Thermal Property Imaging of Aluminum Nitride Composites

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Jia Yang ◽  
Toshiyuki Sato ◽  
Paul Czubarow ◽  
Aaron Schmidt

Frequency domain thermoreflectance (FDTR) imaging is used to create quantitative thermal conductivity maps of porous Aluminum Nitride (AlN) particles embedded in epoxy. The AlN-epoxy composite is polished and coated with a metal layer. A piezo stage is used to move the sample for imaging with our FDTR system. For each pixel, a periodically modulated continuous-wave laser (the red pump beam) is focused to a Gaussian spot, less than 2 um in diameter, to locally heat the sample, while a second beam (the green probe beam) monitors the surface temperature through a proportional change in the metals' reflectivity. The pump beam is modulated simultaneously at six frequencies and the thermal properties of the AlN composite are extracted by minimizing the error between the measured probe phase lag at each frequency and an analytical solution to the heat diffusion equation in a multilayer stack of materials. A schematic of the AlN sample in our measurement system and an optical image of the polished surface of the AlN-epoxy composite before coating with metal is shown in a. Two scanning electron microscope images of the porous AlN particles prior to embedding in epoxy are shown in b. One of the six simultaneously collected phase images of the probe laser is shown in c. The dark blue regions in the phase image are pits on the sample surface. We fit the six phase images to our thermal model and obtain thermal conductivity maps. The conductivity maps of four particles are shown in d. A log color bar is used to highlight the contrast of thermal conductivity in a single particle. The thermal conductivity of the AlN particles ranges from 80W/mK in the dense regions to 5W/mK in the porous regions.

2016 ◽  
Vol 138 (2) ◽  
Author(s):  
Elbara Ziade ◽  
Jia Yang ◽  
Gordie Brummer ◽  
Denis Nothern ◽  
Theodore Moustaks ◽  
...  

Frequency domain thermoreflectance (FDTR) is used to create quantitative maps of thermal conductivity and thickness for a thinning gallium nitride (GaN) film on silicon carbide (SiC). GaN was grown by molecular beam epitaxy on a 4H-SiC substrate with a gradient in the film thickness found near the edge of the chip. The sample was then coated with a 5 nm nickel adhesion layer and a 85 nm gold transducer layer for the FDTR measurement. A piezo stage raster scans the sample to create phase images at different frequencies. For each pixel, a periodically modulated continuous-wave laser (the red pump beam) is focused to a Gaussian spot, less than 2 um in diameter, to locally heat the sample, while a second beam (the green probe beam) monitors the surface temperature through a proportional change in the reflectivity of gold. The pump beam is modulated simultaneously at six frequencies and the thermal conductivity and thickness of the GaN film are extracted by minimizing the error between the measured probe phase lag at each frequency and an analytical solution to the heat diffusion equation in a multilayer stack of materials. A scanning electron microscope image verifies the thinning GaN. We mark the imaged area with a red box. A schematic of the GaN sample in our measurement system is shown in the top right corner, along with the two fitting properties highlighted with a red box. We show the six phase images and the two obtained property maps: thickness and thermal conductivity of the GaN. Our results indicate a thickness dependent thermal conductivity of GaN, which has implications of thermal management in GaN-based high electron mobility transistors.


2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Elbara Ziade ◽  
Aaron Schmidt

