Biomass-Derived Syngas Chemical Looping Combustion Using Fluidizable Oxygen Carriers: A Review

Abstract

This critical review evaluates chemical looping combustion using a syngas derived from gasified biomass (BMD Syngas). It is anticipated that establishing such a process will open new opportunities for CO₂ sequestration and the use of highly concentrated CO₂ in the manufacturing and synthesis of fuels from entirely renewable feedstocks. This review focuses on the process conducted through using two interconnected fluidized bed units: a nickel oxide reduction unit (an endothermic Fuel Reactor) and a nickel oxidation unit (an exothermic Air Reactor). In this respect, a high-performance OC (HPOC) with Ni on a γ-Al₂O₃ fluidizable support (20wt% Ni, 1wt% Co, 5wt% La/γ-Al₂O₃) was developed at the CREC (Chemical Reactor Engineering Centre) of the University of Western Ontario, Canada. The HPOC was studied in a CREC Riser Simulator. The benefits of this mini-fluidized unit are that it can be operated at 2–40 s reaction times, 550–650 °C temperatures, 1.3–2.5 H₂/CO ratios, and 0.5–1 biomass/syngas stoichiometric ratios, mimicking the conditions of industrial-scale CLC units. When using a syngas derived from biomass and the HPOC under these operating conditions, 90% CO, 92% H₂, and 88% CH4 conversions, together with a 91% CO₂ yield, were obtained. These results allowed the prediction of a 1.84–3.0 wt% ($g_{O_2}/g_{{OC}_{}}$) oxygen transport capacity, with a 40–70% nickel oxide conversion. The experimental data acquired with the CREC Riser Simulator permitted the development of realistic kinetic models. The resulting kinetics were used in combination with Computational Particle Fluid Dynamics (CPFD) to demonstrate the operability of a large-scale industrial syngas CLC process in a downer fuel unit. In addition, these CPFD simulations were employed to corroborate that high CO₂ yields are achievable in 12–15 m length downer fuel units.

1. Introduction

The demand for energy is expected to rise by 60% by 2030, with 85% of this energy anticipated to come from fossil fuels [1]. The combustion of fossil fuels yields greenhouse gases containing CO₂, Nox, and CH₄. Of these three gases, CO₂ is the species that has the most significant impact on global warming. CO₂ is released via point sources from power stations, and via distributed sources from automobiles. Fossil-fueled power plants contribute significantly to worldwide CO₂ emissions (~33–40%) [2]. Therefore, it is in these facilities where the application of CLC (chemical looping combustion) shows the best prospects.

CLC is a promising technology that displays unique features. It can provide inherent CO₂ separation, yielding highly concentrated CO₂ with little nitrogen [3,4]. In addition, a CLC method that employs carefully selected oxygen carriers can provide CO₂ ready for capture. This process is highly thermally efficient and uses flameless combustion, yielding small amounts of nitrogen oxide (NO_x).

CLC has been applied by utilizing a number of fossil fuels such as natural gas, coal, crude oil, and various petroleum fractions. However, CLC can also provide a unique alternative for the conversion of renewable feedstocks such as biomass. Biomass is produced naturally. Furthermore, biomass can be converted into a syngas in gasifiers, yielding CO and H₂, together with minor CH₄ and CO₂ fractions. The BMD syngas for CLC has significant value, since it creates energy with minimum ecological impact [5]. The condensation of the water from the CLC outlet stream can lead to a highly concentrated CO₂ gas, ready to be buried. Alternatively, this CO₂ can be used together with green hydrogen produced via water electrolysis or photocatalysis for the synthesis of green fuels.

The availability of oxygen carriers (OCs) is still a concern in large-scale CLC unit implementation. In this respect, Ni, Cu, Co, Fe, and Mn are known possible OC candidates. Detailed reviews of the performance of these oxygen carriers can be found elsewhere [6,7]. However, a major concern is if the proposed oxygen carriers will be able to perform under the typical operating conditions of large-scale industrial units. With this in mind, a fluidizable Ni-based high-performance oxygen carrier (HPOC) with a La-Co modified γ-Al₂O₃ support was developed and evaluated by our team in a fluidized CREC Riser Simulator [8,9,10]. Given the demonstrated potential of this HPOC and its significant prospects for CLC technology, this review aims to provide an overview of OCs reported in the open literature in terms of reactivity, stability, and carbon formation while comparing them to the HPOC under study. This review also assesses the BMD syngas CLC conversion process thermodynamics and demonstrates that the CREC Riser Simulator is a unique experimental tool to evaluate and develop the CLC reduction kinetics of HPOCs. Furthermore, the developed HPOC reduction kinetics are shown to be valuable when used in conjunction with the Barracuda simulations of a combined CLC downer–riser circulating fluidized bed industrial process. This allows one to anticipate the favorable fluidizable HPOC performance in large-scale CLC short contact time reactors using a biomass-derived syngas.

2. The Chemical Looping Combustion (CLC) Process

Lewis and Gilliland were the first to suggest the concept of CLC in 1954 [11]. Subsequently, Lewis et al. [12] proposed a similar approach for producing pure CO₂ from a hydrocarbon gas. It was anticipated that the CLC system can operate with high thermal efficiency and minimum energy losses in power plants [13]. It was argued that CLC can achieve 50–60% electrical efficiency in a 0.33 kg CO₂/kWh power integrated process [14].

CLC can be configured using two interconnected circulating fluidized bed units: an Air Reactor and a Fuel Reactor, as depicted in Figure 1. The OC particles are circulated between the Fuel Reactor and the Air Reactor to be reduced by the fuel and oxidized by air, respectively. The Air Reactor is equipped with heat exchangers using vertical tubes to minimize the disturbance on the particle flow while allowing significant heat transfer.

CLC yields an exiting combustion gas composed mainly of CO₂ and water vapor, with minor amounts of other trace pollutants. By condensing the water vapor, CLC gives a highly concentrated CO₂. This free-of-water CO₂ is available to be sequestrated or eventually used in applications, such as the synthesis of jet fuel.

A description of the overall CLC reaction stoichiometry for the processing of syngas is provided below, with M_yO_x representing a generic metal oxide, using Equations (1) and (2):

Fuel Reactor: Reduction

$$\left(n+m+4k\right)M_y{O}_x+nCO+{mH}_2+kC{H}_4\rightleftharpoons \left(n+m+4k\right)M_y{O}_{x-1}+{(m+2k)H}_{2}O+{(n+k)CO}_2$$

(1)

Air Reactor: Oxidation

$$M_y{O}_{x-1}+{\displaystyle \frac{1}{2}}{O}_2\rightleftharpoons M_y{O}_x$$

(2)

Once the fuel combustion is complete, the reduced metal-oxide M_yO_x−1 (OC) is transported to the Air Reactor where it is reoxidized with the oxygen from air, as described with Equation (2). As a result, this gives an exit stream from the Air Reactor, containing nitrogen as the major component and minor amounts of oxygen. Thus, exit gases are released with minimum negative environmental impact.

3. CLC Process Thermodynamics

The CLC process is subject to two important thermodynamic constraints as follows: (a) thermal levels have to be high enough to attain significant CLC conversions, and (b) the selected temperatures for the redox reactions (Equations (1) and (2)) must be below the OC material temperature limits.

A thorough CLC thermodynamic analysis was reported by McGlashan et al. [15]. This analysis considered the overall CLC process as being similar to the one of an internal combustion (IC) engine. On this basis, the overall process efficiency was determined by using the generated shaft work (W_s1). Figure 2 shows a representation of a CLC process while employing a NiO-based oxygen carrier.

In a BMD syngas CLC process, the resulting shaft work ($W_{s_1}$) involves both the Air Reactor and the Fuel Reactor net enthalpies and the unit heat losses ($Q_{o_1}+Q_{o_2}+Q_{hot}$), as described in Figure 2. In particular, and assuming that $Q_{o_1}+Q_{o_2}\approx 0$ (adiabatic units) in both the oxidizer reactor and the reducer reactor, the overall efficiency can be defined as follows:

$${\eta }_{CLC,syngas}=\mathrm{Ø}{\eta }_{thermalengine1}$$

(3a)

$${\eta }_{thermalengine1}=W_{s_1}/(\Delta H_o)oxidation$$

(3b)

with $W_{s_1}$ representing the work performed in the CLC loop and $\mathrm{Ø}=(\Delta H_o)oxidation/(\Delta H_o)syngas.$

Furthermore, by applying the assumptions described by McGlashan et al. [15], a high reversible efficiency of the BMD syngas CLC system can be established as follows:

$${\eta }_{CLC}={\displaystyle \frac{\mathrm{Ø}-\mathsf{\Omega }}{\mathrm{Ø}\left(1-\mathsf{\Omega }\right)}}\mathrm{w}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{Ø}={\displaystyle \frac{{(∆H}_o)oxidation}{{(∆H}_o)syngas}}\mathrm{a}\mathrm{n}\mathrm{d}\mathsf{\Omega }={\displaystyle \frac{{(\Delta S_o)}_{\mathit{oxidation}}}{{(\Delta S_o)}_{\mathit{syngas}}}}$$

(4)

On this basis, and by using the data reported in

Table 1. Enthalpies and entropies of reduction and oxidation for two types of BMD syngas at 298 K. Notes: (a) Syngas-133, (b) Syngas-250. Further details provided in Appendix A.

