bercic and Levec kinetic model, which is one of the most widely adopted LHHW formulations for methanol dehydration over γ-Al₂O₃ catalysts. The intrinsic reaction rate is given by Eq.12.

$$r_4={\displaystyle \frac{K_4{K}_{\mathit{MeOH}}^2{C}_{\mathit{MeOH}}}{{\left(1+K_{\mathit{MeOH}}{C}_{\mathit{MeOH}}+K_{H_{2}O}{C}_{H_{2}O}\right)}^2}}$$

(12)

where, k₄ is the Arrhenius rate constant, K_MeOH and $K_{{\mathrm{H}}_2\mathrm{O}}$ are adsorption equilibrium constants for methanol and water, respectively, while C_i denotes the concentration of each component. The denominator accounts for competitive adsorption of methanol and water on the catalyst surface, thereby describing the progressive inhibition of active sites as water accumulates during the reaction. Incorporation of this inhibition mechanism is essential for accurately predicting the reduction in reaction rate at high methanol conversion and the corresponding temperature profile along the reactor. Consequently, the Bercic–Levec model provides a more realistic representation of industrial DME synthesis than simplified power-law or equilibrium formulations and has remained a benchmark kinetic model for simulation of fixed-bed methanol dehydration reactors.

3.4. Separation System Specification

Table 2 summarizes the principal design specifications adopted for the separation units incorporated in the ChemCAD simulation. The downstream purification train consisted of two rigorous distillation columns modelled using the SCDS (simultaneous correction distillation system) module. The SCDS model rigorously solves the coupled MESH equations, comprising the component mass balances, vapour–liquid equilibrium relationships, summation equations and energy balances simultaneously for every theoretical stage within the column. This rigorous solution approach provides reliable prediction of temperature profiles, component distributions, condenser and reboiler duties, and product purities, making it well suited for multicomponent DME purification systems. Prior to rigorous simulation, each distillation column was first designed using the shortcut distillation module. The shortcut column was employed to estimate the minimum number of theoretical stages, minimum reflux ratio, practical operating reflux ratio, condenser duty, and reboiler duty based on the specified product separation. These initial design parameters were subsequently transferred to the SCDS model as starting values for the rigorous column calculations. The use of shortcut distillation before rigorous simulation is a widely accepted design strategy because it provides thermodynamically consistent initial estimates that improve convergence and minimize iterative adjustments during rigorous simulation [20,21].

The final rigorous column specifications, including the number of theoretical stages, feed stage location, operating pressure, reflux ratio and thermal duties, were further refined through iterative simulation to achieve stable convergence while satisfying the required DME and methanol separation targets. This iterative refinement of reflux ratio and column operating conditions is consistent with recent process-simulation studies of methanol purification, in which rigorous distillation models are adjusted to achieve specified product purity and separation targets [22].

4. Results and Discussion

4.1. Flash Separator Vapour Outlet

Following methanol synthesis and the methanol dehydration step, the process effluent enters the primary first flash separator. The vapour fraction leaving the top of this vessel constitutes the direct feed to the first distillation column. Its full composition as reported by the converged ChemCAD simulation is given in Table 2.

Table 3. ChemCAD stream data for top stream 37 (Flash Top) for vapour-phase feed to distillation column. (Conditions: T = 40.0 °C, P = 1.5 atm (1.52 bar), vapour fraction = 1.0, total enthalpy = −35,326.1 MJ/h).

Parameter	Value	Unit
Total mass flow	6,475.5	kg h⁻¹
Temperature	40.0	°C
Pressure	1.52	bar
Enthalpy	−35,326.1	MJ h⁻¹
DME	1,108.3	kg h⁻¹
Methanol	473.5	kg h⁻¹
Water	182.9	kg h⁻¹
Methane	500.8	kg h⁻¹
Carbon dioxide	1,375.5	kg h⁻¹
Carbon monoxide	2,768.1	kg h⁻¹
Hydrogen	66.4	kg h⁻¹

Table 3. ChemCAD stream data for top stream 37 (Flash Top) for vapour-phase feed to distillation column. (Conditions: T = 40.0 °C, P = 1.5 atm (1.52 bar), vapour fraction = 1.0, total enthalpy = −35,326.1 MJ/h).

