Recent general results on the statistics of nonequilibrium processes have opened up old debates between the exact dynamical and informational viewpoints on probability. Many of the good properties of equilibrium systems are not rigorously provable without assuming ergodicity. It turns out those arguments are even more relevant, and more pernicious, when working in a dynamical context. Even though nonequilibrium research predates traditional equilibrium thermodynamics, it is still seen by many as a vast, uncharted territory. In this talk, I show how there is a growing...
Hydrogen powered fuel cell cars, developed by almost every major car manufacturer, are ideal zero-emissions vehicles because they produce only water as exhaust. However, their reliability is limited because the fuel cell relies upon a membrane that only functions in when enough water is present, limiting the vehicle’s operating conditions.
Karl Johnson and his group have found that the unusual properties of graphane – a two-dimensional polymer of carbon and hydrogen – could form a type of anhydrous “bucket brigade” that transports protons without the need for water, potentially leading to the development of more efficient hydrogen fuel cells for vehicles and other energy systems. Graduate research assistant Abhishek Bagusetty is the lead author on their paper “Facile Anhydrous Proton Transport on Hydroxyl Functionalized Graphane”, recently published in Physical Review Letters. Computational modeling techniques coupled with the high performance computational infrastructure at the University’s Center for Research Computing enabled them to design this potentially groundbreaking material.
The understanding of the catalytic properties of nanoparticle catalysts and the design of optimal composition and structures demands fast methods for the calculation of adsorption energies. By exploring the adsorption of O and OR (R=OH, OOH, OCH3) adsorbates on a large range of surface sites with 9 transition metals, we propose new structure sensitive scaling relations between the adsorption energy of two adsorbates that are valid for all metals and for all surface sites.1 This opens the way for a new class of activity volcano plots where the descriptor is not an energy...
Prof. Ryan Steele of the University of Utah will be leading a workshop on the efficient calculation of vibrational anharmonicities. The workshop is open to everyone. Sign up by emailing LaShawn Youngblood...
The Behrend Computational Materials Meeting 2016 will be held Saturday, November 19 from 10 am to 4 pm at Penn State Behrend (Erie, PA). The focus of the meeting will be on Atomic Level Methods and Applications
There is no participation fee, and lunch will be provided. To officially register, please fill out the form below. Registration deadline is Wednesday Nov. 9, 2016. (Early registrations preferred).
Questions or concerns? Please e-mail Blair Tuttle at firstname.lastname@example.org
Energy expert Venkat Viswanathan have received funding from the U.S. Department of Energy’s Advanced Research Projects Agency – Energy (ARPA-E) to study the use of dendrite-blocking polymers in lithium-ion batteries.
When charged repeatedly, lithium-ion batteries run the risk of overheating, and even catching fire. This is due to the formation of dendrites, or microscopic fibers of lithium that can form during the charging cycle. Over time, these dendrites can grow long enough that they connect the battery’s electrodes to one another, causing the battery to short-circuit and become a potential hazard. In order to fully implement future lithium-ion battery technologies, which could greatly increase the battery power of our smartphones, electric vehicles, and more, engineers need to find a way to stop these dendrites from forming.
CMMT supports theoretical and computational materials research in the topical areas represented in DMR's core or individual investigator programs, which include: Condensed Matter Physics (CMP), Biomaterials (BMAT), Ceramics (CER), Electronic and Photonic Materials (EPM), Metals and Metallic Nanostructures (MMN), Polymers (POL), and Solid State and Materials Chemistry (SSMC). The program supports fundamental research that advances the conceptual understanding of hard and soft materials, and materials-related phenomena; the development of associated analytical, computational, and data-centric techniques; as well as predictive materials-specific theory, simulation, and modeling for materials research.