i-CREW-International Collaboration for Optimisation of Resource Recovery from Wastewater

为了实现可持续的循环经济，需要优先考虑有用资源的回收和再循环。金属污染的工业废物流引起了巨大的健康和生态问题，但它们也是回收金属等有用资源的宝贵来源。传统的金属回收技术能耗高，化学成分密集。微生物燃料电池（mfc）等生物电化学系统已成为工业废水中金属离子去除和回收的新型可持续技术平台。mfc在阳极通过微生物生物膜处理有机废水，在阴极从含金属废物流中还原金属离子。到目前为止，已经证明了几种金属离子如钴、铬、铜、金、银、硒、钒、锌等的回收。虽然前景看好，但利用mfc回收金属是一个复杂的过程，取决于大量的操作和设计参数，如pH值、金属离子的氧化还原电位、电极材料类型、废水中金属离子的初始浓度等。为了优化工艺，最大限度地利用mfc回收金属，需要进一步研究不同决定因素对工艺的影响。在这个国际合作项目中，我们结合了位于英国和印度的两个世界领先研究小组的优势，开发了一个强大的预测优化工具，可用于确定设计和操作条件，以最大限度地从废水中回收金属。萨里大学的研究人员Siddharth Gadkari博士和Jhuma Sadhukhan博士将根据S Venkata Mohan博士实验室的实验数据，开发过程优化的综合数学模型。

To achieve a sustainable circular economy, recovery and recycling of useful resources needs to be prioritized. Metal contaminated industrial waste streams post great health and ecological concerns, but they are also a valuable source for recovery of useful resources like metals. Traditional metal recovery technologies involve high energy consumption and are chemically intensive. Bioelectrochemical systems such as microbial fuel cells (MFCs) have emerged as a new sustainable technology platform for removal and recovery of metal ions from industrial wastewaters. MFCs combine treatment of organic wastewater by microbial biofilms at the anode with the reduction of metal ions from metal-laden waste streams at cathode. So far, recovery of several metal ions like Cobalt, Chromium, Copper, Gold, Silver, Selenium, Vanadium, Zinc, etc., has been demonstrated. Though promising, metal recovery using MFCs is a complex process and depends on large number of operational and design parameters such as, pH, redox potential of the metal ion, type of electrode materials, initial concentration of metal ions in the wastewater, etc. To optimize the process and maximize metal recovery using MFCs, more research is needed to understand the role of different determinant factors influencing the process. In this international collaborative project, we combine the strengths of two world leading research groups based in UK and India, to develop a robust predictive optimisation tool that can be used to determine the design and operating conditions to maximize the recovery of metals from wastewaters. University of Surrey researchers, Dr. Siddharth Gadkari and Dr. Jhuma Sadhukhan, would develop the comprehensive mathematical models for process optimisation based on the experimental data from the laboratory of Dr. S Venkata Mohan.