Enabling a sustainable renewable energy economy will require development of low cost and large scale energy storage technologies such as redox flow batteries. Inexpensive electrochemical energy storage depends on developing low cost, stable, conductive, and selective membranes. Rational design of the next generation of membranes requires fundamental understanding of the connection between polymer structure and membrane performance (e.g., transport properties, stability). In the proposed fundamental study, we will synthesize cross-linked cation and anion exchange membranes with independently controlled water uptake and charge density that vary over a broad range to systematically investigate the role of water uptake and nature of fixed charge groups on membrane hydrolytic and oxidative stability and ion transport properties.
People
Nirala
Singh
ChE
Engineering
Jovan
Kamcev
ChE
Engineering
Funding: $30K (2022)
Goal: Our project will build a feedforward neural-network emulator that uses inputs from an aerosol/climate model that are adjusted (in the neural network) to better fit available satellite-observations of aerosol optical depth.
Token Investors: Nirala Singh, Jovan Kamcev
Project ID: 1014