{"id":28820,"date":"2025-09-29T11:17:14","date_gmt":"2025-09-29T05:32:14","guid":{"rendered":"https:\/\/www.revoscience.com\/en\/?p=28820"},"modified":"2025-09-29T11:17:22","modified_gmt":"2025-09-29T05:32:22","slug":"technique-makes-complex-3d-printed-parts-more-reliable","status":"publish","type":"post","link":"https:\/\/www.revoscience.com\/en\/technique-makes-complex-3d-printed-parts-more-reliable\/","title":{"rendered":"Technique makes complex 3D printed parts more reliable"},"content":{"rendered":"\n

New research enables computer designs to incorporate the limitations of 3D printers, to better control materials\u2019 performance in aerospace, medical, and other applications.<\/strong><\/em><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n

Zach Winn<\/p><\/div><\/div>\n\n\n

Cambridge, Mass. — People are increasingly turning to software to design complex material structures like airplane wings and medical implants. But as design models become more capable, our fabrication techniques haven\u2019t kept up.Even 3D printers struggle to reliably produce the precise designs created by algorithms. The problem has led to a disconnect between the ways a material is expected to perform and how it actually works.<\/p>\n\n\n\n

Now, MIT researchers have created a way for models to account for 3D printing\u2019s limitations during the design process. In experiments, they showed their approach could be used to make materials that perform much more closely to the way they\u2019re<\/a> intended to.<\/p>\n\n\n\n

\u201cIf you don\u2019t account for these limitations, printers can either over- or under-deposit material by quite a lot, so your part becomes heavier or lighter than intended. It can also over- or underestimate the material performance significantly,\u201d says Gilbert W. Winslow Associate Professor of Civil and Environmental Engineering Josephine Carstensen. \u201cWith our technique, you know what you\u2019re getting in terms of performance because the numerical model and experimental results align very well.\u201d<\/p>\n\n\n\n

The approach is described in the journal Materials and Design<\/em>,in an open-access paper<\/a> co-authored by Carstensen and PhD student Hajin Kim-Tackowiak.<\/p>\n\n\n\n

Matching theory with reality<\/strong><\/p>\n\n\n\n

Over the last decade, new design and fabrication technologies have transformed the way things are made, especially in industries like aerospace, automotive, and biomedical engineering, where materials must reach precise weight-to-strength ratios and other performance thresholds. In particular, 3D printing allows materials to be made with more complex internal structures.<\/p>\n\n\n\n

\u201c3D printing processes generally give us more flexibility because we don\u2019t have to come up with forms or molds for things that would be made through more traditional means like injection molding,\u201d Kim-Tackowiak explains.<\/p>\n\n\n\n

As 3D printing has made production more precise, so have methods for designing complex material structures. One of the most advanced computational design techniques is known as topology optimization. Topology optimization has been used to generate new and often surprising material structures that can outperform conventional designs, in some cases approaching the theoretical limits of certain performance thresholds. It is currently being used to design materials with optimized stiffness and strength, maximized energy absorption, fluid permeability, and more.<\/p>\n\n\n\n

But topology optimization often creates designs at extremely fine scales that 3D printers have struggled to reliably reproduce. The problem is the size of the print head that extrudes the material. If the design specifies a layer to be 0.5 millimeters thick, for instance, and the print head is only capable of extruding 1-millimeter-thick layers, the final design will be warped and imprecise.<\/p>\n\n\n\n

Another problem has to do with the way 3D printers create parts, with a print head extruding a thin bead of material as it glides across the printing area, gradually building parts layer by layer. That can cause weak bonding between layers, making the part more prone to separation or failure.<\/p>\n\n\n\n

The researchers sought to address the disconnect between expected and actual properties of materials that arise from those limitations.<\/p>\n\n\n\n

\u201cWe thought, \u2018We know these limitations in the beginning, and the field has gotten better at quantifying these limitations, so we might as well design from the get-go with that in mind,\u201d Kim-Tackowiak says.<\/p>\n\n\n\n

In previous work, Carstensen developed an algorithm that embedded information about the print nozzle size into design algorithms for beam structures. For this paper, the researchers built off that approach to incorporate the direction of the print head and the corresponding impact of weak bonding between layers. They also made it work with more complex, porous structures that can have extremely elastic properties.<\/p>\n\n\n\n

