The Nanoionics and Electronics Laboratory at the University of Pittsburgh’s Swanson School of Engineering has received $557,000 in funding from the National Science Foundation (NSF) for its work investigating a new type of two-dimensional material. The project, “Two-dimensional Polar Metals and Heterostructures,” is led by Associate Professor, Susan Fullerton, and Visiting Research Assistant Professor Ke Xu, both in the Department of Chemical and Petroleum Engineering.
Mechanical engineering professors Hessam Babaee and Peyman Givi recently received an award from the National Science Foundation (NSF) for a three-year project titled “Real-Time and Adaptive Chemical Kinetic Model Reduction Coupled with Turbulence.”
The chemistry of combustion involves understanding how a large number of species behave and evolve in a given operating condition. The tractability of this technically important problem becomes increasingly difficult when the operation involves turbulent mixing.
Three projects led by PQI professors in the University of Pittsburgh’s Swanson School of Engineering, James McKone, Feng Xiong, and Nathan Youngblood, recently received funding from the National Science Foundation. Additionally, Ken Jordan in the Pitt Department of Chemistry is Co-PI on an NSF-funded project led by Lei Li to use computational methods to understand the mechanisms of wetting transparency of graphene on liquid substrates and demonstrate the real-time control of surface wettability
Dr. Wissam Saidi, Associate Professor in the Department of Mechanical Engineering and Materials Science at the University of Pittsburgh, was selected to receive $600,000 of NSF funding over 3 years. The Saidi group develops and uses multiscale simulation tools, including force-field, density-functional theory, quantum Monte Carlo and quantum chemistry methods, to understand, predict, and design novel materials for applications in energy conversion and storage, surfaces and interfaces, spectroscopy, and nanoparticles.
The goal of the proposal, "DeepPDB: An open-source active-learning framework to enable high-fidelity atomistic simulations in unexplored material space", will be to offer an open-source toolkit with the ability to automatically generate estimates of force-fields parameters using advanced empirical-based computational tools.
Sangyeop Lee, PhD, assistant professor of mechanical engineering and materials science, received a $500,000 CAREER Award from the National Science Foundation (NSF) for research that would utilize machine learning to model thermal transport in polycrystalline materials. The research seeks to create a computer model that can predict the conductive properties of a material in real life, providing guidance to engineer defects for desired thermal properties.
Congratulations Dr. Lee!
The National Science Foundation has awarded Giannis (Yanni) Mpourmpakis $354,954 to continue his research into a promising but poorly understood method of creating olefins. Olefins, simple compounds of hydrogen and carbon, serve as the building blocks in chemical industry and are important for the synthesis of materials, including polymers, plastics and more. However, creating them can be problematic: it requires the use of fossil fuels, energy intensive “cracking” facilities, and limited production control. The team in Dr. Mpourmpakis’s CANELa lab will use computational modeling and machine learning to understand how the dehydrogenation of alkanes takes place on metal oxides, and use that knowledge to screen a wide range of metal oxides and their properties for use in the process.
Congratulations Dr. Mpourmpakis!
Join Angela Wilson of NSF, Cynthia Burrows of the University of Utah, Theodore Goodson of the University of Michigan, and Glenn Ruskin of ACS for an introduction of two of the most impactful "Big Ideas" as well as an overview of this innovative NSF program that will advance prosperity, security, health, and well-being in the United States.
Learn more about : "Why Quantum entangled processes may play a role in our understanding of biological processes?"
NSF recently unveiled 10 Big Ideas — bold, long-term research and process ideas at the frontiers of science and engineering.1 Among these ideas, Quantum Leap aims to exploit quantum mechanical phenomena such as superposition and entanglement to develop next-generation technologies for sensing, computing, modeling, and communication. In the Fall of 2016, the Division of Chemistry (CHE) sponsored a workshop entitled "Quantum Information and Computation for Chemistry",2 led by Alán Aspuru-Guzik of Harvard University and Michael Wasielewski of Northwestern University to explore the relevance of Quantum Leap to the field of chemistry. The workshop identified areas where chemists can contribute to Quantum Leap and areas where advances in Quantum Leap can enable the solution of intractable chemical problems. To follow up on the recommendations of the workshop, the CHE invites submission of supplemental funding requests and EAGER (EArly-Concept Grants for Exploratory Research) (EAGER) proposals on Quantum Leap.
This Dear Colleague Letter (DCL) emphasizes molecular approaches towards problems in quantum computing, sensing, communicating, etc.
Quantum Information Science and Engineering Network (QISE-NET) is housed at the Chicago Quantum Exchange, an intellectual hub and partnership for advancing academic and industrial efforts in the science and engineering of quantum information. QISE-NET is built "Triplets" to Bridge Academia and Industry which is sponsored by the National Science Foundation within the “Quantum Leap” and “Growing Convergent Research” Big Ideas. TRIPLETS program offers excellent opportunities for graduate students in all areas of quantum information science and engineering.
Tevis Jacobs, assistant professor of mechanical engineering and material science at the University of Pittsburgh's Swanson School of Engineering, received a grant from the National Science Foundation (NSF) to observe and measure nanoscale contact inside of an electron microscope-enabling for the first time visualization of the atomic structure of the component materials while they are in contact. The team's project will measure surface roughness of tiny particles and characterize the fundamental relationship between adhesion and roughness at small sizes.