Donghyun Shin

Bio: Donghyun Shin is an academic researcher from Central Michigan University. The author has contributed to research in topics: Molten salt & Nanofluid. The author has an hindex of 19, co-authored 49 publications receiving 1854 citations. Previous affiliations of Donghyun Shin include University of Texas at Arlington & Texas A&M University.

Enhanced specific heat of silica nanofluid

Abstract: Silica nanoparticles (1% by weight) were dispersed in a eutectic of lithium carbonate and potassium carbonate (62:38 ratio) to obtain high temperature nanofluids. A differential scanning calorimeter instrument was used to measure the specific heat of the neat molten salt eutectic and after addition of nanoparticles. The specific heat of the nanofluid was enhanced by 19–24%. The measurement uncertainty for the specific heat values in the experiments is estimated to be in the range of 1–5%. These experimental data contradict earlier experimental results reported in the literature. (Notably, the stability of the nanofluid samples was not verified in these studies.) In the present study, the dispersion and stability of the nanoparticles were confirmed by using scanning electron microscopy (SEM). Percolation networks were observed in the SEM image of the nanofluid. Furthermore, no agglomeration of the nanoparticles was observed, as confirmed by transmission electron microscopy. The observed enhancements are suggested to be due to the high specific surface energies that are associated with the high surface area of the nanoparticles per unit volume (or per unit mass).

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.

Silicon Nanowires for Solar Thermal Energy Harvesting: an Experimental Evaluation on the Trade-off Effects of the Spectral Optical Properties

Abstract: Silicon nanowire possesses great potential as the material for renewable energy harvesting and conversion. The significantly reduced spectral reflectivity of silicon nanowire to visible light makes it even more attractive in solar energy applications. However, the benefit of its use for solar thermal energy harvesting remains to be investigated and has so far not been clearly reported. The purpose of this study is to provide practical information and insight into the performance of silicon nanowires in solar thermal energy conversion systems. Spectral hemispherical reflectivity and transmissivity of the black silicon nanowire array on silicon wafer substrate were measured. It was observed that the reflectivity is lower in the visible range but higher in the infrared range compared to the plain silicon wafer. A drying experiment and a theoretical calculation were carried out to directly evaluate the effects of the trade-off between scattering properties at different wavelengths. It is clearly seen that silicon nanowires can improve the solar thermal energy harnessing. The results showed that a 17.8 % increase in the harvest and utilization of solar thermal energy could be achieved using a silicon nanowire array on silicon substrate as compared to that obtained with a plain silicon wafer.

A Benchmark Study on the Thermal Conductivity of Nanofluids

Abstract: This article reports on the International Nanofluid Property Benchmark Exercise, or INPBE, in which the thermal conductivity of identical samples of colloidally stable dispersions of nanoparticles or “nanofluids,” was measured by over 30 organizations worldwide, using a variety of experimental approaches, including the transient hot wire method, steady-state methods, and optical methods. The nanofluids tested in the exercise were comprised of aqueous and nonaqueous basefluids, metal and metal oxide particles, near-spherical and elongated particles, at low and high particle concentrations. The data analysis reveals that the data from most organizations lie within a relatively narrow band (±10% or less) about the sample average with only few outliers. The thermal conductivity of the nanofluids was found to increase with particle concentration and aspect ratio, as expected from classical theory. There are (small) systematic differences in the absolute values of the nanofluid thermal conductivity among the various experimental approaches; however, such differences tend to disappear when the data are normalized to the measured thermal conductivity of the basefluid. The effective medium theory developed for dispersed particles by Maxwell in 1881 and recently generalized by Nan et al. [J. Appl. Phys. 81, 6692 (1997)], was found to be in good agreement with the experimental data, suggesting that no anomalous enhancement of thermal conductivity was achieved in the nanofluids tested in this exercise.