Prof. Pandey received his Ph.D. from IIT Roorkee in 1981 and worked at the North Carolina State University (1981-1982) as a visiting assistant professor before his postdoctoral work at Cologne University (1983), University of Cambridge (1984), University of Georgia (1984). He became assistant professor at the Jackson State University in 1985 and moved to University of Southern Mississippi (in 1988) where he is professor of physics for about 30 years. His research spans over a wide range of application of statistical physics (transport and flow of fluid in porous media, polymer, interface and roughness, nano-bio-composites, protein). He has over 150 papers in refereed journals. He was awarded Alexander von Humboldt fellowship early in his career and recently became a fellow of the American Physical Society. He is an academic editor of AIP Advances (American Institute of Physics) and has served in several national and international scholarly committees (research funding, program review, promotion etc.) and collaborated with many research groups around the world.

Morphing structures and dynamics by a multigrain approach

R.B. Pandey

Department of Physics and Astronomy

University of Southern Mississippi, Hattiesburg, MS 39406-5046, USA

 E-mail:; Telephone: +1 601 266 4485



A multicomponent system such as self-organizing flow of an immiscible fluid, bio-functionalization of nano-materials, and conformational response of proteins involves multi-scale dynamics and relaxations leading to well-defined morphing structures. Basic constitutive components may consist of particles (solvent), chains (polymer, peptide, and protein), platelets (clay, tethered membrane, graphene sheets) etc. with diverse shapes, sizes, and interactions. Relaxation of these constitutive units resulting from their stochastic movements and driving parameters such as temperature and field are critical in evolution of multi-scale structures. Although it is desirable, but often not feasible to incorporate all details from atomic scale in a large-scale computational modeling of many organizing systems and reach a desirable length scales needed to understand observables. Some degree of coarse-graining, therefore, becomes unavoidable in modeling of large-scale hierarchical assembly. Coarse-graining involves simplifying the complexity via approximations such as reducing the degrees of freedom and implementing efficient and effective computational methods. What and how to incorporate relevant details in coarse or fine-graining to explore a vast ensemble of phase space depends on specific issues.

Using multi-grained mechanism (e.g. simulated interactions, knowledge based data ensemble, and phenomenological interactions) we have examined organizing structures of a number of model systems over the years. Even with a simple particle constituents, one may be able to investigate self-organizing flow in a multi-component fluid and gain insight into linear and non-linear responses [1]. Bio-functionalization of a nano particle (Au, Pd, graphene) requires identifying appropriate peptides based on desirable characteristics, their binding propensity to specific target and stability; the functionalized nanoparticles can constitute a building block in designing smart materials with hierarchical structures for such application as sensing or drug delivery [2]. Investigating the scaffolding of peptides [3] could be useful in understanding such assembly as a templet for silica condensation by a marine microbe (diatom) in biomineralization [4].

Despite enormous interest in protein folding for decades, understanding of how a protein moves, relax, and conform to stable structures with prolific yet specific response remains an open question. Examples include membrane proteins such as unusual structural response of hHv1 and corA in their native and denatured phases [5, 6], self-organizing morphology of amyloid proteins such as lysozymes [7] etc. A number of local and global physical quantities such as the energy and density profiles, contact and mobility maps, mean square displacements, radius of gyration, and structure factor are analyzed to understand multi-scale characteristics. Some of our findings from simplified coarse-grained models augmented by fine-grained data will be presented as time permits.

Keywords: Coarse-grained models, multi-component systems, bio-nano materials, protein folding.

Acknowledgement: RBP acknowledges generous support from the Chulalongkorn University where some of the recent work is performed in our on-going collaboration with the research group of Prof. Pornthep Sompornpisut. Warm hospitality of the Chemistry Department at the Chulalongkorn University is gratefully acknowledged.


  1. Pandey, R.B. and Gettrust J.F., Rev. E 2009, 80, 011130.
  2. Pandey, R.B., Heinz, H., Feng, J., and Farmer, B.L., Chem. Phys. 2010, 133, 095102.
  3. Pandey, R.B., Kuang, Z., and Farmer, B.L. PLoS One 2013, 8, e70847-1 – e70847-8.
  4. Eby, D.M., Johnson, G.R., Farmer, B.L., and Pandey, R.B., Chem. Chem. Phys. 2011, 13, 1123.
  5. Kitjaruwankul, S., Khrutto, C., Sompornpisut, P., Farmer, B.L., and Pandey, R.B. Chem. Phys. 2016, 145, 135101.
  6. Boonamnaj, P., Paudel, S.S., Jetsadawisut, W., Kitjaruwankul, S., Sompornpisut, P., and Pandey, R.B., preprint 2018.
  7. Pandey, R.B., Farmer, B.L., Bernard S. Gerstman, B.S., AIP Advances 2015, 5, 092502-1 – 092502-12.