GINER INC — Department of Energy SBIR Phase I: 09b

Description

Chlorination is the disinfection method of choice in the water management industry. Current technologies and operators still assess levels of chlorinated species manually in the upstream portions utilizing analytical methods such as iodometric titration. Automating the chlorination process would significantly reduce operating costs and frequencies of plant shutdowns related to maintenance needs. The objective is to develop real-time, sensor for the inline measurement of total residual oxidants (TRO) species present in the disinfection process in pre-treatment of RO desalination facilities. Successful work will yield a prototype sensor designed to automatically perform measurements and provide a feedback to the controls system over a long period of time with minimal maintenance under real conditions. This will reduce costs associated with consumables, protect membranes and lower power consumption. The innovation of the proposed method is the use of a high- performance electrode platform combined with the high sensitivity of technique and machine learning for data analytics. Sensor chips and algorithm will be developed, tested and validated under a range of real and simulated desalination operation. Also work also will enable improved machine learning algorithms for TRO detection in complex matrices. Markets in the military, water management industry, waste water industry, and chlorine production industry.