Quantitative dynamic near-field microscopy of thermal conductivity

Altes, A.; Heiderhoff, R.; Balk, L.J.

doi:10.1088/0022-3727/37/6/023

Cited by 43 publications

(28 citation statements)

References 34 publications

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“…The excited 2ω‐pyroelectric current signal was input into the lock in amplifier for imaging. In addition, an additioal 3ω‐thermal signal can also be excited due to the combination of 2ω‐resistant variation and 1ω‐current of the thermal probe based on the 3ω‐technique principle, the resulting 3ω‐thermal signal (V 3ω ) at different frequencies can be expressed:

\frac{V_{3 ω 1} - V_{3 ω 2}}{\ln (ω_{1}) - \ln (ω_{2})} = \frac{1}{4} I_{0} \frac{d R}{d T} \frac{P}{l π λ},

here λ is thermal conductivity of the sample, R the electrical resistance, T the temperature, l the thermal probe length, dR/dT is the corresponding differential coefficient. Thus 3ω‐signal could be measured for local thermal property distribution.…”

Section: Resultsmentioning

confidence: 99%

Scanning Pyroelectric Microscopy of Subsurface Dielectric Failures

Zou

Zeng

et al. 2018

Physica Status Solidi (a)

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Dielectric breakdown is a very important factor determining the reliability of multilayer ceramic capacitors, and its microscopy imaging is still a pending work so far. Here, a high resolution scanning pyroelectric microscopy (SPeM) is developed for direct imaging dielectric failure behavior of multilayer ceramic capacitors (MLCCs) due to the combination of pyroelectric effect and scanning thermal microscopy. Subsurface dielectric‐breakdown regions along the depth profile inside BaTiO3 capacitors are successfully visualized by measuring 2ω‐pyroelectric current via the frequency modulated SPeM. It provides a new approach for exploring subsurface dielectric breakdown microstructures, and for further understanding the underlying physical phenomena inside the MLCCs.

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\frac{V_{3 ω 1} - V_{3 ω 2}}{\ln (ω_{1}) - \ln (ω_{2})} = \frac{1}{4} I_{0} \frac{d R}{d T} \frac{P}{l π λ},

Section: Resultsmentioning

confidence: 99%

Scanning Pyroelectric Microscopy of Subsurface Dielectric Failures

Zou

Zeng

et al. 2018

Physica Status Solidi (a)

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“…II͒. 6,7 The sensitivity of the fit to r c is maximum at high k and it tends to zero at low k. Thus the shape of the V theor ͑k͒ curve is mainly determined by the calibration points corresponding to Mo, Al, and Au while the larger deviations of Ta and glassy C have little influence on the uncertainties of the determined k values. Details will be given elsewhere.…”

Section: -3mentioning

confidence: 99%

Temperature-dependent quantitative 3ω scanning thermal microscopy: Local thermal conductivity changes in NiTi microstructures induced by martensite-austenite phase transition

Chirtoc

Gibkes

Wernhardt

et al. 2008

Review of Scientific Instruments

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We develop the theoretical description of 3omega signals from the resistive Wollaston thermal probe (ThP) of a scanning thermal microscope (SThM) in terms of an equivalent low-pass filter. The normalized amplitude and phase frequency spectra are completely characterized by a single parameter, the crossover frequency f(c)(k) depending on the sample thermal conductivity k. The application concerns polycrystalline NiTi shape memory alloy microstructured by focused Ga ion beam milling and implantation. The calibration of the ThP combined with a novel two-step normalization procedure allowed quantitative exploitation of 3omega signal variations as small as -1.75% in amplitude and 0.60 degrees in phase upon heating the sample from room temperature to 100 degrees C. This corresponds to k increase of 23.9% that is consistent with the expected thermal conductivity variation due to martensite-austenite structural phase transition. To our knowledge this is for the first time that SThM 3omega phase information is used quantitatively as well. The static, calibrated 3omega measurements are complementary to 3omega SThM images of the patterned sample surface. The local SThM measurement of temperature-dependent thermal conductivity opens the possibility to imaging structural phase transitions at submicron scale.

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“…A finite element analysis was used to solve the Poisson equation related to diffusive heat transfer in the system, which is one of the popular approaches for SThM modeling in a diffusive regime [3,10].…”

Section: Finite Element Analysismentioning

confidence: 99%

Methods for topography artifacts compensation in scanning thermal microscopy

Martínek¹,

Klapetek²,

Campbell³

2015

Ultramicroscopy

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Thermal conductivity contrast images in scanning thermal microscopy (SThM) are often distorted by artifacts related to local sample topography. This is pronounced on samples with sharp topographic features, on rough samples and while using larger probes, for example, Wollaston wire-based probes. The topography artifacts can be so high that they can even obscure local thermal conductivity variations influencing the measured signal. Three methods for numerically estimating and compensating for topographic artifacts are compared in this paper: a simple approach based on local sample geometry at the probe apex vicinity, a neural network analysis and 3D finite element modeling of the probe-sample interaction. A local topography and an estimated probe shape are used as source data for the calculation in all these techniques; the result is a map of false conductivity contrast signals generated only by sample topography. This map can be then used to remove the topography artifacts from measured data or to estimate the uncertainty of conductivity measurements using SThM. The accuracy of the results and the computational demands of the presented methods are discussed.

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Quantitative dynamic near-field microscopy of thermal conductivity

Cited by 43 publications

References 34 publications

Scanning Pyroelectric Microscopy of Subsurface Dielectric Failures

Scanning Pyroelectric Microscopy of Subsurface Dielectric Failures

Temperature-dependent quantitative 3ω scanning thermal microscopy: Local thermal conductivity changes in NiTi microstructures induced by martensite-austenite phase transition

Methods for topography artifacts compensation in scanning thermal microscopy

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