	ΔHreduction (kJ/mole O)	ΔHoxidation (kJ/mole O)	ΔHBMD syngasl (kJ/mole O)	ΔSoxidation (kJ/mole O °K)	ΔSfuel (kJ/mole O °K)	ψ	Ω	ηrev
Syngas-133	2.498	−240.1	−238.0	0.2338	0.04001	1.008	6.94	99.0%
Syngas-250	6.391	−240.1	−234.3	0.2423	−0.0362	1.024	5.37	97.0

, a ${\eta }_{CLC}$ efficiency of 97–99% for CLC was obtained when using NiO as oxygen carrier and syngas as a fuel. It is also expected that given that the proposed NiO-γAl₂O₃ oxygen carrier is limited in its operability because it cannot be used at temperatures above 700 °C, its net CLC efficiency in the twin circulating beds (Air Reactor and Fuel Reactor) is 48.6%, as described with Equation (5):

$$\eta ={\eta }_{CLC}{\eta }_{theramalengine2}=0.98{\displaystyle \frac{(T\_hot-T\_cold)}{T_{cold}}}=0.98{\displaystyle \frac{973\mathrm{K}-500\mathrm{K}}{973\mathrm{K}}}100=48.6\mathrm{\%}$$

(5)

with ${\eta }_{CLC}$ being the efficiency of the CLC unit, and ${\eta }_{thermalengine2}$ being the theoretical Carnot efficiency, converting $Q_{hot}$ into electrical power.

In summary, the reported results show that NiO-based OCs have the potential to be valuable for industrial CLC applications that use BDM syngas. This is because, in this case, the ${\Delta H}_{reduction}$ is much smaller than the ${\Delta H}_{oxidation}$, with most of the available enthalpy being utilized for power generation.

4. Oxygen Carrier Requirements

4.1. Oxygen Carriers for CLC

The various requirements for an enhanced OC performance are listed below [6,7]. They include the following:

• Favorable OC thermodynamics for BMD syngas conversion via CLC at the selected temperatures and pressures [16,17]. This is important to minimize the endothermic nature of the OC reduction reactions.
• An OC with good fluidizability properties at the anticipated CLC operating conditions. This is essential for a CLC process configured with circulating beds where fluidization in both the Air and the Fuel Reactor is considered.
• An OC with a high capacity for oxygen transport from the Air Reactor to the Fuel Reactor. This is significant to minimize the OC recirculating flow.
• An OC showing high reactivity and high stability in both the Air Reactor and the Fuel Reactor. This is important to decrease the CLC operational process costs, given that, without these properties, frequent replacements of the used OC with a fresh OC sample will be required.
• A high resistance of the OC to particle attrition with little elutriated solids and negligible solid agglomeration. This is critical to minimize oxygen carrier losses and frequent oxygen carrier replacement impacting in the CLC process operational costs.
• A small carbon deposition on the OC in the Fuel Reactor. If this is not the case, the deposited carbon on the OC, released in the Air Reactor as CO₂, will reduce the desired high CO₂ separation efficiency of the CLC process.
• An OC with a low manufacturing cost and with insignificant environmental impact.

Furthermore, and regarding the various OC properties, one can notice that pure metal oxides do not comply with the above described criteria, with reactivity declining after several redox cycles [18]. This points to the fact that a good OC having a high specific surface area with good fluidization characteristics and high attrition resistance such as is the case with γ-Al₂O₃ [19] is a must for CLC to be implemented successfully.

4.2. OC Preparation Methods

OC preparation methods have an important influence on OC performance and OC stability. Several well-established methods are available for OC preparation, such as the following: (a) co-precipitation, (b) freeze granulation, (c) incipient wetness impregnation, (d) natural mineral grinding, (e) sol–gel, (f) spray drying, and others. These methods were initially developed for catalysts [20] and then were extended to OCs.

Table 2. Oxygen carrier preparation methods.

Method	Advantages and Disadvantages	References
Co-Precipitation	Pros: (i) OCs display high reactivity, (ii) OCs give good metal dispersion. Cons: (i) OC preparation method has a relatively high cost, (ii) OC particle size distributions are unsuitable for fluidized CLC.	[22,23,24]
Freeze Granulation	Pros: (i) OCs have high mesoporosity, (ii) OCs are manufactured from homogenous precursors. Cons: (i) OCs are expensive, (ii) manufactured OCs have wide particle size distributions, (iii) OC preparation requires a binder, (iv) OCs have low mechanical strength.	[25,26]
Wet/Incipient Wetness Impregnation of Fluidizable Supports	Pros: (i) OCs can be impregnated on fluidizable supports with the required particle size distribution, (ii) OCs are suitable for large-scale production. Cons: (iii) OC supports may promote agglomeration, (iv) Metal addition to the fluidizable support may require several impregnations until the appropriate loading is reached, making OC preparation more expensive.	[9,26,27,28]
Natural Mineral Griding	Pros: (i) Low-cost OC preparation using natural minerals, with a desirable particle size is achieved via ball mill grinding. Cons: (ii) Additives are needed for OC particle sizing, (iii) OCs may display poor fluidizability, poor resistance to sintering, and high attrition, (iv) OCs have low metal dispersion, and limited specific surface area, (v) There is a reduced OC performance stability given that mineral impurities may promote particle agglomeration.	[27,28,29]
Sol–Gel	Pros: (i) Good control of OC morphology, and particle size, (ii) Stable OCs, and redox reactivity. Cons: (i) Costly OCs for large-scale fluidized CLC processes.	[30,31,32]
Spray Drying	Pros: (i) Good control of OC particle properties including particle size and fluidizability. Cons: (i) OC particles may have limited surface area metal oxides exposed and as a result provide limited reactivity.	[26,33]

reports different oxygen carrier preparation methods along with their advantages and disadvantages [21].

When the pros and cons of these OC preparation methods are evaluated, the incipient wetness impregnation appears to be the most suitable in order to accomplish high metal dispersion over a selected support [34,35,36]. Furthermore, from the various methods listed, it was found that the incipient wetness impregnation provides the best control of metal loading, given that essentially all of the OC precursor containing solution components are quantitatively transferred to the OC support during support impregnation. One has to consider, however, that the incipient wetness impregnation, while being feasible for large-scale OC preparation, requires special care in order to prevent non-uniform metal dispersion in the OC support pore structure. Given all of these issues, the HPOC developed by our research team was synthesized using incipient wetness impregnation.

4.3. Proposed Oxygen Carriers

Research studies have been conducted employing Ni, Cu, Mn, Co, and Fe as OCs. In addition, various metal oxide supports (e.g., Al₂O_3, TiO_2, SiO_2,) have also been considered to develop stable and fluidizable oxygen carriers.

Table 3. Oxygen carriers used in CLC units larger than 2 kW.

No.	Oxygen Carrier (OC)	Thermal Power (Testing Unit Location)	Fuel Conversion (OC to Fuel Ratio)	Synthesis Method	References
1	Natural gas/Ca-Mn-based OC	1000 kW (Germany)	80% (5)	Spray Drying	[37]
2	Methane/CuO-Fe2O3/Alumina	50 kW (USA)	50 to 65%	Spray Drying and Wet Granulation	[38]
3	Methane/CuO/γ-Alumina	150 kW (Norway)	90% −150 kW 98% −100 kW	Incipient Wetness Impregnation	[39]
4	Syngas, CH4/Iron ore/	2 kW (China)	93%	n/a	[40]
5	Methane/NiO/NiAl2O4/	10 kW (France)	99%	Precipitation	[41]
6	Natural gas/NiO/MgAl2O4 and NiAl2O4	10 kW (Sweden)	98%	Spray Drying and Freeze Granulation	[42]

reports the OCs frequently used in pilot-scale testing, as reported in the technical literature. Table 3 also provides comments regarding the following: (a) the type of testing units larger than 2 kW unit used, (b) the fuel conversion performance obtained, and (c) the synthesis methods of the OCs used.

