Disorder is a fact of life, and controlling it on the nanoscale is complex, expensive, and of limited use. On the other hand, disordered materials do offer a range of possible applications if we know how to identify their useful features. To this end, we propose an approach through Topological Learning  to quantify disorder and to correlate it with physical properties. We use this approach to design and create materials that display promising physical properties. We demonstrate this approach on specific nano systems that show promise and open the way to novel applications and investigations.