Description:PREAMBLE TO THE DESCRIPTION
The following specification particularly describes the invention and the manner in which it is to be performed.

A MICROFLUIDIC SYSTEM AND METHOD FOR DYNAMICALLY DETERMINING A RHEOLOGY OF A PICOLITER-SCALE SAMPLE
FIELD OF INVENTION
The present disclosure generally relates to rheology measuring microfluidic systems, more particularly relates to a microfluidic system and a method for dynamically determining a rheology of a picoliter-scale sample.
BACKGROUND
Generally, viscosity and viscoelasticity of biological fluids such as blood, urine, saliva, cerebrospinal fluid and synovial fluid, includes essential information of a human physiology for improving diagnostics in healthcare. Introduction of homogeneous fluids or heterogeneous fluids containing cells, reagents, micro drops and particles into a microfluidic device and the collection of fluids, cells, reagents and particles output from a microfluidic device is important to implementing biochemical and cell assays in these devices. Further, a microfluidic device needs to be fluidically connected to external macroscale reservoirs containing the different assay components and to a source providing the force to move fluids through the microfluidic channels of the device. The large difference in physical dimensions between the microscopic channels of the microfluidic device and the external macroscopic reservoirs and fluid driving sources necessitates fluidic interfaces for seamless integration with external systems. However, the conventional techniques require microliters or nanolitres of sample.
Further, ideal specifications of the interface includes, first, the interface needs to have minimal to no dead volume, wherein an excess amount of fluid is needed to fill and provide continuity in the fluidic connection between the microdevice and reservoirs. This is especially important if the fluid contains cells or other time or environmentally sensitive materials that could readily degrade or change if the fluid is entrained in a volume that does not interact with the microfluidic device. Further, this problem becomes particularly acute when the fluid contains a limited number of cells from a specimen or an expensive or otherwise valuable reagent. Entrapment of the cells or reagent in a volume that does not interact with the device wastes the cells and precious reagents. Second, the interface needs to minimize or prevent any damage to cells, particles or micro-drops that pass through the interface to maximize the utilization of these materials in the device and the fidelity of any analytical measurement. Thirdly, the interface needs to prevent or limit sedimentation of cells, particles or micro-drops from the carrier fluid. This would further limit the number of cells, particles or micro-drops available for input to the microfluidic device and be available for analysis or interaction with other components in the device. A fourth consideration is the need for the fluidic interface to be simple to use by a human operator and reliable and robust in making and breaking the fluidic interface so the connection can be used multiple times without failure.
Conventionally, viscometers such as drop based viscometer, interface-based viscometer, microbubble-based viscometer, Micro Electro-Mechanical System (MEMS) based viscometers, are used to determine viscosity of biological fluids. Conventionally, in microfluidic viscometers such as, a drop-based viscometer, a viscosity of liquid is measured by generating monodisperse droplets. The monodisperse droplet refers to a population of droplets with a narrow size distribution. The measurement of the viscosity includes, either measuring velocity flow of the monodisperse droplets or measuring a size of the monodisperse droplet. In the interface-based viscometer, the viscosity of liquid is measured by measuring a position of the interface between two or more liquids. In a microbubble-based viscometer, a microbubble, a tiny gas bubble typically microns in size, is introduced into the liquid with particles whose viscosity needs to be measured. An ultrasound waves are then directed at the microbubble. The ultrasound waves cause the microbubble to oscillate. The oscillations create a flow of liquid around the bubble, the flow of particles in liquid around the bubble is termed as acoustic streaming. However, Due to the smaller size of the microbubbles, the oscillations of microbubbles are tended to be smaller. Further, the smaller oscillations limit the accuracy, sensitivity, and range of measurement. However, the introduction of particles to the sample contaminates the samples and limits the use to study homogeneous samples.
While the oscillation amplitude of the microbubble could itself be used to determine the viscosity of liquids, these techniques generally place the microbubble in infinite or semi-infinite liquid media increasing the volume of the liquid required for the measurements. Due to the smaller size of the microbubbles, their oscillations also reduced, limiting the accuracy, sensitivity, and range of measurement, and tendency to dissolve in liquids further reduces durability of a system. In a Micro Electromechanical System (MEMS), the viscometers are miniaturized devices that utilize microfabrication techniques to create micromechanical sensors for measuring fluid viscosity. MEMS-based viscometers may measure the viscosity of low sample volumes, however MEMS based viscometers may not be accurately used for single-cell measurements like integrated microfluidic chips. Traditionally, viscometers are large in size and require large sample volumes, may be in millilitres, the large sample size limits a suitability of the viscometer for applications sensitive to sample size and single cell measurements.
Therefore, there is a need for an improved, efficient systems and methods to address at least the aforementioned issues of the prior arts, by providing a microfluidic system and method for dynamically determining a rheology of a picoliter-scale sample.

SUMMARY
This summary is provided to introduce a selection of concepts, in a simple manner, which is further described in the detailed description of the disclosure. This summary is neither intended to identify key or essential inventive concepts of the subject matter nor to determine the scope of the disclosure.
An aspect of the present disclosure provides a microfluidic system for dynamically determining a rheology of a picoliter-scale sample is disclosed. The microfluidic system includes a microfluidic chip, which includes a pre-defined shaped channel configured to perpendicularly receive, in a picoliter-scale, a fluid and an air for creating an air-fluid interface. The fluid includes at least one of a liquid, a liquid with a cell, a biological fluid, and a viscous fluid. Further, the microfluidic system includes a signal generator to generate one or more electrical excitation signals in one or more pre-defined frequencies. Further, the microfluidic system includes a power amplifier communicatively coupled to the signal generator. The power amplifier amplifies the electrical excitation signal received from the signal generator.
Furthermore, the microfluidic system includes a piezo-electric transducer coupled to the microfluidic chip in proximity to the air-liquid interface, and communicatively coupled to the power amplifier. The piezo-electric transducer receives the amplified electrical excitation signal from the power amplifier, and generates acoustic waves for propagating through the fluid, based on receiving the amplified electrical excitation signal from the power amplifier. The air-fluid interface oscillates in the one or more pre-defined frequencies due to a substantial difference in an acoustic impedance between the air-fluid interface. Further, the microfluidic system includes an image capturing device configured to capture a plurality of images including one or more oscillations in the air-fluid interface.
Furthermore, the microfluidic system includes a processor, and a memory coupled to the processor. The memory includes processor-executable instructions, which on execution, cause the processor to receive, from the image capturing device, the captured plurality of images including one or more oscillations in the air-fluid interface. Further, the processor is configured to analyse at least one of an oscillation pattern of the fluid and a shape pattern of a cell associated with the fluid, in each of the plurality of images. Further, the processor is configured to determine a difference in at least one of the oscillation patterns and the shape pattern between each of the plurality of images. Furthermore, the processor is configured to measure an amplitude of the one or more oscillations of the air-fluid interface, based on determining the difference in at least one of the oscillation patterns and the shape pattern between each of the plurality of images. Further, the processor is configured to determine at least one of a viscosity associated with the fluid and a viscoelasticity associated with the cell, based on measuring the amplitude of the one or more oscillations of the air-fluid interface. Furthermore, the processor is configured to output on an electronic display associated, at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell.
Another aspect of the disclosure provides a method for dynamically determining a rheology of a picoliter-scale sample. The method includes receiving from an image capturing device, a captured plurality of images including one or more oscillations in an air-fluid interface. The air-fluid interface is created on a microfluidic chip including a pre-defined shaped channel configured to perpendicularly receive, in a picoliter-scale, a fluid and an air. The fluid includes at least one of a liquid, a liquid with a cell, a biological fluid, and a viscous fluid.