OC particles may cluster or form unwanted chemical species via metal–support interactions [43,44,45]. Thus, an OC should also be selected with the objective of minimizing such effects.

As a result, and based on thermodynamics (refer to Section 3), NiO is considered as a good option for CLC. However, non-supported NiO particles showed modest performance in repetitive redox cycles. This was assigned to the Ni crystallites tendency to form agglomerates [46]. In contrast, NiO dispersed on γ-Al₂O₃ could be considered as an attractive option for CLC. The γ-alumina support provides high stability to the OC at high temperatures [47,48,49]. Furthermore, the γ-Al₂O₃ support particles display excellent fluidization properties, making the prepared OC appropriate for fluidized bed CLC processes.

However, when employing dispersed NiO on an γ-Al₂O₃ support, unwanted interactions between the metal oxide and the support may occur, with this leading to NiAl₂O₄ formation [34,35,50]. To account for this undesirable event [51], NiAl₂O₄ itself has been proposed as a support instead. However, the use of NiAl₂O₄ as an OC support limits the nickel crystallite density on the OC surface, making the CO₂ yield of the CLC process less predictable. Thus, it can be seen that there are still significant challenges that need to be addressed in the implementation of NiAl₂O₄ as a support for OCs.

Concerning Ni-based OCs, it has been shown that they can provide a 1.84–6wt% oxygen transport capacity, with 40–50wt% NiO conversion at 750–1000 °C under excess oxygen conditions [52,53]. Nonetheless, these OCs display low stability due to metal support agglomeration. However, Ni-based OCs, modified with La and Co, display high thermal stability and very limited metal–support phase interactions [34,50]. It was demonstrated when evaluating the performance of these OCs, using methane as fuel, that they can yield a 1.84–3.45% -O- transport capacity and a 40–72% NiO conversion at lower temperatures (e.g., 600–680 °C).

5. NiO-Based Oxygen Carriers in BMD Syngas CLC

Nickel-based OCs have been used in several methane CLC studies. However, there is limited research that employs them in BMD syngas CLC.

Table 4. Syngas CLC studies using NiO-based OCs. Notes: Various designation codes are reported in the acronyms list.

NiO Loading (%)	Support	Preparation Technique	Reactants	Reactor Type	References
35	γAl2O3	COP	Coal, syngas + H2S, CO, O2	TGA, CLC	[54,55,56]
2.5–20	α-Al2O3	IMP	CH4, H2, O2	TPR, TPO, CREC-RS	[35,57,58]
18	α-Al2O3	IMP	Syngas, CH4, H2, CO	TGA, pxFB, CLC 300 W	[59,60,61]
5	Co-γAl2O3	IMP	CH4, O2	CREC-RS	[50,58]
20	La-γAl2O3	IMP	CH4, Biomass	CREC-RS	[62]
30	MgAl2O4	SC + MM	CH4, Syngas	TGA	[53]
20–40	NiAl2O4	SC + MM	CH4, H2, Syngas	TGA	[53,63]
60	NiAl2O4	DIS + SD	CH4, H2, Syngas	TGA, pFxB	[46,47,64]

reports a summary of the few syngas CLC studies where NiO-based OCs using α-Al₂O₃, γ-Al₂O₃, MgAl₂O₄, and NiAl₂O₄ supports were employed. Evaluations were developed by utilizing fixed bed thermogravimetric methods, temperature programmed oxidation and reduction methods, and the CREC Riser Simulator.

γ-Al₂O₃ has received much attention as an OC support due to its specific surface area (190 m²/g) and the availability of the provided surface area for nickel dispersion [65,66]. However, given the possible nickel aluminate formation, these OCs are recommended to be used at temperatures lower than 750 °C in order to minimize the undesirable presence of nickel aluminate species [36,67].

Furthermore, avoiding the NiAl₂O₄ formation by incorporating cobalt into the γ-Al₂O₃ is another good approach for OC manufacturing [34]. In addition, it was found that controlling the temperature during the preparation of the OC also has a very significant beneficial effect, preventing the formation of nickel aluminate, and as a result, positively affecting the performance of the OC. Thus, as a consequence, and considering all these findings, the CREC-UWO team was able to develop an HPOC with negligible contained amounts of NiAl₂O₄ [9].

6. Preparation of the High-Performance Oxygen Carrier (HPOC)

As already stated in Section 5, OCs can display poor stability due to NiAl₂O₄ formation. Thus, a Ni-based OC has to be modified to minimize these effects. To accomplish this, a HPOC based on using Ni on γ-Al₂O₃ with La and Co dopants was designed and implemented at the CREC-UWO [34,50]. It was shown that when evaluating the performance of this HPOC, when using methane as fuel, that the HPOC can yield a 1.84–3.45% oxygen transport capacity, and a 40–72% NiO conversion, at 600–680 °C [52,53]. It was also proven that the developed HPOC displays good thermal stability and little Ni–alumina support interactions.

These HPOCs were prepared using the incipient wetness technique [34]. The preparation of the HPOC required that a sieved γ-Al₂O₃ support (Sasol CATALOX^® SCCa 5/200, Sasol Limited, Sandton, Johannesbourg, South Africa) with 53–125 µm particles be added to a sealed conical glass flask. The used flask had a lateral outlet attached to a 250-mmHg vacuum line. Following this, the next steps carried out as follows:

(a) First Impregnation. La(NO₃)₃.6 H₂O in a water solution was added to the fluidizable alumina support. This was followed by the drying of the resulting paste at 140 °C for 4 h. The obtained solids were reduced at 750 °C over 8 h under fluidized bed conditions using a 10% H₂ balanced with Ar gas. La addition was performed in order to achieve a 5wt% La loading.

(b) Second Impregnation. A Co(NO₃₎₂.6 H₂O in a water solution was incorporated to the La–alumina particles under vacuum and intense solid mixing. This was followed by the drying of the resulting paste at 140 °C for 4 h, after which the solid particles were reduced at 750 °C for 8 h under fluidization conditions, employing a 10% H₂ balanced with an Ar gas. This was conducted to achieve 1wt% Co loading.

(c) Third Impregnation. Ni(NO₃)₂.6 H₂O in a water solution was added to the La–Co–alumina under vacuum and intense solid mixing. This was followed by the drying of the obtained paste at 140 °C for 4 h, after which the solids were reduced at 750 °C over 8 h in a fluidized bed, with 10% H₂ balanced with Ar. This was conducted to achieve 10wt% Ni loading. The Ni impregnation was repeated twice to reach a combined 20wt% Ni and to obtain a desired HPOC formulation of 20wt% Ni, 1wt% Co, and 5wt% La.

Furthermore, the HPOCs prepared at CREC-UWO laboratories were characterized by using several methods. These techniques included XRD, BET, H₂-TPO, TPR, NH₃-TPD, and pulse chemisorption. It was confirmed that the HPOC displayed favorable properties including (a) a 107.5 m²/g surface area, (b) a 0.35 cm³/g pore volume and a 146A average pore size, (c) 1.27% Ni dispersion, (d) 77A Ni crystallite sizes, (e) reduced support acidity, (f) very stable OC oxidation reduction cycles, and (g) the minimum formation of nickel aluminate. Additional details regarding both the HPOC preparation methods and the oxygen carrier characterization methods are reported in [10].

7. CREC Riser Simulator to Establish HPOC Performance

To evaluate HPOCs for BMD syngas CLC, it is important to develop reactivity studies. Our research team decided to use a batch mini-fluidized bed reactor unit, designated as the CREC Riser Simulator. This device was invented by de Lasa in 1992 [68,69], with further enhancements being introduced in 2019 [70,71]. While there are other possible laboratory bench reactor alternatives that can be used for the evaluation of CLC kinetic studies, the CREC Riser Simulator is the unit most recommended to match the reaction operating parameters of industrial-scale circulating fluidized beds. This is particularly the case if one envisions the CLC process as a combination of a twin Riser Air Reactor and a Downer Fuel Reactor unit, as described in Figure 1. This type of unit can assist in the development of kinetic models, helping with accurate simulation calculations and the design of large-scale CLC reactors.

