Subsurface imaging of rigid particles buried in a polymer matrix based on atomic force microscopy mechanical sensing

doi:10.1016/j.ultramic.2019.112832

Ultramicroscopy

Volume 207, December 2019, 112832

https://doi.org/10.1016/j.ultramic.2019.112832 Get rights and content

Highlights

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Several subsurface imaging methods based on mechanical sensing were compared.
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Maximum detectable buried depth was evaluated quantitatively.
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Depth limit from high to low is contact resonance, bimodal and harmonic AFM.
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Sensitivity to local mechanical properties was analyzed numerically.

Abstract

Several subsurface imaging methods based on atomic force microscopy (AFM) linear nanomechanical mapping, namely contact resonance (CR), bimodal and harmonic AFMs, are investigated and compared. Their respective subsurface detection capability is estimated and evaluated on a model specimen, which is prepared by embedding SiO₂ microparticles in a PDMS elastomer. The measured CR frequency, bimodal and harmonic amplitudes are related to local mechanical properties by analyzing cantilever dynamics and further linked to subsurface depths of the particles by finite element analysis. The maximum detectable depths are obtained from the apparent particle diameters in subsurface image channels via employing a simple geometrical model. Under common experimental settings, results demonstrate that the depth limits reach up to about 812 nm, 212 nm and 127 nm for CR, bimodal and harmonic AFM modes, respectively. The depth sensitivity can be tuned and optimized by using either different cantilever eigenmodes in CR-AFM or spectroscopy analysis in bimodal and harmonic AFMs. The three imaging methods have their own suitable application situations. The comparisons can advance a further step into understanding the subsurface image contrast via AFM mechanical sensing.

Introduction

Non-destructive subsurface imaging at the nanoscale resolution is of significant importance in numerous research fields [1]. For instance, volume organization of nanofillers in a polymer matrix is closely relevant with the functionality of composite materials [2]. Therefore, visualizing subsurface dispersion of the buried nanofillers is highly demanded [3]. Similarly, detecting nanomaterials distribution within a complex biological system is of great interest in biomedicine and nanotoxicity [4]. Identification and diagnosis of underneath defects including voids and cracks can help to enhance the yield limit in micro-and-nano device manufacturing and integration [5]. In all these practical situations, the nano-objects of concern are covered by a medium that conceals their relevant characteristics, which challenge the non-destructive high-resolution imaging.

Currently available tools and techniques for nanoscale non-destructive subsurface imaging are quite limited. Owing to its ultra-high resolution and flexibility, atomic force microscopy (AFM) has drawn considerable interests to fulfill this demand. However, conventional AFM is mainly sensitive to surface or near-surface properties and only allows the shallowly buried nanostructures to be detected [6]. To enhance the subsurface imaging ability, an external wave or force field that can pass through the surrounding medium and interact with the inside nano-objects should be coupled. Following this general principle, several AFM operation modes have been developed to reveal the embedded nanostructures. Incorporating various electromagnetic waves into the tip-sample junction can enable subsurface imaging capability. For example, backscattered infrared light was integrated to visualize gold nanodisks covered by a silicon oxide layer [7] and scanning microwave microscopy was applied to detect in-depth oxygen dissolved in metals [8]. Launching an acoustic wave from either beneath the sample or the tip, subsurface nanostructures and defects were detectable by monitoring the disturbed cantilever oscillations [9], [10], [11], [12], [13], [14], [15], [16]. Heterodyne detection for a sample excited with ultrasonic vibration was also proposed to resolve local stiffness differences [17]. Following this approach, alternatives including scanning ultrasound holography [18,19] and mode-synthesizing AFM [20,21] were further developed. Nanoparticles in macrophages [22] and defects in semiconductor interconnects [23] were then non-destructively probed from amplitude and phase signals at the differential frequency. However, a comprehensive mechanism of the image contrast is not yet available [18,[24], [25], [26]]. In case of acoustic AFM whose tip is in contact with the sample, the combined contributions from both contact mechanics and wave propagation could play a critical role in forming the subsurface image contrast [27].

