The effects of physical morphologies and strain rate on piezoelectric potential of boron nitride nanotubes: a molecular dynamics simulation.

The growing demand for self-powered systems and the slow progress in energy storage devices have led to the emergence of piezoelectric materials as a promising solution for energy harvesting. This study aims to investigate the effects of chirality, length, and strain rate on the piezoelectric potential of boron nitride nanotubes (BNNTs) through molecular dynamics simulation. Accurate data and guidance are provided to explain the piezoelectricity of chiral nanotubes, as the piezoelectric potentials of these nanotubes have previously remained unclear. The present study focuses on calculating the effect of these parameters based on the atomic model. The observed results stem from the frequencies and internal deformations, as the axial frequencies and deformations exhibit more substantial modifications compared to transverse directions. The piezoelectricity was found to depend on chirality, with the order of BNNT piezoelectricity sufficiency being in the sequence of zigzag > chirality > armchair configurations. The length of the BNNTs was also found to influence piezoelectricity, while the strain rate had no effect. The results also indicate that BNNTs can generate power in the milliwatts range, which is adequate for low-power electronic devices and Internet of Things applications. This research provides valuable insights into the piezoelectricity of chiral nanotubes and offers guidance for designing efficient energy harvesting devices.

Energy harvesting from mechanical vibrations: self-rectification effect.

The use of environmental vibrations as an energy source for stimulating small-scale energy harvesting (EH) devices has received significant attention in recent years. The conversion of alternating currents (AC) to direct currents (DC) is essential to powering electronic devices effectively. This study proposes a method where hexagonal boron nitride nanoribbons and nanotubes harvest energy and rectify the output voltage simultaneously with no need for an external rectifying circuit. This is a step to eliminate the necessity of batteries for EH devices, which require a constant power supply to generate electrical energy while maintaining their nanoscale dimensions. A molecular dynamics approach was used to simulate the response of boron nitride structures to mechanical vibrations. The polarization and voltage generated under tensile and compressing strain fields were calculated, and it was demonstrated that the buckling of the nano-mechanical structures could be engineered to rectify the generated voltage. This paves the way for the design of more efficient and scalable energy harvesting devices.

On-chip dielectrophoretic device for cancer cell manipulation: A numerical and artificial neural network study.

Breast cancer, as one of the most frequent types of cancer in women, imposes large financial and human losses annually. MCF-7, a well-known cell line isolated from the breast tissue of cancer patients, is usually used in breast cancer research. Microfluidics is a newly established technique that provides many benefits, such as sample volume reduction, high-resolution operations, and multiple parallel analyses for various cell studies. This numerical study presents a novel microfluidic chip for the separation of MCF-7 cells from other blood cells, considering the effect of dielectrophoretic force. An artificial neural network, a novel tool for pattern recognition and data prediction, is implemented in this research. To prevent hyperthermia in cells, the temperature should not exceed 35 °C. In the first part, the effect of flow rate and applied voltage on the separation time, focusing efficiency, and maximum temperature of the field is investigated. The results denote that the separation time is affected by both the input parameters inversely, whereas the two remaining parameters increase with the input voltage and decrease with the sheath flow rate. A maximum focusing efficiency of 81% is achieved with a purity of 100% for a flow rate of 0.2 µ L / min and a voltage of 3.1 V . In the second part, an artificial neural network model is established to predict the maximum temperature inside the separation microchannel with a relative error of less than 3% for a wide range of input parameters. Therefore, the suggested label-free lab-on-a-chip device separates the target cells with high-throughput and low voltages.

Lower reactive oxygen species production and faster swimming speed of human sperm cells on nanodiamond spin-coated glass substrates.