In the last 25 years, in addition to CLC, the CREC Riser Simulator has helped to elucidate the kinetics of a number of catalytic reactions such as the following: (a) the steam and dry reforming of methane, (b) the catalytic and thermal gasification of biomass, (c) the oxidative hydrogenation of light gases, and (d) the catalytic desulfurization of gasoline, among others [34,66,72,73,74,75,76,77,78,79,80,81,82]. Regarding CLC, the methane CLC in the CREC Riser Simulator was developed by the CREC-UWO team in the early phases of our research [10,58]. In spite of its special features, there are no articles apart from those of the CREC research team [8,9] that study BMD syngas conversion under CLC’s short reaction times in the CREC Riser Simulator.

Figure 3a,b show the CREC Riser Simulator, which includes the reactor itself (catalyst basket, impeller, cooling jacket), and its auxiliary unit components (4PV, 6PV, vacuum box, mass flow controller, gas chromatograph).

The mini-fluidized CREC Riser Simulator is equipped with a rotating upper impeller and a central basket. The basket is manufactured with upper and lower grids in order to ensure that the solids (e.g., catalyst, OC) under evaluation are contained securely. The rotation of the impeller produces an upflow of gas in the center of the basket allows solid particles to be fluidized, with the recirculated gas flowing down in the outer basket section. Thus, this unit allows the fluidization of particles, with intense gas mixing. At 4000 rpm impeller rotational speeds, the high gas recirculation yields a quasi-constant gas phase species concentration. Given the strong gas mixing and simultaneous particle fluidization inside the CREC Riser Simulator basket, the CREC Riser Simulator operates as a “fluidized batch reactor” at quasi-isothermal conditions, as shown by Equation (6):

$$V_T{\displaystyle \frac{{dC}_i}{dt}}=r_{i}W$$

(6)

with V_T being the total reactor volume in cm³, C_i being the mass concentration of any of the “i” chemical species in g/cm³, t being the reaction time in seconds, r_i being the reaction rate of the species formed or consumed in grams of syngas species/(g_OC. s), and W being the mass of OC in grams.

Thus, and in agreement with Equation (6), reaction times in the CREC Riser Simulator are equivalent to residence times in a continuous riser reactor, or alternatively in a continuous downer reactor. This closeness of reaction times in the 2–40 s range allows one to anticipate the OC performance in CLC twin circulating fluidized beds.

Figure 4 displays the pressure profile occurring in a typical CREC Riser Simulator run, lasting 30 s. It shows the sudden pressure increase at the injection of syngas, followed by a modest augmentation of pressure during the OC reduction, and ending with an abrupt pressure decrease, which corresponds with the almost instantaneous evacuation of the reactor basket contents to the vacuum box. These gaseous species consist of the unconverted syngas, as well as formed CO₂ and water. Following this, these gaseous chemical species in the vacuum box are analyzed using a 6PV and gas chromatography unit, as shown in Figure 3b.

On the basis of the GC analysis and the data gathered from every run, the H₂, CO, and CH₄ syngas conversions, and the CO₂ yields, were calculated as follows:

$$SolidConversion,X_{NiO}\%={\displaystyle \frac{N_{OinGasproducts}-N_{Oinsyngasfed}}{N_{Oinsyngasfed}}}$$

(7)

$$SyngasSpeciesConversion,X_i\%=\left(1-{\displaystyle \frac{N_{i,product}}{N_{i,syngasfed}}}\right)\times 100$$

(8)

$$YieldC{O}_2,Y_{C{O}_2}\%=\left({\displaystyle \frac{N_{C{O}_2,product}}{{{(N}_{CO}+N_{C{H}_4}+N_{C{O}_2})}_{fed}}}\right)\times 100$$

(9)

with $N_i$ being the moles of $i$ species and with $i$ being either $CO$, $H_2$, $C{H}_4$, and $O$, denoting the moles of elemental oxygen.

Figure 5a,b report the typical results obtained when testing the HPOC with BMD syngas in the CREC Riser Simulator, mimicking the CLC process at ψ = 0.5 (moles of syngas/moles of NiO) and 550–650 °C. Here, one can see a progressive increase in the CO₂ yields reaching 90% with a 33% OC conversion at 40 s of reaction time.

Figure 5a shows that high 90% CO₂ yields can be achieved with $CO$, $H_2$, and $C{H}_4$ syngas component conversions exceeding 80%, as reported in Figure 6a,b, using a HPOC. This is the case under operating conditions mimicking those of an industrial CLC unit, with temperatures in the 550–650 °C range. These results show that temperatures in this range have a mild effect on OC performance.

8. CLC Reaction Network

In order to establish a syngas CLC reaction model for a NiO-based OC, a suitable reaction mechanism for the anticipated 550–650 °C conditions is required [83,84].

Equation (10) represents the overall stoichiometry, describing the oxidation of the NiO oxygen carrier in the Air Reactor as follows:

$$Ni+{\displaystyle \frac{1}{2}}{O}_2\to NiO;\Delta H^o=-240.1\mathrm{k}\mathrm{J}/\mathrm{m}\mathrm{o}\mathrm{l}$$

(10)

Table 5. Enthalpies of reaction at standard conditions and chemical equilibrium constants for the postulated NiO reactions in the fuel reactor. The formation species enthalpies and entropies are from [85,86].

Reactions Involving an NiO Oxygen Carrier	AHo (kJ/mole) T = 25 °C, 1 atm	Keq (Chemical Equilibrium Constants) T = 600 °C, 1 atm	Equation
$Reaction1:$ $C{H}_4+4NiO\leftrightarrow 4Ni+{CO}_2+2H_{2}O$	156.5	6.49 × 1048	(11)
$Reaction2:$ $C{H}_4+3NiO\leftrightarrow 3Ni+CO+2H_{2}O$	199.8	1.93 × 1036	(12)
Reaction 3: $C{H}_4+NiO\leftrightarrow CO+2H_2+Ni$	204	4.03 × 1011	(13)
Reaction 4: $H_2+NiO\leftrightarrow H_{2}O+Ni$	−43.27	1.36 × 109	(14)
Reaction 5: $CO+NiO\leftrightarrow Ni+C{O}_2$	−2.13	3.51 × 1012	(15)

describes a number of possible reactions, enthalpies of reaction, and equilibrium constants that can be calculated using the syngas components (CO, H₂, CH₄, CO₂), and a NiO-based HPOC. All of these reactions may contribute, to various extents, to the overall nickel oxide reduction as follows:

Table 5 also reports the chemical equilibrium constants (K_eq) at 600 °C and at 1 atm. These are the operating conditions close to the ones of industrial-scale CLC reactors. One can observe in Table 5, that Reactions 1, 2, 3, 4, and 5 all display Keq values much larger than 1. While the various reactions listed in Table 5 are thermodynamically allowed, in practice, Reaction 3 is preferred versus Reactions 1 and 2. This is the case given that Reaction 3 involves a single NiO site in every reduction step, and as a result, is considered as mechanistically more feasible [10,87].

Table 6. Enthalpies of reaction at standard conditions and chemical equilibrium constants for postulated gas phase species reactions in the Fuel Reactor.

Reactions Involving Gas Phase Species in the Fuel Reactor	AHo (kJ/mole) T = 25 °C, 1 atm	Keq, T = 600 °C, 1 atm	Equation
$Reaction6:C{H}_4+C{O}_2\leftrightarrow 2CO+2H_2\left(DRM\right);$	247	0.119	(16)
$Reaction7:CO+H_{2}O\leftrightarrow C{O}_2+2H_2\left(WGSR\right);$	−41.2	1.54	(17)
$Reaction8:C{H}_4+H_{2}O\leftrightarrow CO+3H_2\left(SRM\right);$	206	0.18	(18)

reports three additional reactions that may occur in CLC. These reactions involve gas phase chemical species that may potentially influence the CLC product distribution. These reactions are described in Table 5, as follows: (a) the dry reforming of methane (DRM-Reaction 6), (b) the water gas shift reaction (WGSR-Reaction 7), and (c) the steam reforming of methane (Reaction 8).

Table 6 shows that the dry reforming of methane (DRM), or Reaction 6, and the steam reforming of methane (SRM), or Reaction 8, are not favored thermodynamically, given that these reactions have Keq values of 0.119, and 0.18, respectively. Furthermore, one can also observe in Table 6 that the water gas shift reaction (WGSR), or Reaction 7, shows a Keq of 1.54 at 1 atm and 600 °C. Thus, while one can notice that the WGSR is moderately thermodynamically allowed, one can also observe that the prevailing oxidation state of the nickel species in the OC is NiO, as shown in Figure 5b. As a result, it was considered that the catalytic driven Reaction 7 does not have an influence in CLC, and that all these three reactions (Reactions 6, 7, and 8) can be omitted from the CLC kinetics model.