Parameter	Value	Unit
Total mass flow	6,475.5	kg h⁻¹
Temperature	40.0	°C
Pressure	1.52	bar
Enthalpy	−35,326.1	MJ h⁻¹
DME	1,108.3	kg h⁻¹
Methanol	473.5	kg h⁻¹
Water	182.9	kg h⁻¹
Methane	500.8	kg h⁻¹
Carbon dioxide	1,375.5	kg h⁻¹
Carbon monoxide	2,768.1	kg h⁻¹
Hydrogen	66.4	kg h⁻¹

The stream is entirely vapour at 40 °C and 1.52 bar. CO₂ dominates on a molar basis at 40.63 mol%, followed by hydrogen (13.54 mol%), methane (12.84 mol%), and CO₂ (12.85 mol%). Together these four light gases account for 79.9 mol% of the feed entering the distillation column. DME is present at only 9.89 mol% (17.1 wt.%), reflecting the fact that at 1.52 bar and 40 °C the vapour pressure of DME is above atmospheric and it remains in the gas phase rather than condensing into the liquid fraction of the flash separator.

The dominance of CO at 2,768.1 kg/h (40.63 mol%) is a direct consequence of the stoichiometric mismatch between the dry reforming product and the requirements of methanol synthesis. The DRM stage produces syngas at H₂:CO at 0.93, whereas methanol synthesis requires H₂:CO at 2.0–2.5 for optimal conversion. The unconverted CO passes through the methanol reactor, the dehydration reactor, and the flash separator essentially unchanged and accumulates in the stream alongside residual CO₂ (1,375.5 kg/h), which represents both unreacted feed CO₂ and CO₂ produced by the reverse water-gas shift reaction inside the methanol synthesis reactor. The practical consequence for the distillation column is a very high non-condensable gas load relative to the DME content, which demands either a substantial pre-separation step in an optimized design, or acceptance of a large compressor duty to bring all gases to the column pressure. Methanol is present at 473.5 kg/h (6.08 mol%), representing unconverted methanol from the dehydration reactor. A per-pass methanol conversion of 80–85 % in the dehydration step is consistent with the Bercic–Levec kinetics used in the simulation [16], and the methanol that bypasses conversion partitions between the liquid and vapour phases at the flash conditions. That 473.5 kg/h reports to the vapour at 1.52 bar indicates that the flash separator is not cold enough to fully condense the methanol fraction, which is consistent with the vapour pressure of methanol at 40 °C.

Figure 2. Component mass-fraction distribution in Stream 37 (Flash Top, column feed) and Stream 35 (distillation column 1 Top, column product). DME is enriched from 17.1 wt.% in the feed to 78.3 wt.% in the overhead product? a 4.6-fold mass enrichment. CO₂ co-distils with DME.

Figure 2. Component mass-fraction distribution in Stream 37 (Flash Top, column feed) and Stream 35 (distillation column 1 Top, column product). DME is enriched from 17.1 wt.% in the feed to 78.3 wt.% in the overhead product? a 4.6-fold mass enrichment. CO₂ co-distils with DME.

4.2. Distillation Column separation

The stream for the DME separation in the first distillation column (T-101) enters as fully superheated vapor at 40 °C and 1.52 bar. The column overhead product is specified at 10.13 bar and the calculated product state is a fully condensed liquid. The pressure increase from the feed to the column therefore requires the vapor feed to be compressed from 1.52 to 10.13 bar, a pressure ratio of about 6.7:1. The operation of the DME purification column at elevated pressure is consistent with similar process simulation research that have performed DME distillation at pressure conditions between 10–15 bar for the purpose of condensation and downstream product recovery [22,23]. Stage numbers have vary depending on the separation specification and feed composition, with reported designs including 10 stages at 15 bar for CO₂-derived DME and 32 stages at 10 bar for a high-purity DME separation [22,23]. The selection of 8 theoretical stages in the present study is not a general rule of the literature but a compact column configuration adapted to the simulated feed and separation. The final number of stages was decided by the stringent ChemCAD calculation and the required DME separation performance.