Further, the method includes analysing at least one of an oscillation pattern of the fluid and a shape pattern of a cell associated with the fluid, in each of the plurality of images. The air-fluid interface oscillates, via a piezo-electric transducer, in one or more pre-defined frequencies due to a substantial difference in an acoustic impedance between the air-fluid interface. Furthermore, the method includes determining a difference in at least one of the oscillation pattern and the shape pattern between each of the plurality of images. Additionally, the method includes measuring an amplitude of the one or more oscillations of the air-fluid interface, based on determining the difference in at least one of the oscillation pattern and the shape pattern between each of the plurality of images. Further, the method includes determining at least one of a viscosity associated with the fluid and a viscoelasticity associated with the cell, based on measuring the amplitude of the one or more oscillations of the air-fluid interface. Furthermore, the method includes outputting on a display associated with an electronic device, at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell.
To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF ACCOMPANYING DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which:
FIG. 1 illustrates an exemplary block diagram representation of a microfluidic system for dynamically determining a rheology of a picoliter-scale sample, in accordance with an embodiment of the present disclosure;
FIG. 2 illustrates an exemplary block diagram representation of a computing unit for dynamically determining a rheology of a picoliter-scale sample, in accordance with an embodiment of the present disclosure;
FIG. 3 illustrates an exemplary schematic diagram representation of an exemplary setup of a microfluidic system, in an accordance with an embodiment of the present disclosure;
FIG. 4 illustrates an exemplary schematic diagram representation of an air-liquid interface in a microfluidic chip of a microfluidic system\, in accordance with an embodiment of the present disclosure;
FIG. 5 illustrates an exemplary schematic diagram representation of an air-liquid interface in a microfluidic chip and an expanded view of a dynamic cell , in accordance with an embodiment of the present disclosure;
FIG. 6 illustrates an exemplary schematic diagram representation of an air-liquid interface in a microfluidic chip and an expanded view of a dynamic cell deformation, in accordance with another embodiment of the present disclosure;
FIG. 7A illustrates an exemplary schematic diagram representation of oscillations in An Air-Liquid Interface (ALI) captured using image capturing device 110 such as for example, one or more high speed camera, in an accordance with an embodiment of the present disclosure;
FIG. 7B illustrates an exemplary schematic diagram representation of process of calculating length of Air-Liquid Interface (ALI) , in an accordance with an embodiment of the present disclosure;
FIG. 8 illustrates an exemplary schematic diagram representation of a working principle of a microfluidic system for dynamically determining a rheology of a picoliter-scale sample, in accordance with an embodiment of the present disclosure;
FIG. 9 illustrates an exemplary schematic diagram representation of working principle of a microfluidic system for determining cell oscillations, in accordance with another embodiment of the present disclosure;
FIG. 10 illustrates an exemplary graphical representation of a graph for a measurement of amplitude vs. viscosity of a liquid, in an accordance with an embodiment of the present disclosure;
FIG. 11 illustrates an exemplary graphical representation of a graph for a measurement of amplitude of oscillations varying across different frequencies, in an accordance with an embodiment of the present disclosure;
FIG. 12 illustrates an exemplary graphical representation of a graph for a position of cells over time, in an accordance with an embodiment of the present disclosure;
FIG. 13 illustrates an exemplary graphical representation of a graph for an aspect ratio of cells over time, in an accordance with an embodiment of the present disclosure; and
FIG. 14 illustrates an exemplary flow diagram representation of a method for dynamically determining a rheology of a picoliter-scale sample, in accordance with an embodiment of the present disclosure.
Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
 
DETAILED DESCRIPTION OF THE DISCLOSURE
For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure. It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.
To make objects, technical solutions and advantages of the present disclosure more clear, the present disclosure will be described in further detail with reference to the drawings. It is apparent that the described embodiments are only some embodiments of the present disclosure, not all embodiments. All other embodiments, which may be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
The shapes and sizes of the components shown in the drawings are not necessarily drawn to scale, but are merely for the purpose of facilitating easy understanding of the contents of the present embodiments of the present disclosure.
Unless defined otherwise, technical or scientific terms used herein should have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure belongs. The terms of “first”, “second”, and the like used in the present disclosure are not intended to indicate any order, quantity, or importance, but rather are used for distinguishing one element from another. Further, the term “a”, “an”, “the”, or the like does not denote a limitation of quantity, but rather denotes the presence of at least one element. The term “comprising”, “including”, or the like, means that the element or item preceding the term contains the element or item listed after the term and the equivalent thereof, but does not exclude the presence of any other element or item. The term “connected”, “coupled”, or the like is not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect connections. The terms “upper”, “lower”, “left”, “right”, and the like are used only for indicating relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
The terms "comprise", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, additional sub-modules. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
Accordingly, the term “module” or “subsystem” should be understood to encompass a tangible entity, be that an entity that is physically constructed permanently configured (hardwired) or temporarily configured (programmed) to operate in a certain manner and/or to perform certain operations described herein.
The embodiment of the present disclosure is not limited to the embodiments shown in the drawings, but includes modifications of configurations formed based on a manufacturing process. Thus, regions illustrated in the drawings have schematic properties, and shapes of the regions shown in the drawings illustrate specific shapes of regions of elements, but are not intended to be limiting.
Embodiments of the present disclosure provides a microfluidic system for dynamically determining a rheology of a picoliter-scale sample. The present disclosure provides a microfluidic system includes a microfluidic chip that features a pre-defined shaped channel. This channel is configured to perpendicularly receive picoliter-scale volumes of fluid and air, creating an air-fluid interface. The fluids tested can include liquids, liquids containing cells, biological fluids, or viscous fluids. The system includes a signal generator that produces electrical excitation signals at predefined frequencies. These signals are then amplified by a power amplifier, which is connected to the signal generator. The amplified signals are sent to a piezo-electric transducer, which is positioned near the air-liquid interface on the microfluidic chip. The transducer converts these signals into acoustic waves that propagate through the fluid. Due to the substantial difference in acoustic impedance between air and fluid, these waves cause the air-fluid interface to oscillate. An image capturing device is used to capture multiple images of the oscillations occurring at the air-fluid interface. These images are then analysed by a processor equipped with memory containing executable instructions. The processor analyses the oscillation patterns of the fluid and any shape patterns of cells present in the fluid. By measuring the amplitude of the oscillations, the processor determines the viscosity of the fluid or the viscoelasticity of the cells. The results are then displayed on an associated electronic device. This microfluidic system provides precise measurements of fluid properties at a very small scale. It offers valuable data on the viscosity and viscoelasticity of various types of fluids, enhancing the understanding and analysis of fluid dynamics in picoliter-scale samples.
Referring now to the drawings, and more particularly to FIG. 1 through FIG. 14, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments and these embodiments are described in the context of the following exemplary system and/or method.
FIG. 1 illustrates an exemplary block diagram representation of a microfluidic system 100 for dynamically determining a rheology of a picoliter-scale sample, in accordance with an embodiment of the present disclosure. According to FIG. 1, the microfluidic system 100 includes, a microfluidic chip 102, a signal generator 104, a power amplifier 106, a piezoelectric transducer 108, an image capturing device 110, an electronic display 118, a computing unit 120. The picoliter-scale sample or a sample (hereinafter picoliter-scale sample or the sample) may refer to a fluid capable of flowing through a channel. Thus, the sample may include, but not limited to, a fluid suspension of biologically-derived particles (such as cells, organelles, nuclei, blood, and the like.). The sample may include a material in the form of a liquid/fluid suspension that may be driven through microfluidic channels used in the systems and methods described herein.
