Integrated Calendar

The self-consistent phonons (SCP) method is a practical approach for computing structural and dynamical properties of a general quantum or classical many-body system while incorporating anharmonic effects. In SCP one finds an effective temperature-dependent harmonic Hamiltonian that provides the “best fit” for the physical Hamiltonian, the “best fit” being defined as the one that optimizes the Helmholtz free energy at a fixed temperature. The numerical bottleneck of the method is the evaluation of Gaussian averages of the potential energy and its derivatives. Several algorithmic ideas/tricks are introduced to reduce the cost of such integration by orders of magnitude, e.g., relative to that of the previous implementation of the SCP approach by Calvo et al.
[J. Chem. Phys. 133, 074303 (2010)]. One such algorithmic improvement is the replacement of standard Monte Carlo integration by quasi-Monte Carlo integration utilizing low-discrepancy sequences. SCP has been used to study the equilibrium properties and the structural transitions in small and large Lennard-Jones clusters. The method was also applied to computations of vibrational spectra of water clusters.

An extensive array of surface-sensitive characterization techniques that provide microscopic and spectroscopic information have revealed the structure of many crystal surfaces in their pristine clean state. Most of these studies are carried out in ultrahigh vacuum (UHV), which makes it possible to control sample composition and cleanliness to better than 0.1% of a monolayer. Starting from those by Irving Langmuir, such surface science studies constituted the core of our present understanding of solid surfaces. Under realistic ambient conditions, however, our knowledge is far less extensive. Of particular interest is the structure and chemical state of surfaces in dynamic equilibrium with gases and liquids at ambient conditions. Ambient pressure x-ray photoelectron spectroscopy (APXPS) and high pressure scanning tunneling microscopy (HPSTM) were developed for this purpose, i.e., understanding the atomic, electronic, and chemical structure of surfaces in the presence of reactant gases and liquids.
My talk will have three parts. The first part will be about ‘following surface structures’. I will show that the most compact and stable surfaces of Cu undergo massive reconstructions in the presence of CO at room temperature at pressures in the Torr range, and they decompose into two-dimensional nanoclusters, which is a double effect of low cohesive energy of Cu and the high gain in adsorption energy at the newly formed under-coordinated sites. Finally, it will be shown that the surfaces which are broken up into clusters are more active for water dissociation, a key step in the water gas shift reaction. Such a behavior opens a new paradigm, especially for other soft metals like gold, silver, zinc, etc., and it is clear that we need more of such studies. I will also briefly comment on the predictive power of my results and whether we can extrapolate it to other metals and reactants other than CO.
The second part will centered on ‘following surface reactions’ with APXPS. This technique is so powerful that it allows us to monitor the changes in the chemical state of the adsorbent, as well as coverage of adsorbates. As an example, I chose the CO oxidation reaction on Cu surfaces. It will be shown that if Cu remains metallic, the activation energy of the reactions scales with the oxygen binding energy, which is the manifestation of the Sabatier effect. In the presence of both CO and O2, however, the surface gets covered with 1-3 nm of Cu2O layer, which is more active than metallic Cu, but no CuO forms under the pressure and temperature range chosen in my study.

The final part will be about the possible future directions which I find important in the field for the next 5-10 years. Especially I will mention new approaches I plan to take for technique development which can offer measurements at higher pressures, as well as extend the outreach of the available techniques to other fields where solid-gas and solid-liquid interactions play an essential role.

Arguably, quantitative neuroscience was born when scientists started to correlate the activity of a neuron with sensory stimuli. But complex stimuli, such as natural ones, are encoded in the activity of
entire populations of neurons. What is the grammar of this code? Specifically, how are the correlations among neurons and their physiological diversity involved in this code? In this talk, I will discuss analyses of the output of populations of identified and simultaneously recorded visual neurons. In these populations, and against the textbook picture of neural population coding, correlations in the spiking variability enhance the coding performance. This unexpected phenomenon relies upon a particular structure of the correlations observed in data and, surprisingly, yields a strong effect even in very small populations of neurons. I will, further, explain how the favorable structure of correlations can emerge from simple circuit features. Finally, if time allows, I will present more general theoretical extensions in which, with the use of simple models, one can illustrate the massive influence that correlations and physiological diversity can have on the precision and capacity of the neural code.