Abstract ：

The noise-shaping (NS) successive approximation register (SAR) analog-to-digital converter (ADC) is an innovative hybrid structure that offers performance advantages. The NS-SAR ADC leverages the SAR ADC as its foundation and combines oversampling technology and noise-shaping technology found in Sigma-Delta ADC. This integration effectively combines the strengths of both structures and enhances overall performance. The ADC features a simple circuit structure, compact chip area, and high energy efficiency, which has positioned it as a prominent research area. In this paper, leveraging the TSMC 65 nm GP process, the NS-SAR ADC is designed with a power supply voltage of 1 V. This design adopts an 8-bit differential capacitor structure, operates at a sampling frequency of 16 MS/s, and achieves an oversampling rate of 16 times the desired performance indicators. Through extensive circuit post simulation verification, the SNR obtained reaches 78 dB, providing an effective bit resolution of 12.7 bits. The core chip area of the ADC measures 366 x 333 mu m2, while the power consumption is impressively low at 417 mu W and FoMs is 168 dB.

Keyword ：

noise shaping noise shaping oversampling oversampling successive approximation type successive approximation type analog-to-digital converters analog-to-digital converters

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Abstract ：

Micro-droplet generation for solid particle suspensions is studied experimentally over a wide range of volume fraction of solid (q), using a home build pneumatic ejection system. Ejection is actuated by a solenoid valve, setting to "conduction" state for short period of time At. Pressurized gas of Po enters the reservoir, creating a pressure pulse P(t), forcing the liquid out via a tiny nozzle to produce a micro-droplet. Here, P(t) is measured by a high-speed sensor, and the ejection process is examined by high speed photography and image processing. Single droplet can be ejected for suspensions with 11 up to 33%. For q less than about 18%, the required pressure amplitude increases roughly linearly with 'i" With 'I increased above 18%, the demand for pressure amplitude is significantly higher than the linearly increasing trend. Especially as q is increased above 24u/0, the liquid band stretches much longer, and the break-up is delayed drastically.

Keyword ：

micro-droplet micro-droplet particulate suspension particulate suspension pneumatic pneumatic

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Abstract ：

Electric field-assisted fused deposition modeling (E-FDM) is a promising technique in the field of 3D printing. This paper studies the start-up stage of the printing, which is a process of liquid gradually deforming and making an initial contact with the substrate under the action of electric stress. Polycaprolactone, a popular material for biomedicine, is selected as the printing material. With a home-built E-FDM system, the nozzle-to-substrate distance and the nozzle and substrate temperatures are all held steady. With a photography system, the process of meniscus deformation is recorded. And by image processing methods, the meniscus length and the volume of liquid at the nozzle can be obtained. At a set of initial liquid volumes (Vi), nozzle voltage is ramped to a fixed value at a fixed rate. The effects ofVion the meniscus deformation during the start-up stage of the printing are examined. For sufficiently smallVi, the meniscus deforms into a conical (Taylor cone) shape, and a fine jet with a diameter much smaller than the nozzle diameter appears. For sufficiently largeVi, the meniscus exhibits a spindle shape when it touches the substrate. At an intermediateVi, a Taylor cone is formed, tending to eject a fine jet. After a short period of stagnation or even a slight retraction, no liquid is emitted. Through this study, it is suggested that for high-resolution printing, ramping the voltage at smallVimay be preferable. This proposition is preliminarily confirmed in a direct writing test. © The Royal Society of Chemistry 2021.

Keyword ：

Fused Deposition Modeling Fused Deposition Modeling Deformation Deformation Deposition Deposition Image processing Image processing Liquids Liquids Nozzles Nozzles Electric fields Electric fields

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Abstract ：

Micro-droplet generation is related to liquid dispensing technology that has potential applications in many fields. Specifically, pneumatic micro-droplet generation is controlled by a solenoid valve being briefly turned on, so that high pressure gas enters the liquid reservoir, forming a gas pressure pulse waveform P(t), forcing the liquid out through a tiny nozzle to form a micro-droplet. For each ejection, P(t) is acquired by a high speed pressure sensor, and the ejection state is obtained by machine vision methods. A prediction model based on BP neural network is established, with P(t) as input and the droplet ejection state as output. Experiments show that the BP neural network can predict the number of droplets with an accuracy higher than 99%. It is also shown that the BP neural network can improve the prediction accuracy for the position of droplets relative to the nozzle, at a given moment. Under typical working conditions, P(t) is not consistent. As a result, the ejection state is not consistent either. These prediction models may be used for real time monitoring and control of the pneumatic micro-droplet generator.

Keyword ：

Pneumatic Pneumatic BP neural network BP neural network Ejection state Ejection state Micro-droplet Micro-droplet Machine vision Machine vision

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Abstract ：

Pneumatic micro-droplet ejection is a printing technique that has potential applications in many fields, especially in the field of bio-printing. The ejection is via a solenoid valve being briefly turned on, so that high pressure gas enters the liquid reservoir, forming a gas pressure pulse, forcing the liquid out through a tiny nozzle to form a micro-droplet. For bio-printing applications, the bio-inks are typically non-standard. The difficulties are not only that the initial working parameters are difficult to set, but also the working conditions change over time in many cases. In order to maintain a stable single-drop ejection state, a machine vision based ejection monitoring was designed to obtain the number, positions and sizes of the droplets for each ejection, and a feedback control is realized by adjusting the "ON" time of the solenoid valve or the gas pressure at the front end of the solenoid valve.

