Convergence of Machine Vision and Melt Electrowriting.

Melt electrowriting (MEW) is a high-resolution additive manufacturing technology that balances multiple parametric variables to arrive at a stable fabrication process. The better understanding of this balance is underscored here using high-resolution camera vision of jet stability profiles in different electrical fields. Complementing this visual information are fiber-diameter measurements obtained at precise points, allowing the correlation to electrified jet properties. Two process signatures-the jet angle and for the first time, the Taylor cone area-are monitored and analyzed with a machine vision system, while SEM imaging for diameter measurement correlates real-time information. This information, in turn, allows the detection and correction of fiber pulsing for accurate jet placement on the collector, and the in-process assessment of the fiber diameter. Improved process control is used to successfully fabricate collapsible MEW tubes; structures that require exceptional accuracy and printing stability. Using a precise winding angle of 60° and 300 layers, the resulting 12 mm-thick tubular structures have elastic snap-through instabilities associated with mechanical metamaterials. This study provides a detailed analysis of the fiber pulsing occurrence in MEW and highlights the importance of real-time monitoring of the Taylor cone volume to better understand, control, and predict printing instabilities.

Automated melt electrowritting platform with real-time process monitoring.

Melt electrowriting (MEW) is an additive manufacturing (AM) technology with the ability to fabricate complex designs with high-resolution. The utility of MEW is studied in many fields including tissue engineering and soft robotics. However, current MEW hardware offers only basic functionality and is often designed and built in-house. This affects results replication across different MEW devices and slows down the technological advancement. To address these issues, we present an automated MEW platform with real-time process parameter monitoring and control. We validate the developed platform by demonstrating the ability to accurately print polymer structures and successfully measure and adjust parameters during the printing process. The platform enables the collection of large volumes of data that can be subsequently used for further analysis of the system. Ultimately, the concept will help MEW to become more accessible for both research laboratories and industry and allow advancing the technology by leveraging the process monitoring, control and data collection.

A New Automated Histomorphometric MATLAB Algorithm for Immunohistochemistry Analysis Using Whole Slide Imaging.

The use of animal models along with the employment of advanced and sophisticated stereological methods for assessing bone quality combined with the use of statistical methods to evaluate the effectiveness of bone therapies has made it possible to investigate the pathways that regulate bone responses to medical devices. Image analysis of histomorphometric measurements remains a time-consuming task, as the image analysis software currently available does not allow for automated image segmentation. Such a feature is usually obtained by machine learning and with software platforms that provide image-processing tools such as MATLAB. In this study, we introduce a new MATLAB algorithm to quantify immunohistochemically stained critical-sized bone defect samples and compare the results with the commonly available Aperio Image Scope Positive Pixel Count (PPC) algorithm. Bland and Altman analysis and Pearson correlation showed that the measurements acquired with the new MATLAB algorithm were in excellent agreement with the measurements obtained with the Aperio PPC algorithm, and no significant differences were found within the histomorphometric measurements. The ability to segment whole slide images, as well as defining the size and the number of regions of interest to be quantified, makes this MATLAB algorithm a potential histomorphometric tool for obtaining more objective, precise, and reproducible quantitative assessments of entire critical-sized bone defect image data sets in an efficient and manageable workflow.

OpenWorkstation: A modular open-source technology for automated in vitro workflows.

Automation liberates scientific staff from repetitive tasks, decreases the probability of human error and consequently enhances the reproducibility of lab experiments. However, the use of laboratory automation in academic laboratories is limited due to high acquisition costs and the inability to customize off-the-shelf hardware. To address these challenges, we present an Open Source Hardware concept, referred to as OpenWorkstation, to build an assembly line-inspired platform consisting of ready-to-use and customizable modules. In contrast to current standalone solutions, the OpenWorkstation concept enables the combination of single hardware modules - each with a specific set of functionalities - to a modular workstation to provide a fully automated setup. The base setup consists of a pipetting and transport module and is designed to execute basic protocol steps for in vitro research applications, including pipetting operations for liquids and viscous substances and transportation of cell culture vessels between the modules. We demonstrate the successful application of this concept within a case study by the development of a storage module to facilitate high-throughput studies and a photo-crosslinker module to initiate photo-induced polymerization of hydrogel solutions. We present a Systems Engineering framework for customized module development, guidance for the design and assembly of the presented modules, and operational instructions on the usage of the workstation. By combining capabilities from various open source instrumentations into a modular technology platform, the OpenWorkstation concept will facilitate efficient and reliable experimentation for in vitro research. Ultimately, this concept will allow academic groups to improve replicability and reproducibility in cell culture process operations towards more economical and innovative research in the future.

Printomics: the high-throughput analysis of printing parameters applied to melt electrowriting.

Melt electrowriting (MEW) combines the fundamental principles of electrospinning, a fibre forming technology, and 3D printing. The process, however, is highly complex and the quality of the fabricated structures strongly depends on the interplay of key printing parameter settings including processing temperature, applied voltage, collection speed, and applied pressure. These parameters act in unison, comprising the principal forces on the electrified jet: pushing the viscous polymer out of the nozzle and mechanically and electrostatically dragging it for deposition towards the collector. Although previous studies interpreted the underlying mechanism of electrospinning with polymer melts in a direct writing mode, contemporary devices used in laboratory environments lack the capability to collect large data reproducibly. Yet, a validated large data set is a condition sine qua non to design an in-process control system which allows to computer control the complexity of the MEW process. For this reason, we engineered an advanced automated MEW system with monitoring capabilities to specifically generate large, reproducible data volumes which allows the interpretation of complex process parameters. Additionally, the design of an innovative real-time MEW monitoring system identifies the main effects of the system parameters on the geometry of the fibre flight path. This enables, for the first time, the establishment of a comprehensive correlation between the input parameters and the geometry of a MEW jet. The study verifies the most stable process parameters for the highly reproducible fabrication of a medical-grade poly(ε-caprolactone) fibres and demonstrates how Printomics can be performed for the high throughput analysis of processing parameters for MEW.