For example, a sample may be obtained from an animal, a human, water source, food, soil, air, saliva, urine, synovial fluid, cerebro spinal fluid, sweat, plasma, any other biological fluids, and the like. If a solid sample is obtained, such as a tissue sample or a soil sample, the solid sample may be liquefied or solubilized prior to subsequent introduction into the microfluidic system 100. A sample may include suspensions, liquids, and/or fluids having at least one type of particle, cell, and/or bead, and the like. Further, focusing can produce a flux of particles enriched in a first particle based on size. Cells can be, alive or fixed, such as, but not limited to, adult red blood cells, fetal red blood cells, trophoblasts, fetal fibroblasts, white blood cells, epithelial cells, tumour cells, cancer cells, hematopoietic stem cells, bacterial cells, mammalian cells, plant cells, neutrophils, T lymphocytes, B lymphocytes, monocytes, eosinophils, natural killer cells, basophils, dendritic cells, circulating endothelial cells, antigen specific T-cells, fungal cells, and the like. Samples may or may not be diluted or concentrated to attain a predetermined ratio before and/or during introduction of the sample into the microfluidic system 100. Further, the cell to volume ratio may be less than about 50%. In other embodiments, cell to volume ratios can be less than about 40%, 30%, 20%, 10%, 8%, or 6%. More particularly, in some embodiments, cell to volume ratios can be in a range of about 0.001% to about 5%, e.g., in a range of about 0.01% to about 4%. In general, a maximum cell to volume ratio for a specified cell size and channel geometry can be determined by one of ordinary skill in the art. The term “particle” may also include a particle, such as non-biologically derived sphere (i.e., a bead) having predetermined dimensions. In some instances, the bead can be conjugated to another particle or cell.
As used herein, the term “flow” refers to the passage of a fluid in a specific direction, i.e., downstream, which may change over time. The flow may be continuous and/or discontinuous. The flow may be laminar or turbulent. In specific embodiments of the present disclosure the flow is laminar. A continuous flow may for example move a solution containing one or more cells or particles through a channel. As such, the flow path, shape or rate may depend on the shape of the channels in which the fluid travels or displacement elements therein.
Various techniques exist for moving a sample through a microfluidic channel. For example, a microfluidic system can include a pumping mechanism for introducing and moving the fluid sample into and through one or more microfluidic channels. The pumping mechanism can also regulate and control a flow rate within the channels as needed. A specific pumping mechanism may be provided in a positive pumping configuration, in a negative pumping configuration, or in some combination of both. In one embodiment, a sample can be introduced into the inlet and can be pulled into the microfluidic system 100 under negative pressure or vacuum using the negative pumping configuration. A negative pumping configuration may allow for processing of a complete volume of sample, without leaving any sample within the channels. Exemplary negative pumping mechanisms may include, but are not limited to, syringe pumps, peristaltic pumps, aspirators, and/or vacuum pumps. In other embodiments, a positive pumping configuration may also be employed. A sample can be introduced into the inlet and can be injected or pushed into the microfluidic system 100 under positive pressure. Exemplary positive pumping mechanisms may include, but are not limited to, syringe pumps, peristaltic pumps, pneumatic pumps, displacement pumps, and/or a column of fluid. Oscillations caused by some pumping mechanisms, such as a peristaltic pump, may optionally be damped to allow for proper focusing within the channels.
Flow rates within the channels can be regulated and controlled. For instance, any number and variety of microfluidic valves can also be included in the microfluidic system 100 to block or unblock the pressurized flow of particles through the channels. The microvalve may include one or more mobile diaphragms or flexible membranes formed in a layer above a channel branch, inlet, or outlet such that upon actuation, the membrane may be expanded up to decrease resistance within a channel branch, inlet, or outlet, or expanded down into the channel to increase resistance within the same. Optionally, one or more microfluidic, size-based separation modules or filters can be included to prevent clogging within the channels by preventing certain cell or particle sizes or cell types from entering the channels and/or to facilitate collection of cells or particles for downstream processing.
The fluid stream of cells or particles of interest can pass through a port (inlet or outlet) of a microfluidic channel through a nozzle and into a medium suitable to induce droplet formation from the fluid stream. Droplet formation of the fluid can be induced by injecting the fluid into a second immiscible liquid. The mechanism of droplet formation of the fluid is related to the presence of the surrounding viscous liquid. A liquid forced through an orifice may break into droplets at slow flows, whereas at faster flows the liquid forms a thin stream that breaks into droplets away from the orifice; these are the dripping and jetting regimes.
The microfluidic chip 102 may include one or more shapes and the microfluidic chip 102 may include one or more junctions. In one exemplary embodiment, the microfluidic chip 102 may include T-junction. In some examples, the channel layer may be made of various types of materials. For example, the channel layer may include at least one of silicon, glass, Polymethyl Methacrylate (PMMA), Polycarbonate (PC), and other polymer materials, which is not limited herein. Depending on the material, the microfluidic channels may be formed in the channel layer by using any one of Micro-Electro-Mechanical systems (MEMS) process compatibility, Micro-injection moulding, laser processing, machining, and the like.
Rheology is the study of the deformation and flow of matter, including how materials respond to applied stress and strain. Rheological properties include both chemical and physical characteristics and include viscosity, viscoelasticity, shear rate, surface tension and contact angle of the fluid with respect to a surface material. The viscosity of a material determines how gelatinous, syrupy or viscous that material is and is related to the chemical and physical attractions experienced by the molecules in a fluid. A common comparison to define viscosity is to compare water to honey, with the obvious observation that honey is much thicker or gelatinous than water and flows much slower when poured at room temperature. If honey is heated to near boiling and poured, it flows at nearly the same rate as water, because its viscosity has dropped to nearly the same as water. Thus, viscosity is impacted by the temperature of the material. Applying a force can also impact the viscosity of matter and is defined by a characteristic called shear rate; in some cases, applying force (e.g., shear stress) causes a material’s viscosity to increase (i.e., shear thickening) and in other cases applied force causes the material’s viscosity to decrease (i.e., shear thinning).
Viscoelasticity is a property of materials that exhibit both viscous and elastic characteristics when undergoing deformation. This means that viscoelastic materials have a combination of fluid-like (viscous) and solid-like (elastic) behaviours. These materials respond to stress and strain in ways that are not purely viscous, like honey, or purely elastic, like rubber bands, but a combination of both. Viscosity in viscoelastic materials refers to the resistance of materials to flow. When stress is applied to a viscoelastic material, it deforms over time in a manner similar to a viscous fluid. This behaviour is time-dependent and energy dissipative, meaning that some of the energy applied to deform the material is lost as heat. Elasticity, on the other hand, is the ability of a material to return to its original shape after the applied stress is removed. In viscoelastic materials, this elastic behaviour is also time-dependent. These materials can store energy when deformed, much like an elastic band, and release that energy when the stress is removed. Viscoelastic materials, therefore, combine these properties. Examples of viscoelastic materials include polymers, biological tissues, and certain metals at high temperatures. The behaviour of these materials can be modelled using mechanical analogues such as springs and dashpots. One key aspect of viscoelasticity is its time-dependent behaviour. Creep is the gradual deformation of a viscoelastic material under a constant load over time. Stress relaxation, conversely, is the gradual decrease in stress experienced by a viscoelastic material when it is held at a constant strain over time. Another phenomenon associated with viscoelasticity is hysteresis, which is the energy loss observed in the material during a loading-unloading cycle. This energy loss is evidenced by a lag between the applied stress and the resulting strain. Viscoelastic materials also exhibit frequency-dependent behaviour, which can be studied using Dynamic Mechanical Analysis (DMA). DMA applies an oscillatory stress or strain to the material and measures the resulting strain or stress. This helps in understanding how the material behaves under different frequencies of loading, providing insights into its dynamic mechanical properties.
Yet another property is the surface tension of a fluid, which is a measure of the cohesive interactions between the molecules in a fluid specifically at the fluid’s surface. The most common example of a fluid with very high surface tension is water wherein the strong cohesion of the water molecules with each other (as opposed to attraction between water molecules and air) results in a skin-like surface that can float more dense materials (e.g., a paper clip). Water’s surface tension can be significantly reduced with a drop of dish soap, oil, or other hydrophobic materials. Contact angle is yet another property, which is defined as the angle that is formed between a fluid droplet and a surface it sits on. Contact angle is a combination of the physical and chemical properties of the fluid and the physical and chemical properties of the material it is in contact with.