Keyword ：

Micro-droplet Micro-droplet Machine vision Machine vision Pneumatic Pneumatic Feedback control Feedback control

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Abstract ：

Sample deposition based on micro-droplet ejection (MDE) has broad application prospects in the field of biomedicine. As a potential technology option for cell printing, a hybrid pneumatic-electrohydrodynamic (HPEHD) MDE system is built in the laboratory. Strong electric field is established by applying a high voltage between the nozzle and a collector electrode. The pneumatic actuation is realized via a solenoid valve staying outside of the liquid chamber. The solenoid valve is set in conduction for a short period of time Delta t; gas of high pressure P-0 enters the liquid chamber, and produces a pressure pulse, which extrudes the liquid slightly out of the nozzle. The liquid is deformed further in the electric field into a cone shape (Taylor cone), and then the end of the Taylor cone breaks to form a micro-droplet. The ejection process is studied using machine-vision and image processing. With sodium alginate (1.0%) as bioink, single droplet per ejection is realized, and the droplet size is reduced by 50% due to the presence of the electric field. It is found that increasing the voltage has little effect on the size of droplets. In contrast, increasing source pressure P-0 or increasing Delta t the conduction time of the solenoid valve can change the volume of droplet in a wider range.

Keyword ：

electrohydrodynamic electrohydrodynamic pneumatic pneumatic on-demand on-demand micro-droplet micro-droplet

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Abstract ：

Sample deposition based on micro-droplet ejection has broad application prospects in the field of biomedicine. Ejection of RPMI-1640 culture medium (without cells) is investigated experimentally using a home-build electrohydrodynamic (EHD) ejection system, consisting of a liquid supplier and a nozzle, a voltage source, a droplet collector, and a supplemented photoelectric monitoring module. Electric voltage is applied between the nozzle and the droplet collector. The liquid surface is electrically charged and the ejection takes place when electric force overcomes the surface tension. At appropriate voltages, uniform ejection states are established with ejection frequency ranging from a few to a few tens of Hertz. Monitoring of the ejection process is performed by two methods. The ejection process can be recorded by a high speed camera, and then analysed by image processing. Using output signal of a charge amplifying circuit as a reference, a single shot camera is controlled to capture images at certain delays, anti the entire process of the droplet ejection can be recorded. Experiments have shown that when the liquid meniscus breaks up, the output signal of the charge amplifier reaches the maximum.

Keyword ：

charge-amplifier charge-amplifier electrohydrodynamic electrohydrodynamic micro-droplet micro-droplet single shot camera single shot camera

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Abstract ：

Sample deposition based on micro-droplet ejection has broad application prospects in the field of biomedicine. Ejection of RPMI-1640 medium (without and with cells) is investigated experimentally using a home-build electrohydrodynamic (EHD) ejection system, consisting of a liquid supplier and a nozzle, a high voltage source, a droplet collector, and a high speed photography module. Electric voltage is applied between the nozzle and the droplet collector. The liquid surface is charged and the ejection takes place when electric force overcomes the surface tension. The ejection process is studied by using high speed photography and image processing. At low voltage, a uniform ejection state is established with ejection frequency typically less than 50Hertz. At sufficiently high voltage, another uniform ejection state is reached with ejection frequency as high as 1300Hz. Human peripheral blood mononuclear cells, after ejection, show survival rates higher than 79%, manifesting EHD ejection as a promising technique for cell printing.

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Abstract ：

Sample deposition based on micro-droplet ejection has broad application prospects in the field of biomedicine. Ejection of RPMI-1640 medium (with and without cells) is investigated experimentally using a home-build electrohydrodynamic (EHD) ejection system, consisting of a liquid supplier and a nozzle, a high voltage source, a droplet collector, and a high speed photography module. High electric voltage is applied between the nozzle and the droplet collector. The liquid surface is electrically charged and the ejection takes place when electric force overcomes the surface tension. The ejection process is studied by using high speed photography and image processing. At low voltage, a stable ejection state is established with ejection frequency ranging from a few to a few tens of Hertz. At high voltage, another stable ejection state is reached with ejection frequency as high as 1300Hz. At the transition voltage range, the ejection exhibits a periodic behaviour. During each cycle, the meniscus rapidly oscillates with gradually increased amplitude, and with several non-uniform droplets ejected at the final stage of the cycle. Human peripheral blood mononuclear cells, after ejection, shows survival rates higher than 79%, manifesting EHD ejection as a promising technique for cell printing.

Keyword ：

High speed camera High speed camera Cell printing Cell printing Ejection frequency Ejection frequency Electrohydrodynamic Electrohydrodynamic

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Abstract ：

Pneumatic valve-controlled micro-droplet generation is a printing technique that has potential applications in many fields, especially in the field of biomedical printing. The droplet generation is controlled by a solenoid valve being briefly turned on, so that high pressure gas enters the liquid reservoir, forming a gas pressure pulse P(t), forcing the liquid out through a tiny nozzle to form a micro-droplet. Under the typical working conditions, P(t) is not consistent. Since P(t) is highly correlated with the micro-droplet ejection state, the inconsistency of P(t) results in fluctuation of ejection state. For each injection, the P(t) is acquired by a high speed pressure sensor, and the ejection state is obtained by machine vision processing. A machine learning method based on BP neural network is used to establish a prediction model with P(t) as the input and the droplet ejection state as the output. Experiments show that a BP neural network with only a single hidden layer and two neurons can accurately predict the number of droplets with an accuracy higher than 99%. Another experiment shows that a more complex double hidden layer BP neural network can improve the prediction accuracy for the position of droplets after a certain time delay. In summary, through pressure pulse P(t), the predictive model established by the machine learning method can effectively predict the micro-droplet ejection state. This technique may be used for real time monitoring and control of the pneumatic valve-controlled micro-droplet generator.

Keyword ：

valve-controlled valve-controlled BP neural network BP neural network micro-droplet micro-droplet pneumatic pneumatic

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