Ultrasonic Lamb modes typically propagate as a combination of multiple dispersive wave packets. Frequency components of each mode distribute widely in time domain due to dispersion and it is very challenging to separate individual modes by traditional signal processing methods. In the present study, a method of dispersion compensation is proposed for the purpose of mode separation. This numerical method compensates, i.e., compresses, the individual dispersive waveforms into temporal pulses, which thereby become nearly un-overlapped in time and frequency and can thus be extracted individually by rectangular time windows. It was further illustrated that the dispersion compensation also provided a method for predicting the plate thickness. Finally, based on reversibility of the numerical compensation method, an artificial dispersion technique was used to restore the original waveform of each mode from the separated compensated pulse. Performances of the compensation separation techniques were evaluated by processing synthetic and experimental signals which consisted of multiple Lamb modes with high dispersion. Individual modes were extracted with good accordance with the original waveforms and theoretical predictions.

Wireless nano‐/micromotors powered by chemical reactions and/or external fields generate motive forces, perform tasks, and significantly extend short‐range dynamic responses of passive biomedical microcarriers. However, before micromotors can be translated into clinical use, several major problems, including the biocompatibility of materials, the toxicity of chemical fuels, and deep tissue imaging methods, must be solved. Nanomaterials with enzyme‐like characteristics (e.g., catalase, oxidase, peroxidase, superoxide dismutase), that is, nanozymes, can significantly expand the scope of micromotors’ chemical fuels. A convergence of nanozymes, micromotors, and microfluidics can lead to a paradigm shift in the fabrication of multifunctional micromotors in reasonable quantities, encapsulation of desired subsystems, and engineering of FDA‐approved core–shell structures with tuneable biological, physical, chemical, and mechanical properties. Microfluidic methods are used to prepare stable bubbles/microbubbles and capsules integrating ultrasound, optoacoustic, fluorescent, and magnetic resonance imaging modalities. The aim here is to discuss an interdisciplinary approach of three independent emerging topics: micromotors, nanozymes, and microfluidics to creatively: 1) embrace new ideas, 2) think across boundaries, and 3) solve problems whose solutions are beyond the scope of a single discipline toward the development of micro‐bio‐chemo‐mechanical‐systems for diverse bioapplications.

The 2-D Fourier transform analysis of multichannel signals is a straightforward method to extract the dispersion curves of guided modes. Basically, the time signals recorded at several positions along the waveguide are converted to the wavenumber-frequency space, so that the dispersion curves (i.e., the frequency-dependent wavenumbers) of the guided modes can be extracted by detecting peaks of energy trajectories. In order to improve the dispersion curve extraction of low-amplitude modes propagating in a cortical bone, a multiemitter and multireceiver transducer array has been developed together with an effective singular vector decomposition (SVD)-based signal processing method. However, in practice, the limited number of positions where these signals are recorded results in a much lower resolution in the wavenumber axis than in the frequency axis. This prevents a clear identification of overlapping dispersion curves. In this paper, a sparse SVD (S-SVD) method, which combines the signal-to-noise ratio improvement of the SVD-based approach with the high wavenumber resolution advantage of the sparse optimization, is presented to overcome the above-mentioned limitation. Different penalty constraints, i.e., l -norm, Frobenius norm, and revised Cauchy norm, are compared with the sparse characteristics. The regularization parameters are investigated with respect to the convergence property and wavenumber resolution. The proposed S-SVD method is investigated using synthetic wideband signals and experimental data obtained from a bone-mimicking phantom and from an ex-vivo human radius. The analysis of the results suggests that the S-SVD method has the potential to significantly enhance the wavenumber resolution and to improve the extraction of the dispersion curves.