The present disclosure of the microfluidic system 100 may be designed to provide precise measurements of fluid properties at a very small scale, offering valuable data on the viscosity and viscoelasticity of various types of fluids. The microfluidic chip 102 may be a core component where the fluid sample is introduced. The microfluidic chip 102 includes a pre-defined shaped channel configured to receive fluid and air perpendicularly, creating an air-fluid interface. This interface is critical for the subsequent measurements and analyses performed by the system 100. Microfluidic chip 102 may be tailored for specific functions and applications. Channel-based microfluidic chips include straight channel chips, which are used for simple fluid flow and mixing experiments, curved channel chips designed to enhance mixing efficiency and control fluid dynamics, and network channel chips that incorporate complex networks of channels for multiple fluid manipulations, such as cell sorting or chemical reactions. Droplet-based microfluidic chips include T-junction chips that create droplets at the intersection of two channels, flow-focusing chips that use a sheath flow to generate droplets with precise size control, and electrowetting chips that manipulate droplets using electrical fields, allowing for operations like merging, splitting, and transport.
Paper-based microfluidic chips, or μPADs, include lateral flow assays commonly used in diagnostic tests like pregnancy tests, vertical flow assays where fluids flow through stacked paper layers for filtration and multiplexed assays, and origami chips that use folding patterns to create 3D microfluidic networks within paper for complex assays in a low-cost format. Digital microfluidic chips, such as electrowetting-on-dielectric (EWOD) chips and surface acoustic wave (SAW) chips, manipulate individual droplets on a planar surface using electric fields or acoustic waves, providing highly programmable fluidic operations. Hybrid microfluidic chips combine materials like polymers (e.g., PDMS) for flexibility and biocompatibility, glass or silicon for high precision and durability, and composites integrating different materials to enhance multifunctional performance. Organ-on-a-chip devices, such as lung-on-a-chip, liver-on-a-chip, and gut-on-a-chip, mimic the structure and function of specific organs for studying diseases and drug testing. Lastly, cell sorter and analyser chips, including flow cytometry chips and magnetic bead-based chips, perform cell counting, sorting, and analysis using microfluidic channels, optical detection, and magnetic fields, enabling targeted isolation and analysis of cells or particles. These diverse types of microfluidic chips provide powerful tools for diagnostics, research, and industrial processes across various fields, including biology, chemistry, medicine, and engineering.
Further, the signal generator 104 may generates electrical excitation signals at pre-defined frequencies. These signals are crucial for creating the acoustic waves necessary to induce oscillations at the air-fluid interface. The signal generator 104 may include, but not limited to, function generators, Radio Frequency (RF) signal generators, Arbitrary Waveform Generators (AWGs), pulse generators, audio signal generators, digital pattern generators, sweep generators, vector signal generators, digital pattern generators, DC power supplies with function generator capabilities, low-frequency function generators, modulation capabilities based signal generators, integration with control systems, compact size and low noise signal generators, and the like.
Furthermore, the power amplifier 106 may be communicatively coupled to the signal generator 104. The power amplifier 106 may amplify the electrical excitation signals received from the signal generator, ensuring they are strong enough to drive the piezoelectric transducer. The power amplifier 106 (or a voltage amplifier) may include, but not limited to, linear power amplifiers, RF power amplifiers, class D power amplifiers, audio power amplifiers, pulse power amplifiers, differential power amplifiers, and the like. Additionally, the piezoelectric transducer 108 may be positioned in proximity to the air-liquid interface on the microfluidic chip 102, the piezoelectric transducer 108 receives the amplified electrical excitation signals from the power amplifier 106. The piezoelectric transducer 108 may then generate acoustic waves that propagate through the fluid. The substantial difference in acoustic impedance between the air and fluid causes the air-fluid interface to oscillate at the pre-defined frequencies. Piezoelectric transducers encompass various types including ceramics such as lead zirconate titanate (PZT) for actuators and sensors, crystals such as quartz for oscillators, flexible film transducers for medical probes and sensors, accelerometers for vibration monitoring, buzzers for alarms, actuators for precise movements, pressure sensors for industrial use, and microphones for audio applications.
Further, the image capturing device 110 may capture a series of images that include the oscillations occurring at the air-fluid interface. These images are crucial for the subsequent analysis of fluid properties. Image capturing devices include cameras, video cameras, digital cameras, RGB cameras, depth cameras, thermal cameras, Charge-Coupled Device (CCD), Complementary Metal-Oxide Semiconductor (CMOS) sensors, X-ray detectors, Infrared cameras, multispectral and hyperspectral cameras, fluorescence microscopes, Scanning Electron Microscopes (SEM), digital radiography detectors, high-speed cameras, Light Detection and Ranging (LIDAR) cameras, and the like.
Further, the electronic display 118 may be connected to the computing unit 120, the electronic display 118 shows the results of the analysis, including measurements of viscosity and viscoelasticity. Examples of electronic display 118 include Liquid Crystal Displays (LCD), Light Emitting Diode Displays (LED), Organic Light Emitting Diode Displays (OLED), Electroluminescent Displays (EL), and the like. The displays may or may not be associated with electronic device (not shown) such as, but not limited to, a mobile, a smart phone, a tablet, a wearable device, a server, a laptop, a desktop, and the like. The electronic device may be associated with one or more users, and communicatively coupled to a server (not shown) and the system 100 via a communication network (not shown). The communication network may be a wired network or a wireless network or combination thereof.
The computing unit 120 receives the captured images from the image capturing device 110, analyses the oscillation patterns, and determines the rheological properties of the fluid sample. It then outputs these results to the electronic display 118. The computing unit 120 may be associated with the electronic device, or server or implemented as a stand-alone device. The server may be at least one of, but not limited to, a central server, a cloud server, a remote server, a rake server, an on-premises server, and the like. Further, the system 100 may be communicatively coupled to a database (not shown in FIG. 1), via the communication network. The database may be any kind of databases/repositories such as, but are not limited to, relational database, dedicated database, dynamic database, monetized database, scalable database, cloud database, distributed database, any other database, and combination thereof.
Further, the electronic device may be associated with, but not limited to, a user, an individual, an administrator, a vendor, a technician, a worker, a specialist, a healthcare worker, an instructor, a supervisor, a team, an entity, an organization, a company, a facility, a bot, any other user, and combination thereof. The entity, the organization, and the facility may include, but are not limited to, a hospital, a healthcare facility, an exercise facility, a laboratory facility, an educational institution, a secured facility, any other facility, and the like. The electronic device may be used to provide input and/or receive output to/from the system, and/or to the database, respectively. The electronic device may present to the user one or more user interfaces for the user to interact with the system 100 and/or to the database for dynamically determining a rheology of a picoliter-scale sample need. The electronic device may be at least one of, an electrical, an electronic, an electromechanical, and a computing device. The electronic device 120 may include, but is not limited to, a mobile device, a smartphone, a personal digital assistant (PDA), a tablet computer, a phablet computer, a wearable computing device, a virtual reality / augmented reality (VR/AR) device, Metaverse based devices, a laptop, a desktop, a server, and the like.
Further, the system 100 or the computing unit 120 may be implemented by way of a single device or a combination of multiple devices that may be operatively connected or networked together. The system 100 or the computing unit 120 may be implemented in hardware or a suitable combination of hardware and software. The computing unit 120 includes one or more hardware processor(s) 112, and a memory 114. The memory 114 may include a plurality of modules 116. The computing unit 120 may be a hardware device including the hardware processor 112 executing machine-readable program instructions for dynamically determining a rheology of a picoliter-scale sample. Execution of the machine-readable program instructions by the hardware processor 112 may enable the system 100 or the computing unit 120 to dynamically determining a rheology of a picoliter-scale sample. The “hardware” may comprise a combination of discrete components, an integrated circuit, an application-specific integrated circuit, a field-programmable gate array, a digital signal processor, or other suitable hardware. The “software” may comprise one or more objects, agents, threads, lines of code, subroutines, separate software applications, two or more lines of code, or other suitable software structures operating in one or more software applications or on one or more processors.
