scholarly journals A Sparse Representation Classification Approach for Near Real-Time, Physics-Based Functional Monitoring of Aerosol Jet-Fabricated Electronics

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
Darshana L. Weerawarne ◽  
M. Samie Tootooni ◽  
Prahalada K. Rao ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Real Time ◽  
Functional Properties ◽  
Printed Electronics ◽  
Imaging System ◽  
Monitoring And Control ◽  
Wide Range ◽  
Sparse Representation Classification ◽  
Aerosol Jet Printing

Abstract Aerosol jet printing (AJP) is a direct-write additive manufacturing (AM) method, emerging as the process of choice for the fabrication of a broad spectrum of electronics, such as sensors, transistors, and optoelectronic devices. However, AJP is a highly complex process, prone to intrinsic gradual drifts. Consequently, real-time process monitoring and control in AJP is a bourgeoning need. The goal of this work is to establish an integrated, smart platform for in situ and real-time monitoring of the functional properties of AJ-printed electronics. In pursuit of this goal, the objective is to forward a multiple-input, single-output (MISO) intelligent learning model—based on sparse representation classification (SRC)—to estimate the functional properties (e.g., resistance) in situ as well as in real-time. The aim is to classify the resistance of printed electronic traces (lines) as a function of AJP process parameters and the trace morphology characteristics (e.g., line width, thickness, and cross-sectional area (CSA)). To realize this objective, line morphology is captured using a series of images, acquired: (i) in situ via an integrated high-resolution imaging system and (ii) in real-time via the AJP standard process monitor camera. Utilizing image processing algorithms developed in-house, a wide range of 2D and 3D morphology features are extracted, constituting the primary source of data for the training, validation, and testing of the SRC model. The four-point probe method (also known as Kelvin sensing) is used to measure the resistance of the deposited traces and as a result, to define a priori class labels. The results of this study exhibited that using the presented approach, the resistance (and potentially, other functional properties) of printed electronics can be estimated both in situ and in real-time with an accuracy of ≥ 90%.

In Situ Functional Monitoring of Aerosol Jet-Printed Electronic Devices Using a Combined Sparse Representation-Based Classification (SRC) Approach

2018 ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
Darshana L. Weerawarne ◽  
M. Samie Tootooni ◽  
Prahalada K. Rao ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Functional Properties ◽  
Process Parameters ◽  
Flow Rate ◽  
Gas Flow ◽  
Electronic Devices ◽  
In Situ Monitoring ◽  
Gas Flow Rate ◽  
Aerosol Jet Printing

The goal of this work is in situ monitoring of the functional properties of aerosol jet-printed electronic devices. In pursuit of this goal, the objective is to develop a multiple-input, single-output (MISO) machine learning model to estimate the device functional properties in a near real-time fashion as a function of process parameters as well as 2D/3D features of line morphology. The aim is to use the MISO model for in situ estimation and thus, monitoring of line/device resistance in aerosol jet printing (AJP) process. To realize this objective, silver nanoparticle structures are printed by varying three process parameters: (i) sheath gas flow rate (ShGFR), (ii) exhaust gas flow rate (EGFR), and (iii) print speed (PS). Subsequently, line morphology is captured in situ using a high-resolution charge-coupled device (CCD) camera, mounted coaxial to the nozzle. Besides, utilizing 2D/3D quantifiers (introduced in the authors’ previous publications), the line morphology is further quantified, and the extracted features (e.g., line width, overspray, cross-sectional area, etc.) are fed as inputs to a novel sparse representation-based classification (SRC) model. The four-point probe method is used for measurement of resistance, and definition of a priori classification labels. The outcome of this research paves the way for future control of device functional properties in AJP process.

Real-time monitoring and control of CHO cell apoptosis by in situ multifrequency scanning dielectric spectroscopy

2019 ◽  
Vol 80 ◽  
pp. 138-145 ◽  
Author(s):  
Fuduo Ma ◽  
An Zhang ◽  
David Chang ◽  
Orlin D. Velev ◽  
Kelly Wiltberger ◽  
...  
Keyword(s):  
Real Time ◽  
Dielectric Spectroscopy ◽  
Cell Apoptosis ◽  
Monitoring And Control ◽  
Real Time Monitoring ◽  
Cho Cell ◽  
And Control

Dynamic digital image analysis: emerging technology for particle characterization

2004 ◽  
Vol 50 (12) ◽  
pp. 19-26 ◽  
Author(s):  
G. Rabinski ◽  
D. Thomas
Keyword(s):  
Real Time ◽  
Digital Image Analysis ◽  
Visual Analysis ◽  
Dynamic Imaging ◽  
Operating Conditions ◽  
Particle Sizes ◽  
Particle Characterization ◽  
Imaging Analysis ◽  
Wide Range

The feasibility of applying dynamic imaging analysis technology to particle characterization has been evaluated for application in the water sector. A system has been developed which captures in-situ images of suspended particles in a flowing sample stream and analyzes these images in real time to determine particle size and concentration. The technology can measure samples having a wide range of particle sizes (∼1.5 to 1,000 μm equivalent circular diameter) and concentrations (<1 to >1 million/ml). The system also provides magnified images of particles for visual analysis of properties such as size, shape and grayscale level. There are no sample preparation requirements and statistically accurate results are produced in less than three minutes per sample. The overall system architecture is described. The major design challenges in developing a practical system include obtaining adequate contrast for the range of particle materials found in typical water samples and achieving this under operating conditions permitting an adequate sample processing rate for real time feedback of results. Performance of the instrument is reported in reference to industry accepted particle standards and applications as an analytical tool for the water industries are considered.

