Xiasheng Guo

Label-free separation of multiple micrometer and submicrometer particle populations from complex samples is a critical but elusive capability. We report an integrated acousto-dielectric chip in which the piezoelectric potential associated with tilted-angle standing surface acoustic waves changes the local electric field distribution, thereby increasing the electric field gradient and enhancing dielectrophoretic forces. When combined with acoustic radiation forces in a cascaded geometry, this enhancement enables three distinct, size-governed particle migration modes in a single device. As a proof of concept, we demonstrate continuous-flow separation of 1.0, 0.4, and 0.25 μm radius polystyrene microspheres with removal efficiencies reaching 99.9% for the largest particles and purities of 87.8% and 97.1% for the two smaller fractions. As the underlying mechanism, piezoelectric modulation of the electric field gradient provides a low-voltage, high-resolution strategy for multi-target sorting of nanoscale bioparticles.

Robust displacement estimation is crucial for ultrasound thermal strain imaging (TSI), but is severely hampered by noise and the thermal-acoustic lens (TALs) effect. This article introduces NLOG, a displacement estimator that builds upon the NL (NXcorr + Loupas) method and incorporates a physics-based Gaussian thermal strain prior within a global optimization framework to overcome the limitations of conventional window-based methods. Specifically, after an initial displacement field is obtained using the conventional NL estimator, a Gaussian strain prior is extracted and used to regularize a global cost function, yielding a physically plausible displacement field. Validated via simulations (with ground truth) and ex vivo experiments, NLOG significantly suppresses noise and artifacts, improving strain image quality, with average gains in strain signal-to-noise ratio (SNR) and contrast-to-noise ratio of over 200% in simulations and 300% in experiments compared to the baseline method. Consequently, temperature estimation errors are reduced by more than 36%. The proposed estimator may therefore contribute to safer and more effective clinical thermal therapies by enabling real-time, artifact-robust temperature monitoring during focused ultrasound (FU) treatment.

Numerical simulations of surface acoustic wave (SAW)-induced acoustic streaming are highly sensitive to the choice of second-order boundary conditions. This study systematically compares the no-slip (NS) and Stokes slip (SD) boundary conditions through different numerical approaches. Two- and three-dimensional simulations based on the Reynolds stress method are performed for standing SAW and traveling SAW devices. Results are validated against particle image velocimetry measurements of streaming patterns and velocities. We show that the SD condition yields Lagrangian velocity fields in significantly better agreement with experiments than the NS condition, accurately capturing vortex number, rotation direction, and amplitude across varying device geometries and operating conditions. In contrast, the NS condition overpredicts velocities by 1 to 2 orders of magnitude and often fails to reproduce experimentally observed vortex structures. These findings highlight the essential role of the Stokes drift boundary condition in modeling acoustic streaming and provide clear guidance for its use in future simulations of SAW-based acoustofluidic systems.

Ultrasound (US) imaging is essential for monitoring thermotherapies, but accurate simulation of heating-induced artifacts remains challenging. Conventional single-sound-path (SSP) models approximate thermal effects as a channel-independent axial shift, failing to reproduce thermo-acoustic lens (TAL) artifacts observed in thermotherapy experiments. This study proposes a physically realistic multi-sound-path (MSP) simulation framework that captures TAL artifacts arising from temperature-induced speed-of-sound inhomogeneity in array-based US imaging. Transient temperature fields are computed using an alternating direction implicit solver, and US images are reconstructed via delay-and-sum beamforming. Compared to SSP, the MSP model successfully reproduces characteristic TAL artifacts, including lateral resolution degradation (up to 52.0% increase in full width at half maximum) and speckle brightness reduction (up to 49.1%). When applied to speckle tracking and thermal strain imaging, MSP also reveals substantial decorrelation and displacement errors consistent with experimental observations. By providing a computationally efficient imaging simulation framework that avoids the prohibitive cost of full-wave solvers, the proposed framework is well-suited for large-scale parametric studies and evaluation of US-based thermometry and other speckle-based functional imaging methods.

Sheathless prefocusing of particles and cells is a critical preparatory step in biomedical assays, while focusing performance directly impacts processing throughput and detection sensitivity. Although standing surface acoustic wave (SSAW)-based acoustofluidics has been widely used across nano- and micro-scale applications, reliance on sheath flow remains a major constraint. Here, we introduce an SU-8/PDMS hybrid microchannel fabricated through in situ injection and photopolymerization that eliminates microchannel anechoic corners by augmenting acoustic energy transmission via hybrid sidewalls. The influence of sidewall dimensions on acoustic field distribution was systematically investigated using a two-dimensional finite element model, guiding the design of a cascaded hybrid microchannel that achieved over tenfold focusing of 2.5 and 5 μm polystyrene (PS) beads without sheath flow. Comparable performance was demonstrated with human promyelocytic leukaemia (HL-60) and human umbilical vein endothelial cells (HUVECs) at processing rates up to 3 × 10⁴ cells per min, confirming broad biological applicability. The modular and fabrication-friendly architecture presents a versatile sheathless prefocusing solution for integrated acoustofluidic systems.