The one or more hardware processors 112 may include, for example, microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and/or any devices that manipulate data or signals based on operational instructions. Among other capabilities, hardware processor 112 may fetch and execute computer-readable instructions in the memory 114 operationally coupled with the system 100 or the computing unit 120 for performing tasks such as data processing, input/output processing, and/or any other functions. Any reference to a task in the present disclosure may refer to an operation being or that may be performed on data.
Though few components and subsystems are disclosed in FIG. 1, there may be additional components and subsystems which is not shown, such as, but not limited to, ports, routers, repeaters, firewall devices, network devices, databases, network attached storage devices, servers, assets, machinery, instruments, facility equipment, emergency management devices, image capturing devices, sensors, any other devices, communication infrastructure devices, and combination thereof. The person skilled in the art should not be limiting the components/subsystems shown in FIG. 1. Although FIG. 1 illustrates the microfluidic chip 102, the signal generator 104, the power amplifier 106, the piezoelectric transducer 108, the image capturing device 110, the electronic display 118, the computing unit 120, one skilled in the art can envision that the system 100, may include multiple microfluidic chip 102, signal generator 104, power amplifier 106, piezoelectric transducer 108, image capturing device 110, electronic display 118, and computing unit 120.
Those of ordinary skilled in the art will appreciate that the hardware depicted in FIG. 1 may vary for particular implementations. The depicted example is provided for explanation only and is not meant to imply architectural limitations concerning the present disclosure. Those skilled in the art will recognize that, for simplicity and clarity, the full structure and operation of all data processing systems suitable for use with the present disclosure are not being depicted or described herein. Instead, only so much of the system 100 as is unique to the present disclosure or necessary for an understanding of the present disclosure is depicted and described. The remainder of the construction and operation of the system 100 may conform to any of the various current implementations and practices that were known in the art.
In an embodiment, the microfluidic chip 102 may include a pre-defined shaped channel configured to perpendicularly receive, in a picolitre-scale, a fluid and an air for creating an air-fluid interface. The fluid includes, but not limited to, a liquid, a liquid with a cell, a biological fluid, a viscous fluid, and the like. The pre-defined shaped channel may correspond, but not limited to, a T-junction microfluidic, and the like, channel configured to facilitate perpendicular flow of the fluid and the air.Further, the microfluidic system 100 may include the signal generator 104. The signal generator 104 may be configured to generate one or more electrical excitation signals in one or more pre-defined frequencies. Further, the microfluidic system 100 may include the power amplifier 106 communicatively coupled to the signal generator 104. The power amplifier 106 may be configured to amplify the electrical excitation signal received from the signal generator 104.
In an embodiment, the microfluidic system 100 may include the piezo-electric transducer 108 coupled to the microfluidic chip 102 in proximity to the air-liquid interface, and communicatively coupled to the power amplifier 106. The piezo-electric transducer 108 may be configured to receive the amplified electrical excitation signal from the power amplifier 106, and generate acoustic waves for propagating through the fluid, based on receiving the amplified electrical excitation signal from the power amplifier 106. The generated acoustic waves may vibrate the cell in the fluid to change the shape pattern of the cell. The change in the shape pattern of the cell may be determined to extract at least one of an elastic property and a viscous property of the cell. The acoustic waves generated by the piezo-electric transducer 108 may be propagated to the fluid through the microfluidic chip 102 comprising a glass substrate The air-fluid interface oscillates in the one or more pre-defined frequencies due to a substantial difference in an acoustic impedance between the air-fluid interface. The substantial difference in the acoustic impedance between the air and the fluid interface may include a high acoustic impedance mismatch causing a large motion of the air-fluid interface.
In an embodiment, the microfluidic system 100 may include the image capturing device 110 configured to capture a plurality of images including one or more oscillations in the air-fluid interface. Further, the microfluidic system 100 may include the computing unit 120. The computing unit 120 may include the processor 112, and the memory 114 coupled to the processor 112. The memory 114 may include processor-executable instructions, which on execution, cause the processor 112 to receive, from the image capturing device 110, the captured plurality of images including one or more oscillations in the air-fluid interface. Further, the processor 112 may be configured to analyse at least one of an oscillation pattern of the fluid and a shape pattern of a cell associated with the fluid, in each of the plurality of images. Further, the processor 112 may be configured to determine a difference in at least one of the oscillation patterns and the shape pattern between each of the plurality of images.
Furthermore, the processor 112 may be configured to measure an amplitude of the one or more oscillations of the air-fluid interface, based on determining the difference in at least one of the oscillation patterns and the shape pattern between each of the plurality of images. The amplitude of the one or more oscillations is inversely proportional to at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell. Further, the amplitude of the one or more oscillations is dampened, if at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell is higher. Further, the processor 112 may be configured to determine at least one of a viscosity associated with the fluid and a viscoelasticity associated with the cell, based on measuring the amplitude of the one or more oscillations of the air-fluid interface. Furthermore, the processor 112 may be configured to output on an electronic display 118 associated with an electronic device, at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell.
FIG. 2 illustrates an exemplary block diagram representation of a computing unit 120 for dynamically determining a rheology of a picoliter-scale sample, in accordance with an embodiment of the present disclosure. The computing unit 120 may also function as a computer-implemented system. The computing unit 120 includes the one or more hardware processors 112, the memory 114, and a storage unit 204. The one or more hardware processors 112, the memory 114, and the storage unit 204 are communicatively coupled through a system bus 202 or any similar mechanism. The memory 114 comprises a plurality of modules 116 in the form of programmable instructions executable by the one or more hardware processors 112.
In an embodiment, the plurality of modules 116 may include an image receiving module 206, an oscillation and shape pattern analysing module 208, an oscillation and shape pattern difference determining module 210, an amplitude measuring module 212, a viscosity and viscoelasticity determining module 214, and an information outputting module 216.
The one or more hardware processors 112, as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor unit, microcontroller, complex instruction set computing exceptionally long processor unit, reduced instruction set computing microprocessor unit, very long instruction word microprocessor unit, explicitly parallel instruction computing microprocessor unit, graphics processing unit, digital signal processing unit, or any other type of processing circuit. The one or more hardware processors 112 may also include embedded controllers, such as generic or programmable logic devices or arrays, application-specific integrated circuits, single-chip computers, and the like.
The memory 114 may be a non-transitory volatile memory and a non-volatile memory. The memory 114 may be coupled to communicate with the one or more hardware processors 112, such as being a computer-readable storage medium. The one or more hardware processors 112 may execute machine-readable instructions and/or source code stored in the memory 114. A variety of machine-readable instructions may be stored in and accessed from the memory 114. The memory 114 may include any suitable elements for storing data and machine-readable instructions, such as read-only memory, random access memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like. In the present embodiment, the memory 114 includes the plurality of modules 116 stored in the form of machine-readable instructions on any of the above-mentioned storage media and may be in communication with and executed by the one or more hardware processors 112.
The storage unit 204 may be a cloud storage or a repository. The storage unit 204 may store, but is not limited to, viscosity data, viscoelasticity data, rheology data, pattern data, any other data, and combinations thereof.
In an embodiment, the image receiving module 206 may receive from the image capturing device 110, the captured plurality of images including one or more oscillations in the air-fluid interface. Further, the oscillation and shape pattern analysing module 208 may analyse at least one of an oscillation pattern of the fluid and a shape pattern of a cell associated with the fluid, in each of the plurality of images. Consider, an original image from which certain features are to be detected. The image may be cropped to focus on a specific region of interest, possibly to remove unnecessary portions and isolate the important part for analysis. The cropped image is converted into a binary (black and white) image. This thresholding process turns pixels either completely white or black, depending on their intensity values. Further, a closing operation is a morphological operation that involves dilating (expanding) the white areas and then eroding (shrinking) them back. This process helps to remove small black regions (noise) and fill small holes, thereby making the white regions more solid and easier to process. Further, the oscillation and shape pattern analysing module 208 may identify mid-points in the detected white regions. The mid-point detection typically refers to finding the central axis or centre of mass of the white region after noise has been removed.