Frequency domain thermoreflectance (FDTR) imaging is used to create quantitative maps of both in-plane thermal conductance and cross-plane thermal boundary conductance (TBC) for graphene multilayers encased between titanium and silicon dioxide. A graphene flake is encased between a metal layer and a thermally oxidized p-type silicon wafer and a piezo stage is used to raster scan the sample for imaging. For each image pixel, a periodically modulated continuous-wave laser (the red pump beam) is focused to a Gaussian spot, less than 2 um in diameter, that locally heats the sample, while a second beam (the green probe beam) monitors the surface temperature through a proportional change in reflectivity. The pump beam is modulated simultaneously at six frequencies and the thermal properties of the graphene flake are extracted by minimizing the error between the measured probe phase lag at each frequency and an analytical solution to the heat diffusion equation in a multilayer stack of materials. Phase images at six frequencies for the sample are shown in b. Different layers of the graphene flake are clearly shown in 9.9 MHz and 11.3 MHz images. The six phase data points at every pixel are then fitted to our thermal model to generate two thermal property maps of the graphene flake: in-plane thermal conductance and TBC, shown in c. The in-plane thermal conductance map shows an increased conduction of heat in graphene with the number of layers, while the TBC map indicates a constant cross-plane conduction along the flake. Our imaging technique can be used to study thermal transport in graphene and has implications for thermal management in graphene based electronic devices.


Author(s):  
Dipta Sarkar ◽  
Samuel W. Oxandale ◽  
Tyler J. Hieber ◽  
M. G. Baboly ◽  
Zayd C. Leseman

Abstract Thermoreflectance is a common technique to measure thermal properties of micro/nano devices. Most thermoreflectance techniques use a pump-probe scheme with lasers to heat the sample and analyze the temperature. The limiting characteristics of most of these techniques are that they can probe the temperature at only one spot on the sample, assume a value for either heat capacity or thermal conductivity to find the other, and require a semi-infinite substrate. In this paper, a new technique is described, the Suspended ThermoReflectance (STR) technique, which allows measurement of thermal conductivity by probing multiple points along the length of a suspended micro/nano-scale sample. This technique involves a pump laser for heating the tip of a suspended μ-cantilever Si beam and a probe laser to scan the temperature along the μ-cantilever’s length. Thermal conductivity is obtained by applying the heat diffusion equation for the temperature gradient along the beam length. 2.9 μm thick Si μ-cantilever samples are tested over a range of temperatures from 20–300K. It is found that thermal conductivity of the silicon varies from 28 W/mK to 80 W/mK.


2018 ◽  
Vol 27 (6) ◽  
pp. 096369351802700
Author(s):  
Tao Huang ◽  
Yimin Yao ◽  
Gang Zhang ◽  
Fanling Meng

With the development of polymer-filled composites, the demand of high thermal conductivity materials is much attractive than ever. However, the process of a common method to improve thermal conductivity of composites is considerably complicated. The aim of this study is to investigate thermal conductivity of epoxy filled silver nanoparticle deposited aluminum nitride nanoparticles with relatively convenient process. We found that the thermal conductivities of composites filled with AlN/Ag nanoparticles are effectively enhanced, which is enormously increased from 0.48 Wm-1K-1(1.88 vol%) to 3.66 Wm-1K-1 (19.54 vol%). This can be ascribed to the bridging connections of silver nanoparticle among aluminum nitride nanoparticles. In addition, the thermal contact resistance of the epoxy composites filler with AlN/Ag nanoparticles is decreased, which is proved by the fitting measured thermal conductivity of epoxy composite with one physical model. We believe the finding has great potential for any microelectronic application.


Author(s):  
  Жулиан Берже ◽  
  Денис Дутых

The fidelity of a model relies both on its accuracy to predict the physical phenomena and its capability to estimate unknown parameters using observations. This article focuses on this second aspect by analyzing the reliability of two mathematical models proposed in the literature for the simulation of heat losses through building walls. The first one, named DF, is the classical heat diffusion equation combined with the DuFort-Frankel numerical scheme. The second is the so-called RC lumped approach, based on a simple ordinary differential equation to compute the temperature within the wall. The reliability is evaluated following a two stages method. First, samples of observations are generated using a pseudo-spectral numerical model for the heat diffusion equation with known input parameters. The results are then modified by adding a noise to simulate experimental measurements. Then, for each sample of observation, the parameter estimation problem is solved using one of the two mathematical models. The reliability is assessed based on the accuracy of the approach to recover the unknown parameter. Three case studies are considered for the estimation of ( i ) the heat capacity, ( ii ) the thermal conductivity or ( iii ) the heat transfer coefficient at the interface between the wall and the ambient air. For all cases, the DF mathematical model has a very satisfactory reliability to estimate the unknown parameters without any bias. However, the RC model lacks of fidelity and reliability. The error on the estimated parameter can reach 40% for the heat capacity, 80% for the thermal conductivity and 450% for the heat transfer coefficient.


