Research

Theory on high-temperature superconductors

Our research has been mainly interested in searching the mechanism of high-temperature superconductors (HTS). We have been focusing on using the variational approach and Gutzwiller's approximation to obtain the low energy states of the two-dimensional extended t-J models. The theoretical results have been compared with experiments of HTS to understand the applicability of this model. So far the model has been able to provide qualitative and even quantitative explanation for a number of experiements. We are trying to have more quantitative results to compare with many experimental properties of hole- and electron-doped HTS.

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X-ray diffraction microscopy

With the advance in nanoscience and nanotechnology, x-ray diffraction microscopy, a newly developed imaging technique, is becoming more and more important in structural determination of nonperiodic micro- or nano-objects. The idea of possibly extending the methodology of x-ray crystallography to noncrystalline objects, i.e., x-ray diffraction microscopy was first suggested by Sayre in 1980. It was not until in 1999 that the first demonstration experiment was carried out by Miao et al., which was based on the oversampling phasing method. When the diffraction intensities of a finite object are sampled sufficiently finer than the Nyquist frequency so that the number of correlated intensities is more than the number of unknown variables in real space, phases are usually uniquely encoded in the diffraction intensities.

We have developed an algorithm that combines the concept of optimization with the conventional hybrid input-output (HIO) algorithm for phase retrieval of oversampled diffraction intensities. In particular, the optimization algorithm of guiding searching direction to locate the global minimum has been implemented. Compared with HIO, this guided HIO algorithm retrieves the lost phase information from diffraction intensities with much better accuracy not only on model but also on experimental data.

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Biological physics

A human being produces 50000 to 100000 proteins. Each type of protein has a unique three-dimensional structure and this structure confers a unique function. Once a protein's structure is known, it's often possible to deduce its function, or at least guess at it. That, in turn, can give a hint as to where to look for the protein in the living organism so that it can be studied in detail. Therefore to study protein structure and to predict protein structure is now an important course in biophysical research. We developed an off-lattice minimal model to predict the structures of small proteins. The model is composed of a polypeptide chain with Ramachandran angles as its degrees of freedom. Residues are classified into Hydrophobic and polar groups. The force field of this model is based on hydrogen bonds and the anisotropic hydrophobic forces between hydrophobic residues. The energy form of the anisotropic hydrophobic forces is designed by analyzing the protein data banks. We have successfully predicted the structures of several small proteins with secondary structures including the £\-helix, £]-sheet and the £\/£] structures.

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