Further, the oscillation and shape pattern difference determining module 210 may determine a difference in at least one of the oscillation patterns and the shape pattern between each of the plurality of images. Furthermore, the amplitude measuring module 212 may measure an amplitude of the one or more oscillations of the air-fluid interface, based on determining the difference in at least one of the oscillation patterns and the shape pattern between each of the plurality of images. The amplitude of the one or more oscillations is inversely proportional to at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell. Further, the amplitude of the one or more oscillations is dampened, if at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell is higher. Further, the viscosity and viscoelasticity determining module 214 may determine at least one of a viscosity associated with the fluid and a viscoelasticity associated with the cell, based on measuring the amplitude of the one or more oscillations of the air-fluid interface. For example, the viscosity and viscoelasticity determining module 214 may generate a graph of ALI length vs viscosity of glycerol water mixture as a calibration curve to measure the viscosity of a new liquid. A point may be marked in the graph and the x-axis corresponding to that interface length may indicate the viscosity of the liquid. Furthermore, the information outputting module 216 may output on an electronic display 118 associated with an electronic device, at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell.
FIG. 3 illustrates an exemplary schematic diagram representation of an exemplary setup of a microfluidic system 100, in an accordance with an embodiment of the present disclosure. According to FIG. 3, the microfluidic system 100 includes, the microfluidic chip 102, configured to perpendicularly receive, in picoliter-scale a fluid from a syringe pump 302 through a tubing associated with a syringe 306. Further, the microfluidic chip 102 receives air from an air pumping syringe 304 for creating an air-fluid interface. The fluid includes, but not limited to, at least one of a liquid, a liquid with a cell, a biological fluid, a viscous fluid, and the like.
Further, the microfluidic system 100 includes, the signal generator 104 configured to generate one or more electrical excitation signals in one or more pre-defined frequencies. Further, the microfluidic system 100 includes the power amplifier 106 communicatively coupled to the signal generator 104, configured to amplify the electrical excitation signal received from the signal generator 104.
Further, the microfluidic system 100 includes the piezo-electric transducer 108 coupled to the microfluidic chip 102 in proximity to the air-liquid. The piezo-electric transducer 108 may be configured to receive the amplified electrical excitation signal from the power amplifier 106, and generate acoustic waves for propagating through the fluid, based on receiving the amplified electrical excitation signal from the power amplifier 106. The air-fluid interface oscillates in the one or more pre-defined frequencies due to a substantial difference in an acoustic impedance between the air-fluid interface.
In accordance with an embodiment, the microfluidic system 100 includes the image capturing device 110 configured to capture a plurality of images including one or more oscillations in the air-fluid interface.
In accordance with an embodiment, the microfluidic system 100 includes the processor 112, and the memory 114 coupled to the processor112. The memory 114 includes processor-executable instructions, which on execution, cause the processor 112 to receive, from the image capturing device 110, the captured plurality of images including one or more oscillations in the air-fluid interface. Further, the processor 112 is configured to analyse at least one of an oscillation pattern of the fluid and a shape pattern of a cell associated with the fluid, in each of the plurality of images. Further, the processor 112 determines a difference in at least one of the oscillation patterns and the shape pattern between each of the plurality of images. Furthermore, the processor 112 is configured to measure an amplitude of the one or more oscillations of the air-fluid interface, based on determining the difference in at least one of the oscillation patterns and the shape pattern between each of the plurality of images. Further, the processor 112 determines at least one of a viscosity associated with the fluid and a viscoelasticity associated with the cell, based on measuring the amplitude of the one or more oscillations of the air-fluid interface. Furthermore, the processor 112 outputs on a display 118 associated with an electronic device, at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell.
The microfluidic system 100 may enable measurement of properties of biological fluids such as cells, saliva, urine, cerebrospinal fluid, synovial fluid, and the like. The microfluidic system 100 may improve the detection and study of diseases such as, but not limited to, diabetes, cancer, meningitis, arthritis, and the like, by using the viscosity of biological fluids as a biomarker. Further, the microfluidic system 100 enables single-cell studies to study cancer metastasis. Furthermore, the microfluidic system 100 includes dynamic viscosity sensor based on a microfluidic platform, and utilizes an oscillation of an air-liquid interface for viscosity determination. The microfluidic system 100 includes localized liquid viscosity sensing within picoliter volumes in the channel and improve the sensitivity of the proposed viscometer. Further, the microfluidic system 100 includes a method to determine cell dynamic viscoelasticity using an oscillating air-liquid interface.
Furthermore, the microfluidic system 100 performs dynamic viscoelasticity measurement of a single cell using an oscillating air-liquid interface. Application of air-liquid interface oscillations for dynamic viscosity sensing. While oscillating microbubbles are well used, these techniques oscillate the microbubble in an infinite or semi-infinite liquid medium, thus increasing the sample volume. The channel in the microfluidic chip 102 allows to reduce the sample volume to picolitres and enables precise positioning of the sample in the channel. Further, the microfluidic system 100 uses microstreaming forces to perform single cell analysis.
FIG. 4 illustrates an exemplary schematic diagram representation of an air-liquid interface 402 in the microfluidic chip 102 of the microfluidic system 100, in accordance with an embodiment of the present disclosure. According to FIG. 4, the air-fluid interface 402 may be created in the microfluidic chip 102 including the pre-defined shaped channel configured to perpendicularly receive, in a picoliter-scale, a fluid and an air. Further, the microfluidic chip 102 may receive acoustic waves generated by the piezoelectric transducer 108, the air-liquid interface 402 on receiving the acoustic waves from the piezoelectric transducer 108, may start producing oscillations. An amplitude of an oscillations produced may decide rheological aspects of a liquid at the air-liquid interface 402. More the amplitude of an oscillation less is the viscosity and vice versa.
FIG. 5 illustrates an exemplary schematic diagram representation of the air-liquid interface 402 in the microfluidic chip 102 and an expanded view of a dynamic cell , in accordance with an embodiment of the present disclosure. In an embodiment, the microfluidic chip 102 is capable of receiving one or more liquids such as, for example, but not limited to, blood, urine, saliva, cerebrospinal fluid and synovial fluid. The microfluidic system 100 may be used for cell dynamic viscoelasticity measurement and may be extended to single cell examination. According to FIG. 5, the cell may be in normal and non-deformed condition. A picoliter-scale sample may be received by the microfluidic chip 102. Further, the acoustic waves produced by the piezoelectric transducer 108 may oscillate the air-liquid interface 402 resulting in deformation of the single cell of the picoliter-scale sample. An amplitude of the air-liquid interface is measured to determine a dynamic viscoelasticity of the single in a microfluidic system 100. In an embodiment, the microfluidic system 100 provides control over the positioning of the sample volume and may be used for single-cell analysis, thus extending the scope of microfluidic system 100 to single-cell analysis.
FIG. 6 illustrates an exemplary schematic diagram representation of the air-liquid interface 402 in the microfluidic chip 102 and an expanded view of a dynamic cell deformation, in accordance with another embodiment of the present disclosure. According to FIG. 6, deformation of a single cell with a change in the position of air-liquid interface 402 extends the scope of the microfluidic system 100 to the single cell analysis.
FIG. 7A illustrates an exemplary schematic diagram representation of oscillations in the Air-Liquid Interface (ALI) 302 captured using image capturing device 110 such as for example, one or more high speed cameras, in an accordance with an embodiment of the present disclosure. The microfluidic system 100 may be configured to measure the rheologic characteristics of the sample at plurality of frequencies produced by the piezo electric transducer 108. For example, a high-speed camera may capture the oscillations (ripples or vibrations) of the Air-Liquid Interface (ALI) 302. The ALI 302 may be the boundary where a liquid meets air. The oscillations may be recorded, and the length of the interface may be calculated at different positions during the oscillation. The amplitude of oscillations varies across different frequencies, indicating the presence of multiple resonant peaks.
