Shing-Yun Chang, Sahil R. Vora, Charles D. Young, Abhishek Shetty & Anson W. K. Ma. Viscoelasticity of a carbon nanotube-laden air–water interface. Eur. Phys. J. E 47, 18 (2024). https://doi.org/10.1140/epje/s10189-024-00411-0
Emulsions and foams are ubiquitously found in pharmaceutical, agricultural, personal care, and food products. Although it has been known for more than a century that small, nanoscale particles may be added to stabilize these products and increase their shelf-life, accurately capturing the behavior of these particles remains extremely challenging. In this article, UConn researchers critically compare two state-of-the-art experimental methods for studying particles at an interface, laying the foundation for predicting and improving the stability and performance of a wide range of commercial products.
Prof. Anson Ma demonstrates the machine learning capabilities of the HuskyJet 3D printer at the SHAP3D lab in IPB.
Inkjet printing has evolved from a graphics and marking technology to a broader variety of additive manufacturing and 3D printing processes for electronic, optical, pharmaceutical, and biological applications. The success of adopting inkjet technology for these newer applications is contingent on whether the ink materials can be consistently and reliably jetted by the print systems. Currently, each printer-and-ink combination requires calibration by trial and error, which consumes a considerable amount of time and materials. IPB researcher, Prof. Anson Ma, Site Director of SHAP3D, teamed up with UConn machine learning expert, Prof. Qian Yang, to demonstrate a new concept of “autonomous 3D printing”, leveraging an active machine learning method they developed to efficiently create a jettability diagram that predicts the best conditions for jetting an ink from a printhead.
Briefly, a camera is used to image the printhead and capture the behavior of ink jetted from a printhead. Starting with a few randomly chosen conditions, a machine learning algorithm predicts the optimal jetting conditions and then “cleverly decides” on the next set of experiments that can further improve prediction accuracy. After performing those experiments, the algorithm analyzes the newly acquired images, updates the prediction for the desired jetting conditions, and iteratively selects the next experiments, continuing autonomously until a small experimental budget is reached. This approach has achieved a prediction accuracy of more than 95% while considerably reducing the number of experiments required by 80% compared to a typical grid-search approach. This novel approach is especially powerful for optimizing complex print systems with many tunable process parameters.
This work was recently published in the journal 3D Printing and Additive Manufacturing (http://doi.org/10.1089/3dp.2023.0023) and led to a pending patent application (WO 2023/2788542).
SHAP3D held their eighth bi-annual Industrial Advisory Board Meeting on May 25 – May 26, 2022, at the Innovation Partnership Building (IPB) | UConn Tech Park.
“It is wonderful to reunite with the SHAP3D family and interact with new center members for the first time in person since they have joined after the pandemic began,” says Prof. Anson Ma, UConn Site Director of the SHAP3D center.
SHAP3D is a collaboration between the University of Massachusetts Lowell, University of Connecticut and Georgia Institute of Technology to create a National Science Foundation I/UCRC focused on 3D printing. The mission of the SHAP3D Center is to perform pre-competitive research providing the fundamental knowledge for 3D printing heterogeneous products that integrate multiple engineering materials with complex 3D structures and diverse functionality. The Center’s diverse membership comprises material developers, 3D printer manufacturers, 3D printing end users, and federal agencies with a stake in the growth of this emerging manufacturing platform.
The meeting was attended by more than 55 faculty members, students, and representatives from private companies, and government agencies. At this meeting, project teams currently funded by the SHAP3D center shared their progress and latest findings. Other highlights of the meeting included rapid fire presentations from members and two invited talks by Professor Timothy Long from the Arizona State University and Professor Matthew Becker from Duke University. UConn SHAP3D site, Proof of Concept Center (POCC), and Pratt & Whitney Additive Manufacturing Center (PW AMC) were all featured in the IPB lab tour. During the reception sponsored by UConn School of Engineering, students who are involved in SHAP3D projects also had the valuable opportunity to present their posters and network with the advisory board members.
The month of May brought an advanced 3D printer, the Stratasys Objet 500 Connex, to the Science of Heterogeneous Additive Printing of 3D Materials (SHAP3D) lab in IPB. “We are extremely excited about bringing this state-of-the-art 3D printer to IPB and leveraging it to accelerate our multi-material printing research,” says Professor Anson Ma, SHAP3D UConn Site Director. The printer works by jetting and combining different print materials with high precision, thereby achieving a wide range of physical properties through changing the digital print design. This printer also complements the advanced prototyping capabilities that already exist at IPB’s Proof of Concept Center (POCC), directed by Joe Luciani.
Now armed with this powerful printer, Prof. Ma and team aim to expand the choice of materials that can be printed using this machine. Of interest are functional materials with excellent mechanical, thermal and electrical properties. Another topic of interest is to develop in-situ metrology for monitoring the print process in real time and ensuring the quality of 3D printed parts. This is especially important for high performance applications, such as aerospace, where the printed parts must meet stringent requirements. Ideally, all the printed parts must be qualified as they are produced, termed “born-qualified.” Prof. Ma’s long-term ambition is to develop autonomous 3D printers that are intelligent, through working closely with machine learning experts like Prof. Qian Yang from the Department of Computer Science and Engineering at UConn.
In addition to aerospace, the auto industry, and other major manufacturing sectors, organizations that will benefit from the SHAP3D research include 3D printer manufacturers and material suppliers. As the SHAP3D team continues to expand the material selection and improve the robustness of 3D printing, more application opportunities will open up. Professor Ma is eager to get started, although he cautions, “before we can run, we need to learn how to walk.” With the addition of the Objet 500 Connex, the SHAP3D team will be sprinting soon.
Science of Heterogeneous Additive Printing of 3D Materials (SHAP3D) is an Industry/University Cooperative Research Center (I/UCRC) funded by the National Science Foundation to catalyze the technological development of additive manufacturing, also known as 3D printing.The partners are University of Massachusetts at Lowell (UML), University of Connecticut (UC), and Georgia Institute of Technology (GT). Established in July 2018.
Anson Ma, Director NSF SHAP3D Center for 3D Printing, Associate Professor of chemical engineering
NSF SHAP3D Center Site Director, Professor Anson Ma, has received a prestigious 2020 summer faculty fellowship from the Air Force Research Lab (AFRL) Materials and Manufacturing Directorate. The fellowship is sponsored by the Air Force Office of Scientific Research (AFOSR) with the objectives of enhancing the research interests and capabilities of faculty fellows, elevating the awareness in the U.S. academic community of Air Force research needs, and stimulating professional relationships between the faculty fellows and Air Force researchers.
With the support of this fellowship, Ma and his PhD student, Ethan Chadwick, will be working with researchers at the Wright Patterson Air Force Base on the topic of additive manufacturing, or 3D printing. “I am honored to receive this recognition. My student and I are very excited about the opportunity to interact and work closely with AFRL researchers and other fellowship recipients who are leading experts in their respective research fields,” Ma said.
Ma is the founding Site Director of the NSF SHAP3D center for additive manufacturing at UConn. His research group focuses on understanding fluid dynamics (rheology) and advancing additive manufacturing technologies. Ma has received many accolades, including a National Science Foundation (NSF) CAREER award, Arthur B. Metzner Award from the Society of Rheology, and faculty awards from TA Instruments, 3M, and the American Association of University Professors (AAUP)-UConn Chapter.
