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Abstract The addition of surface acoustic wave (SAW) technologies to microfluidics has greatly advanced lab-on-a-chip applications due to their unique and powerful attributes, including high-precision manipulation, versatility, integrability, biocompatibility, contactless nature, and rapid actuation. However, the development of SAW microfluidic devices is limited by complex and time-consuming micro/nanofabrication techniques and access to cleanroom facilities for multistep photolithography and vacuum-based processing. To simplify the fabrication of SAW microfluidic devices with customizable dimensions and functions, we utilized the additive manufacturing technique of aerosol jet printing. We successfully fabricated customized SAW microfluidic devices of varying materials, including silver nanowires, graphene, and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). To characterize and compare the acoustic actuation performance of these aerosol jet printed SAW microfluidic devices with their cleanroom-fabricated counterparts, the wave displacements and resonant frequencies of the different fabricated devices were directly measured through scanning laser Doppler vibrometry. Finally, to exhibit the capability of the aerosol jet printed devices for lab-on-a-chip applications, we successfully conducted acoustic streaming and particle concentration experiments. Overall, we demonstrated a novel solution-based, direct-write, single-step, cleanroom-free additive manufacturing technique to rapidly develop SAW microfluidic devices that shows viability for applications in the fields of biology, chemistry, engineering, and medicine. 

Abstract Extracellular vesicles (EVs) have been identified as promising biomarkers for the noninvasive diagnosis of various diseases. However, challenges in separating EVs from soluble proteins have resulted in variable EV recovery rates and low purities. Here, we report a high-yield ( > 90%) and rapid ( < 10 min) EV isolation method calledFLocculation viaOrbitalAcousticTrapping (FLOAT). The FLOAT approach utilizes an acoustofluidic droplet centrifuge to rotate and controllably heat liquid droplets. By adding a thermoresponsive polymer flocculant, nanoparticles as small as 20 nm can be rapidly and selectively concentrated at the center of the droplet. We demonstrate the ability of FLOAT to separate urinary EVs from the highly abundant Tamm-Horsfall protein, addressing a significant obstacle in the development of EV-based liquid biopsies. Due to its high-yield nature, FLOAT reduces biofluid starting volume requirements by a factor of 100 (from 20 mL to 200 µL), demonstrating its promising potential in point-of-care diagnostics. 

Machine learning image recognition and classification of particles and materials is a rapidly expanding field. However, nanomaterial identification and classification are dependent on the image resolution, the image field of view, and the processing time. Optical microscopes are one of the most widely utilized technologies in laboratories across the world, due to their nondestructive abilities to identify and classify critical micro-sized objects and processes, but identifying and classifying critical nano-sized objects and processes with a conventional microscope are outside of its capabilities, due to the diffraction limit of the optics and small field of view. To overcome these challenges of nanomaterial identification and classification, we developed an intelligent nanoscope that combines machine learning and microsphere array-based imaging to: (1) surpass the diffraction limit of the microscope objective with microsphere imaging to provide high-resolution images; (2) provide large field-of-view imaging without the sacrifice of resolution by utilizing a microsphere array; and (3) rapidly classify nanomaterials using a deep convolution neural network. The intelligent nanoscope delivers more than 46 magnified images from a single image frame so that we collected more than 1000 images within 2 seconds. Moreover, the intelligent nanoscope achieves a 95% nanomaterial classification accuracy using 1000 images of training sets, which is 45% more accurate than without the microsphere array. The intelligent nanoscope also achieves a 92% bacteria classification accuracy using 50 000 images of training sets, which is 35% more accurate than without the microsphere array. This platform accomplished rapid, accurate detection and classification of nanomaterials with miniscule size differences. The capabilities of this device wield the potential to further detect and classify smaller biological nanomaterial, such as viruses or extracellular vesicles. 

Abstract Nanocarrier and exosome encapsulation has been found to significantly increase the efficacy of targeted drug delivery while also minimizing unwanted side effects. However, the development of exosome-encapsulated drug nanocarriers is limited by low drug loading efficiencies and/or complex, time-consuming drug loading processes. Herein, we have developed an acoustofluidic device that simultaneously performs both drug loading and exosome encapsulation. By synergistically leveraging the acoustic radiation force, acoustic microstreaming, and shear stresses in a rotating droplet, the concentration, and fusion of exosomes, drugs, and porous silica nanoparticles is achieved. The final product consists of drug-loaded silica nanocarriers that are encased within an exosomal membrane. The drug loading efficiency is significantly improved, with nearly 30% of the free drug (e.g., doxorubicin) molecules loaded into the nanocarriers. Furthermore, this acoustofluidic drug loading system circumvents the need for complex chemical modification, allowing drug loading and encapsulation to be completed within a matter of minutes. These exosome-encapsulated nanocarriers exhibit excellent efficiency in intracellular transport and are capable of significantly inhibiting tumor cell proliferation. By utilizing physical forces to rapidly generate hybrid nanocarriers, this acoustofluidic drug loading platform wields the potential to significantly impact innovation in both drug delivery research and applications. 

Abstract A surge of research in intracellular delivery technologies is underway with the increased innovations in cell‐based therapies and cell reprogramming. Particularly, physical cell membrane permeabilization techniques are highlighted as the leading technologies because of their unique features, including versatility, independence of cargo properties, and high‐throughput delivery that is critical for providing the desired cell quantity for cell‐based therapies. Amongst the physical permeabilization methods, sonoporation holds great promise and demonstrates to deliver a variety of functional cargos, such as biomolecular drugs, proteins, and plasmids, to various cells including cancer, immune, and stem cells. However, traditional bubble‐based sonoporation methods usually require special contrast agents. Bubble‐based sonoporation methods also have high chances of inducing irreversible damage to critical cell components, lowering the cell viability, and reducing the effectiveness of delivered cargos. To overcome these limitations, several novel non‐bubble‐based sonoporation mechanisms are under development. This review will cover both the bubble‐based and non‐bubble‐based sonoporation mechanisms being employed for intracellular delivery, the technologies being investigated to overcome the limitations of traditional platforms, as well as perspectives on the future sonoporation mechanisms, technologies, and applications. 

Droplet microfluidics has become an indispensable tool for biomedical research and lab-on-a-chip applications owing to its unprecedented throughput, precision, and cost-effectiveness. Although droplets can be generated and screened in a high-throughput manner, the inability to label the inordinate amounts of droplets hinders identifying the individual droplets after generation. Herein, we demonstrate an acoustofluidic platform that enables on-demand, real-time dispensing, and deterministic coding of droplets based on their volumes. By dynamically splitting the aqueous flow using an oil jet triggered by focused traveling surface acoustic waves, a sequence of droplets with deterministic volumes can be continuously dispensed at a throughput of 100 Hz. These sequences encode barcoding information through the combination of various droplet lengths. As a proof-of-concept, we encoded droplet sequences into end-to-end packages ( e.g. , a series of 50 droplets), which consisted of an address barcode with binary volumetric combinations and a sample package with consistent volumes for hosting analytes. This acoustofluidics-based, deterministic droplet coding technique enables the tagging of droplets with high capacity and high error-tolerance, and can potentially benefit various applications involving single cell phenotyping and multiplexed screening.