Progress and Opportunities for Machine Learning in Materials and Processes of Additive Manufacturing.

In recent years, there has been widespread adoption of machine learning (ML) technologies to unravel intricate relationships among diverse parameters in various additive manufacturing (AM) techniques. These ML models excel at recognizing complex patterns from extensive, well-curated datasets, thereby unveiling latent knowledge crucial for informed decision-making during the AM process. The collaborative synergy between ML and AM holds the potential to revolutionize the design and production of AM-printed parts.

Automated Service Height Fault Detection Using Computer Vision and Machine Learning for Badminton Matches.

In badminton, accurate service height detection is critical for ensuring fairness. We developed an automated service fault detection system that employed computer vision and machine learning, specifically utilizing the YOLOv5 object detection model. Comprising two cameras and a workstation, our system identifies elements, such as shuttlecocks, rackets, players, and players' shoes.

Understanding droplet jetting on varying substrate for biological applications.

In the inkjet printing process, the droplet experience two phases, namely the jetting and the impacting phases. In this review article, we aim to understand the physics of a jetted ink, which begins during the droplet formation process. Following which, we highlight the different impacts during which the droplet lands on varying substrates such as solid, liquid, and less commonly known viscoelastic material.

3D printing and 3D-printed electronics: Applications and future trends in smart drug delivery devices.

Drug delivery devices which can control the release of drugs on demand allow for improved treatment to a patient. These smart drug delivery devices allow for the release of drugs to be turned on and off as needed, thereby increasing the control over the drug concentration within the patient. The addition of electronics to the smart drug delivery devices increases the functionality and applications of these devices.

The Design and Development of Instrumented Toys for the Assessment of Infant Cognitive Flexibility.

The first years of an infant's life represent a sensitive period for neurodevelopment where one can see the emergence of nascent forms of executive function (EF), which are required to support complex cognition. Few tests exist for measuring EF during infancy, and the available tests require painstaking manual coding of infant behaviour. In modern clinical and research practice, human coders collect data on EF performance by manually labelling video recordings of infant behaviour during toy or social interaction.

Machine Learning for Bioelectronics on Wearable and Implantable Devices: Challenges and Potential.

Bioelectronics presents a promising future in the field of embedded and implantable electronics, providing a range of functional applications, from personal health monitoring to bioactuators. However, due to the intrinsic difficulties present in producing and optimizing bioelectronics, recent research has focused on utilizing machine learning (ML) to reliably mitigate such issues and aid in process development. This review focuses on the recent developments of integrating ML into bioelectronics, aiding in a multitude of areas, such as material development, fabrication process optimization, and system integration.

Controlling Droplet Impact Velocity and Droplet Volume: Key Factors to Achieving High Cell Viability in Sub-Nanoliter Droplet-based Bioprinting.

Three-dimensional (3D) bioprinting systems serve as advanced manufacturing platform for the precise deposition of cells and biomaterials at pre-defined positions. Among the various bioprinting techniques, the drop-on-demand jetting approach facilitates deposition of pico/nanoliter droplets of cells and materials for study of cell-cell and cell-matrix interactions. Despite advances in the bioprinting systems, there is a poor understanding of how the viability of primary human cells within sub-nanoliter droplets is affected during the printing process.

Tissue engineering and 3D printing of bioartificial pancreas for regenerative medicine in diabetes.

Diabetes is a severe chronic disease worldwide. In various types of diabetes, the pancreatic beta cells fail to secrete sufficient insulin, at some point, to regulate blood glucose levels. Therefore, the replacement of dysfunctional pancreas, islets of Langerhans, or even the insulin-secreting beta cells facilitates physiological regulation of blood glucose levels.

Aerosol-Jet-Printed Preferentially Aligned Carbon Nanotube Twin-Lines for Printed Electronics.

The alignment of carbon nanotubes (CNTs) is of great importance for the fabrication of high-speed electronic devices such as a transistor as the electron mobilities can be greatly enhanced with aligned CNT architectures. Here, we report, for the first time, a methodology to obtain preferentially aligned CNT traces on a flexible polyimide substrate utilizing the high-resolution aerosol jet printing technique and evaporation-driven self-assembly process. A self-assembled twin-line of CNT ("coffee-ring" effect) is observed in the deposit patterns, and the field-emission scanning electron microscopy (FESEM) images reveal highly self-ordered CNT in the resulting CNT twin-line.

Sessile droplets containing carbon nanotubes: a study of evaporation dynamics and CNT alignment for printed electronics.

Carbon nanotubes (CNTs) are 1-dimensional (1D) and flexible nanomaterials with high electric conductivity and a high aspect ratio. These features make CNTs highly suitable materials for the fabrication of flexible electronics. CNTs can also be made into dispersions which can be used as the feedstock material for droplet-based 3D printing technologies, e.

Wearable Bandage-Based Strain Sensor for Home Healthcare: Combining 3D Aerosol Jet Printing and Laser Sintering.

Flexible and stretchable strain sensors are in great demand for many applications like wearables and home health. This work reports a strain sensor fabricated using aerosol jet printing technology on a commercially available bandage to be used as a low-cost wearable. Laser light is explored to sinter the silver nanoparticle ink on a low-temperature bandage substrate.