Finally, one is able to account for the coke in the CLC kinetic model by including the formation–consumption coke reactions as described via (19)–(22):

$$C+2H_{2}O\leftrightarrow CO+H_2$$

(19)

$$C+C{O}_2\leftrightarrow 2CO$$

(20)

$$C+2H_2\leftrightarrow C{H}_4$$

(21)

$$C+NiO\leftrightarrow Ni+CO$$

(22)

In this respect, one should note that the accounting of coke in CLC, both for the development of kinetics as well as for chemical equilibrium property predictions, is a challenging issue. For instance, the calculation of deposited coke using the C species, as shown in Equations (19)–(22), is an oversimplification and should not be used. On the other hand, the “x”, “y”, and “z” parameters of the recommended coke formula ($C_x{H}_y{O}_x$) cannot be established with certainty. This affects the exact formulation of coke reaction stoichiometries and their thermodynamic equilibria. Fortunately, the net coke formed in the CLC process under the conditions studied in the CREC Riser Simulator is very small [88], and therefore, the effect of coke on the overall CLC reaction network can be neglected.

Thus, it can be argued that based on various stoichiometric and thermodynamic considerations, one can select the following set of reactions for kinetic modeling: (a) Reaction 3 (Equation (13)), which is an irreversible reaction, and (b) Reactions 4 and 5 (Equations (14) and (15)), which include forward and backward reaction terms.

9. Kinetics of CLC Using HPOC

A kinetic rate equation for syngas CLC has to provide the needed information regarding HPOC conversion rates, in both reduction and oxidation cycles. The observed energies of activation for various Ni-based oxygen carriers on Al₂O₃ supports, reported in the technical literature, are shown in Table 7 [7].

One can observe in Table 7 that the magnitudes of the energies of activation obtained for methane, hydrogen, and carbon monoxide reduction are in the 39–78 kJ/mole, 26–96 kJ/mole, and 18–27 kJ/mole ranges, respectively. Furthermore, one can also notice that the oxidation energies of activation are in the 22–44 kJ/mole range for nickel oxidation. These are all indicators that point towards the value of implementing CLC processes at higher temperatures. While this is true, one should note that high temperatures are limited by the thermal stability of the selected OC, as is the case with the HPOC support which is limited to 750 °C.

However, for the simulation of the CLC process using a fluidizable HPOC, it is required to have available intrinsic syngas reduction kinetics. These kinetics are applicable to the small size HPOC particles (e.g., 30–100 micron range), and should involve rates not limited by particle mass and heat transfer. Furthermore, it was also desirable that the HPOC intrinsic kinetics be mechanistically sound, accounting for various possible phenomenological-based mechanistic steps such as the following: (a) nucleation, (b) geometrical contraction, (c) diffusion, (d) reaction order, and (e) Arrhenius law [89,90].

Both the Nucleation Nuclei Growth Model (NNGM) [66,91,92] and the Shrinking Core Model (SCM) [93,94,95] have been employed by others. However, from these two models, the NNGM has been the one favored by our research team [90]. The NNGM considers that once the nickel site reduction is finalized, only then is the oxygen reduction in the neighboring unreacted NiO site started. Factors in this analysis are given by the fact that metal crystallites dispersed in a porous support (e.g., γ-Al₂O₃) may have imperfections such as cracks, surface, and point defects [96]. The OC areas may provide nucleation sites where the activation energies display minimum values [97].

Table 7. Reduction and oxidation kinetic parameters reported in the technical literature for Ni-based OCs using various fuels.

OC/Support	Conditions/Reactants	Kinetics	Activation Energy (kJ/mole)	References
60wt% NiO/Al2O3	TGA (600–950 °C), H2 and CH4	SCM	$E_{C{H}_4}=78,$ $E_{H_2}=26$	[93,98]
20wt% NiO-/Al2O3	TPR-TPO (200–750 °C) H2 and O2	NNGM	$E_{H_2}=53,$ $E_{O_2}=45$	[58]
20wt% NiO/Co-Al2O3	TPO, TPR (200–750 °C) CREC-RS (650 °C) H2 and O2	NNGM	$E_{C{H}_4}=49,$ $E_{H_2}=45,$ $E_{O_2}=44$	[99]
20 wt% NiO/Al2O3	CREC-RS (680 °C) CH4	SCM, NNGM, PLM	$E_{C{H}_4}=39,44,51$	[35]
20wt% NiO/La-Al2O3	TPR,TPO (200–750 °C) CREC-RS (650 °C) H2 and CH4	NNGM	$E_{H_2}=73,$ $E_{C{H}_4}=70,$	[66]
40wt% NiO/NiAl2O4	TPR (300–600 °C)	SCM	$E_{H_2}=96,$	[63]
65wt% NiO/Al2O3	TGA (800–950 °C) H2 and CH4	SCM	$E_{C{H}_4}=55,$ $E_{H_2}=28,$ $E_{CO}=28$	[94]
15wt% NiO/Al2O3	Fixed Bed (600–900 °C) CH4, H2, CO	MVM	$E_{C{H}_4}=77,$ $E_{H_2}=26,$ $E_{CO}=27$	[100]
40wt% NiO/NiAl2O4	TGA (750–1000 °C) CH4, H2, CO	SCM	$E_{C{H}_4}=70,$ $E_{H_2}=35,$ $E_{CO}=34$	[101]
18wt% NiO/Al2O3	TGA (700–950 °C) H2, CO, O2	SCM	$E_{H_2}=20,$ $E_{CO}=18,$ $E_{O_2}=24$	[52]

Notes: (a) Model codes reported in the acronyms list, (b) $E_{C{H}_4},E_{CO},E_{H_2}$: energies of activation for CLC reactions involving methane, carbon monoxide, and hydrogen in the Fuel Reactor, respectively, and (c) $E_{O_2}$: energy of activation for nickel oxidation in the Air Reactor.

Table 7. Reduction and oxidation kinetic parameters reported in the technical literature for Ni-based OCs using various fuels.

OC/Support	Conditions/Reactants	Kinetics	Activation Energy (kJ/mole)	References
60wt% NiO/Al2O3	TGA (600–950 °C), H2 and CH4	SCM	$E_{C{H}_4}=78,$ $E_{H_2}=26$	[93,98]
20wt% NiO-/Al2O3	TPR-TPO (200–750 °C) H2 and O2	NNGM	$E_{H_2}=53,$ $E_{O_2}=45$	[58]
20wt% NiO/Co-Al2O3	TPO, TPR (200–750 °C) CREC-RS (650 °C) H2 and O2	NNGM	$E_{C{H}_4}=49,$ $E_{H_2}=45,$ $E_{O_2}=44$	[99]
20 wt% NiO/Al2O3	CREC-RS (680 °C) CH4	SCM, NNGM, PLM	$E_{C{H}_4}=39,44,51$	[35]
20wt% NiO/La-Al2O3	TPR,TPO (200–750 °C) CREC-RS (650 °C) H2 and CH4	NNGM	$E_{H_2}=73,$ $E_{C{H}_4}=70,$	[66]
40wt% NiO/NiAl2O4	TPR (300–600 °C)	SCM	$E_{H_2}=96,$	[63]
65wt% NiO/Al2O3	TGA (800–950 °C) H2 and CH4	SCM	$E_{C{H}_4}=55,$ $E_{H_2}=28,$ $E_{CO}=28$	[94]
15wt% NiO/Al2O3	Fixed Bed (600–900 °C) CH4, H2, CO	MVM	$E_{C{H}_4}=77,$ $E_{H_2}=26,$ $E_{CO}=27$	[100]
40wt% NiO/NiAl2O4	TGA (750–1000 °C) CH4, H2, CO	SCM	$E_{C{H}_4}=70,$ $E_{H_2}=35,$ $E_{CO}=34$	[101]
18wt% NiO/Al2O3	TGA (700–950 °C) H2, CO, O2	SCM	$E_{H_2}=20,$ $E_{CO}=18,$ $E_{O_2}=24$	[52]

Notes: (a) Model codes reported in the acronyms list, (b) $E_{C{H}_4},E_{CO},E_{H_2}$: energies of activation for CLC reactions involving methane, carbon monoxide, and hydrogen in the Fuel Reactor, respectively, and (c) $E_{O_2}$: energy of activation for nickel oxidation in the Air Reactor.