The approach allows users to add variables to the design algorithms that account for the center of the bead being extruded from a print head and the exact location of the weaker bonding region between layers. The approach also automatically dictates the path the print head should take during production.<\/p>\n\n\n\n

The researchers used their technique to create a series of repeating 2D designs with various sizes of hollow pores, or densities. They compared those creations to materials made using traditional topology optimization designs of the same densities.<\/p>\n\n\n\n

In tests, the traditionally designed materials deviated from their intended mechanical performance more than materials designed using the researchers\u2019 new technique at material densities under 70 percent. The researchers also found that conventional designs consistently over-deposited material during fabrication. Overall, the researchers\u2019 approach led to parts with more reliable performance at most densities.<\/p>\n\n\n\n

\u201cOne of the challenges of topology optimization has been that you need a lot of expertise to get good results, so that once you take the designs off the computer, the materials behave the way you thought they would,\u201d Carstensen says. \u201cWe\u2019re trying to make it easy to get these high-fidelity products.\u201d<\/p>\n\n\n\n

Scaling a new design approach<\/strong><\/p>\n\n\n\n

The researchers believe this is the first time a design technique has accounted for both the print head size and weak bonding between layers.<\/p>\n\n\n\n

\u201cWhen you design something, you should use as much context as possible,\u201d Kim-Tackowiak says. \u201cIt was rewarding to see that putting more context into the design process makes your final materials more accurate. It means there are fewer surprises. Especially when we\u2019re putting so much more computational resources into these designs, it\u2019s nice to see we can correlate what comes out of the computer with what comes out of the production process.\u201d<\/p>\n\n\n\n

In future work, the researchers hope to improve their method for higher material densities and for different kinds of materials like cement and ceramics. Still, they said their approach offered an improvement over existing techniques, which often require experienced 3D printing specialists to help account for the limitations of the machines and materials.<\/p>\n\n\n\n

\u201cIt was cool to see that just by putting in the size of your deposition and the bonding property values, you get designs that would have required the consultation of somebody who\u2019s worked in the space for years,\u201d Kim-Tackowiak says.<\/p>\n\n\n\n

The researchers say the work paves the way to design with more materials.<\/p>\n\n\n\n

\u201cWe\u2019d like to see this enable the use of materials that people have disregarded because printing with them has led to issues,\u201d Kim-Tackowiak says. \u201cNow we can leverage those properties or work with those quirks as opposed to just not using all the material options we have at our disposal.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

Cambridge, Mass. — People are increasingly turning to software to design complex material structures like airplane wings and medical implants. But as design models become more capable, our fabrication techniques haven\u2019t kept up.Even 3D printers struggle to reliably produce the precise designs created by algorithms. <\/p>\n","protected":false},"author":2,"featured_media":28821,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17,28],"tags":[],"class_list":["post-28820","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research","category-techbiz"],"featured_image_urls":{"full":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0.webp",900,600,false],"thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-200x200.webp",200,200,true],"medium":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-675x450.webp",675,450,true],"medium_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-768x512.webp",750,500,true],"large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0.webp",750,500,false],"1536x1536":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0.webp",900,600,false],"2048x2048":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0.webp",900,600,false],"ultp_layout_landscape_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0.webp",900,600,false],"ultp_layout_landscape":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-870x570.webp",870,570,true],"ultp_layout_portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-600x600.webp",600,600,true],"ultp_layout_square":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-600x600.webp",600,600,true],"newspaper-x-single-post":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-760x490.webp",760,490,true],"newspaper-x-recent-post-big":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-550x360.webp",550,360,true],"newspaper-x-recent-post-list-image":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-95x65.webp",95,65,true],"web-stories-poster-portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-640x600.webp",640,600,true],"web-stories-publisher-logo":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-96x96.webp",96,96,true],"web-stories-thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2025\/09\/MIT-Material-Design-01-press_0-150x100.webp",150,100,true]},"author_info":{"info":["Zach Winn"]},"category_info":"Research<\/a> Tech<\/a>","tag_info":"Tech","comment_count":"0","_links":{"self":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/28820","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/comments?post=28820"}],"version-history":[{"count":1,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/28820\/revisions"}],"predecessor-version":[{"id":28822,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/28820\/revisions\/28822"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/media\/28821"}],"wp:attachment":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/media?parent=28820"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/categories?post=28820"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/tags?post=28820"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}