The sperm selection stage is what assisted reproductive technologies have in common and is crucial as it affects the success of the treatment cycle. The employment of microfluidic platforms for sperm selection has emerged showing promising results. In microfluidic platforms, sperm cells encounter micro-confined environments meanwhile having contact with channel walls and surfaces. Modification of contact surfaces using nanoparticles leads to the alteration of surface characteristics which in turn affects sperm behavior especially motility which is an indicator for sperm health. In this article, we present the results of investigating the motility parameters of sperm cells in contact with surface-modified glass substrates using nanodiamond particles. The results show that the sperm swimming velocities are significantly improved within the range of 12%-52% compared to the control surface (untreated). Reactive oxygen species production is also decreased by 14% justifying the increase in swimming speed. Taken together, bonding these modified surfaces to sperm selection microfluidic devices could enhance their efficiency and further improve their outcomes offering new solutions to patients facing infertility.

Rheotaxis-based sperm separation using a biomimicry microfluidic device.

Sperm selection is crucial to assisted reproduction, influencing the success rate of the treatment cycle and offspring health. However, in the current clinical sperm selection practices, bypassing almost all the natural selection barriers is a major concern. Here, we present a biomimicry microfluidic method, inspired by the anatomy of the female reproductive tract, that separates motile sperm based on their rheotaxis behavior to swim against the flow into low shear rate regions. The device includes micropocket geometries that recall the oval-shaped microstructures of the female fallopian tube to create shear protected zones for sperm separation. Clinical tests with human samples indicate that the device is capable of isolating viable and highly motile sperm based on their rheotaxis responses, resulting in a separation efficiency of 100%. The device presents an automated alternative for the current sperm selection practices in assisted reproduction.

3D numerical simulation of acoustophoretic motion induced by boundary-driven acoustic streaming in standing surface acoustic wave microfluidics.

Standing surface acoustic waves (SSAWs) have been widely utilized in microfluidic devices to manipulate various cells and micro/nano-objects. Despite widespread application, a time-/cost-efficient versatile 3D model that predicts particle behavior in such platforms is still lacking. Herein, a fully-coupled 3D numerical simulation of boundary-driven acoustic streaming in the acoustofluidic devices utilizing SSAWs has been conducted based on the limiting velocity finite element method. Through this efficient computational method, the underlying physical interplay from the electromechanical fields of the piezoelectric substrate to different acoustofluidic effects (acoustic radiation force and streaming-induced drag force), fluid-solid interactions, the 3D influence of novel on-chip configuration like tilted-angle SSAW (taSSAW) based devices, required boundary conditions, meshing technique, and demanding computational cost, are discussed. As an experimental validation, a taSSAW platform fabricated on YX 128 [Formula: see text] LiNbO3 substrate for separating polystyrene beads is simulated, which demonstrates acceptable agreement with reported experimental observations. Subsequently, as an application of the presented 3D model, a novel sheathless taSSAW cell/particle separator is conceptualized and designed. The presented 3D fully-coupled model could be considered a powerful tool in further designing and optimizing SSAW microfluidics due to the more time-/cost-efficient performance than precedented 3D models, the capability to model complex on-chip configurations, and overcome shortcomings and limitations of 2D simulations.

Numerical simulation of critical particle size in asymmetrical deterministic lateral displacement.

Microfluidics devices are widely used for particle separation. Deterministic Lateral Displacement (DLD) is a passive method for particle separation. DLD devices mainly separate particles based on their sizes. There are two main modes of movement in DLD arrays; the small particles move in a zigzag path, and the larger particles separate in the displacement mode. It is therefore important to estimate the critical particle size for the transition of modes before the fabrication of DLD devices. Asymmetry in the design of the arrays can affect the fluid behavior and the critical particle size. In this study, we investigate the effects of the asymmetry caused by changing the downstream gap size to the lateral gap size ratio on the fluid behavior and particle trajectories in DLD devices. We used two dimensional (2D) Finite Element Method (FEM) to study the variations in the flow lane's widths and combined the fluid analysis with structural mechanics to model the contact between the particles and the posts in DLD arrays. We simulated the spherical particles' trajectories with diameters ranging from 1.4 to 19.2 µm in circular post DLD arrays with a lateral gap size of 20µm. In contrast to the previous works, in these simulations, the effect of particle movement on the fluid flow profiles was considered. We evaluated the particle movement mode in seven different values of the downstream gap size to the lateral gap size ratio (ranging from 0.5 to 2) and eight different row shift fraction (ranging from 0.025 to 0.3). Our simulations showed that increasing the value of the downstream gap while the lateral gap is fixed increases the veering flow rate and width. By finding the particle with the largest diameter in the zigzag mode and the particle with the smallest diameter in the displacement mode, we estimated the critical particle diameter for each value of shift fraction in different values of the downstream gap to the lateral gap size ratio. Using these data, a curve was fitted for predicting the critical particle diameter in each ratio. Finally, a more general form of the formula for the critical particle diameter was proposed, which considers an extra parameter compared to the previous ones. The results of this study can lead to a better understanding of DLD devices' functions and, thus, save time and costs for better designs and experiments.

