Jaesang Yu

Bio: Jaesang Yu is an academic researcher from Korea Institute of Science and Technology. The author has contributed to research in topics: Graphene & Carbon nanotube. The author has an hindex of 16, co-authored 59 publications receiving 1055 citations. Previous affiliations of Jaesang Yu include Shinshu University.

Thermal conductivity of polymer composites with the geometrical characteristics of graphene nanoplatelets

Abstract: One of the most important physical factors related to the thermal conductivity of composites filled with graphene nanoplatelets (GNPs) is the dimensions of the GNPs, that is, their lateral size and thickness. In this study, we reveal the relationship between the thermal conductivity of polymer composites and the realistic size of GNP fillers within the polymer composites (measured using three-dimensional (3D) non-destructive micro X-ray CT analysis) while minimizing the effects of the physical parameters other than size. A larger lateral size and thickness of the GNPs increased the likelihood of the matrix-bonded interface being reduced, resulting in an effective improvement in the thermal conductivity and in the heat dissipation ability of the composites. The thermal conductivity was improved by up to 121% according to the filler size; the highest bulk and in-plane thermal conductivity values of the composites filled with 20 wt% GNPs were 1.8 and 7.3 W/m·K, respectively. The bulk and in-plane thermal conductivity values increased by 650 and 2,942%, respectively, when compared to the thermal conductivity values of the polymer matrix employed (0.24 W/m·K).

Thermal conductivity of polymer composites based on the length of multi-walled carbon nanotubes

Abstract: The anisotropic development of thermal conductivity in polymer composites was evaluated by measuring the isotropic, in-plane and through-plane thermal conductivities of composites containing length-adjusted short and long multi-walled CNTs (MWCNTs). The thermal conductivities of the composites were relatively low irrespective of the MWCNT length due to their high contact resistance and high interfacial resistance to polymer resins, considering the high thermal conductivity of MWCNTs. The isotropic and in-plane thermal conductivities of long-MWCNT-based composites were higher than those of short-MWCNT-based ones and the trend can accurately be calculated using the modified Mori-Tanaka theory. The in-plane thermal conductivity of composites with 2 wt% long MWCNTs was increased to 1.27 W/m·K. The length of MWCNTs in polymer composites is an important physical factor in determining the anisotropic thermal conductivity and must be considered for theoretical simulations. The thermal conductivity of MWCNT polymer composites can be effectively controlled in the processing direction by adjusting the length of the MWCNT filler.

Synergistic effect of hybrid graphene nanoplatelet and multi-walled carbon nanotube fillers on the thermal conductivity of polymer composites and theoretical modeling of the synergistic effect

Abstract: We found that the thermal conductivity of polymer composites was synergistically improved by the simultaneous incorporation of graphene nanoplatelet (GNP) and multi-walled carbon nanotube (MWCNT) fillers into the polycarbonate matrix. The bulk thermal conductivity of composites with 20 wt% GNP filler was found to reach a maximum value of 1.13 W/m K and this thermal conductivity was synergistically enhanced to reach a maximum value of 1.39 W/m K as the relative proportion of MWCNT content was increased but the relative proportion of GNP content was decreased. The synergistic effect was theoretically estimated based on a modified micromechanics model where the different shapes of the nanofillers in the composite system could be taken into account. The waviness of the incorporated GNP and MWCNT fillers was found to be one of the most important physical factors determining the thermal conductivity of the composites and must be taken into consideration in theoretical calculations.

Ultra-high dispersion of graphene in polymer composite via solvent freefabrication and functionalization

Abstract: Ultra-high dispersion of graphene in polymer composite via solvent free fabrication and functionalization

Thermal conductivity of graphene nanoplatelets filled composites fabricated by solvent-free processing for the excellent filler dispersion and a theoretical approach for the composites containing the geometrized fillers

Abstract: The thermal conductivity of polymer composites containing nanofillers such as GNP (graphene nanoplatelet) and carbon black (CB) was investigated using experimental and theoretical approaches. We developed a fabrication method that allows different shapes and sizes of nanofillers to be highly dispersed in polymer resin. When the bulk and in-plane thermal conductivities of the fabricated composites were measured, they were found to increase rapidly as the GNP filler content increased. The in-plane thermal conductivity of composites with 20 wt.% GNP filler was found to reach a maximum value of 1.98 W/m K. The measured thermal conductivities were compared with the calculated values based on a micromechanics model where the waviness of nanofillers could be taken into account. The waviness of the incorporated GNP filler is an important physical factor that determines the thermal conductivity of composites and must be taken into consideration in theoretical calculations.

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.

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.

Progress in the functional modification of graphene/graphene oxide: a review

Abstract: Graphene and graphene oxide have attracted tremendous interest over the past decade due to their unique and excellent electronic, optical, mechanical, and chemical properties. This review focuses on the functional modification of graphene and graphene oxide. First, the basic structure, preparation methods and properties of graphene and graphene oxide are briefly described. Subsequently, the methods for the reduction of graphene oxide are introduced. Next, the functionalization of graphene and graphene oxide is mainly divided into covalent binding modification, non-covalent binding modification and elemental doping. Then, the properties and application prospects of the modified products are summarized. Finally, the current challenges and future research directions are presented in terms of surface functional modification for graphene and graphene oxide.