Table 3 gives the full composition of the overhead top product, which carries 333.5 kg/h of condensed liquid at −39.9 °C and 10.13 bar. DME accounts for 261.0 kg/h (78.3 wt.%), making it the dominant component. CO₂ is the second-largest component at 54.0 kg/h (16.2 wt.%), and MeOH contributes 18.2 kg/h (5.5 wt.%). All other species, including water, methane, CO, and H₂, are present at trace levels below 0.1 wt.% each.

Table 4. Full composition of top distillation column from the SCDS simulation. Conditions: T = −39.9 °C, P = 10.0 atm (10.13 bar), vapour fraction = 0.0, total enthalpy = −1,835.4 MJ h⁻¹. Molar flows calculated from ChemCAD mass flows using standard molecular weights.

Component	Mass flow (kg/h)	Molar flow (kmol/h)	Mole frac. (mol%)
Dimethyl ether (DME)	261.011	5.666	75.80
Methanol	18.246	0.569	7.62
Water	0.118	0.007	0.09
Methane	0.031	0.002	0.03
Carbon dioxide	53.978	1.226	16.41
Carbon monoxide	0.107	0.004	0.05
Hydrogen	0.002	<0.001	0.01
Total	333.493	7.474	100.00

Table 4. Full composition of top distillation column from the SCDS simulation. Conditions: T = −39.9 °C, P = 10.0 atm (10.13 bar), vapour fraction = 0.0, total enthalpy = −1,835.4 MJ h⁻¹. Molar flows calculated from ChemCAD mass flows using standard molecular weights.

Component	Mass flow (kg/h)	Molar flow (kmol/h)	Mole frac. (mol%)
Dimethyl ether (DME)	261.011	5.666	75.80
Methanol	18.246	0.569	7.62
Water	0.118	0.007	0.09
Methane	0.031	0.002	0.03
Carbon dioxide	53.978	1.226	16.41
Carbon monoxide	0.107	0.004	0.05
Hydrogen	0.002	<0.001	0.01
Total	333.493	7.474	100.00

The DME concentration of 75.8 mol% in the overhead product is lower than the purity anticipated for fuel-grade DME as stipulated from the current ASTM D7901-23 specification for DME in fuel applications and DME/LPG blending [24]. The main impurities in the simulated overhead are CO₂ (16.4 mol%) and MeOH (7.6 mol%), indicating that the first distillation column primarily concentrates the DME but does not fully remove the light CO₂ fraction or the heavier methanol fraction. The high CO₂ content is thermodynamically feasible since CO₂ has good solubility in liquid DME at high pressure [25]. Therefore, the separation of CO₂ in DME is one of the harder steps in the purification of DME. At the simulated condenser condition of −39.9 °C and 10.13 bar CO₂ is below its critical temperature and should therefore not be described as supercritical. The operating point is rather close to the CO₂ vapour-liquid equilibrium region. This phase behavior may contribute to the retention of CO₂ in the condensed DME-rich phase and thus limit the achievable DME purity. The simulated methanol (7.6 mol %) also indicates that the methanol is not completely rejected in the first distillation step. Sequential separation has been used in similar CO₂ to DME process simulations, which allows the recovery of DME in the first column and methanol and water to be sent to further purification, which demonstrates the importance of downstream separation design for high purity DME [16].

Figure 3. Component mass-flow comparison between distillation feed and product, illustrating the 23.6 % single-pass DME recovery and the large CO and CO₂ loads that dominate the feed but are largely rejected to the column bottoms.

