Reactor
A reactor is a specialized vessel designed to safely and efficiently facilitate chemical reactions by providing a controlled environment for the conversion of reactants into desired products. Reactors are widely used in industries such as chemical, pharmaceutical, food processing, and materials science, and are equipped with precise temperature, pressure, mixing, and reactant flow control systems to optimize yield, safety, and energy efficiency. Core design considerations include reaction kinetics, thermodynamics, heat and mass transfer, and fluid dynamics. Common reactor types include batch reactors, continuous stirred tank reactors (CSTRs), and plug flow reactors (PFRs), as well as variations such as fluidized beds, fixed beds, and membrane reactors for specialized applications. Reactors are constructed with materials suitable for corrosive or high-pressure environments (e.g., stainless steel, glass-lined, Hastelloy), and are equipped with sealing systems, heating/cooling jackets, and integrated sensors for real-time monitoring and automation. The choice of reactor depends on the scale of production, reaction conditions, and regulatory requirements, and proper maintenance and safety systems are essential to ensure reliable and compliant operation.
| Equipment type | Classification method | Features | Application scenario |
| Stainless steel reactor | Classification by material | It has good corrosion resistance, high temperature resistance and mechanical properties. It is suitable for most chemical media such as acids, alkalis, and salts, but its tolerance to strong corrosive media such as chloride ions is limited. | Commonly used in food, pharmaceutical, fine chemical and other industries, for example, in the process of producing vitamin C, it is used to treat fermentation liquid. |
| Carbon steel reactor | Classification by material | High strength and low cost, but poor corrosion resistance, usually requires anti-corrosion coating treatment. | Suitable for reaction processes that do not require high corrosion resistance, such as some common organic synthesis reactions. |
| Special alloy reactor | Classified by material | Such as titanium alloy, nickel-based alloy, etc., with excellent corrosion resistance and high temperature performance, but the cost is relatively high. | Used to handle reactions with highly corrosive media or high temperature and high pressure, such as when producing certain high-performance materials. |
| Glass reactor | Classified by material | High transparency, easy to observe the reaction process, strong corrosion resistance, but low strength and easy to break. | Commonly used in laboratories and small-scale production, such as chemical experiments, fine chemicals, etc. |
| Glass-lined reactor | Classification by material | A layer of glass glaze is applied on the metal surface, combining the strength of metal and the corrosion resistance of glass. | Suitable for reactions of corrosive media such as strong acids and strong alkalis, such as dye and pesticide production. |
| Mechanical stirring reactor | Classification by stirring method | The stirring shaft and stirring paddle are driven by the motor to fully mix the materials. There are various stirring forms, such as paddle type, turbine type, anchor type, etc. | Applicable to most liquid and solid-liquid mixed reactions, such as polymerization reaction, emulsification reaction, etc. |
| Magnetic stirring reactor | Classification by stirring method | The power is transmitted by magnetic coupling, which avoids the leakage problem that may be caused by mechanical seals and has good sealing performance. | Commonly used in laboratories and small-scale production, especially for reactions with high sealing requirements, such as organic synthesis, pharmaceuticals, etc. |
| Pneumatic stirring reactor | Classification by stirring method | The agitator is driven by gas (such as air, nitrogen, etc.), suitable for flammable and explosive environments. | Used to handle reactions with flammable and explosive materials, such as certain petrochemical processes. |
| Normal pressure reactor | Classification by operating pressure | The operating pressure is close to normal pressure, the structure is simple, and the cost is low. | Suitable for chemical reactions under normal pressure conditions, such as some simple organic synthesis reactions. |
| Pressure reactor | Classification by operating pressure | The operating pressure is higher than normal pressure, and usually requires high pressure resistant design, such as thick-walled containers and good sealing performance. | Used for reactions that need to be carried out under high pressure conditions, such as hydrogenation reactions, high-pressure polymerization reactions, etc. |
| Decompression reactor | Classification by operating pressure | The operating pressure is lower than normal pressure, and a vacuum system is usually required. | Used for reactions that need to be carried out under vacuum conditions, such as certain degassing reactions and the evaporation process of low-boiling-point solvents. |
| Vertical reactor | Classified by the structural form of the reactor | Vertical installation, small footprint, easy installation and operation. | Applicable to most chemical production processes, especially large-scale production. |
| Horizontal reactor | Classified by the structural form of the reactor | Horizontal installation, convenient for material entry and exit and mixing, but occupies a large area. | It is often used in reaction processes that require frequent inflow and outflow of materials, such as some continuous reaction processes. |
| Double-layer reactor | Classified by the structural form of the reactor | It consists of two layers, the inner and outer layers, and the middle layer can be used for heating or cooling, which is convenient for temperature control. | It is suitable for reactions that require precise temperature control, such as fine chemicals, pharmaceuticals, etc. |