Cell properties assessment using optimized dielectrophoresis-based cell stretching and lumped mechanical modeling.

Cells mechanical property assessment has been a promising label-free method for cell differentiation. Several methods have been proposed for single-cell mechanical properties analysis. Dielectrophoresis (DEP) is one method used for single-cell mechanical property assessment, cell separation, and sorting. DEP method has overcome weaknesses of other techniques, including compatibility with microfluidics, high throughput assessment, and high accuracy. However, due to the lack of a general and explicit model for this method, it has not been known as an ideal cell mechanical property evaluation method. Here we present an explicit model using the most general electromagnetic equation (Maxwell Stress Tensor) for single-cell mechanical evaluation based on the DEP method. For proof of concept, we used the proposed model for differentiation between three different types of cells, namely erythrocytes, peripheral blood mononuclear cells (PBMC), and an epithelial breast cancer cells line (T-47D). The results show that, by a lumped parameter that depends on cells' mechanical and electrical properties, the proposed model can successfully distinguish between the mentioned cell types that can be in a single blood sample. The proposed model would open up the chance to use a mechanical assessment method for cell searching in parallel with other methods.

Quantification of human sperm concentration using machine learning-based spectrophotometry.

Spectrophotometry is an indirect non-invasive and quantitative method for specifying materials with unknown contents based on absorption behavior. This paper presents the first application of artificial neural network in spectrophotometry for quantification of human sperm concentration. A well-trained full spectrum neural network (FSNN) model is developed by examining the absorption response of sperm samples from 41 human subjects to different light spectra (wavelength from 390 to 1100 nm). It is shown that this FSNN accurately estimates sperm concentration based on the full absorption spectrum with over 93% prediction accuracy, and provides 100% agreement with clinical assessments in differentiating the samples of healthy donor from patient samples. We suggest the machine learning-based spectrophotometry approach with the trained FSNN model as a rapid, low-cost, and powerful technique to quantify sperm concentration. The performance of this technique is superior to available spectrophotometry methods currently used for semen analysis and will provide novel research and clinical opportunities for tackling male infertility.

Effect of input voltage frequency on the distribution of electrical stresses on the cell surface based on single-cell dielectrophoresis analysis.

Electroporation is defined as cell membrane permeabilization under the application of electric fields. The mechanism of hydrophilic pore formation is not yet well understood. When cells are exposed to electric fields, electrical stresses act on their surfaces. These electrical stresses play a crucial role in cell membrane structural changes, which lead to cell permeabilization. These electrical stresses depend on the dielectric properties of the cell, buffer solution, and the applied electric field characteristics. In the current study, the effect of electric field frequency on the electrical stresses distribution on the cell surface and cell deformation is numerically and experimentally investigated. As previous studies were mostly focused on the effect of electric fields on a group of cells, the present study focused on the behavior of a single cell exposed to an electric field. To accomplish this, the effect of cells on electrostatic potential distribution and electric field must be considered. To do this, Fast immersed interface method (IIM) was used to discretize the governing quasi-electrostatic equations. Numerical results confirmed the accuracy of fast IIM in satisfying the internal electrical boundary conditions on the cell surface. Finally, experimental results showed the effect of applied electric field on cell deformation at different frequencies.