A Computational Fluid Dynamics Investigation of Pneumatic Atomization, Aerosol Transport, and Deposition in Aerosol Jet Printing Process

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
Darshana L. Weerawarne ◽  
Prahalada Rao ◽  
Mark D. Poliks
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
In Situ Monitoring ◽  
Cfd Model ◽  
Monitoring And Control ◽  
Aerosol Transport ◽  
Jet Printing ◽  
And Control ◽  
Aerosol Jet Printing

Abstract Aerosol jet printing (AJP) is a direct-write additive manufacturing technique, which has emerged as a high-resolution method for the fabrication of a broad spectrum of electronic devices. Despite the advantages and critical applications of AJP in the printed-electronics industry, AJP process is intrinsically unstable, complex, and prone to unexpected gradual drifts, which adversely affect the morphology and consequently the functional performance of a printed electronic device. Therefore, in situ process monitoring and control in AJP is an inevitable need. In this respect, in addition to experimental characterization of the AJP process, physical models would be required to explain the underlying aerodynamic phenomena in AJP. The goal of this research work is to establish a physics-based computational platform for prediction of aerosol flow regimes and ultimately, physics-driven control of the AJP process. In pursuit of this goal, the objective is to forward a three-dimensional (3D) compressible, turbulent, multiphase computational fluid dynamics (CFD) model to investigate the aerodynamics behind: (i) aerosol generation, (ii) aerosol transport, and (iii) aerosol deposition on a moving free surface in the AJP process. The complex geometries of the deposition head as well as the pneumatic atomizer were modeled in the ansys-fluent environment, based on patented designs in addition to accurate measurements, obtained from 3D X-ray micro-computed tomography (μ-CT) imaging. The entire volume of the constructed geometries was subsequently meshed using a mixture of smooth and soft quadrilateral elements, with consideration of layers of inflation to obtain an accurate solution near the walls. A combined approach, based on the density-based and pressure-based Navier–Stokes formation, was adopted to obtain steady-state solutions and to bring the conservation imbalances below a specified linearization tolerance (i.e., 10−6). Turbulence was modeled using the realizable k-ε viscous model with scalable wall functions. A coupled two-phase flow model was, in addition, set up to track a large number of injected particles. The boundary conditions of the CFD model were defined based on experimental sensor data, recorded from the AJP control system. The accuracy of the model was validated using a factorial experiment, composed of AJ-deposition of a silver nanoparticle ink on a polyimide substrate. The outcomes of this study pave the way for the implementation of physics-driven in situ monitoring and control of AJP.

A State-of-the-Art Review on Aerosol Jet Printing (AJP) Additive Manufacturing Process

2019 ◽  
Author(s):  
Roozbeh Ross Salary ◽  
Jack P. Lombardi ◽  
Darshana L. Weerawarne ◽  
Prahalad K. Rao ◽  
Mark D. Poliks
Keyword(s):  
Additive Manufacturing ◽  
Flexible Electronics ◽  
Manufacturing Process ◽  
Device Fabrication ◽  
Synthesis Process ◽  
Monitoring And Control ◽  
Loop Control ◽  
Wide Range ◽  
Jet Printing ◽  
Aerosol Jet Printing

Abstract The goal of this work is to forward a comprehensive framework, relating to the most recent research works carried out in the area of flexible and hybrid electronics (FHE) fabrication with the aid of aerosol jet printing (AJP) additive manufacturing process. In pursuit of this goal, the objective is to review and classify a wide range of articles, published recently, concerning various aspects of AJP-based device fabrication, such as material synthesis, process monitoring, and control. AJP has recently emerged as the technique of choice for integration as well as fabrication of a broad spectrum of electronic components and devices, e.g., interconnects, sensors, transistors, optical waveguides, quantum dot arrays, photodetectors, and circuits. This is preeminently because of advantages engendered by AJP process. AJP not only allows for high-resolution deposition of microstructures, but also accommodates a wide renege of ink viscosity. However, AJP is intrinsically complex and prone to gradual drifts of the process output (stemming from ink chemistry and formulation). Consequently, a large number of research works in the literature has focused on in situ process characterization, real-time monitoring, and closed-loop control with the aim to make AJP a rapid, reliable, and robust additive manufacturing method for the manufacture of flexible and hybrid electronic devices. It is expected that the market for flexible electronics will be worth over $50 billion by 2020 [1].

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