It should be noted that reduction reactions with nickel oxide, including Reaction 3 and the forward Reactions 4 and 5, as shown in Table 5 (Equations (13)–(15)), can be considered as first order functions of the CH₄, CO, and H₂ partial pressures, respectively [50,84,100]. Furthermore, Reactions 4 and 5 (Equations (14) and (15)) can also be accounted for by including the reverse influence of CO₂ and H₂O conversion reactions. These reverse reactions are assumed to be first order functions of CO₂ and H₂ partial pressures. Furthermore, assuming a NNGM random nucleation (n = 1), the CLC kinetics can be expressed as follows:

$${r_1=k}_1{p}_{C{H}_4}\left(1-\alpha \right)$$

(23)

$$r_2-r_4=k_2{p}_{CO}\left(1-\alpha \right)-k_4{p}_{C{O}_2}\alpha$$

(24)

$$r_3-r_5=k_3{p}_{H_2}\left(1-\alpha \right)-k_5{p}_{H_{2}O}\alpha$$

(25)

with $r_2$ and $r_4$ being the forward and backward reaction terms in Equation (16), $r_3$ and $r_5$ being the forward and the backward reaction rates in Equation (17), and $\alpha$ being the fraction of remaining active NiO sites. Furthermore, $k_i=k_{0,i}^{app}{e}^{{\displaystyle \frac{-E_i^{app}\times {10}^3}{R}}\left({\displaystyle \frac{1}{T}}-{\displaystyle \frac{1}{T_c}}\right)}$, $k_{0,i}^{app}$ is the pre-exponential factor, $E_i^{app}$ is the apparent activation energy, and $T_c$ is the 600 °C centering reaction temperature. It is strongly recommended to use $T_c$ in $k_i \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{a}\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{c}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{s}$ to reduce cross-correlation between kinetic parameters.

CLC intrinsic rates (−$r_n$), can be established in CREC Riser Simulator as follows:

$$(-r_i)={\displaystyle \frac{1}{V_R}}{\displaystyle \frac{d{N}_i}{dt}}={\displaystyle \frac{1}{V_R}}{\displaystyle \frac{d\left(\frac{V_R{p}_i}{RT}\right)}{dt}}$$

(26)

where $N_i$ represents the moles of “$i$” species (µmole), $V_R$ stands for the reactor volume ($\mathrm{c}{\mathrm{m}}^3$), $p_i$ denotes the partial pressure ($psi$), $R$ is the universal gas constant ($\mathrm{J}/\mathrm{m}\mathrm{o}\mathrm{l}/\mathrm{K}$), $T$ represents the reactor temperature ($K$), and $t$ stands for the reaction time ($s$).

Given that $V_R$ and $T$ are constant during an experimental run, Equation (26) can be rewritten in terms of the individual chemical species partial pressures as follows:

$${\displaystyle \frac{d{p}_i}{dt}}={\displaystyle \frac{1}{f_1}}{\sum _i(-r}_i);where,f_1={\displaystyle \frac{1}{RT}}\times {\displaystyle \frac{\mathrm{101,325}}{14.7}}$$

(27)

Furthermore, by combining Equations (23)–(25) and (27), this leads to Equations (28)–(32). Equation (33) describes the total change in the α fraction of the reduced NiO active sites, with $N_{NiO}^0$representing the initial moles of nickel oxide:

$${\displaystyle \frac{d{p}_{CO}}{dt}}={(r}_1-r_2+r_4)\delta {\displaystyle \frac{1}{f_1}}$$

(28)

$${\displaystyle \frac{d{p}_{C{H}_4}}{dt}}={-r}_1\delta {\displaystyle \frac{1}{f_1}}$$

(29)

$${\displaystyle \frac{d{p}_{C{O}_2}}{dt}}={(r}_2-r_4)\delta {\displaystyle \frac{1}{f_1}}$$

(30)

$${\displaystyle \frac{d{p}_{H_2}}{dt}}={(2r}_1-r_3+r_5)\delta {\displaystyle \frac{1}{f_1}}$$

(31)

$${\displaystyle \frac{d{p}_{H_{2}O}}{dt}}={(r}_3-r_5)\delta {\displaystyle \frac{1}{f_1}}$$

(32)

$${\displaystyle \frac{d\alpha }{dt}}=\left(r_1+r_2+r_3-r_4-r_5\right)\times {\displaystyle \frac{V_R\times {10}^{-6}}{N_{NiO}^0}}$$

(33)

With the $\delta ={\displaystyle \frac{W_{OC}}{V_R}}$ ratio and $W_{oc}$ representing the weight of oxygen carrier used in the experiments.

Equations (28)–(33), which include $k_{0,i}^{app}$ and $E_i^{app}$, were determined numerically using the following procedure: (a) Initial values were assigned to $k_{0,i}^{app}$ and $E_i^{app}$, (b) then, Equations (28)–(33) were solved by using the “ode45” from MATLAB R2024b, and (c) finally, the $k_{0,i}^{app}$ and $E_i^{app}$ were adjusted, by using a non-linear “lsqnonlin” optimization method, minimizing the following function:

$$f_{obj}=\sqrt{\sum _i^{species}{\left(p_{i,exp}-p_{i,th}\right)}^2+{\left({\alpha }_{exp}-{\alpha }_{th}\right)}^2}$$

(34)

With $p_{i,th}$ and $p_{i,exp}$ being the “$i$” species partial pressures ($i=C{H}_4,CO,C{O}_2,H_2$, and $H_{2}O$) predicted and measured, and ${\alpha }_{i,exp}$ and ${\alpha }_{i,th}$ being the theoretical and experimental OC oxygen conversions.

Kinetic parameters were assessed for the HPOC by using both Syngas-250 and Syngas-133 [8].

Table 8. Kinetic parameters determined using Syngas-250 and Syngas-133 and the HPOC [8].

Apparent Parameters	Syngas-250		Syngas-133
	Value	95% CI	Value	95% CI
k0,1a	3.03 × 10−2	±16%	5.62 × 10−2	±1.7%
k0,2	12.5 × 10−2	±14.9%	10.5 × 10−2	±11.6%
k0,3	29.8 × 10−2	±7%	39.7 × 10−2	±10.6%
k0,4	2.94 × 10−2	±32.0%	1.54 × 10−2	±36.2%
k0,5	19.1 × 10−2	±11.5%	8.9 × 10−2	±14.1%
E1b	3.6 × 10−13	±5.8%	4.02 × 10−14	±27.3%
E2	13.02	±44.5%	5.13	±56.5%
E3	20.10	±34.3%	7.36	±48.9%
E4	40.17	±30.3	36.90	±39.0%
E5	30.31	±35.6	21.23	±36.7%
m	250
DOF	240

^a mol.m⁻³psi⁻¹s⁻¹; ^b kJmol⁻¹; T_c = 873 K; degree of freedom (DOF) = data points (m) – parameters (p) = 250 – 10 = 240.

reports the estimated parameters with their percentual 95% confidence spans. This table shows that these confidence spans fall in a close-range, suggesting kinetic model adequacy, and the independence of the determined kinetic parameters from the syngas composition. Ten kinetic parameters were determined by using 250 observed data points, with at least three repeats per experiment, with a DOF (degree of freedom) of 240. Furthermore, additional studies evaluating the ten-parameter cross-correlation matrix show all cross-correlation coefficients being below one, with this providing additional support to the proposed kinetic model.

Table 8 also reports the frequency factors for the forward reactions. This shows k₁⁰ < k₂⁰ < k₃⁰ differences, with these differences agreeing with the observed $r_{H_2}>r_{CO}>r_{C{H}_4}$. Regarding the backward reactions, the k₄⁰ and k₅⁰ parameters display a k₄⁰ < k₅⁰ difference, with this confirming the high H₂O reactivity versus the reactivity of CO₂ on the reduced nickel sites. In other words, the retardation rates due to the reverse reactions are more significant for H₂ than for CO₂.

Figure 7 and Figure 8 display the parity plots for Syngas-250 and Syngas-133. These figures compare the predicted and experimentally observed chemical species’ partial pressure values, at different reaction times, temperatures, ψ ratios, and using the HPOC.

One can see that runs with Syngas-250 showed a 2.9% standard deviation error, while the runs with Syngas-133 displayed a 3.9% standard deviation error [8]. Both of these standard deviation errors are acceptable and within the anticipated experimental error bands. As a result, both the kinetic parameters and the kinetic model considered using two BMD syngas samples are considered adequate for the CLC while using the HPOC.

10. Large-Scale and Demonstration CLC Unit Simulation

Table 9. Pilot-scale CLC fluidized bed units available at various research centers around the world.

