Shanmugam Kumar

Bio: Shanmugam Kumar is an academic researcher from University of Glasgow. The author has contributed to research in topics: Adhesive & Finite element method. The author has an hindex of 27, co-authored 91 publications receiving 2614 citations. Previous affiliations of Shanmugam Kumar include University of Oxford & Indian Institute of Science.

Gas Barrier Performance of Graphene/Polymer Nanocomposites

Abstract: Due to its exceptionally outstanding electrical, mechanical and thermal properties, graphene is being explored for a wide array of applications and has attracted enormous academic and industrial interest. Graphene and its derivatives have also been considered as promising nanoscale fillers in gas barrier application of polymer nanocomposites (PNCs). In this review, recent research and development of the utilization of graphene and its derivatives in the fabrication of nanocomposites with different polymer matrices for barrier application are explored. Most synthesis methods of graphene-based PNCs are covered, including solution and melt mixing, in situ polymerization and layer-by-layer process. Graphene layers in polymer matrix are able to produce a tortuous path which works as a barrier structure for gases. A high tortuosity leads to higher barrier properties and lower permeability of PNCs. The influence of the intrinsic properties of these fillers (graphene and its derivatives) and their state of dispersion in polymer matrix on the gas barrier properties of graphene/PNCs are discussed. Analytical modeling aspects of barrier performance of graphene/PNCs are also reviewed in detail. We also discuss and address some of the work on mixed matrix membranes for gas separation.

Gas barrier properties of polymer/clay nanocomposites

Abstract: In the field of nanotechnology, polymer nanocomposites (PNCs) have attracted both academic and industrial interest due to their exceptional electrical, mechanical and permeability properties. In this review, we summarize the state-of-the-art progress on the use of platelet-shaped fillers for the gas barrier properties of PNCs. Layered silicate nanoclays (such as montmorillonite and kaolinite) appear to be the most promising nanoscale fillers. These exfoliated nanofillers are able to form individual platelets when dispersed in a polymer matrix. The nanoplatelets do not allow diffusion of small gases through them and are able to produce a tortuous path which works as a barrier structure for gases. The utilization of clays in the fabrication of PNCs with different polymer matrices is explored. Most synthesis methods of clay-based PNCs are covered, including, solution blending, melt intercalation, in situ polymerization and latex compounding. The structure, preparation and gas barrier properties of PNCs are discussed in general along with detailed examples drawn from the scientific literature. Furthermore, details of mathematical modeling approaches/methods of gas barrier properties of PNCs are also presented and discussed.

Electrical conductivity of CNT/polymer composites: 3D printing, measurements and modeling

Abstract: We present electrical conductivity measurements and modeling aspects of carbon nanotube (CNT)/polymer composites enabled via fused filament fabrication (FFF) additive manufacturing (AM). CNT/polylactic acid (PLA) and CNT/high density polyethylene (HDPE) filament feedstocks were synthesized through melt blending with controlled CNT loading to realize 3D printed polymer nanocomposites. Electrical conductivity of 3D printed CNT/PLA and CNT/HDPE composites was measured for various CNT loadings. Low percolation thresholds were obtained from measured data as 0.23 vol. % and 0.18 vol. % of CNTs for CNT/PLA and CNT/HDPE nanocomposites, respectively. Moreover, a micromechanics-based two-parameter agglomeration model was developed to predict the electrical conductivity of CNT/polymer composites. We further show that the two agglomeration parameters can also be used to describe segregated structures, wherein nanofillers are constrained to certain locations within the matrix. To the best of our knowledge, this is the first ever electrical conductivity model to account for segregation of CNTs in the matrix. A good agreement between measured conductivity and predictions demonstrates the adequacy of the proposed model. We further evince the robustness of the model by accurately capturing the conductivity measurements reported in the literature for both elastomeric and thermoplastic nanocomposites. The findings of the study would provide guidelines for the design of electro-conductive polymer nanocomposites.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Synthesis, properties, and applications of graphene oxide/reduced graphene oxide and their nanocomposites

Abstract: Thanks to their remarkable mechanical, electrical, thermal, and barrier properties, graphene-based nanocomposites have been a hot area of research in the past decade. Because of their simple top-down synthesis, graphene oxide (GO) and reduced graphene oxide (rGO) have opened new possibilities for gas barrier, membrane separation, and stimuli-response characteristics in nanocomposites. Herein, we review the synthesis techniques most commonly used to produce these graphene derivatives, discuss how synthesis affects their key material properties, and highlight some examples of nanocomposites with unique and impressive properties. We specifically highlight their performances in separation applications, stimuli-responsive materials, anti-corrosion coatings, and energy storage. Finally, we discuss the outlook and remaining challenges in the field of practical industrial-scale production and use of graphene-derivative-based polymer nanocomposites.

Tunneling effect in a polymer/carbon nanotube nanocompositestrain sensor

Abstract: A strain sensor has been fabricated from a polymer nanocomposite with multiwalled carbon nanotube (MWNT) fillers. The piezoresistivity of this nanocomposite strain sensor has been investigated based on an improved three-dimensional (3D) statistical resistor network model incorporating the tunneling effect between the neighboring carbon nanotubes (CNTs), and a fiber reorientation model. The numerical results agree very well with the experimental measurements. As compared with traditional strain gauges, much higher sensitivity can be obtained in the nanocomposite sensors when the volume fraction of CNT is close to the percolation threshold. For a small CNT volume fraction, weak nonlinear piezoresistivity is observed both experimentally and from numerical simulation. The tunneling effect is considered to be the principal mechanism of the sensor under small strains.