ICDS News

Researchers optimize additive manufacturing on a molecular level

by Erin Cassidy Hendrick, via Penn State News

UNIVERSITY PARK, Pa. — As the complexity and applications of additive manufacturing increase, Penn State researchers are digging down to the smallest scales to optimize the technology on a molecular level. 

“There are still a lot of unknowns about how 3D printing actually works,” said Adri van Duin, principal investigator of the project and professor of mechanical engineering, chemical engineering, and engineering science and mechanics at Penn State. “For this project, we theorized you could learn a lot by looking at the various molecules they’re operating with.” 

A paper published in the Physical Chemistry Chemical Physics Journal details how researchers examined additive manufacturing methods and materials using atomistic-scale simulations to optimize their performance for ultimately stronger and more useful 3D-printed components. 

“We went down to the most fundamental level, looking at the physical chemistry and the strengths of these molecular interactions,” van Duin said.

Specifically, his team scrutinized the reactions occurring within a binder jetting solution used for 3D printing, which essentially acts as the glue that bonds the printed layers of primary materials together.

“You want the glue to organize itself in the space between the nanoparticles,” van Duin said. “It’s also ideal if the molecules still have the ability to move.”

For the purposes of this study, van Duin and his team created a computational framework using ReaxFF, a program for modeling atomistic chemical reactions, to study chromium-oxide nanoparticles, a metal commonly used in additive manufacturing, and binders containing water-based diethylene glycol solutions that form strong connections through a hydrogen bond network. 

“The design focus is modifying these components and examining the impacts of temperature phases to get the optimal binding strength, while also allowing the molecules to move on the surface together,” van Duin said.

After these molecules are successfully bound together, the high temperatures within a 3D printer needed for curing and sintering essentially boil away the now-unnecessary organic molecules, while keeping the metal oxides merged in the finished piece. According to the computational framework designed for the experiment, if these temperatures are too high, it can instead burn out these crucial bonds and result in a decomposition of the final piece. 

However, van Duin and the team of researchers found that by tweaking the amounts of diethylene glycol and water present in the binder solution, they could intensify the occurrence of strong hydrogen bonds, which allowed the mixed material to withstand and thrive under higher temperatures. 

While the results of this experiment have predicted the ability to enhance the creation of 3D-printed parts using chromium-oxide particles, the real strength of this research lies in the computational models. With the creation of this framework, these experiments can be deployed to find the optimal binder chemistry, curing and sintering conditions for any potential materials that can be used in additive manufacturing. 

“Once you understand how strong bindings can be formed, we can apply it to anything we want,” van Duin said. “If we want to try this with peptides, we can simulate that.”

The computations are inexpensive and completed in a relatively short amount of time, which allows researchers to investigate and model new organic molecules to see which methods and materials are most promising for additive manufacturing applications.

The research is the result of a seed grant from the Penn State Institute for Computational and Data Sciences (ICDS), formerly the Institute for CyberScience, which demonstrates the intrinsic interdisciplinary nature of the additive manufacturing field.

In addition, this research brought together van Duin and Guha Manogharan, assistant professor of mechanical engineering and industrial engineering at Penn State, who specializes in additive manufacturing. Since many of his projects work extensively with binder jetting solutions, Manogharan sought to look beyond the traditional confines of manufacturing optimizations. 

“This is a good example of support from complementary institutes and centers within Penn State where the strength of my lab, the SHAPE Lab (Systems for Hybrid Additive Manufacturing), in additive manufacturing, is seamlessly integrated with the strong capabilities of ICDS to explore an uncharted but critical research area,” Manogharan said.

Providing further understanding of how molecules can be modified and enhanced before they ever enter in a 3D printer is an area where the researchers see great promise.

“By understanding the process on a nanoscale, we don’t have to redesign a printer,” van Duin said. “But you can greatly accelerate the optimization of the manufacturing.”

Additional collaborators on the project include Penn State mechanical engineering graduate students Yawei Gao, Yun Kyung Shin and Daniel Martínez Lepp. 

Share

Related Posts

• Featured Researcher: Nick Tusay
• Multi-institutional team to use AI to evaluate social, behavioral science claims
• NSF invests in cyberinfrastructure institute to harness cosmic data
• Center for Immersive Experiences set to debut, serving researchers and students
• Distant Suns, Distant Worlds
• CyberScience Seminar: Researcher to discuss how AI can help people avoid adverse drug interactions
• AI could offer warnings about serious side effects of drug-drug interactions
• Taking RTKI drugs during radiotherapy may not aid survival, worsens side effects
• Cost-effective cloud research computing options now available for researchers
• Costs of natural disasters are increasing at the high end
• Model helps choose wind farm locations, predicts output
• Virus may jump species through ‘rock-and-roll’ motion with receptors
• Researchers seek to revolutionize catalyst design with machine learning
• Resilient Resumes team places third in Nittany AI Challenge
• ‘AI in Action’: Machine learning may help scientists explore deep sleep
• Clickbait Secrets Exposed! Humans and AI team up to improve clickbait detection
• Focusing computational power for more accurate, efficient weather forecasts
• How many Earth-like planets are around sun-like stars?
• Professor receives NSF grant to model cell disorder in heart
• SMH! Brains trained on e-devices may struggle to understand scientific info
• Whole genome sequencing may help officials get a handle on disease outbreaks
• New tool could reduce security analysts’ workloads by automating data triage
• Careful analysis of volcano’s plumbing system may give tips on pending eruptions
• Reducing farm greenhouse gas emissions may plant the seed for a cooler planet
• Using artificial intelligence to detect discrimination
• Four ways scholars say we can cut the chances of nasty satellite data surprises
• Game theory shows why stigmatization may not make sense in modern society
• Older adults can serve communities as engines of everyday innovation
• Pig-Pen effect: Mixing skin oil and ozone can produce a personal pollution cloud
• Researchers find genes that could help create more resilient chickens
• Despite dire predictions, levels of social support remain steady in the U.S.
• For many, friends and family, not doctors, serve as a gateway to opioid misuse
• New algorithm may help people store more pictures, share videos faster
• Head named for Ken and Mary Alice Lindquist Department of Nuclear Engineering
• Scientific evidence boosts action for activists, decreases action for scientists
• People explore options, then selectively represent good options to make difficult decisions
• Map reveals that lynching extended far beyond the deep South
• Gravitational forces in protoplanetary disks push super-Earths close to stars
• Supercomputer cluster donation helps turn high school class into climate science research lab
• Believing machines can out-do people may fuel acceptance of self-driving cars
• People more likely to trust machines than humans with their private info
• IBM donates system to Penn State to advance AI research
• ICS Seed Grants to power projects that use AI, machine learning for common good
• Penn State Berks team advances to MVP Phase of Nittany AI Challenge
• Creepy computers or people partners? Working to make AI that enhances humanity
• Sky is clearing for using AI to probe weather variability
• ‘AI will see you now’: Panel to discuss the AI revolution in health and medicine
• Privacy law scholars must address potential for nasty satellite data surprises
• Researchers take aim at hackers trying to attack high-value AI models
• Girls, economically disadvantaged less likely to get parental urging to study computers
• Seed grants awarded to projects using Twitter data
• Researchers find features that shape mechanical force during protein synthesis
• A peek at living room decor suggests how decorations vary around the world
• Interactive websites may cause antismoking messages to backfire
• Changing how government assesses risk may ease fallout from extreme financial events
• Symposium at U.S. Capitol seeks solutions to election security
• ICS co-sponsors Health, Environment Seed Grant Program
• Differences in genes’ geographic origin influence mitochondrial function
• Using social media to solve social problems- study funded by ICS seed grant