FIG. 7B illustrates an exemplary schematic diagram representation of process of calculating length of Air-Liquid Interface (ALI) , in an accordance with an embodiment of the present disclosure. The processor 112 may select a region of interest from an original image. Further, the processor 112 may convert (i.e., thresholding)the cropped image into a black-and-white (binary) image. Furthermore, the processor 112 may invert the colours (black becomes white and vice versa) and apply a closing operation to remove noise and smooth the image. Additionally, the processor 112 may detect the mid-points of the cleaned-up white regions in the processed image. Using the coordinates of the mid-points, the processor 112 may calculate a length of the curve. This gives the length of the air-liquid interface. When the detected mid-point is discontinuous, i.e., the points have shifted to right or left, those points are ignored while calculating the length of the curve.
FIG. 8 illustrates an exemplary schematic diagram representation of a working principle of a microfluidic system 100 for dynamically determining a rheology of a picoliter-scale sample, in accordance with an embodiment of the present disclosure. In accordance with an embodiment, the microfluidic system 100 may include the piezo-electric transducer 108 coupled to the microfluidic chip 102 in proximity to the air-liquid interface, and communicatively coupled to the power amplifier 106. The piezo-electric transducer 108 may be configured to receive the amplified electrical excitation signal from the power amplifier 106, and generate acoustic waves for propagating through the fluid, based on receiving the amplified electrical excitation signal from the power amplifier 106. The air-fluid interface 302 oscillates in the one or more pre-defined frequencies due to a substantial difference in an acoustic impedance between the air-fluid interface 302. A high acoustic impedance mismatch at the air-liquid interface 302 may cause a large motion at the air-liquid interface 302. The rheologic characteristics of the liquid are measured by amplitude of the air-liquid interface 302. The viscosity of one or more liquids is inversely proportional to the oscillations produced at the air-liquid interface 302.
For example, the acoustic waves generated by the piezoelectric transducer transmits to the fluids through the glass substrate. A high acoustic impedance mismatch at the interface causes a large ALI motion. Liquid viscosity dampens the oscillation; thus, the oscillation amplitude should decrease with increased viscosity. In another example, consider a pressure port, which may be opening where the fluid enters a sensor. Further, a diaphragm may be a thin, flexible membrane that separates the pressure port from the cavity containing the transducer 108. As the fluid pressure increases, the diaphragm deflects upwards. Further, a cavity may be an enclosed space contains the transducer 108 that converts the physical movement of the diaphragm into an electrical signal. Transducer 108 may be a piezoelectric transducer, which converts pressure-induced movements of the diaphragm into a corresponding electrical voltage. Other types of transducers 108 may also be used depending on the specific design. The insulated passage allows electrical wires to connect to the transducer while maintaining a fluid-tight seal between the pressure port and the cavity. Further, one or more electrical pins may function as connection points for the electrical wires that carry the signal from the transducer 108. The microfluidic system 100 may deal with manipulating and analysing very small volumes of fluids.
FIG. 9 illustrates an exemplary schematic diagram representation of working principle of a microfluidic system 100 for determining cell oscillations, in accordance with another embodiment of the present disclosure. The microfluidic system 100 may be configured to determine the viscoelasticity of one or more cells. The ALI 302 may oscillate and drive cell oscillation.
FIG. 10 illustrates an exemplary graphical representation of a graph 1000 for a measurement of amplitude vs. viscosity of a liquid, in an accordance with an embodiment of the present disclosure. The graph 1000 may illustrate the variation of oscillation amplitude with viscosity at for example, 12kHz. The amplitude of oscillations shows an inverse correlation with viscosity at a given frequency, proving that the technique can be used for viscosity sensing. The air-liquid interface 302 may be oscillated with plurality of frequencies produced by the transducer 108. Higher is an amplitude of the oscillation, lower is the viscosity and vice versa. Further, the higher deformation in the air-liquid interface is inversely proportional to the viscosity of one or more liquids.
FIG. 11 illustrates an exemplary graphical representation of a graph 1100 for a measurement of amplitude of oscillations varying across different frequencies, in an accordance with an embodiment of the present disclosure. For example, deionized water may be flown through the microfluidic chip 102 to characterize respective frequency response. For example, the oscillations at various frequencies within the range of 0.5kHz to 21kHz, synchronized with transducer excitation. The oscillations may be recorded, and the length of the interface may be calculated at different positions during the oscillation. The amplitude of oscillations varies across different frequencies, indicating the presence of multiple resonant peaks. In another example, the peak at 12kHz may be considered for viscosity sensing due to its high amplitude. However, any of the peaks may be used for this purpose.
FIG. 12 illustrates an exemplary graphical representation of a graph 1200 for a position of cells over time, in an accordance with an embodiment of the present disclosure. The X-axis represents time, possibly in milliseconds (ms) or seconds (s) based on the range shown in the graph. The Y-axis represents the position of the cells, possibly in microns (µm) based on the scale. The graph 1200 provides a curve that appears to be sinusoidal (wave-like). This suggests a periodic oscillation in the position of the cells over time. The cells may be moving back and forth or vibrating.
FIG. 13 illustrates an exemplary graphical representation of a graph 1300 for an aspect ratio of cells over time, in an accordance with an embodiment of the present disclosure. The X-axis may represents time, and the Y-axis may represents the aspect ratio of the cells. The aspect ratio is a measure of a shape of a cell and may be calculated by dividing length of the cell by a width of the cell. For example, a value of 1 indicates a perfectly square cell, while values greater than 1 indicate an elongated cell and values less than 1 indicate a wider or squashed cell. The aspect ratio of the cells may be changing slightly over time, potentially in response to the position changes observed in graph 1200. The external forces or stimuli affect the position and shape of cells. The graphs 1200 and 1300 may depict how cells respond to mechanical stress or pressure by changing their position and aspect ratio.
For example, the microfluidic chip 102 may include materials, but not limited to, polymers (e.g., PDMS), silicon, glass, and the like. The choice of material depends on factors such as a desired chemical compatibility, temperature resistance, and optical properties. The system 100 may include a high speed camera or a Scanning Electron Microscope (SEM), which is a type of electron microscope that can generate high-resolution images of a sample by scanning it with a focused beam of electrons. The SEM provides detailed information about the surface morphology and topography of the sample.
In an example, the stress may be calculated using the drag forces experienced by a cell of Radius R. The stress may be calculated using an equation 1 shown below:
Stress,σ= 3μV/2R …….Equation 1

Strain may be calculated as shown in equation 2 below:
Strain,γ =(Major axis - Minor axis)/R……Equation 2
The constitutive equation of the Voigt model is shown in equations 3 below:
σ(t)= Eγ(t)+ η dγ(t)/dt….Equation 3

FIG.14 illustrates an exemplary flow diagram representation of a method 1400 for dynamically determining a rheology of a picoliter-scale sample, in accordance with an embodiment of the present disclosure.
At step 1402, the method 1400 includes receiving, by the processor 112 associated with the microfluidic system 100, from the image capturing device 110, a captured plurality of images including one or more oscillations in an air-fluid interface. The air-fluid interface is created on the microfluidic chip 102 including a pre-defined shaped channel configured to perpendicularly receive, in a picoliter-scale, a fluid and an air. The fluid may include, but not limited to, a liquid with a cell, a biological fluid, a viscous fluid, and the like. The pre-defined shaped channel may correspond, but not limited to, a T-junction microfluidic, and the like, channel configured to facilitate perpendicular flow of the fluid and the air.
