No Arabic abstract
While Atomic Force Microscopy is mostly used to investigate surface properties, people have almost since its invention sought to apply its high resolution capability to image also structures buried within samples. One of the earliest techniques for this was based on using ultrasound excitations to visualize local differences in effective tip-sample stiffness caused by the presence of buried structures with different visco-elasticity from their surroundings. While the use of ultrasound has often triggered discussions on the contribution of diffraction or scattering of acoustic waves in visualizing buried structures, no conclusive papers on this topic have been published. Here we demonstrate and discuss how such acoustical effects can be unambiguously recognized and can be used with Atomic Force Microscopy to visualize deeply buried structures.
We use an atomic vapor cell as a frequency tunable microwave field detector operating at frequencies from GHz to tens of GHz. We detect microwave magnetic fields from 2.3 GHz to 26.4 GHz, and measure the amplitude of the sigma+ component of an 18 GHz microwave field. Our proof-of-principle demonstration represents a four orders of magnitude extension of the frequency tunable range of atomic magnetometers from their previous dc to several MHz range. When integrated with a high resolution microwave imaging system, this will allow for the complete reconstruction of the vector components of a microwave magnetic field and the relative phase between them. Potential applications include near-field characterisation of microwave circuitry and devices, and medical microwave sensing and imaging.
Ultrasound Atomic Force Microscopy (US-AFM) has been used for subsurface imaging of nanostructures. The contact stiffness variations have been suggested as the origin of the image contrast. Therefore, to analyze the image contrast, the local changes in the contact stiffness due to the presence of subsurface features should be calculated. So far, only static simulations have been conducted to analyze the local changes in the contact stiffness and, consequently, the contrast in US-AFM. Such a static approach does not fully represent the real US-AFM experiment, where an ultrasound wave is launched either into the sample or at the tip, which modulates the contact stiffness. This is a time-dependent nonlinear dynamic problem rather than a static and stationary one. This letter presents dynamic 3D ultrasound analysis of contact stiffness in US-AFM (in contrast to static analysis) to realistically predict the changes in contact stiffness and thus the changes in the subsurface image contrast. The modulation frequency also influences the contact stiffness variations and, thus, the image contrast. The three-dimensional time-dependent ultrasound analysis will greatly aid in the contrast optimization of subsurface nanoimaging with US-AFM.
High-frequency atomic force microscopy has enabled extraordinary new science through large bandwidth, high speed measurements of atomic and molecular structures. However, traditional optical detection schemes restrict the dimensions, and therefore the frequency, of the cantilever - ultimately setting a limit to the time resolution of experiments. Here we demonstrate optomechanical detection of low-mass, high-frequency nanomechanical cantilevers (up to 20 MHz) that surpass these limits, anticipating their use for single-molecule force measurements. These cantilevers achieve 2 fm / sqrt(Hz) displacement noise floors, and force sensitivity down to 132 aN / sqrt(Hz). Furthermore, the ability to resolve both in-plane and out-of-plane motion of our cantilevers opens the door for ultrasensitive multidimensional force spectroscopy, and optomechanical interactions, such as tuning of the cantilever frequency in situ, provide new opportunities in high-speed, high-resolution experiments.
Morphological features of small vessels provide invaluable information regarding underlying tissue, especially in cancerous tumors. This paper introduces methods for obtaining quantitative morphological features from microvasculature images obtained by non-contrast ultrasound imaging. Those images suffer from the artifact that limit quantitative analysis of the vessel morphological features. In this paper we introduce processing steps to increase accuracy of the morphological assessment for quantitative vessel analysis in presence of these artifact. Specifically, artificats are reduced by additional filtering and vessel segments obtained by skeletonization of the regularized microvasculature images are further analyzed to satisfy additional constraints, such as diameter, and length of the vessel segments. Measurement of some morphological metrics, such as tortuosity, depends on preserving large vessel trunks that may be broken down into multiple branches. We propose two methods to address this problem. In the first method, small vessel segments are suppressed in the vessel filtering process via adjusting the size scale of the regularization. Hence, tortuosity of the large trunks can be more accurately estimated by preserving longer vessel segments. In the second approach, small connected vessel segments are removed by a combination of morphological erosion and dilation operations on the segmented vasculature images. These methods are tested on representative in vivo images of breast lesion microvasculature, and the outcomes are discussed. This paper provides a tool for quantification of microvasculature image from non-contrast ultrasound imaging may result in potential biomarkers for diagnosis of some diseases.
The interaction between a rapidly oscillating atomic force microscope tip and a soft material surface is described using both elastic and viscous forces with a moving surface model. We derive the simplest form of this model, motivating it as a way to capture the impact dynamics of the tip and sample with an interaction consisting of two components: interfacial or surface force, and bulk or volumetric force. Analytic solutions to the piece-wise linear model identify characteristic time constants, providing a physical explanation of the hysteresis observed in the measured dynamic force quadrature curves. Numerical simulation is used to fit the model to experimental data and excellent agreement is found with a variety of different samples. The model parameters form a dimensionless impact-rheology factor, giving a quantitative physical number to characterize a viscoelastic surface that does not depend on the tip shape or cantilever frequency.