Intellectual Merit:

The results of the research include the development of novel computational models for the prediction of the toxicity of nanomaterials, study of structures and properties of various nanomaterials, study of hybrid plasmonic materials, and the design of new materials for  biomolecular identification.

We have developed computational models for chemicals, pharmaceuticals, and nanomaterials that can be used to predict the toxicity and properties of untested and new materials for toxicity assessment. Such predictions can fill the gaps in toxicity and property data and can be used for risk assessment and regulatory decision making as well as for market approval of new products. We have developed new in silico methods for the prediction of hazardous environmental organic pollutants (chemicals, pharmaceuticals, and personal care products: PPCP's). We have also proposed novel tools and time- and cost-efficient nano descriptors to encode the toxicity and/or response features of nanomaterials, which can speed up the toxicity/property prediction of nanomaterials.

Further, we have used computational methods to study silver "nanodots" (a few silver atoms (a cluster) surrounded by "a shield" of non-metal protecting groups), with potential applications arising from the properties of the silver cluster when it interacts with light. The calculations have given detailed information on atomic structures of the nanodots, which is not available from experiment. It is noteworthy that the protecting groups are found to change the silver cluster structure significantly compared with a free cluster. Regarding light absorption and emission, it has been found that absorption occurs at higher energies than visible light, but visible light emission is possible.

Our research  has also involved hybrid plasmonic materials such as metal nanoparticles and biomolecule systems. We have obtained several significant new results regarding the optical properties of these materials that resolved several  outstanding issues and contributed to accurate interpretation of experimental data.

Finally, our research has produced new materials for  biomolecular identification. We have obtained several significant new results regarding  improvement of new sensors using the material we have developed.

Broader Impact:

Our research has contributed to the development of tools for the prediction of the toxicity and properties of nanomaterials, which has implications for protecting human health and environment. Moreover, the results of our research are relevant to several related disciplines such as electrical engineering or biomedical research. The theoretical models we have developed can be useful in a number of applications such as biosensing and imaging.

The project has also facilitated mentoring and support of high school, undergraduate, and graduate students and post-doctoral associates who learned and applied advanced computational methods towards various research tasks. It expanded their knowledge and provided them with intensive hands-on and theoretical training necessary for the next generation workforce. We have published over 84 research and review articles including book chapters over the five-year span. Multiple invited talks, oral and poster presentation were given by PI's, Co-PI's, post-docs, graduate and undergraduate students.

Last Modified: 09/06/2023
Modified by: Jerzy Leszczynski