Figure 3. Component mass-flow comparison between distillation feed and product, illustrating the 23.6 % single-pass DME recovery and the large CO and CO₂ loads that dominate the feed but are largely rejected to the column bottoms.

The 8 stage column shows a significant concentration of DME with a molar enrichment of 7.67 times from 9.89 mol% in the feed to 75.80 mol% in the overhead product. Additionally, CO, H₂ and CH₄ were also rejected from the overhead. The calculated rejection of each component was more than 99.9%, indicating the main non-condensable species were effectively rejected from the DME-rich product. The crucial feature of the feed-to-overhead split is the 16.4 mol % CO₂ remaining in the condensed product. The operating point at −39.9 °C and 10.13 bar is close to the saturation conditions of pure CO₂, the saturation pressure of CO₂ at −40 °C is approximately 10.0 bar, while the critical point is approximately 31.0 °C and 73.8 bar. Thus, the CO₂-rich component is in a region where small changes in temperature, pressure and composition can have a large effect on phase behavior. The CO₂–DME system is characterised by a high affinity between the two components, which makes their separation thermodynamically difficult, a behavior that has been explicitly considered in recent DME purification studies using equation-of-state-based VLE models [25]. Experimental studies of CO₂-DME mixtures have also shown that the critical temperature and pressure of the mixture depend strongly on composition and Peng-Robinson calculations predict the measured critical properties with reasonable accuracy [26]. The 16.4 mol% CO₂ predicted by the present NRTL calculation is physically consistent with the documented non-ideal phase behavior of the CO₂–DME system, although the present comparison should be seen as qualitative rather than as an independent validation of the NRTL parameterisation.

4.3. Mass Balance Closure and Carbon Utilization

A carbon-balance check on the simulation data provides an internal consistency check of the simulation. The feed consists of 1,108.3 kg/h DME, 473.5 kg/h methanol and 1,375.5 kg/h CO₂, which corresponds to a carbon mass flow of about 1,380 kg C/h in organic and CO₂ form. The top product of the distillation contains 261.0 kg/h DME, 18.2 kg/h methanol and 54.0 kg/h CO₂, i.e. a carbon mass flow of about 334 kg C/h. The remainder, some 1,046 kg C/h, is in the column bottoms in methanol, water and trace DME. The carbon balance is within expected rounding tolerance of the stream data. The overall process carbon utilization efficiency (CUE) on a single pass, once through basis is 5.2% as the fraction of feed carbon from CO₂ and CH₄ appearing as DME carbon in the process product stream. In addition to energy and economic metrics, carbon-utilization metrics are increasingly being used to assess the performance of CO₂-to-DME processes [13]. Recycle loop for unconverted carbon containing species, allows for better utilization of carbon by recycling the carbon to the synthesis section instead of rejecting it directly from the process [27].

4.4. Downstream Separation and DME Recovery

The downstream purification section was evaluated from a techno-economic perspective to determine the effectiveness of the separation strategy for recovering DME from the crude reactor effluent. The separation train consists of a primary flash separator, gas compression, refrigerated cooling, a secondary flash separator, and a conventional distillation column. This staged configuration was selected to progressively remove non-condensable gases and concentrate condensable oxygenates before final purification, thereby reducing the separation duty imposed on the distillation column [25]. The primary flash separator removed a significant proportion of condensed water while retaining most of the DME within the vapour phase together with CO, CO₂, CH₄ and H₂. The vapour stream was subsequently compressed to 10 atm and cooled to 10 °C, increasing the dew point of the condensable species and promoting condensation in the second flash separator. Consequently, the bottom product of the second flash separator became a concentrated liquid feed containing predominantly DME, methanol and water, whereas most of the permanent gases remained in the vapour phase [16]. This intermediate concentration step reduced the gas loading entering the distillation column and represents an important process intensification strategy because the column no longer processes the full reactor effluent but only the condensed oxygenate-rich fraction [28].

