Adiponitrile Production Research Articles

Broadband Microwave Microfluidic Spectroscopy to Capture Product Evolution in Electrosynthesis Reactions

Electrosynthesis plays an important role in chemical manufacturing with over 2 billion dollars in annual sales worldwide of products such as chlor-alkali and aluminum. Synthesis with an electrochemical driving force can afford unique chemical products that are difficult to achieve with conventional synthesis techniques. Electrosynthesis can also provide a more sustainable alternative to energy-intensive processes. For example, the most profitable electro-organic synthesis in industry is adiponitrile production, a precursor to Nylon 6,6, and the electrochemical route consumes less energy than conventional thermochemical methods. However, electrosynthesis reaction mechanisms are often complex and involve multiple biproducts that are difficult to distinguish, limiting product yield and cost efficiency. Prior work involves characterization with techniques such as NMR spectroscopy, mass spectrometry, and optical spectroscopy to understand product evolution during the reaction. These methods tend not to capture intermolecular interactions between substances, which is important for understanding the influence of the dielectric environment on reaction outcomes.Here, we propose to analyze the dielectric environment of electrosynthesis reaction mixtures with on-chip broadband microwave microfluidic spectroscopy (MMS) from 40 kHz – 110 GHz (see attached figure). MMS has been implemented previously for capturing broadband fluid effects such as electric double layer formation, ionic conduction, ion pairing, and dipole relaxations in a single measurement. We want to use MMS to diagnose the interactions between species during an electrolysis reaction and correlate these interactions with specific electrochemical mechanisms. We plan to test our idea by analyzing a model reaction, namely the Shono oxidation of N-Boc pyrrolidine, which is a well-studied electrosynthesis reaction. The goal is to validate our method with a known electrosynthesis reaction mechanism, then extend the technique to systems with an unknown mechanism.We performed broadband MMS of the reaction mixture at different time points to capture product evolution during the electrolysis. Then, we calibrated the resulting S-parameters and fit the data to equivalent circuit models. The equivalent circuit parameters were correlated to signatures from specific entities in the product mixture and used to develop a picture of the evolving dielectric environment. After validating our models with known literature about the Shono oxidation mechanism, we plan to extend our technique to other electrolysis reactions with unknown mechanisms. The goal is to provide a high-throughput technique for identifying key species and interactions that influence the outcome of electrolysis reactions. Figure 1

Current and Emerging Electrochemical Approaches for Chemical Manufacturing

R&D on electrochemical approaches for chemical manufacturing is experiencing a renaissance, the direct result of society’s desire to reduce greenhouse gas emissions of the chemical industry, aiming to be carbon neutral by 2050. Two such processes have been performed for decades at scale: the chlor-alkali process that produces chlorine from aqueous sodium chloride, and the production of adiponitrile, an intermediate in the production nylon-6,6. Water electrolysis for hydrogen production is also being deployed now at scale. This report summarizes some of the many efforts to electrify chemical conversions, often using renewable feeds like water, CO2, and biomass-derived adducts, or waste-streams from other processes. Beyond efforts to reduce emissions, a very active research community also pursues a broad range of electro-organic conversions, some of which have major advantages over conventional reaction chemistries. Overarching challenges of implementing electrochemical manufacturing approaches are also discussed (e.g., limited familiarity with electrochemical processes in chemical engineering practice, insufficient availability of electrical power, and the variability of various renewable feeds).

Enhancing Organic Electrosynthesis through Artificial Intelligence: The Case of Adiponitrile Electrohydrodimerization

The continuous increase of fossil fuel-derived carbon dioxide (CO2) emissions has made their impact in climate change self-evident. The chemical industry is a major contributor to this increase, accounting for more than 5.5% of the global CO2 emissions. The electrification of the chemical industry would thus be a major step in the integration of renewable electricity in the industrial sector, helping reduce its carbon footprint significantly. Inorganic electrosynthetic processes have been largely implemented at industrial scale (i.e. chloro-alkali and Aluminum production), however the deployment of electrosynthetic methods for the production of organic chemicals has been limited. Adiponitrile (ADN) is a large-volume (>1.5 million tons/year) precursor to Nylon 6,6 and it can be obtained via the electrohydrodimerization of acrylonitrile (AN). Although the electrochemical production of adiponitrile (ADN) is the largest organic electrochemical process in industry, it faces many challenges owing mainly to its energy conversion efficiency and selectivity. Optimizing the composition of the electrolyte has resulted in significant performance improvements, however mass transport limitations have proven to be a challenge at high current densities, where propionitrile (PN) is the main reaction by-product. In this study, we provide experimental insights on the effects of pulsed potential techniques on the mitigation of mass transport limitations and the effective control of product distribution. Moreover, an integrated approach combining experimental insights and artificial intelligence-driven models is proposed for the rapid optimization of operation conditions and the maximization of reaction performance. The regulation of electron-transfer rates with the use of complex pulse potential waveforms is implemented to control the electrochemical environment surrounding the reaction surface, ultimately favoring ADN production. Electrochemical pulses are used to balance reactant diffusive fluxes to the electrode and the generation/consumption of species in the electrical double layer (EDL), helping mitigate mass transport limitations at high current densities. This, together with their effect on interaction between electroactive species and the reaction surface can help improve reaction selectivity. An improvement of over 250% in the production ratio of ADN:PN (desired to undesired product) was achieved optimizing pulse duration and amplitude. Furthermore, the careful control of overall reaction time and composition of the EDL led to a 20% increase in ADN production with respect to DC operation. The integrated use of machine learning algorithms enabled the prediction of ADN formation in a complete landscape of pulse durations. From this, a new set of optimal conditions was identified, leading to a 30% increase in ADN production with respect to DC operation for periodic pulses varying from -60 mA cm-2 (120 ms) to 0 mA cm-2 (5 ms). A new paradigm in organic electrosynthesis research is proposed, where a combination of electrochemical design principles, artificial neural networks, and judiciously designed experimental campaigns are used to uncover new electrosynthetic processes.

