Supporting Online Materials for “Nanometer-Scale Temperature Imaging for Independent Observation of Joule and Peltier Effects in Phase Change Memory Devices” By: Kyle L. Grosse, Eric Pop, and William P. King University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA I. Frequency Domain Thermoelectric Equations The frequency domain thermoelectric transport equations are derived as follows. Equations S1 and S2 show the modified Poisson and heat diffusion equations to account for thermoelectric transport.1,2 ( S T V ) 0 d cP T (k S 2T )T ( ST )V ( S T V [V ]2 ) t (S1) (S2) The density, heat capacity, thermal conductivity, electrical conductivity, thermopower, temperature, and voltage are given by ρd, cP, k, σ, S, T, and V. Equations S1 and S2 are coupled and must be solved simultaneously. Equation S3 shows the applied sinusoidal bias which generates the temperature oscillations shown in Eq. S4. V V0 V1 cos(2t ) (S3) T T0 T1 cos(2t ) T2 cos(2 2t ) (S4) The subscripts 0ω, 1ω, and 2ω denote the amplitude of V and T at the zero, first, and second harmonics. The device is biased at a frequency ω = 43 kHz. The first and second harmonic components are complex numbers, and the first and second harmonic peak-to-peak temperature rises are defined ΔT1ω = 2|T1ω| and ΔT2ω = 2|T2ω|. Driving the device with a bias at 0ω (DC) and 1ω bias causes a 0ω, 1ω, and 2ω temperature rise as Joule heating scales with V2. The Fourier transform of Eqs. S1-S4 yields Eq. S5 the frequency domain thermoelectric transport equation. 1 4(k S 2T0 ) T0 2 S 2T1 2 S 2T2 4 ST0 2 ST1 2 2 2 2k S (2T0 T2 ) S T1 2 ST1 S (2T0 T2 ) T1 2 S T1 T2 2 S 2T2 S 2T1 2(k S 2T0 ) 2 ST2 ST1 S 0 0 0 V0 V1 0 S 0 0 (S5) 2 2 2 S (2T0 V0 T1 V1 ) 2(V0 ) (V1 ) S (2T0 V1 2T1 V0 T2 V1 ) 4V1 V0 i 4 d cPT1 ... S (T1 V1 2T2 V0 ) (V1 ) 2 i 4 d cPT2 2 0 0 The terms on the left hand side of Eq. S5 are the transport terms. The terms on the right hand side without frequency dependence are generation terms, and the terms with frequency dependence describe periodic heat diffusion. The model is coupled with a thermo-mechanical model for comparison with scanning Joule expansion microscopy (SJEM) measurements. II. Finite Element Analysis Model Equation S5 was implemented in a finite element analysis (FEA) model of a device, shown in Figure 1(a), to predict Joule and thermoelectric device behavior. The model is similar to 2D phase change memory (PCM) device models used in previous SJEM measurements.3,4 The model is bounded by the electrode bias as shown, a heat sink of T0ω = 300 K along the bottom surface, and free surfaces along the top. All other surfaces are insulated and constrained. Joule and Peltier effects are generated in the Ge2Sb2Te5 (GST) device from its high resistivity ρGST = 2.5×10-4 Ω m and large thermopower SGST = 250 μV K-1. The device was modeled as a 22 nm thin GST device with a 4 μm channel length. Joule heating also occurs at the contacts due to finite interface resistivity (ρC = 2×10-9 Ω m2) between the GST and metal. 2 III. The Seebeck Effect Figures 2(e) and (f) show a slight change in ΔT2ω at the channel center with changing thermopower due to the Seebeck effect.5 The model predicts a thermoelectric voltage is induced across the device due to the asymmetric temperature gradient at the edges of the device and its contacts. The induced voltage slightly changes the power dissipation of the device. The changes are typically too small to be observed experimentally. Equations S1 and S2 describe the Seebeck effect, but the PE and JH equations in Figs. 1(b) and (c) do not describe the Seebeck effect. IV. Scanning Joule Expansion Microscopy Scanning Joule expansion microscopy (SJEM) was used to observe Joule and Peltier effects of the PCM devices. The SJEM technique utilizes a sinusoidal waveform with voltage VDS to drive the device. An atomic force microscopy (AFM) cantilever in contact with the surface measures the surface expansion, and two lock-in amplifiers at 1ω and 2ω simultaneously record the peak-to-peak sample surface expansion Δh1ω and Δh2ω. The measured Δh is proportional to the device temperature rise ΔT, and the two are related by the FEA model. V. Measurement and Prediction Uncertainty Observing Peltier effects using a unipolar bias requires two measurements which increases the measured uncertainty. A single SJEM measurement had an average uncertainty of ~2-3 pm. Using a unipolar bias requires two measurements to observe Peltier effects which doubles the variance (the square of the uncertainty) from a single measurement and the drift between the two measurements further increases the average uncertainty. The uncertainty therefore increased from ~2-3 pm for a single SJEM measurement to ~7-8 pm when observing 3 Peltier effects using a unipolar bias. Using a bipolar bias requires a single measurement to observe Peltier effects and the measured uncertainty is the same as a single SJEM measurement. The predicted uncertainty of SGST increases with increasing GST thermopower for the following reason. The measured percent uncertainty of Δh1ω, the measured uncertainty of Δh1ω divided by the measured Δh1ω, was similar for each device. The observed Δh1ω is due to local Peltier heating and cooling, and the PE is proportional to the GST thermopower. Therefore, the measured percent uncertainty of Δh1ω causes a proportional percent uncertainty in the predicted GST thermopower. Supplemental References 1 E. M. Lifshitz, L. D. Landau, and L. P. Pitaevskii, Electrodynamics of Continuous Media. (Butterworth-Heinemann, 1984). 2 J. Martin, in the COMSOL Conference, Hannover, Germany, 4-6 November, 2008, pp. 1-7. 3 K. L. Grosse, E. Pop, and W. P. King, Submitted to J. Appl. Phys. (2014). 4 K. L. Grosse, F. Xiong, S. Hong, W. P. King, and E. Pop, Appl. Phys. Lett. 102, 193503 (2013). 5 D. K. C. MacDonald, Thermoelectricity: An Introduction to The Principles. (John Wiley and Sons, 1962). 4