Dr. Martin Conda-Sheridan and his lab aim to merge material sciences and medicinal chemistry to create tiny materials (nanostructures) to advance science and improve human health. Their goal is to create “on-demand†nanotechnologies tailored to industrial or patient needs. Their first objective is to create two types of nanostructures: those sensitive to different conditions, and those resistant to the environment to meet the needs of the chemical and pharmaceutical industries. Their second objective is to develop computer software that will allow scientists and clinicians to predict the shape and behavior of nanostructures when placed in different environments. Their third objective is to create nanostructures responsive to free radicals, which are linked to aging, illness, and oxidative stress. This can evolve into responsive therapies for health conditions associated with inflammation – including cancer. In summary, Dr. Conda-Sheridan and his team propose to prepare biocompatible nanostructures to develop responsive, on-demand treatments. If successful, a physician may someday consult a computer program to foresee which nanostructure(s) would best treat a health condition. In addition, the team will develop educational activities geared towards students and the general public, seeking to increase the basic understanding of nanotechnology. Wikipedia pages and instructional videos will be translated into several languages in hopes of reaching a wide audience of science enthusiasts. The goal is to teach and share the findings of this project with the wider world, inspiring a new generation of material scientists and engineers working in nanotechnology.
The design of smart, self-assembling nanostructures with easy to modify properties is a thriving new field that can revolutionize material science, engineering, and chemistry. The long-term goal of this project is to create multifunctional nanostructures that possess tunable properties and are responsive to external stimuli. To achieve this final goal, this project is divided into three objectives. The First Objective will focus on tuning intra- and inter-molecular forces to modify properties at the supramolecular level. This will permit the control of the morphology and physicochemical properties of the nanomaterials. The Second Objective will focus on developing theoretical tools (based in statistical mechanics) that can be used to predict supramolecular shape from the self-assembling molecules. This new software will be used to design novel nanostructures. The Third Objective seeks to prepare stimuli responsive nanomaterials. This will lead to nanostructures that can release selected molecules on demand and at various rates by the action of reactive oxygen species. This research will generate new biomaterials that are composed of diverse chemical functionalities with distinct pKas, hydrogen bonding potential, size, spatial orientation, and stereochemistry. It is expected these new biomaterials can lead to smart nanostructures that can adjust their behavior based on pH, salt concentration, temperature etc. The ability to design and tune material properties and molecular release with the aid of theoretical models and by the simple exchange of building blocks can lead to breakthroughs in material science, engineering, and medicine. In addition, this research will support educational activities geared towards high school, undergraduate and graduate students in a variety of science disciplines as well as the general public to increase nanotechnology literacy. Key concepts in self-assembly and nanotechnology will be disseminated by two primary teaching activities: (1) editing and expanding relevant Wikipedia entries, and (2) the creation of educational videos. The educational component will be translated to multiple languages and made available free to the public in order to reach larger audiences across the globe.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
