About MetalNanoDB

In this database we present optimally stable bimetallic nanoparticles to advance the ever-expanding reach of nanotechnology into everyday life. Despite languishing for decades solely as science fiction, recently nanotechnology has achieved stunning advances across many fields, that span from medicine to energy and the environment. For example, in the chemical industry bimetallic nanoparticles yield powerful new catalysts by making molecules react fast on their surface1. Bimetallic nanoparticles can exhibit sites that can bind CO2, a greenhouse gas, and potentially convert it to useful fuels and chemicals2. Much of the nanotechnological revolution has been driven by advances in computational methods, such as our recently developed Bond-Centric Model3, which enables the rapid determination of bimetallic nanoparticle stability. Leveraging this remarkable advancement, we have developed a first-of-its-kind genetic algorithm that predicts the chemical ordering (i.e. how the elements are distributed) of nanoparticles of any size, shape, or composition4. To demonstrate the versatility of our method and facilitate the dissemination of our results, in this database we present the optimal chemical orderings of thousands of bimetallic nanoparticles.

The development of this database is a collaborative effort of the Computer Aided Nano and Energy Lab (CANELA) and the Advanced Data Management Technologies Lab (ADMT) at the University of Pittsburgh.

This database is based upon work supported by the National Science Foundation under Award No. 1634880. This work is also partially supported by the National Science Foundation under Award No. 1609120. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.


[1] Dean, J.; Taylor, M. G.; Mpourmpakis, G., Unfolding adsorption on metal nanoparticles: Connecting stability with catalysis. Science Advances 2019, 5 (9), eaax5101.
[2] Dean, J.; Yang, Y.; Austin, N.; Veser, G.; Mpourmpakis, G., Design of Copper-Based Bimetallic Nanoparticles for Carbon Dioxide Adsorption and Activation. ChemSusChem 2018, 11 (7), 1169-1178.
[3] Yan, Z.; Taylor, M. G.; Mascareno, A.; Mpourmpakis, G., Size-, Shape-, and Composition-Dependent Model for Metal Nanoparticle Stability Prediction. Nano Letters 2018, 18 (4), 2696-2704.
[4] Dean, J.; Cowan, M. J.; Estes, J.; Ramadan, M.; Mpourmpakis, G., Rapid Prediction of Bimetallic Mixing Behavior at the Nanoscale. ACS Nano 2020, 14 (7), 8171-8180.