Designed Capacity (kW)	Fluidization Regime		Feedstock	Location	Ref
	Air Reactor	Fuel Reactor
25	CFB-fast fluidization	Moving bed	Coal	The Ohio State University, USA	[102]
50	Bubbling bed with Riser	Bubbling bed with Riser	Biomass	Instituto de Carbonquímica, Zaragoza, Spain	[103]
100	Bubbling bed with Riser	CFB in bubbling regime	Bituminous coal	Chalmers University of Technology, Sweden	[104]
100	Bubbling bed with Riser	Bubbling bed	Coal	National Energy Technology Laboratory, USA	[105]
120	CFB in fast regime	CFB in fast fluidization regime	Natural gas	Vienna University of Technology, USA	[106]
1000	CFB in fast fluidization	CFB in fast fluidization	Ilmenite and hard coal	Technische Universität Darmstadt, Germany	[107]

reports a summary of CLC fluidized bed units available at various research centers around the world. This demonstrates the far-reaching research on CLC technology that is being developed currently in different countries.

In this respect, Table 9 shows the significant number of CLC units employed based on the twin fluidized bed design, and, in particular, the bubbling bed combined with a riser, a moving bed, and fast fluidization. While these configurations can provide suitable results, the downer–riser configuration was preferred for the HPOC [108]. This was the case given the anticipated close plug flow operation in those units, and as a consequence the anticipated high syngas conversions, CO₂ yields, and oxygen carrier regeneration efficiencies.

Table 10. Simulations of the large-scale CLC process employing various OCs. Adapted from [7].

Oxygen Carrier	Fuel	Reactor Configuration	Reactor Capacity	References
58wt% NiO on Bentonite	CH4	FR:BFB	Batch Mode	[110]
		FR:BFB; AR:Riser	12 kW	[111]
Fe-Ni on Bentonite	CH4	FR:BFB	1 kW	[112]
30.7wt% FeO-Ilmenite	CH4, H2, CO	FR:BFB; AR:DFB and Riser	42 kW	[105]
Glass beads (Geldart A and B)	Cold Run	FR:CFB; AR:CFB	10 kW	[113]

AR: Air Reactor; BFB: bubbling fluidized bed; DFB: dense fluidized bed; FR: Fuel Reactor.

describes the active research being developed with computer-based simulations for the advancement of OCs to be used in large-scale CLC units. Furthermore, one can also mention the significant and valuable efforts being developed to validate the proposed models with experimental data [109].

While all these efforts are commendable, Ahmed and de Lasa [108] recently reported research involving the simulation of a 36.6 kW CLC reactor, consisting of an Air Riser Reactor–Fuel Downer Reactor unit with the following dimensions: (a) Air Reactor: diameter: 0.12 m, height: 8.0 m; (b) Fuel Reactor: diameter: 0.20 m, height: 6 m. Simulations involved Computational Particle Fluid Dynamics (CPFD) implemented in conjunction with the HPOC reduction kinetics, as described in Section 8.

Figure 9 shows a schematic representation of the CLC unit proposed by Ahmed and de Lasa [108]. The HPOC particles flow downwards from the bottom of a cyclone encountering BMD syngas jets. The BMD syngas jets are supplied to the downer via a gas distributor injection port. Thus, HPOC particles are mixed uniformly with the syngas fed before they move downwards.

Regarding the downer design, both the downer dimensions (e.g., height, diameter) are selected to warrant that the gas volumetric flow, and the OC residence times provide the desired high syngas conversions. Furthermore, the cyclone is designed to provide efficient HPOC particle separation, with minimum OC particle entrainment. In the selected CLC configuration, the Downer Fuel Reactor is connected to the Air Reactor via an L-type loop seal [108]. It is in this section where the recycled HPOC is forced to enter into the Air Reactor via an air pulsation system.

The twin CLC reactor system simulations were conducted using CPFD Barracuda VR software. These computations were carried out by employing an Eulerian–Lagrangian method, with computational particles having uniform species composition, size, density, and temperature [108]. The Barracuda VR software included an MP-PIC subroutine accounting for gas–particle and particle–particle interactions. In addition, the OC kinetics, described in Section 8 of this review, were accounted for in the Barracuda VR simulations. This enabled the simulation of a twin reactor scale CLC unit, using an affordable computational time. Additional details regarding the differential equations and the numerical approach using Barracuda are given in [114,115,116].

Table 11. Physical properties of HPOC particles.

Parameters	Value
Particle mean diameter, d50 [µm]	87.1
Particle density, [kg/m3]	1800
Particle sphericity	0.9
Particle close pack volume fraction	0.6
Particle–wall tangential retention coefficient	0.85
Particle–wall normal retention coefficient	0.85
Diffuse bounce	0
Maximum momentum redirection from particle-to-particle collision	40%

reports the various HPOC properties considered in the CPFD simulations. These are as follows: (a) the particle mean diameter, (b) the particle density, (c) the particle sphericity, (d) the particle close pack volume fraction, d) the particle–wall tangential and normal retention coefficients, (e) the diffuse bounce, and (f) the maximum momentum redirection from particle-to-particle collisions.

Furthermore, in both the Riser Air Reactor and in the Downer Fuel Reactor, HPOC particles move as particle clusters rather than as individual particles. Therefore, the accounting of HPOC particle clusters was considered to be very important to accurately describe the downer hydrodynamics and as a result enable the gas–solid interactions in the Downer Fuel Reactor [70].

The CPFD Barracuda simulations also involved other significant applicable assumptions, such as that of the adiabatic and the quasi-isothermal operation of the Downer Fuel Reactor. This was considered adequate given the small OC reduction enthalpy in the Fuel Reactor, as reported in Section 3. Concerning the Air Reactor, it was also assumed that all the heat generated as a result of HPOC re-oxidation was removed in the lower Energy Extraction Air Reactor System, described in Figure 9.

CPFD Barracuda considers the Reynolds Averaged Navier–Stokes equations to simulate fluid dynamics in a 3D Downer Fuel Reactor. As a result, volume averaged mass continuity and momentum balances [117,118] can be considered for the gas phase, as shown in Equations (35) and (36):

$${\displaystyle \frac{\partial \left({\epsilon }_g{\rho }_g\right)}{\partial t}}+\nabla ·\left({\epsilon }_g{\rho }_g{u}_g\right)=r_g{\epsilon }_g$$

(35)

$${\displaystyle \frac{\partial ({\epsilon }_g{\rho }_g{u}_g)}{\partial t}}+\nabla ·\left({\epsilon }_g{\rho }_g{u}_g{u}_g\right)=-\nabla P-F+{\epsilon }_g{\rho }_{g}g+\nabla ·({\epsilon }_g{\tau }_g)$$

(36)

where ${\epsilon }_g$ is the gas phase volume fraction, ${\rho }_g$ is the gas phase density, $t$ is the time, $u_g$ is the gas velocity vector, $r_g$ is the gas mass production rate in the gas phase per unit volume due to the particle-gas reaction, $p$ is the mean gas phase pressure, $F$ is the exerted particle force per unit fluid volume, $g$ is the acceleration vector due to gravity, and ${\mathit{\tau }}_g$ is the stress tensor in the gas phase.

Furthermore, the properties of the gaseous phase components were evaluated by solving the transport equation for the individual gas phase species, as follows:

$${\displaystyle \frac{\partial \left({\epsilon }_g{\rho }_g{y}_i\right)}{\partial t}}+\nabla ·\left({\epsilon }_g{\rho }_g{y}_i{u}_g\right)=\nabla ·\left({\epsilon }_g{\rho }_g{D’\nabla \mathrm{y}}_i\right)+r_i{\epsilon }_g$$

(37)

with $D’$ being the turbulent mass diffusivity ($D’=\mu /\rho gSc$), µ representing the shear viscosity, which is the sum of laminar and turbulent viscosity [119], and $Sc$ denoting the turbulent Schmidt number.

The MP-PIC method employed in the simulations of the Downer Fuel Reactor considered a transport equation to describe particle phase dynamics. This equation includes a particle distribution function (PDF) [108]. Equation (38) expresses a PDF as $f(x_p,u_p,m_p,t)$. This f variable depends on the following: the $x_p$ HPOC location in space, the $u_p$ HPOC particle velocity, and the $m_p$ HPOC mass. The f variable is also affected by the A HPOC acceleration parameter, the D drag function, and the ${\tau }_p$ HPOC inter-particle normal stress.

$${\displaystyle \frac{\partial f}{\partial t}}+{\nabla }_{{\mathrm{x}}_{\mathrm{p}}}·\left(f{u}_p\right)+{\nabla }_{{\mathrm{u}}_{\mathrm{p}}}·\left(fA\right)={\left({\displaystyle \frac{\partial f}{\partial t}}\right)}_{coll}^D$$

(38)

$$A={\displaystyle \frac{d{u}_p}{dt}}=D\left(u_g-u_p\right)-{\displaystyle \frac{1}{{\rho }_p}}\nabla P-{\displaystyle \frac{1}{{\epsilon }_p{\rho }_p}}\nabla {\tau }_p$$

(39)

The selected PDF includes a collision term (right-hand side of Equation (38)), as suggested by O’Rourke et al. [120].

