This award supports research and education in computational and theoretical studies of nonequilibrium phenomena in electrochemical materials science. These studies are concerned with modeling of specific experimental systems, with investigation of fundamental nonequilibrium phenomena of importance to such systems, and with further development of computational and theoretical methods.
The particular experimental phenomena, which will be investigated in collaboration with experimental groups, are island growth and dissolution in electrochemical pulsed-potential studies of single-crystal gold surfaces, and verification of a new method to study the dynamics of electrode surfaces that was suggested by the PI's computer simulations. Particular nonequilibrium phenomena that are investigated include the influence of lateral diffusion during electrochemical metal deposition and in heterogeneous catalytic reactions, and hysteresis in systems that are driven far from equilibrium by an oscillating force.
The main method that will be used in the proposed research is large-scale computer simulation of model systems. Both continuous and discrete models will be used, and the computational methods will include kinetic Monte Carlo (KMC) simulations and numerical solution of stochastic differential equations, both with model parameters obtained from quantum-mechanical density-functional-theory calculations. The simulation data will be analyzed using several theoretical methods, including finite-size scaling theory, theory of stochastic processes, and statistics.
The research has broader impact beyond the particular scientific investigations undertaken and contributes broadly to understanding issues of nonequilibrium processes and is relevant to technological development and has educational benefits. Since all time-dependent phenomena in nature, as well as in technology, are out of equilibrium by definition, nonequilibrium statistical mechanics is an essential research area. This research adds to our fundamental understanding of nonequilibrium processes. More specifically, this research improves understanding of nonequilibrium processes at electrode-electrolyte interfaces, and thereby contributes to the future development of new, electrochemistry-based manufacturing processes for advanced nanomaterials. Such fundamental knowledge and simulation algorithms developed through the research are applicable in many scientific and technological fields, including materials science, chemistry, biology, and even to the design and analysis of communications networks and power grids. This computationally intensive research is ideal for involving apprentices at all levels in the discovery process. It will contribute to education at all levels while including women and minorities by involving undergraduate and graduate students and postdoctoral fellows, who will mentor K-12 students. The results of the research will be communicated through articles in a wide spectrum of professional journals, through talks at scientific meetings, and through presentations for the general public, as well as through the World Wide Web.
NONTECHNICAL SUMMARY:
This award supports theoretical and computational research, and education on the growth of materials and structures of atoms on the scale of nanometers, about one ten-millionth of an inch, by electrochemical methods. During the last two decades experimental techniques have become available that enable electrochemical methods to manufacture high-tech materials that derive their functionality from structure on the nanometer scale. These methods are rapidly becoming cost-effective alternatives to traditional methods. These impressive experimental developments are matched by spectacular progress in computer technology and computational methods. The PI will use computer simulation methods to study how nanoscale structures grow on the surface of electrode materials immersed in a chemical solution with an electric current flowing through the electrodes. The study of growth phenomena like these advances the understanding of phenomena that are intrinsically out of equilibrium, an area of intense interest in modern statistical physics. Since all time-dependent phenomena in nature, as well as in technology, are out of equilibrium by definition, nonequilibrium statistical mechanics is an essential research.
This computationally intensive research is ideal for involving apprentices at all levels in the discovery process. It will contribute to education at all levels while including women and minorities by involving undergraduate and graduate students and postdoctoral fellows, who will mentor K-12 students. The results of the research will be communicated through articles in a wide spectrum of professional journals, through talks at scientific meetings, and through presentations for the general public, as well as through the World Wide Web.
This project has concentrated on applications of large-scale computing and theoretical methods from statistical physics to various problems in electrochemical materials science. Methods developed through these efforts have also been applied to a broader range of problems in materials science, engineering, and biology. Intellectual Merit Electrochemical materials science encompasses the study of electrochemical energy sources, such as batteries and fuel cells, catalytic reactions of technological and scientific interest, and new methods for synthesizing nanostructures and designer catalysts by deposition of atoms and molecules on electrode surfaces. This project has delivered outcomes in all three areas. Lithium-ion batteries are the state-of-the-art energy source for devices ranging from cell phones to electric cars. However, the time necessary to charge such batteries is generally several hours. We performed numerical simulations of the motion of the ions near the cell’s graphite anode. Charging the battery involves the entrance, or intercalation, of lithium ions between the carbon layers of the anode. Our simulations suggest that charging can be accelerated by adding an oscillating voltage to the DC charging voltage. A snapshot from the simulations is shown as Image 1. Catalysis of chemical reactions on solid surfaces is essential for a host of applications in industry and science. One example is the oxidation of carbon monoxide (CO) to carbon dioxide (CO2) in automotive catalytic converters. A problem with this reaction is that the catalyst surface can be saturated, or "poisoned," by CO at high pressures. In collaboration with colleagues in Venezuela, we have therefore studied the effects of removal (desorption) of unreacted CO from the surface, and of inert impurities in the feed gas. We find that the former enables the reaction to continue at a reduced rate, even at high CO pressures. The latter, on the other hand, may lead to a poisoned surface, even in the presence of both unreacted CO and O. Image 2 shows such a case of poisoning, in which the impurities form a barrier between the two reactants, thus preventing the reaction from taking place. Electrodeposition of halides, such as chlorine and bromine, on electrode surfaces provides a useful model system for electrochemical synthesis of nanostructures. To understand the structures formed during such deposition, it is necessary to know several energy parameters that can best be estimated by quantum-mechanical calculations. We have successfully used a computational method known as Density Functional Theory to determine the interaction energies between chlorine and bromine atoms on the surface of a silver electrode. Images of the simulated system and several possible atomic configurations, whose energies were evaluated, are shown in Image 3. Broader Impacts The mathematical description of adsorption on a surface is in many ways similar to the description of magnetization reversal in ultra-high density recording media such as computer hard disks. Recording involves a trade-off between long storage times and rapid writing. One method, which has been suggested to achieve both, is to locally heat the recording area during writing, known as Heat Assisted Magnetization Reversal (HAMR). Using large-scale kinetic Monte Carlo simulations, we predict that the relative speed-up due to the heating has an optimum at an intermediate value of the writing field. A snapshot of the simulated system during the switching process is shown in Image 4. Spin-crossover materials are molecular crystals that can exist in different states, called "low-spin" (LS) and "high-spin" (HS), which have different volumes. They are important candidate materials for nanoscale electronic components, such as switches and memory elements. As a result of the different volumes of the two states, a long-range elastic interaction between different molecules exists, in addition to short-range interactions. This mixture of short- and long-range interactions results in interesting and potentially technologically useful effects. We have studied models of such materials by several computational and theoretical methods in collaboration with colleagues in Japan, France, and Romania. A snapshot of our model in the process of switching from the LS state (red) to the HS state (blue) is shown in Image 5. Statistical physics is the science of systems that consist of large numbers of interacting parts. Methods developed through this project have therefore also proven useful in elucidating problems outside the usual confines of chemistry and physics. One example is a project we have started to develop network-theoretical methods to partition a power grid into "islands" that are tightly connected internally, but loosely connected with each other. Knowledge of optimal island partitionings can be useful in limiting the spread of large-scale blackouts. A partitioning of the Florida high-voltage power grid is shown as Image 6. In collaboration with colleagues in Canada and Japan, we have also studied several applications of our simulation techniques to problems in ecology and evolutionary biology. Two undergraduate students, eight graduate students, and two postdoctoral associates have received research training through this project.