2018 ◽  
Vol 15 (29) ◽  
pp. 257-265
Author(s):  
R. HECHAVARRÍA ◽  
O. DELGADO ◽  
A. HIDALGO ◽  
S. ESPÍN ◽  
J. GUAMANQUISPE

Nanofluids have become nowadays of special importance because of their different uses in industry, therefore, to propose methods to calculate their thermal properties would be useful. In this work, a new variant for the calculation of thermal conductivity and diffusivity of nanofluids is proposed; the possibilities and limitations of this non-stationary method, which uses light radiation as the heat source, are studied. Here, the light is homogenously incident on one of the end surfaces of a cylinder that has a thermally insulated side surface, setting the temperature at the other end to a constant value, then the temperature distribution is obtained as a function of the coordinate and time; adjusting the theoretical model, parabolic heat diffusion equation, to the experimental data obtained. The conditions of validity of the method to measure thermal diffusivity and thermal conductivity of fluids are analyzed; as well as, the way in which it could be used to verify the validity of the Hamilton and Crosser (HC) model in the case of nanofluids. Currently, nanofluids are used to exchange heat, as they have been found to exceed the potential of conventional refrigerants; however, the calculation of thermal properties still does not offer definitive values.


2021 ◽  
Author(s):  
Siddharth Saurav ◽  
Sandip Mazumder

Abstract The Fourier and the hyperbolic heat conduction equations were solved numerically to simulate a frequency-domain thermoreflectance (FDTR) experiment. Numerical solutions enable isolation of pump and probe laser spot size effects, and use of realistic boundary conditions. The equations were solved in time domain and the phase lag between the temperature of the transducer (averaged over the probe laser spot) and the modulated pump laser signal, were computed for a modulation frequency range of 200 kHz to 200 MHz. Numerical calculations showed that extracted values of the thermal conductivity are sensitive to both the pump and probe laser spot sizes, while analytical solutions (based on Hankel transform) cannot isolate the two effects, although for the same effective (combined) spot size, the two solutions are found to be in excellent agreement. If the substrate (computational domain) is sufficiently large, the far-field boundary conditions were found to have no effect on the computed phase lag. The interface conductance between the transducer and the substrate was found to have some effect on the extracted thermal conductivity. The hyperbolic heat conduction equation yielded almost the same results as the Fourier heat conduction equation for the particular case studied. The numerically extracted thermal conductivity value (best fit) for the silicon substrate considered in this study was found to be about 82-108 W/m/K, depending on the pump and probe laser spot sizes used.


2021 ◽  
pp. 026248932198897
Author(s):  
Serife Akkoyun ◽  
Meral Akkoyun

The aim of this work is the fabrication of electrically insulating composite rigid polyurethane foams with improved thermal conductivity. Therefore, this study is focused on the effect of aluminum nitride (AlN) on the thermal and electrical conductivities of rigid polyurethane foams. For this purpose, aluminum nitride/rigid polyurethane composite foams were prepared using a three-step procedure. The electrical and thermal conductivities of the foams were characterized. The thermal transitions, mechanical properties and morphology of the foams were also examined. The results reveal that AlN induces an increase of the thermal conductivity of rigid polyurethane foam of 24% which seems to be a relatively noticeable increase in polymeric foams. The low electrical conductivity of the foams is preserved.


2000 ◽  
Vol 43 (3) ◽  
pp. 114-117 ◽  
Author(s):  
Yaocheng Liu ◽  
Heping Zhou ◽  
Yin Wu ◽  
Liang Qiao

Sign in / Sign up

Export Citation Format

Share Document