Furthermore, for non-spherical HPOC clusters, with particle cluster distributions as given in Figure 10, the following Ganser Model [121] was considered adequate for $C_D$ drag calculations.

$$D={\displaystyle \frac{3}{8}}{C}_d{\displaystyle \frac{{\rho }_g|u_g-u_p|}{{\rho }_p{r}_p}}$$

(40)

$$C_d={\epsilon }_g^{n_o}{K}_2\left[{\displaystyle \frac{24}{Re{K}_1{K}_2}}\left(1+c_0{\left(Re{K}_1{K}_2\right)}^{n1}\right)+{\displaystyle \frac{24c_1}{1+\frac{c_2}{Re{K}_1{K}_2}}}\right]$$

(41)

With ψ being the particle cluster sphericity and with c_1, c₂, n₀, n_1, n₂, and n₃ being 0.1118, 0.01794, 3305, 2.65, 0.6567, 1.8148, and 0.5743, respectively. In addition, K₁ and K₂ isometric shape parameters in Equation (41) are defined as $K_1=3{\left(1+2{\psi }^{-0.5}\right)}^{-1}$ and $K_2={{10}^{n_2\left(-\mathit{log}\psi \right)}}^{n_3}.$

Figure 11a describes the CPFD simulations while using the HPOC for the following operating conditions: (a) Syngas flow feed: 0.0059 kg/s, (b) Air flow feed: 0.010 kg/s, (c) Fuel Reactor temperature: 923 K, (d) Inlet Fuel Reactor pressure: 101 KPa. The results obtained are for the Downer Fuel Reactor and the Riser Air Reactor. Figure 11b,c show that 60 s computational times were needed to obtain a stabilized solid flow as well as an air flow and syngas flow in the Fuel and Air Reactor, respectively. Reported results are given at the designated “cut off” planes, as shown in Figure 11a.

Therefore, as reported in Figure 11a, 1.5 Kg/s HPOC circulation was used in the CPFD simulation with a 1–3% HPOC volume fraction in the Fuel Reactor after 60 s of computational time. In addition, and as is shown in Figure 11c, a 500 kg/s/m² mass flux in the Riser Air Reactor and a 50 kg/s/m² mass flux in the Downer Fuel Reactor can both be achieved. These values agree with typical experimental values and industrial requirements [122].

Figure 12a,b report the fluid velocity, the particle velocity, and the average volume fraction along the Downer Fuel Reactor unit, as calculated via CPFD simulations.

One can notice from Figure 12a,b that the cross-section average particle volume fractions and cross-section average particle velocities are relatively constant. This is consistent with the quasi-isothermal conditions of the downer as well as with the modest change in the total number of moles in the Fuel Reactor while the reduction reaction is progressing. The only exception to this trend is in the downer section where the BMD syngas is fed. In this section, a particle densification was observed. However, once a distance of 1–2 m of downer length away from the BMD syngas feed level is reached, and the downer flow pattern is established, the particle volume fraction stabilizes in the 1% level, with the gas and cluster average velocities being at 0.75 m/s and 2.76 m/s, respectively.

Table 12. Calculated Syngas-250 components conversions and CO₂ yields for downers of various heights (3.75 m, 7.5 m and 15 m) using the HPOC kinetics, described in Section 8.

Downer Fuel Reactor Length/Vapor Phase Reaction Time	H2 Conversion %	CO Conversion %	CH4 Conversion %	CO2 Yields %	NiO Conversion %
3.75 m or 5 s	97.7	49.4	64.5	79.7	29.1
7.5 m or 10 s	98.75	72.3	73.9	84.4	33.4
11.25 m or 15 s	99.3	84.5	72.71	85.99	34.0
15 m or 20 s	99.6	91.2	71.9	87.03	35.0

reports the calculated BMD syngas component conversions and CO₂ yields for the Syngas-250 under isothermal conditions. Assessments were performed for a Downer Fuel Reactor having 3.75 m, 7.5 m, and 15 m heights, under the selected operating conditions: (a) syngas flow feed: 0.0059 kg/s, (b) air flow feed: 0.010 kg/s, (c) Fuel Reactor temperature: 923 K, (d) Inlet Fuel Reactor pressure: 101 KPa.

One can observe, based on the results in Table 12, that the HPOC at a 15 m height in the Downer Fuel Reactor gives high syngas component conversions (99.6% for H₂, 91.2% for CO, 71.9% for CH₄) with high CO₂ yields (87.0%). The CPFD results also show that the 1.5 kg/s HPOC circulation in such a configuration is possible, with a close to 1% solid volumetric concentration. The proposed 36 KW twin reactor CLC configuration also benefits from the little CO₂ gas leaking, made possible by the implemented L-type loop-seal placed between Downer Fuel Reactor and Riser Air Reactor.

11. Conclusions and Future Perspectives

Industrial-scale fast catalytic fluidized beds, and especially CLC Downer Fuel Reactor units and Riser Air Reactor units, have the potential to provide the reaction environment for the efficient combustion of biomass-derived syngas. As a result, biomass-derived syngas could be used as fuel in power stations, avoiding the adverse ecological impact of employing fossil fuels. These fast-fluidized beds reactors can operate with high-performance fluidizable oxygen carriers (HPOC) free of particle mass and heat diffusional transport rate limitations. These fast-fluidized beds reactors can be operated with high syngas throughputs and short OC residence times, and can provide a high conversion of syngas components (CH₄, H₂, CO) into a free nitrogen CO₂.

CLC thermodynamics is an area of significant importance for CLC process development and evaluation. For instance, it is proven in this review that when using NiO oxygen carriers, much smaller enthalpies are needed for oxygen carrier reduction than the ones required for the oxygen carrier oxidation. This allowed us to predict a 48.6% overall energy conversion efficiency with this favoring fluidizable NiO oxygen carriers for industrial-scale applications as a result.

Given the promise of HPOCs, this review focuses on the preparation of such oxygen carriers with their performance being demonstrated using a mini-fluidized CREC Riser Simulator. This experimental tool has the ability to anticipate the high syngas species conversion and CO₂ yields that can be obtained in industrial size CLC fluidized bed units. On the basis of the data obtained in the CREC Riser Simulator, phenomenological-based kinetics, involving solid–gas reactions and NiO supported oxygen carriers, were successfully developed. This provided an adequate description of the HPOC performance and of the high CO₂ yields obtained.

Furthermore, CPFD computations such as the ones obtained with Barracuda VR were shown to be valuable in order to account for the kinetics and the fluid dynamics in both the Downer Fuel Reactor and the Riser Air Reactor. These simulations demonstrated the scalability of an integrated Downer Fuel Reactor–Riser Air Reactor CLC unit with the proposed reactor configuration providing high 86% CO₂ yields and a 85% overall conversion of syngas components.

Based on the state-of-the art CLC process described, one can predict that new HPOCs with low-cost preparation, stable performance, and very low fluidizable support attrition will be needed in the near future. One can also anticipate the great importance of conducting quick performance evaluations and developing mechanistic-based kinetics of OCs using laboratory scale tools, such as the CREC Riser Simulator, which emulate industrial-scale CLC unit operating conditions.

Furthermore, and to complement this research effort, it is anticipated that in the near future more refined CPFD simulations will be required for the full development of a Downer Fuel Reactor and a Riser Air Reactor combined twin unit process. It is also expected that the CLC design will require innovative components such as the following: (a) a L-type loop-seal located between Fuel Reactor and Air Reactor, (b) a syngas injection system placed at the top of the Downer Fuel Reactor unit, (c) high efficiency particle separation cyclones, and (d) Air Reactor vertical tube heat exchangers with minimum flow disturbance.

In summary, this review highlights the recent progress in CLC obtained with an HPOC oxygen carrier. It studies the potential value of a promising process where biomass-derived syngas is combusted with NiO, yielding CO₂ and water as the sole products. The condensation of the water from the CLC outlet stream can lead to a highly concentrated CO₂ gas stream ready to be either buried or alternatively be used together with green hydrogen for the synthesis of green fuels produced from renewable feedstocks.