Texas Tech University
TTU HomeDepartment of Chemistry and Biochemistry Faculty Dr. L. William Poirier

Dr. L. William Poirier


Professor of Chemistry and Biochemistry, Joint Professor of Physics, Chancellor's Council Distinguished Research Awardee


Ph.D., University of California, Berkeley, 1997; Postdoctoral Study, University of Chicago, 1997-2000; Postdoctoral Study, University of Montreal, 2000-01

Research Area:

Theoretical and Computational Chemistry and Chemical Physics




Chemistry 033




Research Group

Principal Research Interests

Professor Poirier's research group is concerned with the development and application of new methods for performing accurate quantum dynamics calculations for molecular systems. These calculations encompass rovibrational spectroscopy (especially highly excited states), reactive scattering of molecules in the gas phase and in nanomaterials, and resonance phenomena (energies, widths, phase shifts). Applications of interest include hydrogen storage in carbon nanomaterials, dynamics of rare gas clusters, thermal rate constants pertinent to environmental chemical kinetics, and mass-independent fractionation of SO2 photodissociation products as a proxy for the Archaen Earth atmosphere.

The methods development research is motivated by the inadequacy of conventional numerical techniques for dealing with large molecules, insofar as accurate, quantum dynamics calculations are concerned. Traditionally, the computational effort required scales exponentially with problem size, as a result of which such calculations have traditionally been limited to systems with four or fewer atoms. Dr. Poirier's group is exploring a variety of new approaches that improve the computational efficiency by orders of magnitude, thereby making it possible to handle a much larger class of systems than has heretofore been realized. The quantum trajectory approach, inspired by Bohmian mechanics, incorporates quantum effects into classical-like trajectory simulations. Symmetrized Weyl-Heisenberg wavelets defeat exponential scaling in basis set methods, and have been applied to Taylor-expanded-potential systems with up to 27 dimensions, and adapted for massively parallel computing platforms. Traditional iterative discrete variable representation methods have also been adapted for massively parallel computers, with up to tens of thousands of cores.



Representative Publications