| Synthesis Reactor | Classification by Application | Used for chemical synthesis reactions, usually require precise control of temperature, pressure and stirring conditions. | Such as organic synthesis, polymerization reaction, etc. |
| Decomposition Reactor | Classification by Application | Used for decomposition reactions, usually require high temperature or catalysts. | Such as the decomposition and treatment of certain wastes. |
| Extraction reactor | Classification by purpose | Used in the extraction process, usually requires two or more phases to be mixed. | Such as solvent extraction, liquid-liquid extraction, etc. |
| Fermentation reactor | Classification by purpose | Used in biological fermentation processes, usually requiring aseptic conditions and temperature control. | Such as pharmaceuticals, food fermentation, etc. |
| References | Authors | Abstract | DOI |
| Nonlinear robust control of continuous stirred reactor system | Liu Song, Li Donghai, Xue Yali, Chen Jinli | Based on the nonlinear robust control theory, a nonlinear robust controller (ONRC) with a high gain observer is designed for a single-input single-output continuously stirred reactor (CSTR) model, and a simple controller parameter tuning method is proposed. The simulation results compared with those of nonlinear robust controller (NRC) and sliding mode control (SMC) show that ONRC has a better suppression effect on system uncertainty and disturbance. Monte Carlo experiments show that ONRC has better performance robustness when model parameters are perturbed. | 10.3321/j.issn:0438-1157.2008.02.021 |
| Application and simulation study of fuzzy control in polymerization reactor | Park Chunjun, Chen Cailian | According to the large inertia and large hysteresis characteristics of the polymerization reactor, traditional PID control, fuzzy PID control, segmented fuzzy control and Smith-fuzzy control are used for simulation research, and finally a more ideal Smith-fuzzy control method is obtained. | 10.3969/j.issn.1004-731X.2001.05.004 |
| Application of Genetic Algorithm in Fault Diagnosis of Intermittent Reactor | Song Tong, Qi Ruiqin | The intermittent reaction process is an important chemical production process. The nonlinearity, time lag and uncertainty of the process itself determine the complexity and danger of the process operation. With the development of large-scale and integrated equipment in industries such as fine chemicals and biopharmaceuticals, the importance of fault diagnosis in intermittent reaction processes continues to increase. A fault diagnosis method based on improved genetic algorithm optimized BP neural network is proposed. By extracting the fault feature data of the reactor, the weights and thresholds of the BP neural network are optimized using the improved genetic algorithm, and then the optimized BP neural network is used to train the fault feature data, establish a fault diagnosis model, and output the diagnosis results. It is applied to the temperature fault diagnosis of the intermittent reactor. The simulation results show that the improved algorithm can improve the fault diagnosis accuracy, shorten the fault diagnosis time, and has good practical effects. | 10.3969/j.issn.1006-9348.2012.07.053 |
| Robust Data Reconciliation in Chemical Reactors | Alexandre Santucci da Cunha, Fernando Cunha Pessotto, Diego Martínez Plata | Robust data reconciliation is an effective technique that aims to minimize the negligence error in estimating process variables. This paper reviews reactor problems, which present challenging scenarios due to strong nonlinear constraints and have not been compared in terms of several robust estimators. The main contribution is a comparative analysis of 16 robust estimators, ranging from the Smith estimator developed in the 19th century to the more recent Jin, Correntropy, and Xie estimators. The performance of these estimators is analyzed in three case studies under steady-state conditions, including a non-isothermal CSTR reactor with a Van de Vusse reaction system. The IPOPT and simulated annealing optimizers implemented in Scilab software were used. The results show that the efficiency and consistency of the implemented methods are high, and although the impact of the error error is significant, the reduced-order estimator still outperforms the other methods. | 10.1016/j.compchemeng.2020.107170 |
| LSTM and GRU neural networks as dynamic process models used in predictive control: A comparison of models developed for two chemical reactors | Krzysztof Zaczycki, Maciej Laurenczuk | This study comprehensively compares the efficiency of long short-term memory (LSTM) and gated recurrent unit (GRU) neural networks as dynamic process models used in model predictive control (MPC). Two simulated industrial processes are considered: a polymerization reactor and a neutralization (pH) process. First, the MPC prediction equations for both models are derived. Next, the efficiency of LSTM and GRU models is compared for various model configurations. The impact of dynamic order and number of neurons on model accuracy is analyzed. Finally, the efficiency of the considered models in MPC is evaluated. The impact of model structure on different control quality indicators and computation time is discussed. It is found that although the GRU network has fewer parameters than the LSTM network, it can be successfully used in MPC without a significant decrease in control quality. | 10.3390/s21165625 |
Procurement and Cooperation
We supply all kinds of chemical machinery and equipment, chemical reagents and raw materials, focus on research and development, and integrate chemical synthesis and purification technologies as well as small-scale, pilot and mass production supply chain construction.
Email:net.fei@163.com