Optimizing organic electrosynthesis through controlled voltage dosing and artificial intelligence

Organic electrosynthesis can transform the chemical industry by introducing electricity-driven processes that are more energy efficient and that can be easily integrated with renewable energy sources. However, their deployment is severely hindered by the difficulties of controlling selectivity and achieving a large energy conversion efficiency at high current density due to the low solubility of organic reactants in practical electrolytes. This control can be improved by carefully balancing the mass transport processes and electrocatalytic reaction rates at the electrode diffusion layer through pulsed electrochemical methods. In this study, we explore these methods in the context of the electrosynthesis of adiponitrile (ADN), the largest organic electrochemical process in industry. Systematically exploring voltage pulses in the timescale between 5 and 150 ms led to a 20% increase in production of ADN and a 250% increase in relative selectivity with respect to the state-of-the-art constant voltage process. Moreover, combining this systematic experimental investigation with artificial intelligence (AI) tools allowed us to rapidly discover drastically improved electrosynthetic conditions, reaching improvements of 30 and 325% in ADN production rates and selectivity, respectively. This powerful AI-enhanced experimental approach represents a paradigm shift in the design of electrified chemical transformations, which can accelerate the deployment of more sustainable electrochemical manufacturing processes.

Modeling of electro-organic synthesis to facilitate cleaner chemical manufacturing: Adiponitrile production

Electro-organic synthesis provides more efficient and green technologies for the production of many traditional chemicals. Production of adiponitrile via an electrochemical process is one example of electro-organic synthesis which has been successfully adopted as one of a few commercial electro-organic syntheses. Sustainability metrics indicate the merits of the process compared to the hydrocynation process but suggest a need to improve the energy efficiency of the process. Further development and process optimization require a comprehensive mathematical model for electrohydrodimerization process. In order to develop an accurate model, the mechanistic multistep model is needed. The mechanism of electrohydrodimerization of acrylonitrile to adiponitrile is complex, as it consists of many multiple reactions with series and parallel reactions occurring simultaneously, thus making the modeling complicated. The bi-phasic nature of the system with organic and aqueous phases needs incorporation of the liquid–liquid mass transfer effects as well. This work develops a mathematical model for the electrohydrodimerization of acrylonitrile to adiponitrile in a batch reactor. Electrochemical and chemical reactions and diffusion in an aqueous liquid film surrounding the electrode, with mass transfer between aqueous and dispersed organic phases, are included in the model. The diffusion–reaction equations for the film model are solved by boundary element method. The results show the calculated concentration in both phases, selectivity of the main product and by-products, voltage and current. In addition, the effects of operating parameters on the selectivity of adiponitrile have been examined in detail.

An Experimental Study of the Competing Cathodic Reactions in Electrohydrodimerization of Acrylonitrile

The production of adiponitrile (ADN) uses an electrochemical reactor in which organic reactant, acrylonitrile (AN), which is very slightly soluble in water and forms an emulsion in the aqueous electrolyte, undergoes an electrohydrodimerization reaction at a solid lead cathode. In addition to ADN, some byproducts including propionitrile (PN) and 1,3,5-tricyanohexane (trimer) are also formed at the surface of the cathode. Since the open literature on the study of the parameters influencing the course of this reaction is scarce, the current study was launched to identify the effects of various process parameters on the selectivity of adiponitrile and its by-products. The electrosynthesis was conducted in an electromembrane reactor employing an oxygen-evolution dimensionally stable anode (DSA-O2®), a lead cathode, and a Nafion® 115 membrane. The concentration of all products was determined through NMR analysis. Process parameters under investigation were: temperature (25–55°C), acrylonitrile concentration (15–30 wt%), current density (1–4 kA/m2), catholyte flow rate (100–400 mL/min) and catholyte pH (3–9). The results demonstrate that the selectivity of ADN is enhanced by increasing all studied process parameters, except the current density. In the case of by-products, the selectivity of PN decreases by raising AN concentration, flow rate, and pH. On the other hand, the selectivity of trimer was reduced by temperature, current density, and flow rate.

The influence of mass transfer on the electrochemical synthesis of adiponitrile

The production of adiponitrile uses an electrochemical reactor in which organic reactant, acrylonitrile, is present as an additional phase in an aqueous electrolyte which undergoes an electrochemical reaction at a solid cadmium cathode. This electrode forms part of a thin rectangular channel (electrolytic cell) in which oxygen gas is generated. The overall cathodic reactions in the synthesis involve a set of six steps to the organic product and by-products, as well as the generation of hydrogen gas and the reduction of oxygen. This paper shows how current density and the mass-transfer behaviour at the cathode surface affects the yield of the synthesis of adiponitrile during batch operation. The experimental data are theoretically interpreted using a simplified multiphase reaction model.

Development of ion exchange membrane technology

Ion exchange membrane and its applications have been mainly developed for manufacturing salt by seawater concentration in Japan in the early stage of their development. The company started its research in 1950 and the total area of the membrane installed by the company and currently used in the world exceeds 370,000 square meters as of January 1, 1977. Besides seawater concentration, the application presently covers desalination of seawater or brackish water, sewage desalination, whey desalination, caustic soda production, adiponitrile production, uranium enrichment, etc. General application of ion exchange membrane is briefly reviewed and a stress is placed on large module developed by the company and other possible applications.