At step 1404, the method 1400 includes analysing, by the processor 112, at least one of an oscillation pattern of the fluid and a shape pattern of a cell associated with the fluid, in each of the plurality of images. The air-fluid interface oscillates, via a piezo-electric transducer 108, in one or more pre-defined frequencies due to a substantial difference in an acoustic impedance between the air-fluid interface.
At step 1406, the method 1400 includes determining, by the processor 112, a difference in at least one of the oscillation pattern and the shape pattern between each of the plurality of images.
At step 1408, the method 1400 includes measuring, by the processor 112, an amplitude of the one or more oscillations of the air-fluid interface, based on determining the difference in at least one of the oscillation pattern and the shape pattern between each of the plurality of images. The amplitude of the one or more oscillations is inversely proportional to at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell. Further, the amplitude of the one or more oscillations is dampened, if at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell is higher.
At step 1410, the method 1400 includes determining, by the processor 112, at least one of a viscosity associated with the fluid and a viscoelasticity associated with the cell, based on measuring the amplitude of the one or more oscillations of the air-fluid interface.
At step 1412, the method 1400 includes output on a display 118 associated with an electronic device, at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell.
The order in which the method 1400 is described is not intended to be construed as a limitation, and any number of the described method blocks may be combined or otherwise performed in any order to implement the method 1400 or an alternate method. Additionally, individual blocks may be deleted from the method 1400 without departing from the scope of the ongoing description. Furthermore, the method 1400 may be implemented in any suitable hardware, software, firmware, or a combination thereof, that exists in the related art or that is later developed. The method 1400 describes, without limitation, the implementation of the computing unit 120 and/or microfluidic system 100. A person of skill in the art will understand that method 1400 may be modified appropriately for implementation in various manners without departing from the scope of the ongoing description.
Various embodiment of the present disclosure provides a microfluidic system and a method for dynamically determining a rheology of a picoliter-scale sample. The microfluidic system enables viscosity measurement using an oscillating air-liquid interface. This allows for highly localized sensing within incredibly small sample volumes (picolitres). The microfluidic system extends beyond simple viscosity measurement, in which the microfluidic system may also be used to measure the dynamic viscoelasticity of cells, allowing to be valuable for studying biological fluids and cellular properties. The ability to work with picolitre volumes enables the microfluidic system suitable for potential single-cell studies, allowing for analysis of individual cells. The microfluidic systems include an air-liquid interface oscillations for viscosity sensing. The microfluidic system overcomes challenges associated with traditional microfluidic viscosity sensors. By using an oscillating air-liquid interface, the microfluidic system achieves accurate measurements with significantly lower sample volumes compared to existing methods that rely on microbubbles.
The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope of the disclosed embodiments. Also, the words “comprising,” “having,” “containing,” and “including,” and other similar forms are intended to be equivalent in meaning and be open-ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the embodiments of the present invention are intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.
, Claims:CLAIMS
We claim:
1. A microfluidic system (100) for dynamically determining a rheology of a picoliter-scale sample, the microfluidic system (100) comprising:
a microfluidic chip (102) comprising a pre-defined shaped channel configured to perpendicularly receive, in a picoliter-scale, a fluid and an air for creating an air-fluid interface (302), wherein the fluid comprises at least one of a liquid, a liquid with a cell, a biological fluid, and a viscous fluid;
a signal generator (104) configured to generate one or more electrical excitation signals in one or more pre-defined frequencies;
a power amplifier (106) communicatively coupled to the signal generator (104), configured to amplify the electrical excitation signal received from the signal generator (104);
a piezo-electric transducer (108) coupled to the microfluidic chip (102) in proximity to the air-liquid interface (302), and communicatively coupled to the power amplifier (106), wherein the piezo-electric transducer (108) is configured to:
receive the amplified electrical excitation signal from the power amplifier (106); and
generate acoustic waves for propagating through the fluid, based on receiving the amplified electrical excitation signal from the power amplifier (106), wherein the air-fluid interface oscillates in the one or more pre-defined frequencies due to a substantial difference in an acoustic impedance between the air-fluid interface (302);
an image capturing device (110) configured to capture a plurality of images comprising one or more oscillations in the air-fluid interface (302); and
a processor (112), and a memory (114) coupled to the processor (112), wherein the memory (114) comprises processor-executable instructions, which on execution, cause the processor (112) to:
receive, from the image capturing device (110), the captured plurality of images comprising one or more oscillations in the air-fluid interface (302);
analyse at least one of an oscillation pattern of the fluid and a shape pattern of a cell associated with the fluid, in each of the plurality of images;
determine a difference in at least one of the oscillation pattern and the shape pattern between each of the plurality of images;
measure an amplitude of the one or more oscillations of the air-fluid interface (302), based on determining the difference in at least one of the oscillation pattern and the shape pattern between each of the plurality of images;
determine at least one of a viscosity associated with the fluid and a viscoelasticity associated with the cell, based on measuring the amplitude of the one or more oscillations of the air-fluid interface (302); and
output on a display (118) associated with an electronic device, at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell.

2. The microfluidic system (100) as claimed in claim 1, wherein the amplitude of the one or more oscillations is inversely proportional to at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell, wherein the amplitude of the one or more oscillations is dampened, if at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell is higher.

3. The microfluidic system (100) as claimed in claim 1, wherein the generated acoustic waves vibrate the cell in the fluid to change the shape pattern of the cell.

4. The microfluidic system (100) as claimed in claim 3, wherein the change in the shape pattern of the cell is determined to extract at least one of an elastic property and a viscous property of the cell.

5. The microfluidic system (100) as claimed in claim 1, wherein the pre-defined shaped channel corresponds to a T-junction microfluidic channel configured to facilitate perpendicular flow of the fluid and the air.

6. The microfluidic system (100) as claimed in claim 1, wherein the acoustic waves generated by the piezo-electric transducer (108) is propagated to the fluid through the microfluidic chip (102) comprising a glass substrate.

7. The microfluidic system (100) as claimed in claim 1, wherein the substantial difference in the acoustic impedance between the air and the fluid interface comprises a high acoustic impedance mismatch causing a large motion of the air-fluid interface (302).

8. A method for dynamically determining a rheology of a picoliter-scale sample, the method comprising:
receiving, by a processor (112) associated with a microfluidic system (100), from an image capturing device (110), a captured plurality of images comprising one or more oscillations in an air-fluid interface (302), wherein the air-fluid interface (302) is created on a microfluidic chip (102) comprising a pre-defined shaped channel configured to perpendicularly receive, in a picoliter-scale, a fluid and an air, wherein the fluid comprises at least one of a liquid, a liquid with a cell, a biological fluid, and a viscous fluid;
analyse at least one of an oscillation pattern of the fluid and a shape pattern of a cell associated with the fluid, in each of the plurality of images, wherein the air-fluid interface oscillates, via a piezo-electric transducer (108), in one or more pre-defined frequencies due to a substantial difference in an acoustic impedance between the air-fluid interface (302);
determine a difference in at least one of the oscillation pattern and the shape pattern between each of the plurality of images;
measure an amplitude of the one or more oscillations of the air-fluid interface (302), based on determining the difference in at least one of the oscillation pattern and the shape pattern between each of the plurality of images;
determine at least one of a viscosity associated with the fluid and a viscoelasticity associated with the cell, based on measuring the amplitude of the one or more oscillations of the air-fluid interface (302); and
output on a display (118) associated with an electronic device, at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell.

9. The method as claimed in claim 8, wherein the amplitude of the one or more oscillations is inversely proportional to at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell, wherein the amplitude of the one or more oscillations is dampened, if at least one of the viscosity associated with the fluid and the viscoelasticity associated with the cell is higher.

10. The method as claimed in claim 8, wherein the generated acoustic waves vibrate the cell in the fluid to change the shape pattern of the cell, wherein the change in the shape pattern of the cell is determined to extract at least one of an elastic property and a viscous property of the cell.