Recycling of spent lithium ion batteries (LIBs) has received increasing attention in recent years, because of the increasing usage of LIBs in electronic products and the potential leakage of heavy metals to the soil when they are disposed to the landfills. Chemical precipitation has been widely applied in the recycling process of spent LIBs. However, most processes are developed based on trial and error, leading to the possibility of recovering the wrong product in the precipitation process or excess usage of chemicals. Solid−liquid equilibrium (SLE) phase behavior governs the products to be recovered from the precipitation process and can be used to guide and optimize the process. Case studies on the recycling of LiFePO 4 and LiCo x Mn 1−x O 2 have been studied in this paper to demonstrate how the SLE phase behavior can be used to design the recovery process. Both case studies illustrate that pure metal salts can be recovered from the precipitation process with high recovery. The case studies also demonstrate how the SLE phase behavior helps to rationalize the separation process developed by previous researchers based on trial and error. The SLE phase behavior can be utilized to determine the optimal operating conditions such as the amount of precipitant to be added to the system. With the insights provided from the SLE phase behavior, new process alternatives can be generated. Process alternatives can be compared with the base case process to determine the optimal process for recycling metal salts from spent LIBs.

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A systematic procedure is presented for synthesizing and de®eloping a manufacturing process for pharmaceutical tablets and capsules. The product quality factors ᎏ functional, physical and sensorial ᎏ are first identified. The dosage form and excipients are then selected, and the process flowsheet is synthesized along with the suitable equipment and operating conditions. Finally, the product and process are e®aluated to ensure that the product possesses the desired quality factors. Design heuristics and physical models are pro®ided to assist decision-making. Examples in®ol®ing Vitamin C, antacid, and ginseng are pro®ided to illustrate the procedure. IntroductionPharmaceuticals with global sales expected to reach $406 billion in 2002 constitute a significant fraction of the chemi-Ž . cal processing industries Bailey, 2000 . They are delivered in different dosage formsᎏsolids, liquids, creams, pastes, and Ž . aerosols. Since active pharmaceutical ingredients API are normally in the solid state, most common are solid dosage Ž . forms, particularly tablets and capsules Zanowiak, 1988a , which are convenient to use and provide precise dosage.There are a wide variety of tablets and capsules. While the majority are designed to be absorbed in the gastrointestinal tract, lozenges are expected to act on the mouth and throat. Most tablets are directly swallowed, but some are supposed to be chewed by children or elderly with swallowing difficulty. Effervescent tablets are dissolved either directly in the mouth or in water before ingestion. Prolonged release tablets and capsules provide an extended therapeutic effect.Despite the economic significance of solid dosage forms, relatively little has been done from the process systems engineering perspective. This is a serious omission because an effective workflow is expected to reduce the time and effort required for launching a product. Indeed, it is generally accepted that product engineering and solids processing de-Ž serves much more attention Tanguy and Marchal, 1996;Villadsen, 1997;Kind, 1999; Wintermantel, 1999;Cussler and . Ž . Moggridge, 2001 . Recently, Wibowo and Ng 2001b consid-Correspondence concerning this article should be addressed to Ka M. Ng. ered the integration of product design and process design for creams and pastes; customer preferences lead to desirable quality factors that are then achieved by properly designing the process. This article presents such a product-centered systematic procedure for the synthesis and development of tablet and capsule manufacturing processes. Systematic Procedure Ž .There are 4 steps: 1 Identification of product quality fac-Ž . Ž . tors, 2 Product formulation, 3 Design of manufacturing Ž . process, and 4 Product and process evaluation. Design heuristics and physical models are presented to assist decision-making in each step.Step 1: identification of product quality factors Product quality factors other than therapeutic effects can be divided into functional, physical, and sensorial. For pharmaceuticals, the primary concern...

At present, food products are designed by trial and error and the sensorial ratings are determined by a tasting panel. To expedite the development of new food products, a hybrid machine learning and mechanistic modeling approach is proposed. Sensorial ratings are predicted using a machine learning model trained with historical data for the food under consideration. The approach starts by identifying a set of food ingredient candidates and the key operating conditions in food processing based on heuristics, databases, etc. Food characteristics such as color, crispness, and flavors are related to these ingredients and processing conditions (which are design variables) using mechanistic models. The desired food characteristics are optimized by varying the design variables to obtain the highest sensorial ratings. To solve this gray-box optimization problem, a genetic algorithm is utilized where the design constraints (representing the desired food characteristics) are handled as penalty functions. A chocolate chip cookie example is provided to illustrate the applicability of the hybrid modeling framework and solution strategy.

A systematic procedure is presented for the synthesis of chromatography-crystallization hybrid separation processes, which are widely used in the fine chemical and pharmaceutical industries for the recovery of high-purity products. The separation objectives and input information such as chromatograms and solid-liquid equilibrium phase diagrams are first identified. Second, the basic process structure is determined by specifying the order in which chromatography and crystallization units are used in the process. Third, the fractions of the chromatographic effluent and their destinations are specified to complete the process flowsheet. Finally, the generated process alternatives are evaluated to select the best one. Design heuristics are provided to assist decision making. The application of the procedure is illustrated using three examples.

A selective dissolution process to recover lithium from cathode materials by oxalic acid was investigated. The chemical reaction responsible for dissolution was identified, and the effects of operating parameters including temperature, acid concentration, as well as solid-to-liquid feed ratio on lithium recovery were studied using LiNi0.5Mn0.3Co0.2O2 (NMC-532) as the base case cathode materials, leading to a lithium recovery of 96.3% from cathode materials. However, 2.16% of manganese was also dissolved with lithium. An integrated process based on chemical and antisolvent precipitation was synthesized to separate and recover manganese and lithium with high recovery and high purity from the liquid after dissolution. This process was also shown to work on other cathode materials including LiNi x Mn y Co1–x–y O2 of various metal ratios, LiMn2O4 and LiCo0.95Mn0.05O2.

Abstract The nature of chemical product design problems is diverse and multidisciplinary. It involves many design issues such as project management, market study, product design, process design, and economic analysis for better organizing the product design project and achieving better products. This article provides an overview of chemical product design with a multidisciplinary hierarchical framework including all the design issues and tasks. Each of the design issues and tasks are introduced and discussed, methods and tools are summarized and compared, challenges and perspectives are presented to help the chemical product design researchers on finding more novel, innovative and sustainable products, by the combined effort from academia and industry to develop a systematic generic framework, and tools including product simulator, process simulator, database manager, modeling tool, and templates for design problems.

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