The distribution of DME across the separation train is summarized in Table 4. The vapour leaving the first flash separator contained 1108.28 kg/h of DME, while the condensed liquid recovered in the second flash separator contained 237.05 kg/h of DME and was subsequently fed to the distillation column. The distillation overhead recovered 261.01 kg/h of DME, corresponding to a column recovery of approximately 90.82% based on the DME entering the column. These results demonstrate that the distillation column itself performs efficiently, with negligible DME losses during purification. However, only 19.1% of the total DME entering the separation section reaches the column because the remaining DME leaves with the vapour stream from the flash separation stage. The overall process recovery is therefore limited by the upstream flash separation rather than by the distillation operation itself. This finding has important implications for process optimization because increasing the number of distillation stages or the reflux ratio would provide little additional benefit unless the recovery of DME during flash condensation is simultaneously improved.

Table 5. DME distribution through the downstream purification process.

Separation stage	DME (kg h⁻¹)
Flash 1 vapour (after primary flash)	1108.28
Flash 2 bottom (feed to Distillation 1)	237.05
Distillation 1 overhead	261.01

Table 5. DME distribution through the downstream purification process.

Separation stage	DME (kg h⁻¹)
Flash 1 vapour (after primary flash)	1108.28
Flash 2 bottom (feed to Distillation 1)	237.05
Distillation 1 overhead	261.01

From an economic perspective, the principal operating costs of the purification section arise from gas compression, refrigeration and reboiler duty. The refrigeration system is required to cool the compressed vapour sufficiently to condense DME and methanol before distillation, while the distillation column operates with a reboiler duty of approximately 901 MJ/h to achieve the desired separation. Although these utilities increase the operating expenditure, the staged separation strategy reduces the vapour throughput of the column, enabling efficient recovery of DME from a significantly smaller liquid stream. The additional capital investment associated with the compressor, chiller and secondary flash separator is offset by improved column performance and reduced separation complexity. Similar staged condensation and purification strategies have been reported for oxygenated fuel synthesis processes, where upstream condensation reduces downstream separation costs and improves process operability [29,30]. The present process represents a once-through configuration and therefore does not include recycling of the DME-rich vapour leaving the flash separation stage. Future process development should prioritize optimization of the flash separation and recycle configuration rather than further refinement of the distillation system.

5. Conclusions

Steady-state ChemCAD simulation of an integrated three-stage process for dimethyl ether (DME) production from carbon dioxide and methane via dry reforming, methanol synthesis and methanol dehydration has been successfully developed. The simulation combined kinetic reactor models with rigorous thermodynamic calculations to establish a complete process flowsheet comprising reaction, flash separation, compression, refrigeration and distillation. The DRM reactor provided efficient syngas generation, while the methanol synthesis and dehydration reactors achieved methanol conversion of approximately 80% and DME selectivity consistent with values reported for industrial γ-Al₂O₃ catalysts. The downstream purification section produced a DME-rich overhead product with a purity of 90.82%, demonstrating the suitability of the proposed separation strategy for high-purity DME production. The second flash separator recovered approximately 23.6% of the available DME into the condensed phase, confirming that flash condensation rather than distillation represents the principal opportunity for improving overall DME recovery. The preliminary techno-economic assessment showed that staged flash separation combined with compression, refrigerated cooling, and distillation provides an effective purification strategy by reducing the vapour load entering the distillation column and improving separation efficiency. Although these additional unit operations increase utility requirements, they contribute significantly to product purification and process operability. The developed simulation therefore provides a robust engineering framework for evaluating integrated DME production from greenhouse gas feedstocks and establishes a reliable basis for subsequent process optimization and scale-up studies. The process configuration developed in this study establishes a robust engineering platform for the design and evaluation of integrated DME production systems. The simulation framework can be readily applied to process optimization, heat integration studies, scale-up analysis, supporting the continued development of sustainable DME production from carbon dioxide and methane.