Anticipating the increased need for better oxygen concentrators as the fight against COVID-19 rages on, researchers have laid a computational framework to design the most optimal concentrator to filter ambient air and produce oxygen that can scale with patient demand. Oxygen concentrators based on their design would also help those suffering from other respiratory conditions, such as chronic obstructive pulmonary disease, pneumonia, and asthma.
To enhance the design of current medical oxygen concentrators, they first selected three types of zeolites, LiX, LiLSX, and 5A, for his analysis. Next, they ran a physics-based simulation that modeled different properties of the zeolites along with characteristics of the oxygen concentrator, including the size of the adsorption chamber and the different stages within the adsorption process.
Then, using a high-performance computing cluster, they varied all these inputs of the simulation simultaneously to arrive at the most optimal operating range that would yield a compact, easy-to-transport and high-performance medical oxygen concentrator. In particular, the LiLSX performed better than LiX and 5A zeolites, producing 90 percent pure oxygen at a high rate. In addition, researchers found the LiLSX-based system could be used to generate different levels of oxygen purity and flow rates.
The experts said their study is also a first step in creating portable cyber-physical systems for home use that can change oxygen supply depending on the patient’s needs. So, if a patient requires more oxygen as symptoms worsen, built-in algorithms could analyze data from oxygen sensors to predict if more ventilation is needed, relay that information to off-site physicians who can then use their judgement to remotely change settings on the medical oxygen concentrator.