In addition to the waves, numerous tip-sample interaction force fields are feasible for subsurface imaging. When the medium and the embedded nanomaterials have obvious differences in certain physical properties, the nano-objects are detectable by characterizing the corresponding features. The force fields could be electric [28], [29], [30], magnetic, thermal, mechanical [31,32]. Among them, subsurface detection based on mechanical characterization has a prominent advantage of no special requirement for the buried materials and the probe, that is, being magnetic, conductive, etc. The presence of nanomaterials having different elasticity as compared with the medium will change the effective local modulus or the contact stiffness and they can be subsequently sensed. Some AFM techniques, which allow simultaneous topography acquisition and mechanical characterization, have been applied for subsurface imaging. To enhance the mechanical sensitivity as compared with conventional AFM tapping mode, detection of higher harmonics was employed where the dynamic responses at an integer multiple of the fundamental resonance frequency were analyzed [33]. Multifrequency methods such as bimodal and triple-frequency AFMs were verified to have the capability of characterizing mechanical properties [34] and imaging shallow subsurface nanoparticles [35]. Several eigenmodes of the cantilever are excited simultaneously in multifrequency AFM [36]. Another approach to determine the local stiffness quantitatively is contact resonance (CR) method where the CR frequency of a specified eigenmode is tracked during scanning. Such an approach enables accurate measurement of sample modulus [37,38]. In addition to mechanical characterization, CR-AFM was also exploited to probe buried nanoparticles [39,40], nanotubes [31], cavities [41], and atomic structures in two-dimensional materials and heterostructures [42].

Despite all these rapid progresses, the subsurface detection capability such as spatial resolution and detectable depth limit has not been completely understood. Here, we compared several methods based on mechanical sensing, namely CR, bimodal and harmonic AFMs. With experiments on microparticles embedded in a polymer matrix, finite element analyses (FEA) of local elastic modulus of the composite and theoretical calculations of cantilever oscillations, the maximum detectable subsurface depths by the three methods were evaluated and compared. These studies are toward the main purposes of understanding the subsurface imaging mechanism via AFM mechanical sensing modes and evaluating the corresponding depth limit quantitatively.

Section snippets

Experimental setup

The experiments were performed on a commercial AFM (MFP-3D Origin, Asylum Research). The Multi75Al-G cantilevers (Budget Sensors, Bulgaria) were used. The spring constants of the cantilevers were determined to be typically 2.69 N/m by using the thermal calibration and the first two natural frequencies were respectively 66.1 kHz and 430.7 kHz. The sample was prepared by dispersing SiO₂ microparticles into a polydimethylsiloxane (PDMS) matrix. The particle diameter was 5.0 ± 0.125 μm by scanning

Results and discussion

Typical comparisons of CR, bimodal and harmonic AFM subsurface imaging on the SiO₂ microparticles buried in a PDMS matrix are presented in Fig. 2. The spring constant of the cantilever was calibrated to be 2.69 N/m. The first two free resonance frequencies were 66.1 kHz and 430.7 kHz. The corresponding quality factors were respectively 173 and 470. In both bimodal imaging and harmonic imaging, the free amplitude was 133.9 nm and the ratio of feedback amplitude to free amplitude was set to 0.9.

Conclusion

In summary, subsurface AFM nano-imaging based on linear nanomechanical sensing was investigated. Three methods, namely CR, bimodal and harmonic AFMs were compared. By embedding microscale SiO₂ particles in a PDMS matrix as a reference sample, the detectable depth limit was determined from mapping the apparent particle diameters in the subsurface images into a simple geometrical model. Results demonstrated that the depth limit from high to low is CR-AFM, bimodal AFM and harmonic AFM. In CR-AFM,

Acknowledgements

This work was supported by the National Natural Science Foundation of China (no. 51675504) and Anhui Major Scientific Instruments Development Project(no. 1704c0402198).

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Subsurface imaging of rigid particles buried in a polymer matrix based on atomic force microscopy mechanical sensing

Highlights

Abstract

Introduction

Section snippets

Experimental setup

Results and discussion

Conclusion

Acknowledgements

Eur. Polym. J.

Ultramicroscopy

Ultramicroscopy

Sens. Actuators A: Phys.

J. Phys. Condens. Matter

Energy Env. Sci.

Nanotechnology

Sci. Rep.

ACS Nano

Opt. Express

Nanoscale

Jpn. J. Appl. Phys.

Appl. Phys. Lett.

Nanotechnology

J. Appl. Phys.

ACS Nano

Microsc. Res. Tech.

J. Phys. D. Appl. Phys.

Science

IEEE Trans. Nanotechnol.

Nat. Nanotechnol.

Appl. Phys. Lett.

Appl. Phys. Lett.

Appl. Phys. Lett.

Appl. Phys. Lett.

J. Appl. Phys.

Nanotechnology

Nanoscale