Biomedical subjects

Xiangqian Hu

Publications and source records attributed to Xiangqian Hu.

3 recordsLinked to original sources

PubMed2007

Designing molecules with optimal properties using the linear combination of atomic potentials approach in an AM1 semiempirical framework.

The linear combination of atomic potentials (LCAP) approach is implemented in the AM1 semiempirical framework and is used to design molecular structures with optimized properties. The optimization procedure uses property derivative information to search molecular space and thus avoid direct enumeration and evaluation of each molecule in a library. Two tests are described: the optimization of first hyperpolarizabilities of substituted aromatics and the optimization of a figure of merit for n-type organic semiconductors.

Journal Article↗

PubMed2006

Designing molecules by optimizing potentials.

The astronomical number of accessible discrete chemical structures makes rational molecular design extremely challenging. We formulate the design of molecules with specific tailored properties as performing a continuous optimization in the space of electron-nuclear attraction potentials. The optimization is facilitated by using a linear combination of atomic potentials (LCAP), a general framework that creates a continuous property landscape from an otherwise unlinked set of discrete molecular-property values. A demonstration of this approach is given for the optimization of molecular electronic polarizability and hyperpolarizability. We show that the optimal structures can be determined without enumerating and separately evaluating the characteristics of the combinatorial number of possible structures, a process that would be much slower. The LCAP approach may be used with quantum or classical Hamiltonians, suggesting possible applications to drug design and new materials discovery.

Journal Article↗

PubMed2005

Parallelization of MRCI based on hole-particle symmetry.

The parallel implementation of multireference configuration interaction program based on the hole-particle symmetry is described. The platform to implement the parallelization is an Intel-Architectural cluster consisting of 12 nodes, each of which is equipped with two 2.4-G XEON processors, 3-GB memory, and 36-GB disk, and are connected by a Gigabit Ethernet Switch. The dependence of speedup on molecular symmetries and task granularities is discussed. Test calculations show that the scaling with the number of nodes is about 1.9 (for C1 and Cs), 1.65 (for C2v), and 1.55 (for D2h) when the number of nodes is doubled. The largest calculation performed on this cluster involves 5.6 x 10(8) CSFs.

Algorithms↗